ROLE OF INSTITUTIONS AND POLICIES IN ECONOMIC GROWTH …prr.hec.gov.pk/jspui/bitstream/123456789/11849/1/azra khan_Eco_20… · Ihtisham ul Haq for their moral support. Dr. Sadia

i

ROLE OF INSTITUTIONS AND POLICIES IN ECONOMIC

GROWTH: A CROSS COUNTRY ANALYSIS

DOCTOR OF PHILOSOPHY DISSERTATION

BY

AZRA KHAN

FUUAST, SCHOOL OF ECONOMIC SCIENCES

FEDERAL URDU UNIVERSITY OF ARTS, SCIENCE AND TECHNOLOGY

ISLAMABAD

2016

ii



A thesis for the partial fulfillment of the degree requirement of

Doctor of Philosophy

BY

AZRA KHAN



ISLAMABAD

2016

iii



A thesis for the partial fulfillment of the degree requirement of the

degree of

Doctor of Philosophy

BY

AZRA KHAN

SUPERVISED BY

PROF. DR. SYED NAWAB HAIDER NAQVI



ISLAMABAD

2016

iv

Acknowledgement

In The Name of Allah, Most Beneficial and Merciful

I would like to start this page with my heartfelt, deepest gratefulness and gratitude

presented to Allah Almighty “Praise be to Allah, the Lord of the worlds”. His

benevolence, affection, generosity, and blessings are even beyond our imaginations and

deeds. The completion of this dissertation would have been entirely a dream without the

strength and guidance provided by Allah Almighty. Thanks to God for wisdom and

perseverance which has been bestowed upon me as we are able to turn impossible in to

possible through Him who gives us strength.

I would like to express my sincere and wholehearted gratitude to my principal advisor

Professor Dr. Syed Nawab Haider Naqvi, HEC Distinguished National Professor and ex

Director General, School of Economic Sciences, Federal Urdu University of Arts Science

and Technology (FUUAST) Islamabad, for his invaluable encouragement and support. He

is no doubt a professional, competent and expert economist along with strong personal

traits as being the most generous, affectionate, patient and loving one. I really feel lucky

and among the blessed ones to get an opportunity to work under his supervision.

My special appreciation goes to Professor Dr. Abdul Salam who was always available to

encourage and motivate me. He has always been very much kind, affectionate and

generous to me. His motivation has been the most supportive factor in the completion of

this dissertation.

I am also thankful to my other fellow colleagues especially Dr. Adiqa K. Kiani and Dr.

Ihtisham ul Haq for their moral support.

Dr. Sadia Safdar, a very close friend of mine and colleague, has also been very supportive

to me since the times I know her. I present my heartfelt thanks to her as being a sincere

and close friend of mine.

With due regard and respect, I would also like to thank my father, for his support,

encouragement and best wishes.

At last but not least I cannot forget the sincere wishes of my family and dear students, they

also deserve my special appreciation and thanks.

v

Table of Contents

Chapter # 1 Introduction ......................................................................................................... 1

1.1 Motivation and background of the study .............................................................................. 1

1.2 Review of policies and institutions in developing countries ................................................ 2

1.2.1 Institutions in developing countries ............................................................................. 2

1.2.2 Stabilization policies in developing countries ............................................................ 4

1.2.3 Liberalization policies in developing countries ........................................................... 7

1.2.4 Link between institutions and policies ...................................................................... 10

1.3 Significance and contribution of the study ......................................................................... 11

1.4 Choice of the countries and time period ............................................................................. 13

1.5 Objectives of the study ....................................................................................................... 14

1.6 Organization of the study .................................................................................................... 17

1.7 Concluding remarks ............................................................................................................ 17

Chapter # 2 Literature Review .............................................................................................. 19

2.1 Institutions and economic growth ....................................................................................... 19

2.1.1 Theoretical review ..................................................................................................... 19

2.1.2 Empirical review ........................................................................................................ 20

2.1.3 Concluding remarks ................................................................................................... 28

2.2 Financial liberalization and economic growth ................................................................... 30




2.3 Trade liberalization and economic growth ......................................................................... 38




2.4 Fiscal policy and economic growth .................................................................................... 47




2.5 Monetary policy and economic growth .............................................................................. 57

vi




2.6 Policy volatility and economic growth ............................................................................... 65



2.6.2.1 Fiscal policy volatility and economic growth ................................................. 66

2.6.2.2 Monetary policy volatility and economic growth ........................................... 69

2.6.2.3 Capital flows volatility and economic growth ................................................ 72

2.6.2.4 Trade flows volatility and economic growth .................................................. 75

2.6.2.5 External factors volatility and economic growth ............................................ 77


2.7 Determinants of policy volatility ........................................................................................ 82


2.7.1.1 Determinants of capital flows volatility ........................................................... 82

2.7.1.2 Determinants of trade flows volatility ............................................................. 87

2.7.1.3 Determinants of fiscal policy volatility ............................................................ 90

2.7.1.4 Determinants of monetary policy volatility ...................................................... 94


2.8 Literature gap .................................................................................................................... 100

Chapter # 3 An Over View of Selected Developing Countries ........................................ 102

3.1 An overview of the economies of selected countries ....................................................... 102

3.2 Dynamics of institutions and policies of selected countries ............................................. 129

3.3 Institutional reforms in developing countries ................................................................... 132

3.4 Concluding remarks .......................................................................................................... 137

Chapter # 4 Model Specification ......................................................................................... 139

4.1 Theoretical Model ............................................................................................................. 139

4.2 Description of variables .................................................................................................... 148

4.3 Methodology ..................................................................................................................... 159

4.4 Concluding remarks .......................................................................................................... 161

Chapter # 5 Results and Discussion .................................................................................... 164

5.1 Descriptive statistics ......................................................................................................... 164

vii

5.2 Pairwise correlation matrix ............................................................................................... 165

5.3 Results of GMM ............................................................................................................... 167

5.3.1 Effect of institutions and policies on economic growth ......................................... 167

5.3.1.1 Diagnostic tests ............................................................................................. 179

5.3.1.2 Concluding remarks ...................................................................................... 180

5.3.2 Disaggregated analysis of institutions .................................................................... 181



5.3.3 Effect of policy volatility on economic growth ...................................................... 188



5.3.4 Determinants of policy volatility ........................................................................... 195

5.3.4.1 Determinants of fiscal policy volatility ........................................................ 198

5.3.4.1.1 Diagnostic tests ............................................................................... 200

5.3.4.1.2 Concluding remarks ........................................................................ 200

5.3.4.2 Determinants of monetary policy volatility ................................................... 201



5.3.4.3 Determinants of capital flows volatility ........................................................ 205



5.3.4.4 Determinants of trade flows volatility .......................................................... 209



Chapter # 6 Conclusions and Policy Recommendations ................................................... 220

6.1 Conclusions....................................................................................................................... 214

6.2 Policy recommendations ................................................................................................... 220

6.3 Limitations and future research directions ...................................................................... 224

References .............................................................................................................................. 226

viii

Appendices:

Appendix I: Percentile score of countries at governance index ............................................. 247

Appendix II: Summary of literature review ........................................................................... 248

Appendix III: Trends of the variables .................................................................................... 266

Appendix IV: Policy volatility in selected countries ............................................................. 276

Appendix V: Cyclical behaviour of policies in selected countries ........................................ 279

Appendix VI: Scattered plots of variables .............................................................................. 288

Appendix VII: Unit Root Test ............................................................................................... 290

Appendix VIII: Pairwise correlation matrix .......................................................................... 291

List of Tables

Table 1.1 Percentile score of selected countries at institutional index .................................... 14

Table 3.1 Main economic indicators of selected countries .................................................... 103

Table 3.2 Indicators of fiscal and monetary policy and trade liberalization (Pakistan) ......... 106

Table 3.3 Indicators of fiscal and monetary policy and trade liberalization (India) .............. 108

Table 3.4 Indicators of fiscal and monetary policy and trade liberalization (Bangladesh) ... 110

Table 3.5 Indicators of fiscal and monetary policy and trade liberalization (Srilanka) ........ 112

Table 3.6 Indicators of fiscal and monetary policy and trade liberalization (Maldives) ....... 114

Table 3.7 Indicators of fiscal and monetary policy and trade liberalization (Nepal) ............ 116

Table 3.8 Indicators of fiscal and monetary policy and trade liberalization (Thailand) ........ 118

Table 3.9 Indicators of fiscal and monetary policy and trade liberalization (Vietnam) ........ 120

Table 3.10 Indicators of fiscal and monetary policy and trade liberalization (Philippines) .. 122

Table 3.11 Indicators of fiscal and monetary policy and trade liberalization (Mexico) ........ 124

Table 3.12 Indicators of fiscal and monetary policy and trade liberalization (Brazil) .......... 126

Table 3.13 Indicators of fiscal and monetary policy and trade liberalization (Kenya) ......... 128

Table 4.1 Description of variables ......................................................................................... 157

Table 5.1 Descriptive Statistics ............................................................................................. 165

Table 5.2 Pair wise correlation matrix ................................................................................... 166

Table 5.3 Effect of institutions and policies on economic growth ........................................ 169

Table 5.4 Disaggregated analysis of institutions ................................................................... 182

Table 5.5 Effect of policy volatility on economic growth .................................................... 190

Table 5.6 Determinants of policy volatility .......................................................................... 197

ix

List of Figures

Figure 3.1 Governance indictors (Pakistan) ........................................................................... 106

Figure 3.2 Indicators of financial liberalization (Pakistan) .................................................... 106

Figure 3.3 Governance indictors (India) ................................................................................. 108

Figure 3.4 Indicators of financial liberalization (India) .......................................................... 108

Figure 3.5 Governance indictors (Bangladesh) ...................................................................... 110

Figure 3.6 Indicators of financial liberalization (Bangladesh) ............................................... 110

Figure 3.7 Governance indictors (Srilanka) ............................................................................ 112

Figure 3.8 Indicators of financial liberalization (Srilanka) .................................................... 112

Figure 3.9 Governance indictors (Maldives) .......................................................................... 114

Figure 3.10 Indicators of financial liberalization (Maldives) ................................................. 114

Figure 3.11 Governance indictors (Nepal) ............................................................................. 116

Figure 3.12 Indicators of financial liberalization (Nepal) ...................................................... 116

Figure 3.13 Governance indictors (Thailand) ......................................................................... 118

Figure 3.14 Indicators of financial liberalization (Thailand) .................................................. 118

Figure 3. Governance indictors (Vietnam) ............................................................................. 120

Figure 3.16 Indicators of financial liberalization (Vietnam) .................................................. 120

Figure 3.17 Governance indictors (Philippines) ..................................................................... 122

Figure 3.18 Indicators of financial liberalization (Philippines) .............................................. 122

Figure 3.19 Governance indictors (Mexico) ........................................................................... 124

Figure 3.20 Indicators of financial liberalization (Mexico) .................................................... 124

Figure 3.21 Governance indictors (Brazil) ............................................................................. 126

Figure 3.22 Indicators of financial liberalization (Brazil) ...................................................... 126

Figure 3.23 Governance indictors (Kenya) ............................................................................ 128

Figure 3.24 Indicators of financial liberalization (Kenya) ..................................................... 128

x

Abstract

Given the importance of institutions this study tries to find out the relatively unexplored

areas on the relationship between institutions, policies and economic growth. As there is

extensive literature so far on institutions-growth relationship as well as macroeconomic

policies-growth relationship therefore the study contributes by filling the gap on

institutions-policies link for developing countries specifically the role of institutions in

reducing policy instability. Choice of the countries is based on the governance status or

percentile rank of the countries provided by the World Bank, World Governance

Indicators. Choice of the time period is relevant to policy initiatives in developing as an

agenda of neoliberal approach. Our empirical analysis employs annual data for a set of 12

developing countries, according to the World Bank classification, from South Asia, East

Asia and Pacific, Latin America and Sub Saharan Africa. The sample period spans from

1990–2014. In the light of motivation and significance of the study there are three main

objectives and also sub objectives. Main objectives discuss the role of policies (both

stabilization and liberalization policies) and institutions in economic growth. In addition to

the level effect of domestic macroeconomic policies on economic growth the study also

evaluates the volatility effect and last the indirect effect of institutions on economic

growth through reducing the policy instability or volatility which contributes to the

literature as an unexplored area.

We have derived a dynamic panel data model to study the role of institutions and policies

in economic growth, following Mankiw et al. (1992), in the empirics of neoclassical

growth model. Derived model shows the effect of institutions and policies (stabilization

and liberalization policies) on economic growth along with traditional factors and

convergence. We have further manipulated our equation according to our objectives. To

xi

control the unobserved country specific effects and econometric problems related to the

possible endogeniety of explanatory variables with the growth we use dynamic panel data

GMM method of estimators developed by Arellano and Bond (1991), and Arellano and

Bover (1995). Regarding the empirical results of GMM we explain these according to our

objectives below.

Regarding our first objective we analyze the effect of institutions and policies on

economic growth. There is evidence of conditional convergence moreover the traditional

growth variables; physical capital, human capital and population growth also follow the

empirical literature. Institutions promote the economic growth by creating an environment

for capital creation. Regarding the fiscal policy our results support the Keynesian

hypothesis. Capital expenditures positively contribute to economic growth by providing

necessary infrastructure for the encouragement of private sector investment. Results

regarding the monetary policy support the Monetarists hypothesis, monetary policy do

affect the economic growth through aggregate demand. Trade liberalization increases the

economic growth. Liberalizing the capital goods promotes the economic growth through

technology transfer. Regarding financial liberalization both the De jure and De facto

measure negatively affect the economic growth. Literature provides the evidence that in

developing countries financial liberalization increases the risk of crisis, especially due to

short run capital flows. Disaggregated analysis shows that FDI inflows positively

contribute to economic growth being long term and stable investment while short term

investment (portfolio equity and debt) negatively contribute to economic growth due to

higher reversal rate. Disaggregated analysis of institutional quality shows that political

stability is insignificant in affecting the economic growth while all other indicators of

institutional quality positively contribute to economic growth. Rule of law is the most

significant factor in affecting the economic growth.

xii

Regarding our second objective we evaluate the effect of policy instability or volatility on

economic growth. We accomplish that volatility of domestic macroeconomic policies

brings the uncertainty regarding investment decisions therefore reducing the growth.

Volatility of the fiscal policy creates uncertainty about future taxes and the future behavior

of fiscal parameters which negatively affects the behavior of economic agents. Volatility

of the monetary policy brings volatility in consumption and investment decisions. Access

to the external market has destabilized the economies of less developed countries because

of volatility associated with trade and capital flows. Volatility of both negatively affects

the economic growth by reducing the domestic and foreign investment. Higher integration

makes countries vulnerable to external fluctuations that can deteriorate their growth rate.

Regarding our third objective we examine the effect of institutions on policy volatility.

Results show that institutions play an important role in reducing policy volatility by

putting restrictions on policy makers. Regarding the fiscal policy volatility institutional

constraints make it difficult for the governments to frequently change the policy.

Regarding monetary policy an independent central bank can provide more consistent

policy by reducing the uncertainty, in addition to lower inflationary outcome. High

institutional quality enables countries to stabilize financial markets and capital flows.

Good institutions make the trade flows stable through greater predictability which reduces

the trading cost. Besides the institutional quality volatility of domestic macroeconomic

policies can be reduced by increasing the level of income, reducing macroeconomic

instability indicated by inflation volatility, ensuring the exchange rate stability, higher

export diversification, controlling the external debt or reducing the deficit, improving the

financial sector development which plays the role of shock absorber in globally integrated

world and managing the external shocks.

xiii

Findings propose that increased globalization has raised the need for transparent, efficient

and responsive institutions. To encourage the private investment it is the responsibility of

the state to create a suitable legal and economic environment that ensure protection of

property rights, strong judiciary and improved transparency. Moreover strong fiscal,

monetary and economic institutions reduce policy uncertainty.

1

Introduction

This is an introductory chapter of the thesis. It is divided into seven sections; first section

provides the motivation and background of the study, second section describes a review of

institutions and policies in developing countries and develops an institution-policy link,

third section explains the significance and contribution of the study by highlighting the

research gap, section four discusses the rationale for the choice of countries and time

period, fifth section broadly explains the objectives of the study, sixth section explains the

organization or sequence of the study and last section discusses the concluding remarks of

this chapter.

1.1 Motivation and background of the study:

The neoliberal approach to development stresses the importance of market competition

and of policies that provoke market competition such as free-trade policies, financial

liberalization, deregulation, and privatization. International organizations such as the

World Bank explicitly advocated this approach in the 1980's and 1990's. Under

Washington consensus the policy advice consist of change in fiscal composition including

tax reforms, central bank independence, capital account and trade liberalization,

maintaining exchange rates competitiveness, denationalization and deregulation, etc1.

In many developing countries the Washington consensus policies were extensively

implemented and several policies followed wide reforms however, in providing

sustainable growth the policy program terribly failed. By the 1990s it was recognized that

policy incentives will not provide the required results until there are suitable institutions

and regulatory framework to support. Policy failures in many countries provided the

1 See Rodrik (2006)

Chapter # 1

Chapter # 1 Introduction

2

initiative to institutional reforms. First was the failure of price reform and privatization in

Russia in the absence of a helpful legal, regulatory, and political framework. A second was

the failure of market led reforms in Latin America and the third was the financial crisis of

Asia which has revealed that financial liberalization without the financial regulation brings

instability and crunch, same as the crises of Mexico, Brazil, and many other places.

In 1991 the World Bank recognized that;

“The reasons for underdevelopment are sometimes attributable to weak institutions, lack

of an adequate legal framework, damaging discretionary interventions, uncertain and

variable policy frameworks and a closed decision making process which increases risks of

corruption and waste”

In recent years it has become the aim and condition of development assistance to

strengthen the good governance in developing countries. It indicates the move in policies

and approaches of the World Bank during the 1990s. The Bank has significantly extended

its policy frontiers by pursuing good governance as a core element of its development

strategy.

The objective of first generation reforms was stabilization and liberalization of the

economy while second generation reforms focus on strengthening governing institutions

(Naim 1995).

1.2 Review of institutions and policies in developing countries:

Given the motivation and background of the study this section discusses the characteristics

of institutions and policies of developing countries. At the end we develop a link between

institutions and policies.

1.2.1 Institutions in developing countries:

Institutions are defined as the rules of the game in a society or constraints on human

behavior, whether political, social or economic. These rules can be formal as well as


3

informal, formal ones include laws and regulations while informal ones include culture,

norms and behaviour.

The institutional concept in the economic growth acquired thrust in the mid-1990s, with

the publication of two innovative studies: one “Institutions and Economic Performance”

by Stephen Knack and Philip Keefer and the other “Corruption and Growth” by Paolo

Mauro. Knack and Keefer (1995) explain that the institutional quality such as secured

property rights and contract enforcement is vital to economic growth and investment.

Economic institutions have implications for long run growth in particular they provide the

stimulus to investment and technology. Better rule of law, lower corruption, secure

property rights, contract enforcement and better citizen access to justice all foster growth.

Political institutions affect the economic institutions and vice versa. Institutions enhance

the return of private investment by reducing the risk of doing business. Institutions also act

as a securing device for foreign investors. Institutions put checks and balances on the

government, restricting the desirability to abuse its own power, enforce property rights.

Developing countries’ institutions are characterized by poor legal structures, corrupt

governments, lack of property rights and weak contract enforcement. The East Asian crisis

has highlighted the importance of strong institutions in enabling countries to successfully

integrate with global world. It needs improved financial market transparency and a strong

financial system that ensure financial stability and market discipline. Developing countries

have made progress towards a well-developed financial system in the past few years.

There is a lack of system of formal property rights in developing countries. Weak

enforcement frameworks raise transaction costs of investors significantly. It encourages

and develops a dead capital or non-market transfers, a large informal economy in which

assets are undervalued, unreported and untaxed in developing countries. In countries like

China, investors in productive sectors enjoy greater stability regarding their expectations


4

of future profits while in other sectors property rights are weak. In contrast, in poor

countries the problem is that productive entrepreneurs often face great uncertainty

regarding their future profits and as a result investments are low.

According to the liberal market consensus institutional structure that maximizes growth is

one that ensures the absence of rent seeking behaviour. Markets fail when participants

engage in rent seeking behavior. In developing countries corruption is common whereby

the rent-seeker have the usual practice to use bribes to influence public officials. In

developing countries the absence of democracy and an inefficient bureaucracy are the

main cause of rent-seeking. Corruption diverts the resources from productive uses, as well

as disturbs the normal functioning of the markets and thereby creates uncertainty for

investors. Moreover political corruption is also common in almost all the developing

countries.

Institutional characteristics of developing countries indicate the need for well-established

supporting institutions for the development of a well-functioning market economy.

1.2.2 Stabilization policies in developing countries:

The objective of stabilization policy is to keep the current account deficit and inflation at

adequate levels while stabilizing the output. Fiscal and monetary policy are the main

instruments of stabilization policy, each has its own focus and instruments.

The main objective of fiscal policy in developing countries is long run growth but in past

there has been an excessive focus on the objective of short-run stabilization as opposed to

long-run growth. Government finances in many developing countries are weak due to

inflexible public expenditures and low tax revenues which lead to high deficits, debts and

debt-servicing obligations. There seems a more need for discretionary fiscal policy in


5

developing countries as automatic stabilizers seem less powerful2. Tax structures in

developing countries are not particularly progressive. The share of income tax is smaller

within that smaller tax base, taxes on consumption are the more important source of

revenue in developing countries while import tax revenue has declined due to the

liberalization and world integration. Globalization also puts pressure on developing

countries by making it difficult to increase taxes due to the fear of capital flight. It may

raise the issue of developing alternative revenue sources. There is also extensive tax

evasion due to the informal sector which is twice in size as compared to developed

countries. Financial liberalization has reduced the cost of capital there by improving the

international allocation of savings in developing countries but it has also increased the

opportunities of tax evasion. There are also limited automatic stabilizers on the

expenditure side in developing countries. Government expenditures do not change very

much in the short run because the level of government expenditures are determined by

what the economy needs in terms of public services (general administration, social

services, etc.). Most of government current expenditure is on salaries and it becomes

difficult to reduce these expenditures. Moreover an important expenditure category in

developed countries with a highly anti-cyclical pattern is social security expenditure,

which is absent in most developing countries.

Besides the characteristics of tax and expenditure level in developing countries as

discussed above another important characteristic of fiscal variables is their relative

instability, uncertainty or volatility. For many developing countries fiscal variables are

more volatile and also the movement of fiscal variables is pro-cyclical3. The credit

2 Strong automatic stabilizers ensure the stability of expenditures and revenues; which may reduce

uncertainty having positive effects on long run growth. 3 Due to low tax revenues and narrow tax base and inelastic public expenditure tax revenues and

expenditures decline during recession while during expansion revenues and expenditures both increase for

similar reasons.


6

constraints at the level of the government lead to procyclical fiscal policy at the time of

downturn. There are likely to be considerable pressures for expanding public expenditures

when the budgetary position is favourable leading to a procyclical bias. Expenditures

outpace revenues and the resultant deficit is financed through external sector and the

central bank. Many developing countries have to opt monetary financing of the deficit by

compromising central bank autonomy.

It is generally accepted that in developing countries the primary role of monetary policy

is to facilitate economic growth with stability in prices. Today due to world integration

mostly developing countries’ economies are tied to the business cycles of the advanced

industrialized economies, having very little control over it. Hence most developing

countries sometime find themselves pursuing short-term goals of monetary policy.

The institutional features of monetary policy differ widely between developed and less

developing countries which hinder the transmission of monetary policy to the real

economy in developing countries. Developing countries are characterized by weak

financial sector, low reliability of monetary authorities, fiscal dominance and exogenous

shocks (Ghatak and Sanchez-Fung 2007). Due to these features the transmission of

monetary policy differs from advanced countries. Underdeveloped financial sector is

exposing the developing countries to considerably prolonged consequences of financial

shocks. Inappropriate legal framework and poor fiscal management has resulted in fiscal

dominance in these countries which has led to macroeconomic instability. Furthermore

developing countries are more prone to exogenous shocks than advanced countries, which,

combined with substantial supply shocks, lead to prolonged macroeconomic instability.

In many developing countries the framework of monetary policy has followed the

monetary targeting or exchange rate targeting. However many developing countries have

adopted inflation targeting over the last two decades. Interest rates have been historically


7

high in many developing countries. In the same way interest rate spread in these countries

has been high there by discouraging the savings and investment. The high interest rate also

has consequences for capital inflows and exchange rate volatility. There is little room for

the implementation of an independent monetary policy in developing countries due to the

limited degree of central bank independence4. In an underdeveloped economy monetary

policy has an important role to play in managing the balance of payment deficit and debt

management.

In developing countries in spite of its various limitations an appropriate monetary policy

supports in controlling inflation, reducing balance of payments gap, boosting capital

formation and stimulating economic growth.

1.2.3 Liberalization policies in developing countries:

Economic liberalization refers to the reduction of government regulations in an economy

to increase the participation of the private sector in order to encourage the economic

development. In developing countries, economic liberalization mentions to further opening

up of their respective economies to trade and foreign capital.

Trade liberalization signifies to the reduction and elimination of trade barriers (tariff and

non-tariff barriers). The concept of import-substitution policy was wide spread in late

1960s and mid 1970s as an instrument for economic development in the third-world. It

was believed that developing countries would produce substitute of imports and these

industries would need protection at their initial stage. Another supportive measure of fixed

exchange rate was also adopted to get access to cheap imports of capital goods.

Historically import-substitution proved to be inefficient in most of the countries. Krueger

(1997) explains that protectionist measures violated the basic principle of the comparative

advantage. Moreover it increased capital intensity, unemployment, inflation and foreign

4 However central banks are becoming increasingly independent as a result of economic reforms among developing

countries.


8

borrowing. Export and agriculture sectors were neglected therefore export earnings were

very low and balance of payment was deteriorated. Fiscal deficit and higher borrowing

caught the countries to debt trap. The resulting debt crises in the mid-1980s led to the trade

liberalization policy as advised by donor organizations, especially the World Bank and

International Monetary Fund. Moreover East Asian miracle also directed towards export

led growth policies therefore countries moved from an inward oriented trade policy

towards outward oriented policy.

To stimulate the economic growth, development and poverty reduction world integration

has proven a potent instrument for developing countries. The globalization and integration

has raised living standards of the people all over the world. Trade liberalization has

changed the export pattern of developing countries. Share of manufacture export has

increased in many developing countries while share of primary export has declined.

Contribution of manufactures has risen to 80 percent in total exports of developing

countries. Many developing countries in Asia and Latin America have made progress due

to the participation in global trade. Trade liberalization has also helped these countries to

attract foreign direct investment inflows. This is true for China and India since they

incorporated trade liberalization and other market based reforms and also other countries

in Asia, like Korea and Singapore. The developing countries that reduced the trade barriers

quickly developed more in 1990s than those that did not.

Though protection has dropped significantly over the past three decades, it remains

significant where developing countries have comparative advantage; mostly in areas such

as agriculture goods or labor-intensive manufactures. Trade liberalization also entails

substantial cost to developing countries due to loss of quota rents and the worsening of

terms of trade. Tariff has been a larger source of government finance in many developing

countries therefore in order to manage their budgets these countries will have to


9

compensate through large increases in other taxes. It is also argued that liberalization

brings with itself important distributional changes in domestic economies. It has worsened

the income distribution, decreasing the relative wage of low-skilled workers, by

encouraging the adoption of skill-biased technology.

Financial liberalization denotes to ease restrictions on capital flows across a country’s

borders by domestic residents and foreigners. Openness to capital flows makes investors

or countries sensitive regarding corporate or capital tax rates, changes in interest rates,

credit controls etc. Debate on the merits of financial liberalization started after the severe

consequences of the emerging market crises of the 1990s, particularly the Mexican and the

Asian crisis. There is a broad literature trying to assess the benefits from financial

integration. Empirical literature provides the evidence of some direct channels through

which financial liberalization could benefit developing countries.

Risk sharing is regarded as one of the important channels. This risk sharing process

ultimately reduces the level of income volatility. Regarding developing countries literature

does not provide any reliable evidence of such volatility reductions as a result of financial

liberalization. During the 1980s and 1990s as a result of increased liberalization

consumption-growth as well as income volatility increased in the more financially

integrated economies (Prasad et al. 2003).

The second major channel describing the benefit from capital account liberalization is the

relaxation of capital scarcity or borrowing constraint in developing countries. Gourinchas

and Jeanne (2006) provide the evidence that benefits to developing countries from foreign

borrowing are very little because of insecure property rights. Prasad and Rajan (2008)

explain that over the 2000s, there was evidence of capital flows from poor to rich

countries, rather than from rich to poor. Only exception was the FDI that followed the

predictable pattern of moving from rich to poor countries.


10

Kose et al. (2006) define four structural characteristics of an economy that can raise the

benefits countries obtain from financial liberalization: improved financial sector, over all

institutional quality, the macroeconomic policy and the trade openness. Financial sector

distortions have historically lead to financial crises. Various other institutions also play an

important role for financial inflows. These include protection of property rights, political

stability, judicial efficiency and the control of corruption. Institutional weaknesses reduce

the overall level of financial inflows to an economy. The macroeconomic policy also plays

an important role to stabilize the capital flows. Institutions that ensure fiscal limits and

transparency can all participate to the stabilization of capital flows. The exchange-rate

regime also plays an important role regarding financial liberalization. Fixed or inflexible

exchange rate regime has caused most of the financial crises. Finally more openness also

decreases the exposure to a sudden stop in foreign lending. Martin and Rey (2006) explain

that higher trade barriers are prone to financial crash more likely.

The financial crises of Asia, Latin America and Russia provide the lesson that

liberalization of short-term capital flows has adverse consequences for developing

countries due to their volatile and procyclical nature. Nonetheless, long-term capital flows,

FDI flows particularly, are considered as stable and positively affect the long term growth.

The capital markets in developing countries are imperfect: there is the problem of

information asymmetry and investors’ behaviour is often based on herd instincts which

lead to unsustainable investment booms and then large outflows of capital.

1.2.4 Link between institutions and policies:

We conclude from the above discussion that developing countries tend to have the

characteristics of poor legal framework, inefficient governments, weak property rights

protection and contract enforcement. An insecure environment deters foreign firms to

invest abroad. Government finances in many developing countries are weak due to


11

inflexible public expenditures and low tax revenues which lead to high deficits and debts.

The lack of political stability and an inefficient bureaucracy allow rent-seeking to

continue. Moreover political corruption is also common in almost all the developing

countries. The institutional features of monetary policy are characterized by weak

financial sector, low reliability of monetary authorities, fiscal dominance and exogenous

shocks which slow down the transmission of monetary policy to the real economy. There

is little room for the enactment of a sovereign monetary policy in developing countries due

to the limited degree of central bank sovereignty. Macroeconomic instability, political

instability and other institutional weaknesses have destabilized the financial inflows to

developing countries. Financial sector distortions have historically lead to financial crises.

In the light of above discussion we accomplish that without a well-established and secure

institutional framework, that ensure policy implementation and enforcement, policy

objective cannot be achieved. For example strong budgetary institutions provide the rules

to govern the budget process and checks and balances over public finances. In the same

way a sovereign central bank can provide more consistent policy in addition to lower

inflationary outcome. Good quality institutions enable the countries to apply counter-

cyclical monetary and fiscal policies. Improved financial market transparency, strong

financial system and institutional checks and balances lead to stable trade and capital

flows.

1.3 Significance and contribution of the study:

The study highlights the importance of institutions in developing countries for steady state

growth as well as for policy stability and effectiveness. As discussed in the previous

section that policy failures in many developing countries were caused by weak institutions

and regulatory framework which have led towards the importance of institutions and their

strengthening.


12

Empirical literature on the institutions-growth nexus describes that institutions stimulate

the economic growth by creating a favourable environment for capital creation. Higher

economic growth is characterized by higher bureaucratic efficiency, lesser degree of

corruption, judicial efficiency and protection of property rights. Stronger institutions also

reduce the policy instability, uncertainty or volatility by putting constraints on the policy

makers thereby reducing uncertainty in private investment. Poor institutional structure

provides an environment that allows inefficient and politically motivated policies to take

place. Given the importance of institutions for investment and policy effectiveness

institutional reforms ranked high on the agenda of IMF and the World Bank containing

issues relating to market regulation, decentralization, tax reforms and public sector

management as well as corruption.

Study tries to find out the relatively unexplored areas on the relationship between

institutions, policies and economic growth. Detailed review of the literature, in the next

chapter, specifies that there is extensive literature available on the relationship between

institutions and economic growth as well as macroeconomic policies and economic

growth. However, not much work has so far been done on the institutions-policies link for

developing countries, specifically with respect to its implication for policy uncertainty or

volatility which provides the gap in the empirical literature as discussed in detail in the

next chapter (section 2.8) and also constitutes the contribution.

Study will also be useful to policy makers or authorities regarding policy perspective. The

study will also provide the help to other researchers, by providing a stimulus to carry out

further research on the same subject matter or related so as to increase the already existing

volume of knowledge.


13

1.4 Choice of the countries and time period:

We have selected the countries based on the percentile score on institutional quality index.

Table in the appendix-I provides the percentile score of 211 countries in the year 2014 as

provided by the World Bank, World Governance Indicators. Percentile score is also

divided into different categories which provides the guideline about the status of each

country at institutional index, table below provides this information.

Percentile score Status

0-10 Extremely low

11-25 Very low

26-50 Low

51-75 Average

76-90 High

91-100 Very high

A closer look at the table in appendix-I shows that low income countries lie in the category

of extremely low and very low at institutional quality index. Lower middle income

countries mostly lie in the category of low but with distance from average. Upper middle

income countries lie in the category of average and some closer to average. While high

income countries mostly lie in the categories of high and very high at institutional quality

index.

We have selected twelve developing countries from different regions, some lower middle

income countries and some upper middle income countries given the World Bank

classification. These are Pakistan, India, Bangladesh, Srilanka, Maldives, Nepal,

Philippines, Thailand, Vietnam, Brazil, Mexico and Kenya. As for as institutional status is

concerned, Pakistan persistently lie in the category of very low at institutional quality

index. Nepal and Kenya both keep switching between very low and low. India and

Vietnam both persistently lie in the category of low. Philippines and Brazil both lie in low

and closer to average. Bangladesh keeps switching between average and low. Maldives

and Thailand moves between average and closer to average. Srilanka persistently remains


14

closer to average. Mexico switches between average and closer to average. We have

skipped the categories of extremely low, high and very high. We have taken a mixed

sample of very low, low, closer to average and average (but with a distance from upper

limit) to avoid the biasedness. Table below shows the percentile score of selected countries

over time with their status as discussed above.

Table 1.1 Percentile score of selected countries at institutional index Countries 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 Status

Maldives 68.2 65.67 61.43 60.33 48.8 49.89 39 42.4 39.22 48.19 Average and closer to average

Thailand 59.1 61.15 62.06 50.01 52.07 43.92 43.1 43 44.18 43.96 Average and closer to average

Bangladesh 56.9 55.36 52.9 33.49 38.2 43.23 40.4 41.3 39.66 36.29 Average and low

Philippines 49.6 53.31 41.63 42.02 36 37.25 37.2 35 39.96 45.36 Low and closer to average

Nepal 44.2 33.87 32.76 29.19 20 24.25 23.8 22.2 20.87 26.69 Very low and low

Srilanka 42.8 42.19 42.76 48.31 44.7 42.09 40.2 40 41.86 44.72 Closer to average

Mexico 42.6 46.42 50.84 53.33 52.3 48.92 44.6 45.9 47.82 43.49 Closer to average and average

Vietnam 35.9 34.78 34.1 32.03 32.2 34.93 33.7 33.3 34.85 36.81 Persistently low

Brazil 32.8 34.74 33.46 34.75 38.8 41.43 41.9 41.6 43.47 43.15 Low and closer to average

India 24.2 35.13 32.04 31.07 32.1 28.83 29.9 29.2 28.34 26.7 Persistently low

Kenya 24.1 23.94 26.76 26.89 27 20.12 18 14.6 16.85 18.88 Very low and low

Pakistan 23.4 24.79 19.97 22.15 18.8 25.09 21 20.5 17.56 20.95 Persistently very low

As for as the choice of the time period is concerned macroeconomic stabilization, trade

and financial liberalization were imposed on developing countries in the form of

neoliberal policy agenda in the late 1980s while in1990s second generation reforms

highlighted the importance of well-functioning institutions for development. Therefore our

rational choice regarding the selection of the time period becomes from the decade of

1990s.

1.5 Objectives of the study:

Our empirical analysis will employ annual data for a set of 12 developing countries,

according to the World Bank classification, from South Asia, East Asia and Pacific, Latin

America and Sub Saharan Africa. The sample period spans from 1990–2014.

Keeping in mind the motivation and background of the study and also the significance the

main objectives of the study are following.

First, to identify the role of countries’ institutions and policies in economic growth.

Also the analysis of disaggregated institutions and economic growth.


15

Second, to analyze the effect of policy instability or volatility on economic growth.

Third, to develop a link between countries’ institutional environment and policy

instability or volatility.

Beside the main objective there are also other sub objectives;

To provide theoretical foundations to the per-capita growth equation.

To test for conditional convergence across countries and to determine the role of

traditional factors of production in economic growth.

To present an overview of the economies of selected countries with a dynamic

analysis of their institutions and policies.

To determine the level of volatility of individual countries and also cyclical

behaviour of policies in sample countries.

To provide suitable policy implications based on empirical findings.

Now we discuss our main objectives with more detail;

Regarding our first objective we will evaluate the role of institutions and policies (both

stabilization and liberalization policies) in economic growth. We will also disaggregate the

institutional quality into its components; voice and accountability, political stability,

government effectiveness, regulatory quality, rule of law and control of corruption for a

wider analysis and comprehensive policy implication. Empirical literature infers that

institutional quality affect the economic growth through capital formation. The objective

of stabilization policies is to ensure macroeconomic stability through fiscal and monetary

policy. The liberalization policies ensure movement towards more global integration, a

more free economy with less restriction on trade and capital flows. For a comprehensive

policy analysis we will use alternative indicators of fiscal and monetary policy and

similarly of trade and capital account liberalization. The empirical analysis will shed light

on the alternative institutions and policies for generating long term growth. Regarding the


16

institutional quality we will test the null hypothesis of no significant relationship between

institutional quality and economic growth against the alternative. Regarding the fiscal

policy we will test the null hypothesis that fiscal policy has no effect on economic growth

(Classical hypothesis) against the alternative (Keynesian hypothesis). Regarding monetary

policy we will test the null hypothesis that monetary policy does not affect economic

growth (Keynesian hypothesis) against the alternative (Monetarist hypothesis). Regarding

trade liberalization our null hypothesis will be to test that trade liberalization is not

associated with economic growth against the alternatives. For financial liberalization we

will test the null hypothesis that there is no significant relationship between financial

liberalization and economic growth against the alternatives.

First objective is related to the level effect of domestic macroeconomic policies on

economic growth. Second objective evaluate the effect of policy volatility on economic

growth as there is problem of frequent policy switching in developing countries, due to

some internal and external factors that lead to lower rates of investment and economic

growth by causing uncertainty to investors. We will test the null hypothesis that policy

volatility does not affect the economic growth against the alternative.

As described above that policy volatility or uncertainty is harmful to economic growth by

making investment uncertain therefore it is important to analyze the factors that contribute

to policy volatility. Regarding the third objective we will analyze the role of institutions

in reducing the policy instability. Empirical literature explicates that institutions play an

important role to reduce policy volatility or instability by putting restrictions or check and

balances on policy makers. We will test the null hypothesis that institutions do not affect

policy volatility against the alternative. Besides the institutional quality we will also

examine the effect of some domestic macroeconomic and external factors contributing to

policy volatility. This last objective will indirectly analyze the effect of institutions on


17

economic growth, by reducing the policy instability or volatility. The empirical analysis

will fill the gap in existing literature as discussed in section 1.4 and also identified by

literature gap in the next chapter (section 2.8).

1.6 Organization of the study:

Chapter one discusses the introduction, chapter two deals with theoretical as well as

empirical literature regarding the role of institutions and policies in economic growth

moreover the link between policy instability and economic growth and last the institution

policy link with the discussion of the literature gap. Chapter three describes an overview

of the economies of selected developing countries, dynamics of their institutions and

policies and an overview of institutional reforms. Chapter four develops the theoretical

foundations of the per capita growth model. It also discusses the variables and

methodology. Chapter five discusses the empirical results of the panel data model by using

generalized method of moments (GMM) introduced for dynamic panel data models. Last

chapter discusses the conclusion emerging from theoretical discussion and empirical

estimation. This chapter also presents policy recommendations and highlights the

limitations of the study and areas of future research.

1.7 Concluding remarks:

The chapter discusses in background of the study that policy failure in developing

countries was due to weak institutional structure; the failure of price reform and

privatization in Russia, failure of market-oriented reforms in Latin America and the

financial crisis of Asia were all the results of the lack of helpful legal, regulatory and

political framework. The review of institutions and policies in developing countries

indicate that the monetary transmission mechanism is weak in developing countries due to

weak monetary, financial and fiscal institutions. Government finances in many developing


18

countries are also weak which lead to high deficits, debts and debt-servicing obligations.

The lack of political stability and an inefficient bureaucracy allow rent-seeking to

continue. Financial sector distortions have historically lead to financial crises. All it

provides the rationale for the importance of institutions and their strengthening in

developing countries for policy effectiveness. The study tries to find out the relatively

unexplored areas on the relationship between institutions, policies and economic growth.

As there is extensive literature so far on institutions-growth relationship as well as

macroeconomic policies-growth relationship therefore the study contributes by filling the

gap on institutions-policies link for developing countries specifically the role of

institutions in reducing policy instability. Choice of the countries is based on the

governance status or percentile rank of the countries provided by the World Bank, World

Governance Indicators. Choice of the time period is relevant to policy initiatives in

developing as an agenda of neoliberal approach. In the light of motivation and significance

of the study there are three main objectives and also sub objectives. Main objectives

discuss the role of policies (both stabilization and liberalization policies) and institutions

in economic growth. In addition to the level effect of domestic macroeconomic policies in

economic growth the study also evaluates the volatility effect and last the indirect effect of

institutions in economic growth through reducing the policy instability or volatility which

contributes to the literature as an unexplored area of institutional policy link.

19

Literature Review

This chapter provides an overview of the available empirical and theoretical literature on

the link between policies, institutions and economic growth. Its main objective is to

discover the unexplored areas which need to focus and that require further research.

Chapter is divided into eight sections. First section discusses the available studies on the

relationship between institutions and economic growth. Second and third section presents

a brief overview of the available literature regarding liberalization policies, both financial

and trade liberalization, and economic growth. Fourth and fifth section deals with the

available literature regarding stabilization policies, both fiscal and monetary policy, and

economic growth. Section six provides an over view of the available literature on the

relationship between policy volatility and economic growth. Section seven discusses the

empirical evidence from the literature on determinants of policy volatility. Last section

discusses the literature gap.

2.1 Institutions and economic growth:

2.1.1 Theoretical review:

In the period of 1990s the institutional concept gained popularity, with the publication of

two revolutionary studies: “Institutions and Economic Performance” by Stephen Knack

and Philip Keefer and “Corruption and Growth” by Paolo Mauro. These pioneer studies

provided a motivation towards a new wave of research regarding the institutional

proposition in a cross country setting. Knack and Keefer (1995) describe that institutional

quality represented as secured property rights and contract enforcement, is important for

investment and ultimately for growth. Mauro (1995) explains that corruption is inversely

Chapter # 2

Chapter # 2 Literature Review

20

related to investment and growth. Further empirical investigations support these initial

findings. The literature provides the empirical support to the notions of North (1990) and

Olson (1994) who emphasized the role of protection of property rights and contract

enforcement for growth and prosperity.

Some earlier studies have highlighted the importance of economic and political freedom

for economic growth and development including Owens (1987) and Sen (1991). However

most of the previous literature emphasized only on some specific features of governance,

which are theoretical in nature.

Endogenous growth theory provides the evidence of conditional convergence which

depends on institutional characteristics of a country. New growth theory explains this

concept through “knowledge spillovers” assumption, where less developed countries can

catch up through technological development which in turn depends upon the institutional

measures. As discussed by North and Thomas (1975) that technological changes depend

on the prevailing institutions and their incentive structures.

2.1.2 Empirical review:

To date there has been an ample body of empirical literature that has examined the

institutional growth link. These studies have evaluated the effect of institutions on

economic growth by using different measures of institutional quality. Differences in

findings are based on changes in the sample period, sample size and specification. Below

we examine some empirical literature.

Mauro (1995) analyzes the association between corruption and economic growth for a

cross section of countries from 1980-83. Objective is to explore the ways through which

corruption and other institutional indicators affect the economic growth. Findings illustrate

that an important mechanism through which corruption affects the economic growth is by

depressing the private investment. He uses the data of Business International (BI) indices


21

on corruption, red tape, and the judicial efficiency. Political stability is also used

representing other indicator of institutional quality. He has also taken an aggregate

measure of bureaucratic efficiency, aggregating the above three indicators, because it’s a

more comprehensive index of corruption. Study contributes well to the literature by using

a comprehensive indicator of bureaucratic efficiency.

Knack and Keefer (1995) examine the link between property rights and economic growth

for a cross section of countries from 1974-89. The study contributes by using property

rights and rent seeking in growth model. Findings comprise that property rights are

associated with greater investment and economic growth besides they increase the rate of

convergence. The study contributes well regarding the indicator of property rights as many

earlier studies have used indicators of political stability to represent property rights; like

political freedom, civil liberties, coups and revolutions etc. But these indicators only

partially capture the variations in the property rights which incorporate considerable

measurement error.

Goldsmith (1995) observes the connection between democracy, property rights and

economic growth for 59 less developed and transitional economies. The study examines

the link among institutional factors and economic growth in the 1980s and early 1990s.

Study uses the data of political freedom from Freedom House while of economic freedom

from Heritage Foundation. Findings infer that democratic freedom and property rights

significantly contribute to economic growth. Results also imply that higher protection of

property rights is associated with more democratic economies due to the effect of strong

lobby, which induces the private investment and growth. The study is in contrast to many

other studies which show a negative effect of democracy.

Kaufmann et al. (1999) provide the evidence that better governance contribute to

development, such as higher per capita income, lower mortality rate and higher literacy


22

rate etc. The study uses a cross section of more than 150 countries. They compile a

comprehensive indicator of governance based on six aggregate dimensions of the

governance. These include; voice and accountability, political instability and violence,

government effectiveness, regulatory burden, rule of law, and control of corruption. All

these indicators significantly contribute to economic growth as well as development.

Study also checks the reliability of results exclusive of all OECD economies which

provides the similar results by assuring that differences in the sample do not matter. The

study does not discuss the channels through which governance will contribute towards

development. Revised version of 2008 extends the data further to 212 countries. Moreover

the revised version has also discussed a number of important measurement issues

regarding the construction of these indicators and implicit margins of errors.

Campos and Nugent (1999) evaluate the effect of institutions on the development of East

Asia and Latin America. Per capita income, infant mortality rate and adult literacy

represent the level of development of the countries. Four dimensions of governance are

addressed; the executive, the bureaucracy, the rule of law and civil society. The study

utilizes the data for institutional measures from three sources, ICRG, BERI and polity III.

Institutional characteristics of both regions are different so the study analyzed the data for

both regions separately and also jointly. As for as the differences in per capita income are

concerned strength of civil society significantly contributes in East Asia while rule of law

and bureaucratic efficiency play an important role in Latin America. Regarding the infant

mortality rule of law plays an important role in Latin America while in East Asia quality

of bureaucracy plays an important role. While regarding the adult literacy rule of law and

bureaucratic efficiency are significant for both regions. For Latin America rule of law

significantly contributes to development in all specifications while in East Asia


23

bureaucratic efficiency plays its role. The study can be enriched by expanding the sample

size and also other regions.

Mauro (2002) analyses the corruption growth relationship by extending his previous study

(1995), incorporating two models of multiple equilibrium. The two models view the

corruption from different angels. In first model individuals play role in corruption by

stealing from the government (offering bribe to obtain a driving license). While in second

model government steal from the public (political corruption), it incorporates political

instability in the model through the probability of reelection. The model obtains multiple

equilibrium in corruption, political instability and economic growth. Large public sectors

and more government intervention are associated with higher corruption in developing

countries. Broad policy implications imply comprehensive reforms moreover policies of

improved transparency.

Kaufmann et al. (2002) inspect the connection between income per capita and institutional

quality using governance indicators covering 175 countries for the period 2000-01 and

results are interpreted for Latin American and Caribbean countries. The findings show a

robust positive association between per capita income and institutional quality while a

weak negative correlation running in the opposite direction. The first highlights the

prevailing evidence regarding the significance of good governance for development while

second shows the lack of virtuous circles where higher growth leads to good governance.

The negative correlation can be attributed to the measurement error or the biased created

due to omitted variables. Moreover the elite influence and state capture are more relevant

to the developing countries. There is lack of much empirical evidence as this reverse

channel of causation has not been addressed in the literature. The study does not discuss

the channels by which institutions contribute to growth.


24

Glaeser et al. (2004) evaluate the association between institutions and economic growth

using cross country evidence from 1960-2000. The study examines two hypotheses first,

institutional development promotes human and physical capital investment and therefore

economic growth while the second stresses the need for human and physical capital to

promote the institutional development. The reverse that growth in income and human

capital causes institutional improvement relates to the Martin Lipset (1960) hypothesis.

Lipset relate his hypothesis to the economic success of East Asia in the post war era. Three

measures of institutional quality are used; risk of expropriation by the government,

government effectiveness and constraints on the executive. Results provide the support to

the Martin Lipset (1960) hypothesis. We cannot generalize these results, which relates to

the specific post war experience of East Asian countries. Moreover there might be some

conceptual problems related to the institutional measures used in the study as well as the

limitations of econometric techniques.

Chong et al. (2004) explore the link between institutional quality and economic growth for

Latin America. History of Latin American shows the role of military supported

autocracies. Institutions were characterized by bureaucratic traditions and highly

politicized, passed over from its Spanish and Portuguese tradition. Study uses three

measures of institutional quality; possibility of expropriation, abandonment of contracts by

government, law and order tradition from International Country Risk Guide (ICRG) and

Business Environmental Risk Intelligence (BERI). Since the subjective measures can be

biased, as they depend upon the rating of experts. As an objective measure of institutional

quality they also use Contract Intensive Money5 (CIM). Higher the ratio more favorable

5 It is the proportion of non-currency money to the total money supply, or (M2 - C)/M2, where M2 is broad

money and C is currency held outside banks.


25

the institutional environment will be. Results show that all the measures of institutional

quality contribute to economic growth.

Drury and Lusztig (2006) explore the association between corruption, democracy and

economic growth for more than hundred countries from 1982–97. Corruption is adversely

related to economic growth while democracy indirectly affects the growth through its

effect on corruption as it alleviates the harmful effects of corruption. Although corruption

certainly occurs in democracies, the electoral system inhibits politicians from engaging in

corrupt activities by threatening their political endurance.

Siddique and Ahmed (2010) explore the institutional-growth relationship for Pakistan

from 1984-2006. Findings provide the evidence of long run association between the both.

While there is evidence of unidirectional causality running from institutions to economic

growth. For institutional measure study develops an index of institutionalized social

technologies. This index is made up of risk reducing technologies. This index put weights

to technologies that help to restrict the rent seeking prospect arising from institutions and

political system. It is proposed that there is need of strong political and social institutions

that reduce rent seeking behaviour and also businesses risk. Study contributes in a way

that it incorporates the institutional quality index different from all other studies. But the

significance of the study can be increased by incorporating other indicators of institutional

quality commonly used in the literature which will also provide a sensitivity analysis.

Gani (2011) empirically examines the governance growth link for 84 developing

economies using panel data from 1996 – 2005. The study examines the various

dimensions of governance using data from (WGI) for low and middle income countries.

Regression specification shows that political stability and government effectiveness are

directly associated to economic growth while voice and accountability and corruption are

adversely related to economic growth. The regulatory quality and rule of law remain


26

insignificant. The results for voice and accountability is surprising, which is mostly

positive in many other studies as well as rule of law and regulatory quality, which are

insignificant. The study does not provide the rationale for such relationship.

Ahmad and Marwan (2012) examine the relation between institutions and economic

growth in a panel of 69 developing countries from1985-2008. Three institutional measures

are used; property rights, bureaucratic efficiency and political institutions. Three sources

of institutional variables are utilized; International Country Risk Guide (ICRG), Gastil

index and polity II. Property rights appear as the most significant institutional indicator for

growth for whole sample as well as for East Asia. Bureaucratic efficiency also contributes

to growth in whole sample but not in East Asia. Negative coefficient for political rights for

East Asia favours the non-democratic government in the East Asian economies. Study

confines that institutions affect the growth through total factor productivity.

Albassam (2013) observes the relationship between governance and economic growth in

the presence of crisis. The study is different in a way that most of the earlier literature

discusses only the governance growth link. The study examines the relationship between

governance and growth in the presence of crisis. Economic crisis of 2008 has affected the

economies of all the countries economically and politically as a result of weak

infrastructure at global as well as local level. Taking the data of all the countries from

(WGI) study considers the time period from 2006-11. Study divides the sample into pre

(2006-08) and post crises period (2009-11). Results of the correlation show that before and

after crisis a significant relationship holds between economic growth and each indicator of

governance. Further he analyzes the effect of level of development on this relationship, by

dividing the sample into four groups; very high, high, medium and low level of

development, based on HDI statistics. Now previous results do not hold for each group. In

groups with very high and high level of development previous relationship hold but in


27

other two groups reverse hold. It is suggested for the governments to adopt the measures

that maintain a strong association between governance and economic growth in the long

run as well as short run.

Fayissa et al. (2013) evaluate the relationship between governance and economic growth

for 28 Sub Saharan African countries from 1990-2004. The economies of these countries

are characterized by political instability, government ineffectiveness, poor law and

massive corruption which represent the bad governance. Six governance measures are

used both at aggregate and disaggregate level as given by (WGI). Results imply that good

governance positively contributes to economic growth regardless of the measure used.

Government effectiveness highly contributes to economic growth followed by voice and

accountability while control of corruption has least contribution. Study also evaluates the

impact of good governance on different income groups (low, middle and high income

groups). Study concludes that good governance is important for growth especially for

those countries which are at lower level of income.

Yerrabati and Hawkes (2015) empirically examine the relationship between governance

and growth for South Asia, East Asia and Pacific region from 1980-2012. Governance has

been a highly controversial matter in the Asian context. Six disaggregated measures of

governance by (WGI) are used, findings through the Meta regression analysis imply that

voice and accountability and extent of corruption are positively related to economic

growth. They explain that if corruption reduces the bureaucratic delays then it facilitate

investment and hence economic activity. Political stability, government effectiveness and

rule of law are negatively associated to economic growth. Regarding the political stability

it is argued that if it is achieved through oppression or if it produces stagnation then it

negatively contributes to economic growth. Negative effect of government effectiveness is

surprising. Negative effect of regulation is also surprising as most of the countries in this


28

region have gone under deregulation process since late 1980s. There is need of further

research regarding this aspect of institutions. The study does not discuss the channels

through which governance will affect the growth.

Bhattacharjee et al. (2015) empirically examine the role of institutions in economic growth

for four major South Asian economies. Poor institutional quality especially political

instability and crisis along with other factors make South Asia an appropriate case

regarding this context. Institutional measures provided by (WGI) are used for the period

1996-2010. Findings from both the fixed effect and dynamic panel data by GMM provide

the evidence that institutions significantly contribute to economic growth. Voice and

accountability and government effectiveness contribute to economic growth while others

measures of institutional quality remain insignificant in explaining the growth. Speed of

convergence slightly improves while controlling voice and accountability. The study

proposes reforms regarding the institutional framework. The study does not discuss the

rationale for the insignificant indicators.

2.1.3 Concluding remarks:

Empirical review of literature on institutions-growth link shows that these studies have

concentrated on either one or more institutional measures. Main sources of the institutional

measures are; Worldwide Governance Indicators, International Country Risk Guide

(ICRG), Business Environmental Risk Intelligence (BERI), Freedom House and Polity.

Dimensions of institutions that these sources discuss are; political rights, economic

freedom, bureaucratic efficiency, corruption and regulatory infrastructure. Studies use

different sources also for sensitivity analysis. We have examined the empirical literature

regarding developing countries. All the studies included show that institutions positively

contribute to economic growth except one study, Yerrabati and Hawkes (2015), which

shows the negative association between institutions and economic growth because many


29

of the individual indicators are adversely associated to economic growth. There is also

another study which explains the inverse causality from economic growth to institutional

quality, Glaeser et al. (2004), supporting the East Asian experience. The way through

which institutional quality enhances economic growth is the provision of secure

environment for investment. Regarding individual institutional indicators voice and

accountability, government effectiveness, rule of law positively contribute to economic

growth. Political stability, regulatory quality and corruption show mixed results, some

studies show positive effect, some show negative or insignificant effect. Political stability

or democracy may indirectly contribute to economic growth through reduction in

corruption and increasing bureaucratic efficiency, rule of law which provides a favourable

environment for investment. While the negative sign of political stability shows that that if

it is achieved through oppression or if it produces stagnation then it negatively contributes

to economic growth. Moreover the negative sign for those samples where East Asian

countries are included shows that autocratic government are able to govern the markets

and pursue pro-growth policies. Regarding corruption only one study shows that

corruption increases the growth while all other studies follow the empirical literature that

corruption reduces the economic growth by misallocation of resources. Negative sign is

supported that some types of corruption might increase the growth by reducing the

bureaucratic delays and contribute to investment. Negative sign of regulatory quality in

one study is surprising as most of the developing countries have reduced the regulatory

burden to promote economic growth. Excess regulatory burden might retard the growth

but it needs further research. At the end we conclude that differences in institutional

measures, time period, sample and econometric methods have provided mixed results.

Most of the studies do not explain the channels through which institutions contribute to


30

economic growth. Moreover there is limitation of the data of institutional quality, which is

subjective and more prone to measurement error.

2.2 Financial liberalization and economic growth:


McKinnon and Shaw (1973) introduced the concept of financial liberalization. They

recognized that the inadequate growth performance of developing countries is caused by

financial repression therefore they advocated the need for financial liberalization.

Financial liberalization theory explains that financial control keeps interest rates low

which discourages savings and investment. Under a regime of repression low return

projects will be under taken therefore the quality of investment will be low. With financial

liberalization interest rate will increase thereby encouraging the savings and investment

which will encourage high yield projects. The theory of financial liberalization, since

McKinnon (1973) and Shaw (1973) has advanced merely focusing on credit markets

towards the equity markets and their association with economic growth in developing

countries.

Orthodox economists based their arguments on the assumption that markets are efficient.

Opponents of capital account liberalization propose that it makes a country prone to

external shocks and capital flight thereby reducing economic growth. Arnott, Greenwald

and Stiglitz (1994) criticize that poor information prevalent in the financial markets of less

developed countries can be harmful to financial liberalization. Van Wijnbergen and Taylor

(1983) criticized the McKinnon-Shaw hypothesis. They explain, using Tobin’s portfolio

framework for a household, that households will make substitution for gold or cash and

loans in the informal sector as a result of higher interest rate.


31


Over the past three decades there has been enormous capital account liberalization in

many countries, including developing and emerging countries. Liberalization has provided

benefits to some countries while some have not experienced higher economic growth or

have even undergone severe financial crises and recessions. Hence, a question as to

whether financial openness is crucial to sustained economic growth requires further

clarification. Below we review some empirical literature regarding the relationship

between both.

Alesina, Grilli and Milesi-Ferretti (1993) provide the indication of a direct relationship

between capital account liberalization and economic growth for a sample of 20 high-

income countries from 1950s to the 1990s. They measure the openness by the share of

years in which transactions on capital account are unrestricted, as indicated by IMFs

Annual Report on Exchange Arrangements and Exchange Restrictions. While Grilli and

Milesi-Ferretti (1995) considers a larger cross section of 61 countries and the findings

show an inverse relation between capital account openness and economic growth in a

sample dominated by developing Countries. But both the studies do not explain the

channels through which this relationship might occur.

Quin (1997) examines the correlations of capital account liberalization and economic

growth for a sample of 65 OECD and non OECD countries from 1958-89. Using de jure

measure of IMF capital account openness he finds a positive correlation between the two

variables. Another study by Quin et al. (2008) also provides the same findings for 95

developed and developing countries. The study uses a new measure of capital account

liberalization6 that also not only considers the limitations or controls but also the

magnitude of de jure controls for residents as well as nonresidents. The study replicates six

6 It is scaled from 0–4, where 4 represents full capital account liberalization.


32

prior studies that show conflicting results. With new measure of capital account liberation

findings show significant results. They argue that measurement error in capital account

variables, different time periods, choice of methods and collinearity among the variables

might be the reasons for different outcome of previous studies.

Rodrik (1998) evaluates the link between capital account openness and economic growth

for a sample of 100 developed and less developing countries using data for the period

1975-1989. He uses binary measure for financial openness constructed by the IMF. He

finds no association between financial liberalization and economic growth. He provides

the evidence of Asian financial crisis which tells us that liberalization will always bring

financial crises and there is no magic bullet to stop them. Interacting capital-account

liberalization with institutions quality also provides insignificant results.

Edwards (2000) investigates the effect of capital mobility on economic performance of 20

industrial and developing economies during the 1980s. He evaluates the behaviour of FDI

flows, debt flows and portfolio flows during the sample period. Behaviour of capital flows

seems different across regions and periods. Using Quinn’s measure of openness he

concludes that liberalization contributes to growth in high-income countries while slows it

down in low-income countries. However, the evidence also points to the fact that the

positive impact of liberalization is constrained to a certain degree of economic

development. Findings propose the sequencing of capital account liberalization.

Klein and Olivei (2001) explore the relationship between capital account liberalization and

economic growth through the channel of financial deepening in a cross section of

developed and developing countries from 1986-95. They use de jure measure of

liberalization. Results regarding the developed countries infer that these countries with

higher financial liberalization have experienced greater financial deepness than countries

with higher capital controls and enjoyed higher economic growth. Results of the sub


33

sample show that financial liberalization does not provide same benefits to all countries.

Benefits are more concentrated towards developed countries. Results imply that policy

reforms in developing countries should concentrate on legal, economic and social

institutions before the liberalization of capital account, in order to have greater financial

depth. Study can be enriched through sensitivity analysis using other measures of

liberalization.

Arteta et al. (2001) empirically explore the association between capital account

liberalization and economic growth for 61 developed and developing countries. Capital

account openness is measured by Quinn’s index of liberalization and IMF capital account

openness measure. The findings imply that liberalization of capital account contribute to

economic growth only in countries that have well developed institutions. The study also

tests two hypotheses regarding sequencing of capital account. Results suggest that capital

account openness contributes to growth when a country has greater macroeconomic

stability and higher degree of trade openness.

Reisen and Soto (2001) observe the relationship between private capital inflows and

economic growth in a panel of 44 developing countries over the period 1986–97. Study

highlights that domestic saving solely is not enough to enhance the economic growth there

is also need of foreign resources of finance. Study emphasizes on the wide-ranging

categories of inflows; foreign direct investment, portfolio equity investment as well as

short-term and long-term bank lending. The findings propose that to stimulate the long run

growth developing countries should boost foreign direct investment and portfolio equity

investment.

McLean and Shrestha (2002) investigate the correlation between international financial

integration and economic growth for 40 developed and developing countries. The sample

period spans 1976–1995. They use the data of total capital inflows also disaggregated into


34

FDI inflows flows, portfolio inflows and bank inflows. The relationship between capital

account liberalization and economic growth is not robust. Findings regarding FDI and

portfolio flows remain robust moreover FDI remains the largest contributor followed by

portfolio flows and bank flows. Historically the contribution of foreign direct investment

has remained higher in developing countries as compared to other forms of capital flows.

Edison et al. (2002) examine the link between financial integration and economic growth

for a sample of 57 countries from 1980-2000. They use different measures of financial

liberalization (de jure as well as de facto measures); IMF’s restriction measure, Quinn

(1997) measure of capital account restriction, total stock of capital flows and stock of

capital inflows by Lane and Milesi-Ferretti (2002). De jure measures show the

government restrictions but do not show the magnitude and effectiveness of government

restrictions whereas de facto measures are not the subjective measures and show actual

integration. Findings do not provide the evidence of robust relationship between financial

openness and economic growth. Moreover findings also do not remain robust when

controlling for level of development, financial deepening, institutional and policy

characteristics. Study does not explain the underlying causes of such results.

Eichengreen and Leblang (2003) explore the association between capital account openness

and economic growth for a panel of 21 countries from 1880-1997 and as well for wider

panel for the post 1971 period. Capital controls is captured by presence or absence of

control during the initial year of each period while for recent years IMFs binary measure

of restrictions on capital transactions is utilized. They contend that previous studies

provide inconclusive results because they have not considered the impact of crisis on

growth and for the capability of controls to limit those effects. They consider these effects

by including capital controls and crisis in their dynamic panel. Findings infer that controls

neutralize the impact of crisis on growth and otherwise they have no additional effects.


35

Singh (2003) examines the empirical literature regarding capital account liberalization,

specifically short and long term capital account liberalization. The study consists of 118

developed and developing countries spanning the period 1972-98. The study analyzes the

relationship between capital flows and economic growth as well the effect of short run and

long run capital flows on saving and investment behaviour. Findings provide the evidence

of adverse consequences of short-term capital flows in Asia and Latin America in the

1990s. Contrary to this, the long term capital flows are considered more stable and growth

promoting. Such flows contribute to growth through better technology and access to an

improved human capital.

Bekaert et al. (2005) analyze the impact of financial openness on economic growth,

especially equity market liberalization. They use panel data of 95 countries from 1980 to

1997. Different de jure measures7 of capital account liberalization are employed for

robustness where each measure represents 0-1 scale. For robustness they also use

alternative measures of financial liberalization: First sign measure, capital intensity

measure, IMF openness measure and the other proposed by Quinn (1997). As the

liberalization effect is not expected to be same in all countries so heterogeneity effect is

related to the reforms regarding financial development and quality of institutions. Findings

imply that financial openness decreases the cost of capital thereby increasing the

investment and the efficiency of investment which leads to higher growth. In addition,

countries with improved legal structure, better institutional quality and supportive

investment climate show larger growth effects. Results remain valid with different group

of countries, measures of financial liberalization, regional indicators and other

specifications.

7 See for detail Bekaert et al. (2005)


36

Bonfiglioli (2005) evaluates the effect of financial liberalization and crises on investments

and productivity in a sample of 93 countries from 1975 to1999. He employs two measures

of openness one, de jure measure, for capital account openness and other for equity market

openness by Bekaert et al. (2003). He also uses binary variable for banking crisis. Study

discusses two channels through which capital account openness contributes to growth;

investment and productivity. Findings imply that financial liberalization boosts

productivity growth through financial development. Capital account liberalization

increases the likelihood of financial crises in developed countries only which dampens

both investments and TFP. Institutions and level of development indirectly enhance the

positive effects of financial openness on productivity.

Mody and Murshid (2005) evaluate the link between capital flows and investment for a

panel of 60 developing countries from different regions for the time span 1979 to 1999.

Study uses aggregate capital flows and also their components; foreign direct investment,

portfolio flows and bank lending. For financial integration binary variable of liberalization

dates is used. Findings show that main channel of the capital flows is foreign direct

investment (FDI) whereas the portfolio investment has the characteristic of weak

investment stimulus. Findings propose that stronger policy environment will not only

stimulate the foreign direct investment in these economies but it can also strengthen the

link between foreign inflows and domestic investment.

Kim et al. (2012) examine the dynamic relationship between financial openness, economic

growth and macroeconomic uncertainty for a panel of 70 developed and developing

countries for the period 1960-2007. They use de facto measure of financial liberalization;

external financial stocks, stock of inflows and outflows as a ratio to GDP and FDI stocks.

Findings provide the evidence of adverse effects of financial liberalization in the short run

while favourable effects in the long run. Liberalization also reduces macroeconomic


37

uncertainty in the long run while increases it in short run. Liberalization increases the

chances of financial crises and instability that have short-run concerns but also strengthens

financial sector that affect long-run growth and macroeconomic uncertainty.


Despite intensive research regarding the association between capital account openness and

economic growth literature has produced conflicting results; positive, negative or

insignificant and conditional on other factors. An important issue regarding the capital

account liberalization is related to its measurement. There are de jure measures of capital

account liberalization that are mostly used; IMF capital account openness measure, Quin

(1997) measure of capital openness, Bekaert and Harvey (2002) measure of equity market

liberalization, Chinn and Ito (2008), Schinlder (2009) and there are many other such

measures available developed by many researchers. All these measures are based on

information by IMFs Annual Report on Exchange Arrangements and Exchange

Restrictions. All these are binary or subjective measures which only describe the presence

or absence of restriction and also have certain other shortcomings. Many researchers have

explained that variability in the results regarding capital account liberalization is also

caused by these subjective measures that increase the possibility of measurement error.

There are some studies that provide a positive association between capital account

liberalization and economic growth. These studies have used the data prior to the financial

crisis or of shorter span that undermines the effect of crisis. Few studies provide the

evidence of positive effect only in long run but not in the short run. Some studies consider

only few low income developing countries and more developed countries and find the

positive effect only for developed countries. Positive effect indicates that financial

liberalization decreases the cost of capital thereby increasing the investment and the

efficiency of investment which leads to higher growth. Empirical evidence also indicates


38

that financial liberalization does not provide same benefits to all countries, benefits are

more concentrated towards developed countries having well developed legal, financial and

institutional framework and fewer market distortions. Disaggregated analysis of capital

flows shows that the long term capital flows (particularly FDI) are considered more stable

and growth promoting. Such flows provide the access to technology to poor developing

countries.

Studies that show the negative correlation between the both are either of developing

countries or they explain that capital account liberalization brings with it financial crisis

mostly in developing countries that deteriorate the long run growth and some discuss that

negative relationship exists only in short run. Moreover capital account liberalization

negatively contributes to growth in countries having lower level of development, weak

institutional and financial structure and poor macroeconomic environment.

Some studies show insignificant or non-robust effect of capital account liberalization on

economic growth. It proposes sequencing of capital account liberalization and

strengthening of legal, economic and social institutions before the liberalization of capital

account.

Many studies do not explain the channels through which capital account liberalization

contributes to growth. We conclude that measurement error in liberalization measures,

sample selection, time period and methodology all contribute to different findings.

2.3 Trade liberalization and economic growth:


Trade has been regarded as a source of efficient allocation of resources and well-being in

orthodox theories, since the Ricardian era. The neoclassical theory proposes that trade

liberalization increases the output and consumer welfare due to efficient resource

allocation and lower prices of output and intermediate inputs.


39

Differences in opportunity cost between the countries determine the pattern of trade in the

Ricardian model. In the absence of trade barriers comparative advantages determine

country’s trade pattern which ensures efficient resource allocation and income distribution.

Herschel-Ohlin model determines the trade pattern through the relative abundance of

factors and their intensity in production. Models of imperfect competition propose that

trade openness and liberalization provides better resource allocation and enhances welfare.

Free trade between the countries increases competition which ultimately leads to lower

prices of inputs and output. Additionally higher openness becomes a source of technology

and which increases the growth.

The predictions of traditional trade theories, Heckscher-Ohlin and Stolper-Samuelson

models, failed abruptly as the resource abundant countries were not growing by utilization

of their abundant factor. Prebisch-Singer theory explains that rapid deterioration of the

terms of trade was the main cause of this failure due to the heavy dependence of

developing countries on primary commodities exports.

The failure of the traditional theories provided the space for the new theories which

emphasize on the industrialization and liberalization as the engine of growth. Moreover

they also explain that most comparative advantages are not inherent and they might be

developed through learning-by-doing, knowledge creation and technology transfer.


Over the last 20 years trade liberalization in developing countries has often been

encouraged with the probability of higher growth nevertheless the evidence on its growth

promoting effects is mixed. Below we review some empirical literature.

Sachs and Warner (1995) explain that one of the sufficient condition for poor countries to

achieve higher growth and convergence lies behind the open trade policies. They introduce

an index of openness policy. The index is a dummy variable which classifies countries as


40

open or closed based on five criteria; tariffs, nontariff barriers, exchange rate distortion,

export marketing boards and socialist system of production. Countries are called open if

they do not fulfill any one of the criteria above mentioned. Findings show that countries

with liberal trade regimes experience 2.45 percentage points higher growth than those

under a restricted trade regime. A number of other researchers also used the Sachs and

Warner index as a measure of liberalization.

Harrison and Hanson (1999) examine the association between trade liberalization and

economic growth, employment and wage inequality. They estimate a cross-country growth

regression using individual indicators of the Sachs and Warner measure. Findings do not

provide a robust relationship between more liberal trade policy and economic growth.

They argue that previous studies that provide positive association between the both are

suffered from many econometric and data complications. Moreover the impact of

liberalization reforms on employment is small. Micro data for both Mexico and Morocco

from 1984 to 1990 provides the evidence of lesser profit margins and falling wages in

previously protected sectors. There is also evidence of rising wage inequality which is

against the Heckscher–Ohlin proposition.

The widespread belief that trade liberalization promote the growth is severely criticized by

Rodriguez and Rodrik (2000) by discussing the methodological errors in the five most

illustrative empirical studies regarding the relationship between trade liberalization and

economic growth; Dollar (1992); Ben-David (1993); Sachs and Warner (1995); Edwards

(1998); and Frankel and Romer (1999). They argue that these studies provide the strong

results which are caused either by misspecification or by the use of liberalization measures

that are proxies for other policy or institutional variables. They criticize the tariff averages

as they undervalue the high tariff rates while nontariff coverage does not discriminate


41

between high restrictive and less restrictive barriers. There are also conceptual

imperfections such as (effect of smuggling, data weaknesses, coding problems, etc.).

Zhang (2001) provide the evidence regarding trade liberalization, economic growth and

convergence for 10 East Asian economies from 1960 to 1996. East Asia has experienced

not only strong economic performance, but also rapid and impulsive integration over the

past few decades. The study examines the interrelationship between regional integration

and economic convergence. Exports as a ratio to GDP indicate to trade liberalization

measure. Findings provide the week evidence of convergence. It is argued that the kind of

FDI that some of the East Asian developing economies have attracted is mainly in labour-

intensive industries with low value-added, creating immiserizing growth. There is

evidence of substantial convergence of the four Asian NIEs8 and Japan. Study can be

criticized on the grounds of trade liberalization measure, exports as a ratio to GDP is a

poor indicator of liberalization which represents only trade orientation but not trade

liberalization. The evidence of week convergence among the East Asian economies might

be the result of this poor indicator of trade liberalization.

Greenaway et al. (2002) examine the impact of trade liberalization on economic growth

for a sample of 73 developing countries from 1975-93. They explore the relationship in a

panel framework using three indicators of liberalization; World Bank (1993), Dean et al.

(1994) and Sachs and Warner (1995). First indicator is a binary variable which indicates

the beginning of reform, representing a country’s first structural adjustment loan (SAL).

Second indicator is of Dean et al. (1994), which assesses timing of liberalization with

reference to four indicators: tariffs, quotas, export barriers and exchange rate distortions.

Third indicator is of Sachs and Warner (1995), a measure of movement from a closed

towards open trade policy regimes based on five criterions also described previously.

8 Newly industrializing economies; Hong Kong, Singapore, South Korea, and Taiwan.


42

Findings imply that liberalization contributes to growth though the effect appears after lag

as liberalization never leads to an instant shift to free trade. Sachs–Warner index provides

the stronger growth effects and whereas (SAL) provides the weakest.

Wacziarg and Welch (2003) observe the link between trade liberalization and economic

growth for 141 countries from 1970-99. For the trade liberalization measure they use the

dummy variable approach developed by Sachs and Warner (1995) but with an extended

data set for the 1990s. Findings show that trade liberalization contributes to economic

growth, investment and trade openness. Countries with liberalized trade regimes have

experienced higher growth as compared to pre-liberalization period. Time pattern reveal

that growth is raised two years after the reforms. Individual country effects show that

countries where trade liberalization contributes to growth are those with massive trade

reforms.

Goldar and Kumari (2003) analyze the effect of import liberalization on productivity

growth in Indian manufacturing industries during 1990s. During the decade of 1990 major

economic reforms took place in India regarding industrial and trade policy. The objective

of these reforms along with changes in industrial policy was to make industrial sector

more efficient and technology oriented. Tariff rate was reduced and quantitative

restrictions were also removed. Study compares the productivity growth of major

manufacturing and industrial groups for the post reform period (1990s) with pre reform

period (1980s). Findings show that reduction in the effective protection to industries

increased the productivity growth.

Dollar and Kraay (2004) discuss an important dimension of liberalization, its effect on

inequality and poverty. They have selected a sample of developing countries that have

substantially reduced tariffs and experience large increases in trade volumes since 1980.

China, India and numerous other large economies are included in this sample. Study


43

conducts analysis of 39 developing countries where changes in trade volumes indicate the

liberalization. Per capita growth rates of the economies have increased in the 1990s

comparative to the 1980s; China, Argentina, Philippines, Mexico are few of the successful

examples. Findings show that greater openness has reduced the gap between rich and poor

countries. Inequality has reduced in many countries such as India, Malaysia, Philippines

and Thailand. Absolute poverty has declined sharply in globalizing economies in the past

20 years. Findings are contrary to many other studies exhibiting that globalization hurts

the poor.

Aksoy Ataman (2006) analyzes the growth effects of trade liberalization, before and after

the trade reforms, for 39 developing countries from 1970-2004. He uses dummy variable

representing liberalization (zero for pre reform period and one after reform period). Trade

liberalization reveals a significant increase in GDP. Moreover, trade liberalization has also

increased investment and manufacturing exports. Acceleration occurred irrespective of

region and income per capita level moreover small countries benefited most from the

reforms. It is concluded that in developing countries trade liberalization has contributed to

sustained economic development.

Yasmin et al. (2006) examine the role trade liberalization in economic development of

Pakistan. Four measures representing economic development are examined; per capita

GDP, income inequality, poverty and employment over time span 1960-2003. For nearly

four decades Pakistan has followed a mixed inward-oriented/outward-oriented trade

policy. But this policy generated rent seeking attitudes, anti-export bias and inefficiencies.

Therefore benefits of outward-orientation policies motivated Pakistan to open up its

economy for trade in the early 1990s. Findings imply that trade liberalization has reduced

the GDP per capita. This is in contrast with previous literature. It may be due to the import

substitution policies. It has increased the employment level while it has no effect on


44

poverty and distribution of income has become worse. Liberalization has reduced the

proportion of labor in production and concentration of income more in favor of capital

owners. The study can be enriched by undertaking before and after analysis of

liberalization which will also provide a sensitivity analysis.

Morgan and S. Kanchanahatakij (2008) examine the effect of trade liberalization on

economic growth for a sample of 37 liberalizing countries from 1970-98. As a measure of

liberalization they use the liberalization dates from Sachs and Warner (1995) index and

updated by Wacziarg and Welch (2003). As this measure does not capture the extent of

liberalization therefore they also use another measure the ratio of trade taxes and several

measures of trade volume. Findings imply that trade liberalization promotes the economic

growth. It is concluded that countries can benefit from trade liberalization with lower trade

taxes, higher human capital and higher imports of R & D. It is proposed that to examine

the true impact of trade liberalization study of single country can provide a more fruitful

finding.

Chang et al. (2009) empirically explore that free trade contributes to faster growth using

an unbalanced panel of 82 countries spanning the 1960–2000. The sample includes 22

developed countries and 60 developing ones. Using two measure of outward orientation;

trade openness and import duties, they also find that to improve productive efficiency and

growth trade liberalization needs to be supplemented by corresponding reforms. These

include macroeconomic and institutional reforms (including governance and financial

development). Findings are robust to various specifications.

Ghani (2011) analyzes the link between trade liberalization and economic performance

(exports, imports and GDP per capita) for 24 OIC9 countries that have undergone trade

liberalization process between 1970 and 2001. Liberalization is represented by dummy

9 Organization of Islamic Cooperation.


45

variable that equals zero before liberalization and one after liberalization. Findings imply

that trade liberalization has improved GDP per capita but unlike the GDP the ratio of

exports, imports and trade has not improved much after liberalization. The improvement in

GDP per capita does not reflect the dynamic gains from trade as there is not much gain

from trade.

Mani and Afzal (2012) examine the effect of trade liberalization on the economy of

Bangladesh from 1980-2010. Liberal trade policies of late 1980s provided an opportunity

to Bangladesh economy to enhance economic growth and development. In the last two

decades Bangladesh has expanded its export oriented garment and textile industry. The

study analyzes the achievement of the economy in the sense of growth, inflation, exports

and imports after liberalization. Liberalization is measured as trade openness. Empirical

findings show that GDP growth has increased after liberalization. Liberalization has also

increased real exports and imports but it has not affected the inflation. Increase in exports

has increased the economic growth after 1990s. Use of other liberalization measures

commonly used in literature can strengthen the validity of results.

Falvey et al. (2013) observe the impact of trade liberalization on economic growth for 58

developing countries from 1970-2005. They use Sachs-Warner index of openness and also

the date of liberalization. In panel growth regression trade liberalization and openness

contributes to economic growth. They identify the effect of liberalization on economic

growth through four channels; capital formation, government finance, openness to trade

and price distortions.

Paudel (2014) investigates the relationship between trade liberalization and economic

growth for a large set of panel data covering the period of 1985-2010. He updates the

Sachs and Warner (1995) index of trade liberalization for 193 countries up to 2010.

Findings comprise that trade liberalization positively contributes to economic growth and


46

consistent with the previous literature. Study concludes that not all income group benefit

equally by the liberalization their stage of development matters to benefit from

liberalization. Their trade and investment capability, and distortion level determines the

benefit from the liberalization.


Literature on trade liberalization and growth is not as broad as that on trade orientation and

growth. Most of the literature identifies positive association between trade liberalization

and economic growth. Very few studies find no relationship, or even a negative one

between both variables. Some studies emphasize on other conditional factors to get the

benefit of liberalization. Most of the literature also undertakes before and after analysis.

Most of the literature that emphasizes on the contribution of trade liberalization in

economic growth analyses its role indirectly through different channels; capital

accumulation, export diversification, higher imports of R & D that indicate technology

transfer and through total factor productivity (TFP) enhancement. In the same way few

studies discuss that contribution of trade liberalization in economic growth can be

enhanced through macroeconomic and institutional factors as well as level of development

of countries also matters to benefit from liberalization.

The channel through which trade liberalization negatively contributes to economic growth

explains the evidence of increase in poverty, income inequality and declining wages.

Liberalization has reduced the fraction of labor in production making distribution of

income concentrated towards capital owners. It is also argued that imports increase after

liberalization and generally trade balance become worse. In the same way only few studies

discuss that trade liberalization and growth are unrelated and do not provide robust results.

Main reason of no association is the misspecification and use of misleading indicators of

trade liberalization.


47

Normally the indicators of liberalization that are extensively used in the literature are

subjective measures; dates of liberalization, Dean et al. (1994) and Sachs and Warner

Index (1995). All these are dummy variables that do not show the extent of liberalization

and as well the policy reversals. Although most of the studies use trade openness as an

indicator of liberalization but it’s the measure of trade orientation not liberalization.

Rodriguez and Rodrik (2000) criticize the previous literature on the grounds of proxies

used.

2.4 Fiscal policy and economic growth:

2.4.1Theoretical review:

Classical model has the characteristics of perfectly competitive markets and there is price,

wage and interest rate flexibility. It assumes that there is full employment in the economy

and the aggregate supply curve becomes vertical. Higher government expenditures raise

the interest rate through the demand for funds, deficit financing, which reduces the private

investment. This crowding out effect offset any positive effects of the policy implemented

thus fiscal policy has no effect on the economy and it cannot be used as a stabilizing tool.

Keynesian theory is characterized by short run price rigidity while individuals experience

money illusion10

. There is unemployment in the economy as there are unused resources.

Aggregate supply curve is fully elastic in short run at unchanged prices while it is vertical

in the long run at full employment. Fiscal policy significantly affects the output and

employment while the total effect of higher government spending depends on relative

magnitude of the multiplier and crowding out effects (Mankiw 2000).

In the neoclassical model there comes the role of expectations, workers predict the price

level and adapt their expectations at the real level of prices (P = Pe). Differences between

the real and the expected levels of prices in short run can affect the level of equilibrium

10

It refers to the behavior of people to think of money in nominal, rather than real, terms. The nominal value

of money is wrongly considered for its real value.


48

output and the aggregate supply curve becomes positive sloped in the short-run. While in

the long run it becomes vertical therefore for the stabilization of the economy fiscal policy

is not important. The neoclassical model has been used widely for the analysis of fiscal

policy and was developed by Lucas, Sargent and Wallace.

Unlike the Keynesian theory the assumption of money illusion is not central in neo-

Keynesian models. Due to imperfect information, as workers do not have complete

knowledge regarding future prices, economic activity fluctuations. Aggregate supply curve

is more elastic and the level of output fluctuate more in the short run.

2.4.2 Empirical Review:

Fluctuations in fiscal policy either through taxation or expenditure have been extensively

investigated in the empirical literature. Endogenous growth models predict that the effect

of fiscal policy on economic growth is of both temporary and permanent nature. Empirical

studies regarding the relationship between fiscal policy and economic growth, however,

have produced mixed outcomes. Below we review the literature regarding developing

countries.

Barro (1989) analyses the relationship between growth, savings and government policies

for a cross section of about 120 countries from 1960-85. Government consumption

expenditures excludes the defence and education expenditures, which he treats productive

expenditures. Investment expenditures represents to a proxy for infrastructure activities

that affect the private investment. Defence expenditures represent national security and

property rights. Their effects on investment and growth are expected as productive

government spending. Variable of education also works like investment expenditures.

Government transfers for social insurance and transfers represent the consumption

expenditures. Consumption spending declines with per capita income. Transfers are

positively associated with growth but negatively associated with investment. This positive


49

relationship might reflect the reverse causation from growth to spending. Public

investment positively contributes to growth and investment. Education and defence

spending remain insignificant in explaining the growth and investment contrary to the

expectations.

Engen and Skinner (1992) examine the link between fiscal policy and economic growth

for 107 developed and developing countries from 1970-85. Government expenditures and

average tax rate indicate fiscal policy instruments. Findings comprise that both are

negatively related to economic growth. Government spending reduces the output growth

in Africa, Latin America and developing countries. The study can be improved by further

undertaking disaggregated analysis of expenditures and revenues which can provide the

rationale for the negative effect of both. Regarding the tax rate it can be argued that

structure of the tax and tax base across the countries might undermine the results.

Easterly and Rebelo (1993) evaluate the effect of fiscal policy on economic growth and

development in a wide cross section of 100 countries from 1970-1988. Findings imply that

government budget surplus positively contribute to private investment and economic

growth. Investment on transportation and communication is robustly related to growth.

Public investment has a positive effect on capital formation and growth. Fiscal structure

contribute to level of economic development; less developed countries rely more on trade

taxes while developed countries rely more on direct taxes moreover rich countries have

higher health and social security expenditures.

Devarajan et al. (1996) analyse the relationship between public expenditures and

economic growth for a panel of 43 developing countries from 1970-90. Findings show that

current expenditures positively contribute to per capita income and while capital

expenditures are negatively associated to economic growth which is opposite to believed

hypothesis. Aggregate government expenditures remain insignificant. Expenditure share


50

according to functional classification show that defence and infrastructure expenditures

are negatively related to growth which is in sharp contrast to earlier findings. Different

categories of health and education expenditure are negative or insignificant. Findings

remain robust while using other methodologies. It is argued that some white elephant

capital expenditures might be in governments’ objective function which lowers the

marginal productivity of capital. Findings imply that developing countries’ governments

are misallocating the resources. There are also problems in the data that might be liable to

contradictory results as some countries include development expenditures in productive

expenditures while others contain some current expenditure as well.

Guseh (1997) examines the relation between government size and economic growth across

political and economic systems in 59 middle income developing countries from 1960–85.

As a measure of government size he uses two specifications; one is the current expenditure

growth rate while the other is the growth of the relative size of public expenditure. Former

indicates the short run effect while latter reveals the long run effect. Findings show that

government creates distortions in the economy through the devices of taxation and

spending and also through rent seeking behaviour. These distortions retard the economic

growth but the existence of socialist and nondemocratic systems brings higher decline.

Findings propose that a suitable remedy for economic growth and development includes a

fall in government size and the provision of economic and political freedom.

Gupta et al. (2002) evaluate the relationship between fiscal adjustment, structure of public

expenditures and economic growth for 31 low income countries from 1990-2000. Findings

reveal that strong fiscal position and improvement in the fiscal balance, is related to

economic growth in the short as well as long run. Fiscal composition shows that

expenditures on wages and salaries are negatively related to growth while expenditures on

other goods and services and capital expenditures foster the growth. Moreover a


51

reallocation of current outlays to capital is positively associated to more persistent fiscal

consolidation. It is concluded that fiscal composition towards more productive uses is

important for enhancing the growth and towards fiscal adjustment.

Bose et al. (2003) examine the impact of disaggregated government expenditures on

economic growth for a panel of 30 developing countries over the period 1970-90. Findings

show that capital expenditures positively contribute to growth while current expenditures

remain insignificant. The sectoral analysis shows that government investment and

expenditures on education remain significant and contribute to growth. While public

investments and expenditures in other sectors (transport and communication, defence) do

not remain robust. Government budget deficit is negatively associated to economic

growth. Analysis strongly supports the widespread belief in modern growth theory that

education is the key to success. Findings propose that developing countries should invest

on capital expenditures in order to enhance the growth. The study does not provide the

supportive arguments why the current expenditures do not contribute to growth as well the

capital expenditures.

Kukk Kalle (2007) evaluates the effect of fiscal policy on economic growth using a panel

of 52 developed and developing countries. Findings show that indirect taxes positively

contribute to economic growth while direct taxes remain insignificant. It implies that if the

government wants to increase the revenue it should chose the indirect taxes instead of

direct taxes. Direct taxes are distortionary in the sense that they distort the decision to

invest. On the expenditures side spending on employees, consumption spending or social

benefits are negatively related to economic growth while investment expenditures are

positively related to growth. Interest spending is negatively associated to economic growth

indicating that debt financing do not contribute to growth. It is proposed that to accelerate


52

growth, government should raise taxes and cut current expenditure or increase investment

expenditures.

Alam and Butt (2010) examine the long run relationship between social sector

expenditures such as education, health and social security and economic growth in 10

developing countries from (1970-2005). Empirical analyses provide the evidence of a long

run dynamic relationship among education, health and social security expenditures and

economic growth for all countries included in the sample. These social sector expenditures

increase the economic growth through productivity enhancement. Panel cointegration

investigation also provides the evidence of a long run dynamic relationship. Findings

imply that expenditure composition has a significant role in stimulating the economic

growth. There is need of modification in fiscal expenditures such that that a decrease in

unproductive expenditures and increase in the social sector expenditures.

Ali and Ahmad (2010) empirically evaluate the effect of fiscal policy on economic growth

for Pakistan from 1972-2008. In Pakistan the growing budget deficit is considered as one

of the key restraints to economic growth. Findings show that in the long run fiscal deficit

is negatively associated to national savings and reduces the economic growth. Politically

motivated and unproductive expenditure of the government is a major constraint to

economic growth in Pakistan. Only the debt servicing and security expenditures outstrip

the development budget. Findings propose that the government should curtail

unproductive expenditures while paying high attention on the public sector development

plan to promote the long run growth.

Gallo and Sagales (2011) evaluate the impact of different fiscal policy instruments on

economic growth and inequality for a panel of 43 upper, middle and high income countries

from 1972-2006. The empirical findings show that higher current expenditures and direct

taxes reduce the economic growth and inequality. Public investment expenditures increase


53

the growth rate and reduce the inequality. Current expenditures show the tradeoff between

growth and inequality while investment expenditures improve both. Findings propose that

government can avoid the trade off by curtailing the current expenditures and increasing

the capital expenditures.

Acosta Ormaechea and Yoo (2012) examine the effect of tax composition on economic

growth for 69 high, middle and low income countries from 1970-2010. Findings show that

with constant overall tax burden an increase in income tax and reduction in consumption

and property taxes is negatively related to economic growth. A shift from income to

property taxes significantly fosters the growth and remains robust. When the decrease in

income tax is adjusted with a rise in VAT and sales taxes it significantly contributes to

growth. Disaggregated sample according to income levels also provide consistent findings

as earlier in case of middle and upper income countries. Findings do not remain robust for

low income countries. It might be due to their poorer quality of tax administration and tax

enforcement.

Ormaechea and Morozumi (2013) examine the public expenditures-growth relationship for

56 low, medium and high income countries from 1970-2010. There are many studies

relating the change in expenditure composition to economic growth. They highlight the

components which can be used as compensating factors in order to keep the level of total

spending fixed. Reallocations of government spending across different expenditures do not

show a robust behaviour except the education spending. When a rise in this spending is

compensated by a fall in social protection spending, there appears to be a robust relation

with economic growth. This implies that education could have been a relatively more

efficient outlay to foster growth, through human capital accumulation. Finding is robust to

additional control variables and the use of a subset of countries.


54

Gangal and Gupta (2013) evaluate the link between public expenditures and economic

growth for India from 1998-2012. One of the objectives of public expenditure policy is

higher and sustainable growth. Findings reveal that public expenditures are positively

associated with growth. Moreover there is evidence of unidirectional causality from public

expenditures to economic growth. There is also positive effect of shocks in public

expenditures to GDP. Findings imply that government should increase the public

expenditures to encourage the economic growth. Study does not explain the channels

through which public expenditures contribute to growth.

Morozumi and Veiga (2014) examine the role of institutions in spending growth

relationship for 80 developed and developing countries from 1970-2010. They use

constraints on executives as a proxy for checks and balances on the policy makers, and the

type of government as democracy/autocracy as a measure of political and economic

freedom of citizen’s. Findings show that capital expenditures significantly contribute to

economic growth in the presence of institutional constraints. An increase in current

spending does not provide robust findings. Institutions enhance the efficiency of capital

spending providing little room for rent seeking behaviour and thus promote growth11

.


Empirical literature regarding the role of fiscal policy in economic growth contrasts in

terms of data sets, indicator used regarding fiscal policy, econometric techniques and

sample selection. There are numerous deficiencies in the quality of fiscal data regarding

the classification that might be accountable to contradictory results as some countries

include development expenditures in productive expenditures while others contain some

current expenditure as well. Structure of the tax and tax base across the countries also

11 There tends to be larger possibility for discretion in capital than current spending because current spending

is on fixed outlays (e.g., wages, pensions and interest payments on the debt).


55

differ as some countries have high tax base and low tax rate while others go opposite so it

becomes difficult to intercept the results with these limitations. The link between public

expenditure and economic growth is highly dependent on the set of countries taken into

consideration. A large body of literature is based on the experiences of developed

countries there remains little prospect of economic growth for developing countries.

Most common findings regarding the public expenditure and their composition across the

countries show that aggregate government spending adversely contribute to economic

growth while the disaggregated analysis shows that public investment expenditures

positively contribute to growth while current or consumption expenditures are negatively

associated with economic growth or remain insignificant. It is argued that fiscal policy

depresses the economic growth through distortionary effect of taxes and inefficient public

spending. On the other hand the opposing view also holds that there is an important role of

the government in providing public goods and services and infrastructure. Capital

expenditures provide necessary infrastructure to promote private investment. Regarding

current expenditures it is argued that some categories of these expenditures are

unproductive moreover these expenditures are utility or welfare enhancing not growth

enhancing. Higher taxes need to finance the consumption expenditures reduce the

incentive to invest. Functional classification of expenditures shows that government

investment expenditures such as infrastructure services, transportation and communication

increase the private sector productivity and growth. While certain government

consumption expenditures such as transfers to households increase the utility or welfare of

the households but lower the economic growth as higher taxes need to finance the

consumption expenditures reduces the incentive to invest. Expenditures on wages and

salaries, interest payment adversely affect the growth while expenditures on goods and

services foster the growth. Regarding the social sector expenditures findings are


56

ambiguous. In developing countries fiscal adjustment that relies on cuts in transfers and

wages can be expansionary while those rely on tax increase and cuts in investment

spending tend to be contractionary. Empirical literature proposes the reallocation of

expenditures composition from current to capital expenditures as growth enhancing

strategy for developing countries as these countries already lack infrastructures like

transport and communications, roads, railways etc. that help promote private capital

accumulation.

There is exception of some studies that provide conflicting results like; Devarajan et al.

(1996) provides the evidence of positive association between current expenditures and

economic growth while a negative one between capital expenditures and growth in

developing countries. It is argued that there might be some white elephant projects which

lower the marginal productivity of capital investment. However several components of

current expenditure might have higher return than capital expenditure. Sattar (1993) finds

that government consumption expenditures positively contribute to economic growth for

Asian developing countries therefore efficiency enhancing role of government outweighs

the efficiency reducing role. Gong and Zou (2002) argue that higher infrastructure

spending may deteriorate the economic growth if spending on basic economic services is

ignored.

Regarding the tax revenue and tax composition empirical literature shows that tax revenue

positively contribute to growth while tax composition shows that direct taxes are

negatively associated with growth while indirect taxes (VAT and sales taxes) positively

contribute to growth. Direct taxes are called production taxes they decrease the rate of

return to private investment by discouraging the investment and reducing the rate of

growth.


57

2.5 Monetary policy and economic growth:


Regarding the effect of monetary policy on economic activity there are two limiting cases

in theoretical literature, Keynesians and Monetarists. Keynesians intend that money policy

has no role to play therefore it is ineffective to influence the long run growth. While

Monetarists believe that money does play a role thereby monetary policy affects the

economic growth. Monetarists on the other hand believe on a direct association between

the real and monetary sector of the economy. There are two important considerations that

ensure the relation between changes in real money stock and changes in income. First, the

relation between interest rate and money stock and second the interest rate and aggregate

demand. It is concluded that expansionary monetary policy increases the output and

economic activity by increasing the aggregate demand in the short run.

Keynes introduced the concept of liquidity trap which explains that at very low level of

interest rate a rise in money supply will not affect the output and growth. Monetarists

support their argument through the equation of exchange specified by Irvin Fisher, where

only the money supply brings changes in output. Keynes argues that in order to curtail

recession and to control the inflation stimulating the demand is accurate approach, but

both cannot be achieved at the same time.

Robert Mundell (1963) advocates monetary policy, in response to Keynes doctrine, if the

objective is to manage inflation whereas in order to stimulate the employment and output

fiscal policy can play its role.


Monetary policy has an important role to play in economic stability; price and output

stability. The central bank autonomy has often been limited in developing economies due

to fiscal pressures leaving little room for independent monetary policy actions.


58

Nonetheless, as a result of recent economic reforms in less developed economies central

banks are becoming increasingly independent. The monetary transmission mechanism is

weaker in developing countries as compared to advanced and emerging economies. Below

we examine the empirical evidence regarding the effectiveness of monetary policy in

developing countries.

Christiano et al. (1996) evaluate the impact of monetary policy shocks on the US economy

from 1960Q1-1992Q4. They use federal funds rate and non-borrowed reserves as

indicators of monetary policy to analyse the effect of monetary policy shocks on flow of

funds between different sectors. VAR analysis shows that contractionary monetary policy

declines business sector flow of funds. Net funds raised by the households remain

unchanged for several quarters as households do not adjust their financial assets and

liabilities instantaneously after a monetary shock. The net funds raised by the government

sector increases after a temporary reduction as the deficit goes up. Monetary shock also

affects the macroeconomic aggregates; decline in real GDP, employment, retail sales, non-

corporate financial profits and a sharp decline in prices. It increases the unemployment

and manufacturing inventories.

Fatima and Iqbal (2003) analyse the relative efficiency of fiscal and monetary policy for 5

developing countries from South and East Asia for the time span 1970-2000. They use

money supply and government expenditures as indicators of monetary and fiscal policy

respectively. In case of Thailand there is evidence of bidirectional causality between fiscal

policy, monetary policy and economic growth (economic growth negatively affects the

fiscal and monetary variables). In case of Indonesia, Pakistan and India there is

unidirectional causality between the fiscal and monetary variables and economic growth

(fiscal policy negatively influence the economic growth). Unidirectional causality in

Malaysia provides the evidence of effectiveness of both policies in economic growth. It is


59

concluded that effectiveness of both policies differ in each country depending on the

nature of the economy.

Cheng (2006) investigates the effect of monetary policy shock on output, prices and

nominal effective exchange rate for Kenya from 1976-2005 using VAR analysis. Using

short term interest rate as an indicator of monetary policy findings infer that a positive

monetary policy shock reduces the prices and leads to appreciate the currency value.

Monetary policy shock has no effect on output. One reason for no response of output

against the shock might be the poor financial and regulatory system of Kenya which

hampers the monetary transmission to the real sector. Effectiveness of the study can be

enhanced by including some other countries from the same region and comparing their

results with the results of Kenya which will also provide a robustness check.

Ali et al. (2008) examine the relative significance of fiscal and monetary policies for

South Asian countries from 1990-2007. Though fiscal and monetary policies are

implemented by different authorities hence both are not independent. Fiscal balance and

broad money represent fiscal and monetary policy respectively. Findings indicate that

money supply significantly contribute to economic growth while fiscal balance remains

insignificant. Findings illustrate that monetary policy is a powerful tool than fiscal policy

in order to boost economic growth. We can criticise the study on the grounds that it does

not provide the mechanism through which monetary policy will affect the growth.

Buigut (2009) identify the importance of interest rate channel for the East African

countries from 1984-2005. A parallel monetary policy action leads to different outcome

between countries. Study uses the VAR to assess the similarity of transmission mechanism

in the East African countries. Impulse response functions ascertain the speed and size of

the effects of unanticipated monetary policy tightening. Findings imply that a monetary

contraction affect the output in a relatively similar way for all the countries but seems


60

insignificant while its effect on inflation rate in terms of the speed and direction seems

different for the countries. One of the most important underlying reason for insignificant

effect of interest rate channel might be the underdeveloped financial system in these

economies therefore it is likely that the credit channel might constitute the main source of

investment finance.

Gul et al. (2012) examine the linkage between monetary policy instruments and economic

growth for Pakistan from 1995-2010 by using monthly data. The objective of central bank

is to stabilize the output and prices through an efficient monetary policy. Findings reveal

that a positive interest rate shock (contractionary monetary policy) shows a persistent rise

in the price level. A tight monetary policy is generally believed to reduce the price level,

not increase it. It suggests that monetary policy shocks are not a source of output

fluctuations in Pakistan. Regression results intend that contractionary monetary policy in

terms of higher interest rate is negatively associated to economic growth which

discourages the private investment. It is proposed that central bank can improve the

economic health by by eradicating the price uncertainties associated with inflation.

Hussain and Siddiqi (2012) analyze the relationship between fiscal, monetary policies,

institutions and economic growth for Pakistan from 1976 to 2008. Fiscal and monetary

policies both play an important role in the economic growth and stabilization of a country.

In the developing countries like Pakistan growth is not consistent at a certain level.

Therefore to enhance the effectiveness of these policies and to foster the economic growth

institutions can play their role. Findings show that monetary policy is effective and

economic institutions play an important role in increasing the per capita GDP growth.

Fiscal policy, political and social institutions have no significant association with

economic growth. Findings propose that there is need to enhance the efficiency of


61

institutions. Effectiveness of the study can be enhanced by including some countries from

the same region for comparison.

Coric et al. (2012) examine the impact of monetary policy shocks on output and prices in a

cross country analysis of 48 developed and developing countries by using the structural

VAR model. They use quarterly data from 1975-2009. Money supply and domestic

interest rate are used as monetary policy indicators. Findings show that a monetary policy

shock has a greater effect on output and prices in countries with a larger financial sector.

The effect of a monetary policy shock on output and prices are smaller in the countries

with fixed exchange rates. In financially open economies, a flexible exchange rate regime

leads towards a more effective monetary policy12

. In larger economies monetary policy

shock has a larger effect on output as well. The effects of a monetary policy shock on

output and prices are not different while considering different income groups. It is

concluded that higher integration has increased the significance of foreign factors.

Younus (2013) examine the effect of fiscal and monetary policy on output growth for

Bangladesh from 1980-2011. Since 1970s Bangladesh has been following expansionary

monetary policy with substantial fiscal deficits. Centrally planned framework of early

1970s has also contributed significantly in accumulating huge fiscal deficits. As a result of

economic reforms since early 1990s monetary policy has gained some independence in

achieving and sustaining price stability. Broad money and government expenditures

represent monetary and fiscal policy respectively. The empirical findings show that both

the monetary and fiscal policies significantly contribute to output growth with different

magnitudes and significance. Monetary policy has relatively stronger impact than that of

12

As in fixed exchange rate regime any monetary policy shock is compensated by the opposite reaction in

order to maintain the exchange rate fixed.


62

fiscal policy on output growth in Bangladesh. Findings propose that there is need to rely

more on monetary policy as compared with fiscal policy to achieve higher growth.

Fetai (2013) explores the effectiveness of fiscal and monetary policy during financial

crises in developing economies. Financial crisis are associated with output loss or cost.

The banking crises and currency crises are related to intense recession in these economies.

They use two measures of monetary stance; change in discount rate and change in

international reserves. Stance of fiscal policy is measured through discretion in the fiscal

policy. Findings show that contractionary fiscal and monetary policy increases the cost of

crisis. Expansionary monetary policy is unrelated to output cost associated with financial

crises while fiscal expansion is associated with lower output cost of crises. Findings

propose that a policy mix, expansionary fiscal and a neutral monetary policy, decreases the

output cost in the presence of crisis in developing countries. Study can be criticized as it

does not explain the mechanism through which expansionary fiscal policy will be more

effective during the crisis while expansionary monetary policy will remain neutral.

Ivrendi and Yildirim (2013) analyze the impact of monetary policy shocks on

macroeconomic variables for six emerging economies (BRICS_T)13

from 1995: M01-

2012:M08. Findings through the VAR analysis show that contractionary monetary policy

shock appreciates the domestic currency as nominal exchange rate initially rises in all the

countries, there is evidence of overshooting behavior. Monetary policy shock controls the

inflation by exchange rate appreciation in all countries except Russia as Russian monetary

policy has failed to achieve sustained low inflation due to the policy of exchange rate

targeting. These shocks are effective in reducing output in India, South Africa, Russia and

China. Moreover these shocks have negative effects on exports while the response of

13

Brazil, Russia, India, China, South Africa and Turkey.


63

imports is significantly positive in the all countries. Net effect on the trade balance is

negative as the shock initially deteriorates the trade balances in these economies.

Kandil (2014) examine the impact of monetary policy shocks on output and prices for a

sample of 105 developing countries from 1968 to 2008. He undertakes both the time series

and cross country analysis. Many central banks in developing countries are not

independent in their operations and are somehow obliged to finance the government

spending. Study undertakes two channels that cause the interaction between monetary

policy shocks and the aggregate economy: an aggregate demand channel and an aggregate

supply channel. Time series evidence shows that expansionary monetary shocks increase

both the output and price. Supply related constraints impede output expansion and increase

price inflation against the expansionary shocks. Cross country analyses shows that the real

effects of monetary shocks depends on price flexibility, demand elasticity, and monetary

policy variability. Findings show that output growth decreases significantly against the

expansionary monetary shocks with price flexibility. This specifies a strong substitution

between the real and inflationary effects of monetary shocks, reflecting supply-side

constraints. Expansion in the aggregate demand increases the real effect of monetary

shocks, implying that transmission channel of aggregate demand appears to be more

strong. Monetary shocks increase the price variability moreover the variability of

monetary shocks is positively related to inflation variability.


The analysis of monetary policy in developing countries has been hindered due to the lack

of a clear announcement of the direction of monetary policy. It is common perception that

central banks in many developing countries lack independence in their operations as they

are obligated to finance the government deficits. There are different monetary

transmission channels such as interest rate, credit and exchange rate. Monetary policy


64

affects the real economy through these channels. The significance of each of these

channels is determined by the economic, legal and financial structure of the economies. A

similar monetary policy action can lead to different behaviour between countries.

Conventional economic literature links the monetary policy and the real economy through

the aggregate demand. There is also some supply side evidence where a change in the

nominal interest rate is associated to output changes through production costs.

Empirical findings of almost all the studies show that contractionary monetary policy

declines the economic activity by discouraging the private investment through the

aggregate demand channel. Expansionary monetary policy increases the output and

decreases the output variability, indicating an important role for monetary policy to revive

growth by availing liquidity. There are only few studies that show the insignificant effect

due to the underdeveloped financial and regulatory framework especially from Afrcican

countries. Many studies evaluate the relative efficiency of fiscal and monetary policy by

using St. Louis equation14

. Findings are relevant to the empirical literature of developed

countries that monetary policy is an important tool to stabilize the economy. Additionally,

Vector Autoregressive (VAR) models have also been used extensively to examine the

transmission mechanism of monetary policy. They analyze the influence of monetary

policy shocks on aggregate economic activity. Monetary policy shock largely effect the

output in countries with a larger financial sector. The effect of a monetary policy shock is

smaller when there is fixed exchange rate. Negative monetary policy shocks raise the real

output growth through expansion in economic activity. Contractionary monetary policy

shock declines business sector flow of funds, real GDP, employment, retail sales and non-

corporate financial profit. Monetary policy shock controls the inflation by exchange rate

14

A three variable equation (including output, fiscal and monetary policy indicators), known as St. Louis

equation in the economics literature, was developed by Anderson and Jordan (1968) with the objective of

testing the relative significance of monetary and fiscal policy for stabilization in the US.


65

appreciation. These shocks have negative effects on exports while they make the imports

cheaper by deteriorating the trade balance.

Short term interest rate and money supply are mostly used as indicators of monetary

policy. Most of the empirical literature has focused on the developed countries moreover

cross country evidence is scarce as studies focus on time series data using quarterly

frequency mostly.

2.6 Policy volatility and economic growth:


Business-cycle theory and growth theory have traditionally been treated as unrelated. Fynn

Kydland and Edward Prescott (1982) and Long and Plosser (1983) presented new

evidence for analyzing economic variations that combined growth and business-cycle

theory. These models assume that output variations are influenced by stochastic variations

in technology. Long run growth is not influenced by policy uncertainty in the standard

neoclassical growth model. Due to policy shocks economy deviate from its long run

growth path only temporarily. In contrast, endogenous growth model propose that policies

and policy instabilities can have permanent effects on growth.


In order to improve the climate for private investment and growth countries have adopted

macroeconomic and structural policies however these policies have unproductive to

provide the required outcome. New wisdom focuses not only at the right policies but also

the need to minimize the uncertainty about the future policies. As a predicted or certain

environment reduces the risk associated with private entrepreneurs and increases the

productivity of investment and growth. Below we review empirical studies regarding the

relationship between policy volatility and economic growth.


66

2.6.2.1 Fiscal policy volatility and economic growth:

Aizenman and Marion (1991) explore the links between policy uncertainty and economic

growth for 46 developing countries from 1970-85. They use government expenditures,

revenue and budget deficit as indicators of fiscal policy while growth in money and

domestic credit represent monetary policy indicators. Volatility is measured as the

standard deviation of the residual. Findings show that volatility of government

expenditures adversely affects the economic growth in both Latin America and Asia, but

the correlation is much higher in Asia. There is evidence of negative association between

monetary policy volatility and economic growth in Latin America but positive in Asia.

There is evidence of a negative association between all policy volatility measures and

economic growth in low growth countries while for the high-growth countries, some

correlations are negative but others are positive. Cross-sectional regressions show that

policy volatility adversely contributes to economic growth. Findings are consistent

with above correlation results. Theoretical model explain that policy volatility

might change the pattern of investment.

Ramey and Ramey (1995) provide an empirical analysis of volatility (growth volatility,

government spending volatility and innovations volatility) and economic growth in a

sample of 92 developed and developing countries from 1960- 1985. They use the standard

deviation of growth rate of GDP, variance of innovations and government spending as a

measure of volatility. Findings provide the evidence of lower growth rates for countries

with higher volatility. Government spending-induced volatility adversely affects the

economic growth even after controlling time and country fixed effects. Innovations

volatility is also inversely related to economic growth. Findings remain robust by the


67

addition of control variables. Empirical literature link volatility to growth via investment

however findings reveal the little impact of volatility on the investment share of GDP.

Gong and Zou (2002) examine the link between volatility of public expenditures and

economic growth for 90 developed and developing countries from 1970-1994. Variance of

the growth rate of public expenditures measures volatility. They disaggregate government

expenditures by economic15

and functional classification.16

Economic classification shows

that volatility of both the current and capital expenditures adversely affect the economic

growth. Functional classification shows that volatility of general public services is directly

related to economic growth. Volatility of education and defence expenditures as well as

economic services is inversely related to economic growth. Volatility of transportation and

communication expenditures is directly and weekly related to economic growth.

Ali., M. Abdiweli (2005) examine the effect of volatility of fiscal policy on economic

growth and investment for 90 developed and developing countries from 1975-1998.

Literature emphasizes that certainty of the fiscal policy is important for the decision to

invest. Uncertainties regarding future behavior of fiscal parameters reduce the growth rate

by making investment riskier. Aggregated and disaggregated revenue and expenditure

represent fiscal policy measure. The standard deviation of the residual measures the

volatility or the uncertainty associated with changes in fiscal policy. Findings imply that

most of the fiscal policy parameters are inversely related to economic growth. Through the

investment channel fiscal volatility does not seem to have much impact. With the

exception of government expenditure and trade taxes all the other fiscal volatility

measures have no noticeable impact on economic growth.

15

Expenditures are divided into current and capital. 16

Expenditures are divided into six broad categories: general public service, defence, education, human

welfare services, transportation and communication and economic affairs.


68

Sirimaneetham Vatcharin (2006) evaluate the volatility of macroeconomic, fiscal and

development policies in 65 developing countries from 1970-99. Policy volatility is

measured by standard deviation of the residuals from a first order autoregressive process

or AR(1). Budget deficit and central government debt are used to represent the volatility of

fiscal policy. Macroeconomic volatility is represented by interest rate, inflation rate and

exchange rate. Development policy volatility is represented by trade liberalization and

government regulations and protection of property rights. Findings show that only

macroeconomic volatility is inversely related to economic growth while fiscal and

development policy volatility remain insignificant in explaining the growth. Regarding the

role of fiscal volatility statistics in the study show that low-income countries are not

subject to much higher budget deficits, most studies which provide an inverse relationship

between fiscal policy volatility and growth use government consumption as a proxy. The

limited role of development policy volatility is surprising as it is expected that unstable

government regulations discourage the investment and growth.

Davide Furceri (2007) explore the link between cyclical volatility of government

expenditure and long run growth using panel data of 116 developed and developing

countries from 1970-2000. Standard deviation of the government expenditure measures

the volatility while cyclical part is obtained through different filtering methods; HP and

BP filters17

. Findings show that government expenditure volatility and economic growth

are inversely related. Findings remain robust to different cyclical measures and

subsamples. It is concluded that government expenditure volatility indicate a larger effect

on long-run growth for developing countries while a smaller effect for OECD countries.

This might be due to the better domestic stabilizers in developed countries which absorb

the volatility of expenditures.

17

Hodrick–Prescott and Baxter King filters.


69

Fatas and Mihov (2008) empirically explore the effect of fiscal policy volatility on

economic growth, investment and output volatility for ninety-one for the period 1960-

2000. They use only government spending for the empirical analysis of fiscal policy

because it remains less volatile as compared to taxes, as spending reacts less to economic

cycle. As a measure of discretionary change in fiscal policy they use the volatility of the

residual. Empirical analysis shows that volatility of discretionary fiscal policy adversely

affects the output and investment. It is concluded that fiscal policy volatility leads to more

volatility of output, which in turn lowers investment and economic growth. There is also

evidence of a procyclical behavior of fiscal policy for many countries included in the

sample. In poor countries a combination of discretionary fiscal policy and procyclical

fiscal policy increases the volatility and harms long-run growth.

Afonso and Jalles (2012) examine the link between fiscal volatility, financial crisis and

economic growth for a sample of developed and developing countries from 1970-2008.

They use the standard deviation of cyclical component of aggregate government

expenditures and revenues. Findings imply that government expenditures volatility lowers

the economic growth, finding is also robust across country groups. Government revenue

volatility appears to be larger for OECD countries than for emerging economies. Moreover

with a financial crisis government spending is less flexible than revenues. Revenues drop

substantially due to the crisis therefore magnifying the imbalance. Findings propose that

the implementation of stable and smoother fiscal policy can help to create an investment

friendly environment that allows private investors to plan better in the long run.

2.6.2.2 Monetary policy volatility and economic growth:

Peterson (1998) evaluates the association between monetary instability and economic

growth for 87 developed and developing countries from 1968-92. The sample period is

divided into two equal parts one from 1968-80 and other from 1980-92 as the rate of


70

growth of the sample countries declined in the 1980-92 period as compared to 1968-80.

The key intent of the study is to explore the circumstances causing to this decline.

Findings show that higher instability of money supply growth contributed to this decline

of growth rate. This instability seems highest in the middle and low income countries

whereas in high income countries money supply growth seems to reduce from the first to

the second period. Findings propose that a sustainable (3 to 4) percent growth rate requires

moderate, non-inflationary, and stable money supply growth in the (4 to 5) percent range.

It further requires a well-organized fiscal policy where spending keeps in line with

revenue, eradicating the need to print money to finance deficits.

Ismail et al. (1999) observe the effect of interest rate uncertainty on economic activity in

Malaysia using monthly data from 1998-2002. Interest rate represents three month

treasury bill rate and its volatility is measured by conditional variance from the GARCH.

The study investigates the effect of uncertainty in interest rate on industrial production

used as a proxy to aggregate output. Findings show an inverse association between interest

rate uncertainty and aggregate output. It also shows that investor has information about

market and he can predict small probability of change.

Bo and Sterken (2002) evaluate the relationship between interest rate volatility, debt and

firm investment using a panel of 82 Dutch firms for the period 1984–1995. There is ample

literature discussing the impact of uncertainty on investment behavior. Irreversibility

indicates an inverse relationship between investment and uncertainty. Study uses three

measures of volatility; the ARCH model of volatility, the variance of the residual through

AR(1) process and the normal variance. Two measures of interest rate are used; firm

interest rate and market interest rate. Besides the whole sample study uses two sub

samples; one for high indebted firms and other for low indebted firms. Finding show that

higher interest depresses the firm investment while the interest rate volatility shows


71

ambiguous result. Interest rate volatility and debt jointly increase the investment and this

effect is larger for highly indebted firms. Findings imply that the debt readjustment work

for highly indebted firms as a higher interest rate volatility decreases the real value of

debt.

Bloom and Bond (2007) explore the dynamics of uncertainty and investment both at

aggregate level using time series properties and also firm level data for UK manufacturing

firms from (1972-91). Standard deviation of daily stock returns measure volatility. The

empirical findings show consistency with the partial irreversibility theory where

investment becomes unresponsive to demand shocks due to higher uncertainty. This

specifies that an increase in uncertainty during major shocks, such as September eleven

and the oil shocks of 1970s, reduce the sensitivity of investment to consequent monetary

or fiscal policy.

Gulen and Ion (2013) investigate the correlation between uncertainty and corporate

investment using a quarterly data of 7861 US firms from 1987-2011. They use uncertainty

index by Baker, Bloom, and Davis (2012) which is a comprehensive indicator representing

monetary as well as fiscal policy uncertainty. Businesses often face uncertainty related to

the timings and content of policy changes. Findings show that policy uncertainty reduces

the industry and firm investment with a substantial magnitude. Relationship is not alike to

all US firms included in the sample hence it is stronger for firms having higher degree of

irreversibility, have more financial constraints and those who are less competitive.

Moreover statistics show that two thirds of the 32% drop in corporate investments during

the 2007-2009 crisis can be attributed to policy uncertainty.

Bretscher et al. (2016) examine the effect of uncertainty on investment both at the

aggregate and firm level by using the data of 1600 firms from 1994-2014. Interest rate

uncertainty reveals uncertainty about the future stance of monetary policy. Uncertainty can


72

lead firms to delay investment projects when these are irreversible. Interest rate

uncertainty is measured by treasury implied volatility. Findings show that uncertainty

adversely affects the investment both at the aggregate and firm level. Findings also show

that the negative relationship of interest rate uncertainty and future investment is stronger

in more financially constrained and levered firms. Findings imply the need to reduce

uncertainty around the future path of monetary policy as the Fed’s main policy instrument

by means of effective forward guidance.

2.6.2.3 Capital flows volatility and economic growth:

Lensink and Morrissey (2001) examine the link between FDI flows, volatility and

economic growth for 88 developed and developing countries from 1975-1998. Standard

deviation of the residual represents volatility. Findings of the cross section and panel data

provides consistent finding that FDI is positively associated to economic growth whereas

FDI volatility is inversely related. FDI volatility may represent underlying economic,

political, institutional uncertainty and risks in a country. These uncertainties reduce the

growth and the productivity of investment. Effectiveness of the study can be enhanced by

incorporating other capital flows and then comparing their results.

Sulla and Willett (2007) examine the reversibility of different capital flows to emerging

markets using data of 35 economies from 1990-2003. As sharp reversals of capital inflows

accompanied by currency crises have severe consequences in the form of output losses in

emerging market. The study explores the behavior of different type of capital flows

during crises. Study uses the volatility measure while splitting the sample into crisis and

non-crises periods. Disaggregated capital flows are represented by foreign direct

investment, portfolio investment and private loans. Findings show that excluding for FDI,

all other flows exhibit large reversals during crises. The reduction appears largest


73

regarding private loans during the Asian crises. The findings propose the demand for

international reserves and risk management to avoid the crisis.

Demir Firat (2009) explore the link between volatility of short term capital flows and

private investment in emerging markets from 1991-2001 using the biannual data. There

was a sharp surge in private capital flows to developing countries during the decade of

1990s. There is growing body of literature representing that unregulated short-term capital

flows have adversely affected the long-term investment and growth in developing

countries. Study employs firm level data for three countries separately; Argentina, Turkey

and Mexico. Standard deviation of net short term net capital inflows represents volatility.

Findings imply that higher volatility of the short term capital inflows is inversely related to

economic growth. Moreover this volatility has a significantly larger effect on small firms

as large firms have better access to capital and can manage reversals better. Findings

propose capital controls to decrease the excess volatility of short term capital flows.

Ferreira and Laux (2009) analyze the association between portfolio flows, volatility and

growth for a panel of 50 developed and developing countries from 1988-2001.Volatility is

considered an important characteristic of hot money which badly affect the growth in

developing countries, especially during crisis. Portfolio flows are usually considered most

volatile and their volatility has increased in emerging markets after liberalization. Findings

imply that the volatility of portfolio flows is weakly related to growth whereas it does not

dampen growth. Findings remain robust to different measures of portfolio flows, volatility,

presence or absence of controls and estimation methodology. Finding is in sharp contrast

to many other studies explaining that volatility of short term flows has severe negative

consequences for growth and investment especially in developing countries having less

developed financial and legal system.


74

Choong et al. (2011) analyze the link between foreign direct investment volatility and

economic growth in 5 ASEAN countries from 1974-2005. FDI volatility has increased

considerably since the late 1990s owing to domestic and international shocks therefore the

rate of return on foreign investment has become more uncertain. When foreign investors

face the risk they may reverse or withdraw the investments. Findings show that FDI

volatility is negatively associated with growth in Indonesia, Malaysia, Philippines and

Thailand while it has a minimal effect on Singapore. The financial system of Singapore is

highly developed than other sample countries and has a much higher ability to stabilize the

variability of FDI.

Carp (2014) examines the correlation of capital flows volatility and economic growth in

emerging economies from 1991-2012. World integration and financial openness has

enhanced the connections and interdependencies between countries. After the financial

crisis the destination of these capital flows has changed. At the start of the crisis,

developed economies observed a sharp decline in capital flows, mostly FDI. By contrast,

emerging markets experienced a surge in FDI inflows contributing their growth. During

the same period there was a sharp increase in portfolio inflows as these flows are thought

to be a form of short term speculations. Findings imply that macroeconomic instability has

augmented the volatility of capital flows, especially short term flows, by exerting a

downward influence on economic growth.

Neanidis (2015) observes the impact of volatile capital flows on economic growth using

cross country data of 78 developed and developing countries from 1973-2013. Standard

deviation of capital flows represents volatility. Findings show that aggregate capital flows

remain insignificant in influencing the economic growth while from disaggregated flows

debt flows are negatively related to economic growth whereas equity flows are positively


75

related. Volatility of all the capital flows, aggregated and disaggregated both, are

negatively related to economic growth.

2.6.2.4 Trade flows volatility and economic growth:

Yotopoulos and Nugent (1976) examine the effect of export instability on economic

growth for 38 developing countries from 1958-68. They measure instability through

squared deviations from an exponential trend. Findings show that export instability

reduces the marginal propensity to consume thereby increasing savings and growth.

Findings of the study are in sharp contrast to many other studies that explain the negative

effect of export instability on economic growth.

Ozler and Harrigan (1988) empirically examine the link between export instability and

economic growth and investment in 26 developing countries from 1963-82. Instability

index is measured by applying autoregressive conditional heteroscedasticity (ARCH)

model. Findings shows that export instability adversely affect the economic growth.

Country differences matters as instability hurts the countries that are more open, having

large exports. Regarding the composition of exports the largest negative effect is on the

countries whose exports are concentrated in capital intensive sectors, chemicals and

machinery. This indicates that negative effect of export instability works through reducing

the productivity of capital stock. Effect of instability on investment is much smaller than

its effect on growth.

Love (1989) evaluates the association between export instability and income instability for

20 developing countries. Selection of the sample is based on composition of exports,

representing the primary commodities as these goods face more fluctuations in demand

and supply as compared to manufacture goods export. Instability is measured through

deviations from a five-year moving average. Findings show that export instability brings

instability in capital goods imports and, in turn, investment and growth.


76

Gyimah-Brempong (1991) examines the association between export instability and

economic growth for 34 Sab Saharan African countries from 1960-86. Three indicators of

export instability are used; coefficient of variation, trend method and average of the

squares of the ratio of actual export earnings to trend earnings. Using the aggregate

production function, findings show that all the measures of export instability indicate a

negative association with economic growth.

Sinha (1999) examines the link between exports instability and economic growth in nine

Asian countries; India, Japan, Malaysia, Myanmar, Pakistan, Philippines, Korea, Sri Lanka

and Thailand, using annual data from 1950-97. Study uses the deviations of exports from a

five-year moving average as an indicator of instability. The results are not identical across

countries. Export instability adversely affects the economic growth in Japan, Malaysia,

Philippines and Sri Lanka. Negative relationship implies that instability in exports brings

instability in foreign reserves that affect the industrial production by deteriorating

important imports and making the investment and growth riskier. Export instability is

directly related to economic growth in (South) Korea, Myanmar, Pakistan and Thailand

whereas India shows ambiguous findings. The positive association between both variables

specifies a decrease in consumption which induces an increase in saving and investment

and thereby growth.

Chaudhary and Qaisrani (2002) evaluate the link between trade instability and economic

growth in Pakistan from 1972-1994. Pakistan economy is dependent on imports of certain

goods; industrial inputs, machinery, fuel etc. Import of these goods depends on the foreign

exchange earnings from exports while exports consist of mostly primary commodities and

agricultural products. Due to the composition of exports, term of trade shocks and other

domestic factors exports remain highly unstable. Findings shows that export instability do

not affect investment, growth and imports of capital goods in Pakistan. The trade deficit is


77

continuously met through foreign borrowings. The study can be criticized as it does not

explain the measurement of export instability index.

Rashid et al. (2012) evaluate the relationship between export instability and economic

growth of SAARC countries; Pakistan, India, Sri-Lanka and Nepal from 1972-2008.

Export is an important source of foreign exchange earnings and for the payments of

imports for LDCs. They experience higher export instability due to their export patterns

and inelastic and unstable demand and supply of their exports. Instability index is

measured by the trend method. Empirical findings imply that export instability is inversely

associated with economic growth for all selected countries. Magnitude of export instability

is highest in Sri-Lanka while it is lowest for Pakistan. Findings propose export

diversification and liberalization of foreign exchange markets as a control of instability.

Kaushik et al. (2008) examine the effect of export instability on economic growth of India

from 1971 to 2005. Export instability is measured through the squared deviations of export

earnings. Findings infer that export instability is inversely related to short-run stability and

directly related to longer-run growth of income. Findings propose that that if India wants

to reduce the short run negative effect it should diversify its exports. The study can be

criticized on the ground that it does not provide the economic rationale or channels

through which export instability adversely affects the economic growth in the short run

while relationship turns to positive in the long run.

2.6.2.5 External factors volatility and economic growth:

Mendoza (1997) evaluates the correlation between term of trade uncertainty and economic

growth in 40 industrial and developing countries from 1970-91. As a result of world

integration global markets volatilities have a substantial impact on the macroeconomic

indicators of participating economies. The effect of these volatilities is more severe on less

developed economies as compared to developed ones. Standard deviation of the residual


78

through autoregressive process measures volatility. Findings show that consumption

growth is directly associated with term of trade volatility whereas economic growth is

adversely affected by term of trade volatility. Findings remain robust with the addition of

other control variables. It is concluded that increased global uncertainty reduces social

welfare.

Andrews and Rees (2009) examine the link between term of trade volatility and

macroeconomic volatility using a sample of 71 countries from 1971–2005. As a result of

globalization economies have become more prone to external shocks. Terms of trade

shock is likely to have a greater impact on macroeconomic volatility in countries more

open to international trade. Standard deviation of growth rate of terms of trade represents

volatility. Findings show that term of trade volatility is positively related to output growth

and inflation volatility. Differences in the magnitudes depend on the policy and the market

structures. Study also explores the channels through which term of trade volatility affect

the macroeconomic volatility. Findings reveal that terms of trade volatility primarily

affects through the volatility of household consumption, exports and imports while

investment volatility seems less affected by terms of trade volatility.

Olaberria and Rigolini (2009) examine the effect of East Asia’s macroeconomic volatility

on economic growth and its volatility for a sample of 80 countries from 1966-2005.

Standard deviation of residuals through AR (1) process represents volatility of each

respective variable. Findings show that beside the volatility of domestic factors volatility

of external factors or shocks has also contributed to the slow growth of emerging

economies. On the one hand, higher openness has contributed to economic growth on the

other hand, it has increased the exposure of countries to external shocks. Volatility of

terms of trade, growth rates of trading partners, foreign interest rate and foreign capital


79

flows reduces the growth rate of domestic economy by transmitting these shocks through

globalization and making the domestic growth more volatile.

Abaidoo (2012) evaluate the effect of macroeconomic volatility on different indicators for

39 Sub Saharan African countries from 1980-2011. The study determines the effect of

external and domestic volatility indicators on economic growth, investment and savings.

Access to external market together with weak domestic structures and policies creates

significant threats to long term growth prospects in the sub-region. Volatility is measured

by standard deviation of specific macroeconomic variable. Findings suggest that external

volatility parameters have more influence on macroeconomic performance in the sub-

region than domestic indicators.


The empirical studies of macroeconomic policies and economic growth have concentrated

predominantly on the level effects of policy parameters on economic growth and largely

ignored the volatility of macroeconomic policies. Regarding the volatility of stabilization

and liberalization policies and external shocks we conclude below the findings from the

empirical literature discussed above.

Regarding volatility of fiscal policy empirical evidence shows that uncertainties

regarding future behavior of fiscal parameters reduce the growth rate by making

investment riskier. In an uncertain policy environment, investors might delay investment

as a result of irreversibility. There is also evidence that fiscal policy is procyclical mostly

in developing countries. Countries that face more political constraints exhibit more

procyclical fiscal policy. In poor countries a combination of discretionary fiscal policy and

procyclical fiscal policy increases the volatility and harms long-term growth. The effect of

fiscal volatility in developed countries is marginal due to strong automatic stabilizers.

Volatility of fiscal policy is measured by standard deviation of the residuals.


80

Regarding volatility of monetary policy empirical literature provides the evidence that it

adversely affects the economic growth through investment channel. Interest rate

uncertainty reveals uncertainty about the future stance of monetary policy. Uncertainty of

the interest rate affects the firm’s profitability by reducing the corporate investment

especially when there is irreversibility. Moreover link between interest rate uncertainty

and future investment is stronger in more financially constrained and levered firms and

also those firms who are less competitive. Opposite also holds as for more indebted firm’s

interest rate volatility can increase the investment by reducing the real value of debt

holdings. This debt readjustment effect has important implications for highly indebted

firms.

There is mostly firm level literature that explains the link between interest rate volatility

and investment. Literature is scarce at aggregate level and also for developing countries.

Mostly used volatility measures are standard deviation of residual of short term interest

rate through auto regressive process, conditional variance through ARCH and GARCH

model, Standard deviation of daily stock returns measure.

Regarding volatility of capital flows empirical literature provides the evidence that it

reduce the economic growth. Over the past decades, World integration and financial

openness has enhanced the connections and interdependencies between countries. Higher

volatility is an indicator of country specific risk, when foreign investors face the risk they

may reverse or withdraw the investments. FDI volatility discourages the technology

adaption and thereby is harmful to economic growth. There is growing body of literature

representing that unregulated short-term capital flows have adversely affected the long-

term investment and growth in developing countries. Volatility of capital flows affects

domestic investment through interest rates, exchange rate and inflation expectations.

Portfolio flows and debt flows are usually considered more volatile part of capital flows


81

while FDI remain the most stable and are less associated with output volatility. Asian

crisis represents the largest reversal in private loans. Moreover the pro-cyclical behavior of

capital flows adds to their volatility in developing countries. Volatility of capital flows is

measured by standard deviation of the residual of respective capital flow indicator through

auto regressive process.

Regarding volatility of trade flows empirical literature provides ambiguous findings.

Almost all the available literature examines the effect of export instability on economic

growth regarding developing countries. Export is an important source of foreign exchange

earnings and for the payments of imports for LDCs. They experience higher export

instability due to their export patterns and inelastic and unstable demand and supply of

their exports. Composition of exports toward primary commodities plays an important role

in their instability. Such factors may contribute to destabilize the investment and economic

growth. Most of the studies examine negative association between both variables and

some studies find positive association. Negative association between both variables

indicate that export instability bring instability in foreign reserves that reduces the imports

of important capital goods and hence reduces the productivity of industrial sector. Positive

association between both variables implies that export instability reduces the consumption

thereby increasing the saving and investment and hence economic growth.

Volatility is measured by export instability index; using the trend method, deviations of

exports from a five-year moving average, autoregressive conditional heteroscedasticity

(ARCH) model, the coefficient of variation.

Regarding the volatility of external factors or external shocks empirical literature

shows that these volatilities; term of trade, foreign growth and foreign interest rate

volatility, volatility of capital flows, deteriorate economic growth especially in developing

countries. As a result of world integration global markets volatilities have a substantial


82

impact on the macroeconomic indicators of participating economies. The effect of these

volatilities is more severe on less developed economies as compared to developed ones

due to poor macroeconomic and institutional framework to absorb such shocks. These

shocks directly or indirectly reduce the growth of domestic economies.

We can conclude the above discussion that volatility of domestic and foreign

macroeconomic policies deteriorate economic growth mostly through the investment

channel. Regarding the volatility measurement most of the studies have used standard

deviation measure.

2.7 Determinants of policy volatility:


As we have concluded from the previous section that policy uncertainty or volatility

reduces the economic growth specifically through investment channel therefore it is

important to investigate the factors that contribute to volatility to identify the policy

options to reduce the volatility. Below we provide the evidence from the empirical

literature regarding the volatility of stabilization policies, capital flows and trade flows.

2.7.1.1 Determinants of capital flows volatility:

Beck Ronald (2001) examines the volatility of capital flows to emerging markets and role

of foreign banks and trade liberalization regimes in the stability of the capital flows in 54

developing countries from 1990-98. It is argued that regarding trade in financial services

Asian countries had fairly restricted regime. Foreign banks play an important role in

reducing the information asymmetry and bring higher transparency. Volatility of capital

flows is measured through standard deviation. Share of foreign bank numbers and share of

foreign bank assets reflect foreign bank penetration. Limitations on foreign banks measure

the magnitude to which activities of foreign banks are restricted. Other variables include

inflation rate, economic freedom and rule of law. Findings show that foreign bank


83

penetration tends to increase the volatility of capital flows by increasing competitive

pressures. Rule of law reduces the volatility of capital flows. It shows that the regulatory

environment matters more than macroeconomic indicators.

Alfaro et al. (2005) examine the factors that determine the volatility of capital flows by

focusing particularly on institutional weaknesses versus bad policies for a sample of 97

countries from 1970-2000. Aggregated and disaggregated net capital flows are considered

which include net equity flows (FDI and portfolio equity investment) and debt. Inflation

rate, inflation volatility and government consumption as a ratio to GDP represent the

policy variables. All are hypothesized to be positively related to volatility. Institutional

quality also plays an important role in determining the pattern of capital flows. Initial level

of GDP represents the level of development of countries. Findings show that institutional

quality remains insignificant in explaining the volatility of total capital flows. Volatility of

aggregated and disaggregated capital flows reduces the GDP per capita. Inflation,

inflation volatility and government consumption are positively associated with net equity

flows. Robustness analysis including other monetary and fiscal indicators also provides

the consistent findings. Institutional quality does not appear to be significant there might

be a role of measurement error in the institutional quality indicators hence causing a

downward bias. Findings illustrate the role of poor macroeconomic policies towards the

high volatility of capital flows. Study ignores the external factors as important

determinants of volatility of capital flows in globally integrated world.

Broner and Rigobon (2005) explore the factors responsible for higher volatility of capital

flows in emerging countries from 1965-2003. Volatility is measured by standard deviation

method. They consider domestic and foreign macroeconomic factors and country

characteristics as the fundamental cause of volatility. Domestic macroeconomic factors

include GDP, inflation, exchange rate, nominal interest rate and term of trade. External


84

factors include foreign real interest rate, GDP, nominal exchange rate and inflation of

major trading partners. Income per capita, financial sector development and institutional

quality represent country characteristic. Findings show that internal and external

macroeconomic factors contribute very little towards the volatility of capital flows while

country characteristics explain substantial amount of volatility. Financial development,

good institutional quality and higher per capita income decrease the volatility of capital

flows. It is concluded that supply side factors are more important in explaining the capital

flows to emerging markets than the demand side factors. Findings propose that developing

countries can reduce the volatility of capital flows by improving their financial sector and

institutions.

Broto et al. (2008) evaluate the factors that affect the volatility of different type of capital

inflows in emerging economies for the period1980-2006. These factors are categorized

into domestic macroeconomic factors, financial sector factors, institutional and

geopolitical factors and global factors. Domestic macroeconomic factors include; GDP per

capita and growth rate, inflation and public deficits, stock of foreign exchange reserves

and trade openness. Financial sector variables represent the factors determining the

domestic banking system. Global determinants include world growth rate, global liquidity,

US inflation and the 3-months T-bill rate. Institutional variables include economic and

political liberties, corruption, law and order and bureaucratic quality. Geopolitical factors

include average of oil and gas assets and the countries’ nuclear capability. Findings

provide the evidence of a non-linear relation between economic development and the

volatility of capital inflows. Financial factors play an important role in reducing the

volatility of all inflows. Regarding the volatility of portfolio flows domestic

macroeconomic factors paly a very little role. Economic and political stability play an

important role in reducing the volatility of portfolio inflows while global and geopolitical


85

factors contribute in reducing the volatility of all type of capital inflows. It is concluded

that global factors have reduced the relative importance of domestic factors however

domestic factors can still play their role in reducing the volatility, in particular stable

macroeconomic policies and a sound financial system.

Neumann and Tanku (2009) analyze the relationship between financial openness and

volatility of capital flows for of 22 developing and developed countries using panel data

from 1981–2000. They examine the response of different capital flows to financial

liberalization; foreign direct investment, portfolio investment and debt flows. Other

control variables include changes in world rate of interest, world output growth and

domestic output growth. Findings show that liberalization increases the volatility of FDI

flows especially in emerging markets while unexpectedly portfolio flows show a slight

response. Higher world interest rate volatility reduces the volatility of all capital flows.

Higher world growth volatility increases the volatility of portfolio and other flows except

foreign direct investment volatility. Volatility of domestic growth rate increases the

volatility of almost all capital flows. Results of the study regarding the volatility of foreign

direct investment are in contrast to many other studies that explain FDI flows are most

stable and less volatile as compared to other flows. Study does not provide any rationale

for this outcome.

Mercado and Park (2011) explore the factors that affect the size and volatility of different

capital inflows to emerging economies from 1980–2009. They examine the impact of

internal and external factors on the level and volatility of disaggregated capital flows.

Internal macroeconomic factors comprise economic growth, inflation, trade openness and

exchange rate. Financial sector indicators include stock market capitalization and interest

rate differential. Apart from the macroeconomic and financial indicators, institutional

quality index is also examined. Global economic indicators are global growth expectation


86

and global broad money growth. Findings show that trade openness and volatility of real

exchange rate is directly associated to the volatility of all capital inflows in full sample as

well as in Developing Asia. Stock market capitalization, economic growth and

institutional quality decrease the volatility of capital inflows in Developing Asia. Global

money growth is inversely related to the FDI inflows in Developing Asia. The findings

suggest that pull factors play an important role in the determination of capital inflows for

both the full sample and developing Asia as well. The findings propose that stable

macroeconomic environment and higher institutional quality is crucial to attract stable

capital flows.

Globan (2012) investigates the relationship between reversals of capital flows during

global financial crisis and composition of capital flows for 75 developed and developing

countries. Capital flows came to a sudden stop with the spread of the financial crisis in

2008. Findings show that those countries with higher dependence on foreign loan (debt)

rather than FDI (equity) financing observed higher reversals of foreign capital during the

crisis. Developing and emerging economies were harder hit by the crisis than advanced

economies.

Waqas et al. (2015) explore the macroeconomic factors that determine volatility of

portfolio investment for South Asian countries based on monthly data from 2000-2012.

Macroeconomic variables considered in the study are; interest rate, exchange rate,

inflation, stock market return, industrial production, GDP growth rate and foreign direct

investment. Less volatility in international portfolio investment is associated with high

interest rate, currency depreciation, lower inflation, higher stock market return, higher

GDP growth, higher industrial production and higher foreign direct investment. Findings

show that inflation rate reduces the volatility in case of China and India, while it has no

effect for Pakistan and Srilanka as both of these countries have hyper inflation rate which


87

reduces the real rate of return on portfolio investment. Real exchange increases the

volatility in case of China as China is intentionally increasing its currency value which has

reduced the return thereby increasing the volatility. In Pakistan and India, higher interest

rate raises the volatility because higher inflation rate reduces the benefit of portfolio

investment to foreigners. Foreign direct investment, economic growth and industrial

production reduce the portfolio investment volatility in all countries. Higher stock market

return reduces portfolio volatility but opposite hold in case of China and Pakistan as stock

market is not fully liberalized in China and in case of Pakistan sudden breakages enhance

the volatility. Study focus on stable macroeconomic environment of the country while

ignoring the external factors and also institutional quality. In a globalized world external

factors have an important role to play in determining the volatility of capital flows.

2.7.1.2 Determinants of trade flows volatility:

Massell (1970) analyze the effect of a set of variables, that describe an economy’s

structure, on export instability for 55 developed and developing countries from 1950-66.

He discusses some supply side as well as demand side factors that determine export

instability. Some foods and agriculture products face supply instability. Demand side

factors include change in income and change in prices of related goods. Goods having

more income elasticity of demand (raw material) are more unstable as compared to goods

having less income elasticity of demand (food). Moreover commodity concentration as

well as geographic concentration also affects the instability of exports. On the bases of

above discussion he uses commodity concentration, geographic concentration,

specialization on food, specialization on raw materials, export market share, domestic

consumption of exported goods, size of the export sector and per capita income as

determinants of export instability. He uses Hirschman index to measure export

concentration and geographical concentration. Findings show that less export


88

diversification and higher domestic consumption increases the instability. Higher size of

the export sector, specialization in food items and higher level of development reduce the

instability. Study ignores exchange rate fluctuations and global factors as determinants of

export instability.

Aslam (1985) examines the determinants of export instability in case of Pakistan 1960-61

to 1979-80. The study considers the determinants such as commodity concentration and

geographical concentration, size of the export sector, income per capita, share of food and

exports raw material exports. Gini-Hirschman index is used to measure commodity

concentration and geographical concentration. Findings show that geographical

concentration reduces the instability of exports. As a result of commodity agreements with

its partners during the sixties and seventies trade fluctuations smoothed out in Pakistan.

Size of the export sector reduces the instability as the larger size of the export sector

reduces fluctuations. Higher per capita income increases the diversification hence reducing

the instability. Exports share of food in total exports increases instability as they are

subject to supply side fluctuations. Export share of raw material reduces instability due to

commodity agreements and price pegging policies in Pakistan on the part of importing

countries. Study ignores domestic macroeconomic and external factors as determinants of

export instability. Inclusion of such factors can enhance the significance of the study.

Charette (1985) investigates the determinants of export instability in 15 less developing

countries’ primary commodity markets between 1960 and the mid-1970's. He examines

the price, quantity and earning instability. As described above fluctuations or shift in

demand and supply both brings fluctuations in export earnings. Shifts in exports supply

are caused by fluctuations in output and domestic demand. Demand shifts are caused by

cyclical fluctuations in developed countries. Higher geographical concentration as a result

of international commodity agreements increases the stability. Geographical concentration


89

is measured through Herfindahl index. Percentage of exports as a share of domestic output

and percentage of exports as a share of world exports and dummy variables representing

agricultural and raw material markets are the other explanatory variables. Findings show

that higher share of exports out of domestic production reduces the instability of exports

earnings, prices and output. Geographical concentration reduces the instability also.

Sarada et al. (2006) investigates the determinants of Indian sea food export instability

from 1981-82 to 2003-04. Most of the developing countries (including India) find their

major share of export earnings from particular few commodities and the trade is

concentrated with a few nations as well. These developing countries have hardly any

mechanisms at their disposal to hedge against the adverse consequences of instability.

Bearing in mind the strengths of Indian fisheries sector the causes of instabilities in export

of seafood is of enormous importance. Study includes commodity concentration and

geographical concentration as determinants of export instability of seafood. Other

variables include shrimp production, fisheries and non- fisheries GDP. Findings show that

commodity concentration reduces the instability while geographical concentration, the

instability of fisheries and non-fisheries GDP and instability of shrimp production

increases the instability of seafood export. Study proposes that government can take

stabilization measures using domestic stabilization schemes as well as external measures

by the international community.

Baum and Caglayan (2009) examine the association between exchange rate uncertainty

and volatility of trade flows over 1980–2006 including Eurozone countries, other

industrialized countries, and newly industrialized countries (NICs). It is commonly

believed that exchange rate uncertainty lowers the trade volume by increasing the riskiness

of trading activity. It affects the investors’ decision-making process, in particular

production, investment and hiring decisions. They measure the exchange rate and trade


90

volatility through bivariate GARCH model. Findings show that exchange rate uncertainty

is positively related to the volatility of trade flows.

Neena (2015) explores the sources of export instability in India by using time series data

from 1987-88 to 2012-13. Most of the literature in this context link the instability of

export with commodity and geographic concentration of exports. Composition of exports

especially overdependence on primary exports in LDCs is an important determinant of

export instability. Study includes different explanatory variables like instability index of

primary exports, chemical products exports, engineering products exports, petroleum

products exports, commodity concentration and geographic concentration index by using

multiple regression analysis. Findings show that instability of textile products and

petroleum products reduces the export instability while instability of primary products,

chemical products, engineering products and geographical concentration of exports

increases the total export instability.

2.7.1.3 Determinants of fiscal policy volatility:

Henisz (2004) evaluates the relationship between political institutions and volatility of

fiscal policy for 91 developed and developing countries from 1971-92. Disaggregated

expenditure and revenue represent the fiscal policy. Constraints on the policy maker’s

discretion are represented by political constraints index. Findings show that higher

political constraints reduce the volatility of different categories of capital and current

expenditures as well as tax and non-tax revenues. Volatility of tax and non-tax revenue

seems to be highly affected by institutional changes. It implies that government can

readily alter these sources against the short term need to increase availability of funds.

Regarding the expenditures it appears that capital expenditure volatility is highly related to

political institutions which shows large discretion in these expenditures for political

motive. Volatility in goods and services expenditure and political institutions is smaller


91

representing the less discretion. Study ignores the role of macroeconomic and global

factors that play an important role in fiscal policy volatility.

Fatas and Mihov (2008) analyze the association between institutions and volatility of

fiscal policy for ninety one developed and developing countries over the period 1960-

2000. They use only government spending for the empirical analysis of fiscal policy

because it remains less volatile as compared to taxes. They examine the effect of

macroeconomic and institutional determinants on volatility of fiscal policy. Institutional

determinants include political constraints, political system, electoral system and number of

elections. Other determinants include urbanization, openness, dependency ratio and GDP

per capita. Empirical analysis shows that institutional quality represented by political

constraints significantly and robustly contributes to fiscal policy volatility which implies

that increasing the degree of checks and balances reduces policy volatility. Political and

electoral system and number of elections do not show the robust behavior. Urbanization

and dependency ratio increases the volatility while openness and GDP per capita reduces

the volatility of fiscal policy. Findings propose imposition of institutional constraints to

reduce the volatility of fiscal policy. Fatas and Mihov (2013) add an additional variable of

institutional quality to earlier study which is represented as constraints on the executive.

Findings show that constraints significantly reduce the policy volatility.

Agnello and Sousa (2009) evaluate the factors that determine volatility of public deficit for

a panel of 125 countries from 1980-2006. High and volatile fiscal deficits can lead towards

inefficient allocation of resources, they may raise the debt-to-GDP ratio thereby reducing

the fiscal sustainability. The main objective of the study is to evaluate the political,

institutional and economic determinants of fiscal policy volatility. Political instability,

democracy, per capita income, inflation, trade openness and budget deficit represent the

political, institutional and economic determinants of fiscal policy volatility respectively.


92

Findings show that higher political instability increases the volatility of public deficit

while democracy reduces the volatility. Poor countries tend to have more volatile budget

deficits due to weak automatic stabilizers while richer countries are characterized with

stable deficits. Higher inflation increases the fiscal volatility as it brings economic

uncertainty making volatile the spending and revenue. Trade openness increases the

volatility of budget deficit as it exposes the countries to external shocks. Higher public

deficit increases the instability due to unanticipated changes in government expenditures

and taxation.

Bleaney and Halland (2009) examine the effect of primary exports on output volatility and

fiscal volatility for 75 countries from 1980-2004. Due to the volatile prices of primary

products countries experience greater real exchange rate volatility that increases growth

volatility and also fiscal volatility. Exports of primary product are disaggregated into sub

components; fuels and raw materials and food. Study focuses on resource curse as a source

of fiscal policy volatility. Share of primary exports is directly associated to both output

and fiscal volatility. Institutional constraints reduce the volatility of fiscal policy. Study

has given no importance to macroeconomic variables which are also considered an

important source of fiscal volatility.

Albuquerque Bruno (2010) provides empirical evidence regarding the quality of fiscal

institutions and volatility of discretionary fiscal policy for a panel of 25 EU countries over

the 1980-2007. Developed countries have experienced a general surge in budget deficits

along with higher public debt during last decades. Study focuses on institutional and other

factors that can reduce such volatility. Following Fatas and Mihov (2008) they measure

the discretionary fiscal policy18

. Fiscal institutions are represented by the fiscal rule index

18

Volatility of the residuals by running a regression of government consumption growth on output growth,

lagged government consumption growth and on other control variables measures the discretionary fiscal

policy.


93

and the delegation index. Fiscal rules and delegation index represent explicit and implicit

constraints faced by the policy makers. Political variables include type of the electoral

system and the number of elections. Macroeconomic variables include per capita income,

government size, country size, openness to represent the degree of integration, inflation as

an indicator of macroeconomic uncertainty. Empirical findings provide the evidence that

fiscal institutions reduce the volatility of fiscal policy significantly. Political variables

remain insignificant. Bigger countries and larger government reduces spending volatility

due to larger automatic stabilizers. Findings propose the strengthening of fiscal institutions

to manage the fiscal volatility.

Attiya et al. (2011) empirically examine the determinants of fiscal deficit volatility for

South Asian and ASEAN countries from 1984 to 2010. Beside the persistent increase in

budget deficits its volatility has also become a great concern for many developed and

developing countries. They focus on the economic, political and institutional determinants

of budget deficit volatility. Economic factors include level of budget deficit, income per

capita, inflation and openness. Political and institutional factors include political stability,

democracy and low level of corruption. Findings show that income per capita, deficit to

GDP, inflation and openness increase the volatility of budget deficit. Countries with

higher level of development are more dynamic and this dynamic characteristic increases

the volatility though this finding is in contrast to many other empirical studies. Moreover

budget deficit volatility has persistence effect. Findings show that all the political and

institutional variables reduce the volatility of budget deficit.

Agnello and Sousa (2014) examine the factors influencing the volatility of fiscal discretion

for 113 countries from 1980-2006. Main focus of the study is to highlight the importance

of institutions in reducing fiscal discretion. They use the discretionary component of fiscal

policy with respect to deficit, revenue and spending. They emphasize on political,


94

institutional and macroeconomic determinants of the volatility. Political and institutional

determinants include democracy, cabinet changes in addition to the political system and

political constraints. Economic variables include trade openness, financial openness and

the exchange rate regime. The importance of the country size is considered through

population. Findings show that fiscal policy volatility shows persistence. Higher

democracy and parliamentary systems reduces volatility. Higher government turnover

increases volatility. Country size and less flexible exchange rate regime reduces the

volatility. The results remain robust by considering different regions and country sub

groups. The presidential regimes are related to larger instability in non-OECD countries,

developing countries and non-EU countries and the effects of the country size is more

important for this sample also.

2.7.1.4 Determinants of monetary policy volatility:

Koedijk et al. (1997) examine the dynamics of interest rate volatility using monthly and

weekly data of short term interest rate for the US from January 1968–July 1996. To

analyze the behavior of volatility they use CKLS19

and the conditional heteroskedasticity

GARCH model. Findings propose that both GARCH and level effect play an important

role in determining the interest rate volatility. Weekly frequency provides the most

accurate evaluation of the volatility.

Ball and Torous (1999) examine the dynamics of short-term interest rates over a number

of countries using monthly data. They use a variety of short term interest rates and

estimate a stochastic volatility model of short-term interest rate dynamics. They also use

EGARCH model for comparison. Analysis shows that interest rate dynamics are affected

by economic shocks. Short-term interest rates are more responsive to these shocks.

19

Chan, Karolyi, Longstaff and Sanders (1992)


95

Moreover interest rate dynamics are similar across a number of countries. Level of the

interest rate is also an important determinant of volatility.

Edwards and Susmel (2003) analyze the behavior of interest rate volatility using high

frequency weekly data from 1994-1999 for Latin American and Asian countries. They use

univariate and bivariate switching volatility model and also rolling standard deviation

model. Findings provide the signal of co-movement of interest-rate volatility across

countries. These co-movements depict the effect of domestic and international shocks;

Mexican (1995), East Asian (1997), Russian (1998), and Brazilian (1999) crises.

Argentine’s interest rate illustrates the largest increase in the aftermath of the Mexican and

Russian crisis. Mexican interest rate increased sharply in the aftermath of the Mexican

peso crisis and also has been sensitive to major international crises. Hong Kong

experiences a larger increase at the time of the East Asian crisis and around the time of the

Russian crisis.

Olweny (2011) examines the relationship between level of short term interest rate and its

volatility for Kenya using monthly data of 3 month Treasury bill rate from 1991M8 to

2007M12. The financial sector in Kenya suffered from severe repression before the

implementation of Structural Adjustment Programme (SAP) in 1983. Interest rate

deregulation took place accompanying the SAP. Findings illustrate that volatility is

positively associated with the level of the short term interest rate. Findings also reveal that

the GARCH model is a better measure of volatility of short rates as compared to ARCH

model. GARCH model provides a better description of interest rate dynamics with

normality assumptions.

Duncan (2013) evaluates the impact of institutional quality on the cyclicity and volatility

of monetary policy and volatility of output for 56 developed and developing countries

from 1984.Q1-2008.Q4. Emerging markets are characterized by procyclical or acyclical


96

monetary policy. This characteristic of monetary policy can be related to weak

institutional quality. Findings show that institutional quality is significantly related to

monetary cyclicity. The model shows a positive co-movement between output and the

interest rate (countercyclical monetary policy) at relatively high levels of institutional

quality. There is an inverse relationship between volatility of both output and interest rates

and the institutional quality. Moreover lower institutional quality discourages both FDI

and foreign borrowing. Study ignores other macroeconomic and external factors that can

enrich the findings of the study.


Regarding the determinants of the volatility of capital flows empirical literature

examines the domestic and global factors as a cause of volatility. Domestic factors are also

called pull factors while global factors are called push factors. Domestic factors include

macroeconomic variables, financial sector variables and institutional variables.

Macroeconomic variables include income per capita as a measure of level of development,

inflation as a measure of economic uncertainty, trade openness as a measure of world

integration, government consumption or budget deficit, interest rate and its volatility,

exchange rate and its volatility, stock market return and industrial production. Empirical

literature shows that higher level of development shows improvement in economic

conditions; saving, investment, financial system all of which make capital flows less

volatile. Volatility of capital flows increases in countries with higher inflation rates as it

reflects unpredictable and distortionary monetary conditions. Trade openness increases the

volatility as countries become more vulnerable to external conditions and especially if

their export base is weak. Higher public deficits increase the probability of undergoing a

debt crisis there by increasing volatility. Higher interest rate increases the capital flows, by

decreasing the borrowing cost, while decreasing their volatility. Devaluation of host


97

country currency encourages the foreigners to invest due to higher return thereby

decreasing their volatility. Higher interest rate and exchange rate volatility increases the

volatility of capital flows. The stock of foreign exchange reserves lowers volatility as low

reserves lead to liquidity crises by increasing the volatility. Industrial production signals

higher and stable economic growth which decreases volatility

Financial sector variables include bank asset, credit and deposit ratios as a ratio to GDP

and represent the size or level of development of the banking sector. Empirical findings

show that higher asset, credit and deposit ratios are the representative of more developed

banking systems, thereby reducing volatility.

Institutional factors include institutional quality, economic freedom, rule of law etc.

Higher institutional quality lowers the volatility of capital flows. Higher institutional

quality is an indicator of stable macroeconomic conditions, strong financial and legal

system which makes capital flows stable.

Global factors which are also called push factors in the empirical literature include global

growth, foreign interest rate, interest rate volatility, inflation and global liquidity.

Countries that are dependent more on international funds become more sensitive to global

push factors. Higher foreign interest rate, global growth rate and global liquidity lower the

volatility of capital flows in developing countries. It reduces the incentive for foreign

investors to go offshore as well as it increases the risk for investing in developing

countries which discourage foreign capital inflows. Higher inflation is associated to higher

volatility. On the other hand higher foreign interest rate may also increase the volatility in

domestic market if there is business cycle co-movement. Higher foreign growth can also

increase the volatility in domestic market by the availability of funds for investment.

Regarding the determinants of volatility of trade flows literature provide the empirical

evidence regarding instability of exports. Empirical literature discusses both the demand


98

and supply side factors. Based on these factors studies analyze some determinants that

affect instability these include commodity concentration, geographical concentration,

share of primary exports (food and raw materials), domestic consumption of exported

goods, export market share, size of the export sector, per capita income, exchange rate

uncertainty etc.

Instability reduces if exports are more diversified. Geographic concentration also brings

higher export instability as it increases the dependence on one or few countries and any

change in economic condition of these countries bring higher export instability. More

diversified export destinations reduce the export instability. There is also opposing view

that higher geographical concentration as a result of international commodity agreements

increases the stability. Primary products face more unstable demand and supply curves and

lead to greater degree of fluctuation in export receipts. Higher domestic consumption

increases the export instability. Larger export market share contributes to more diversified

exports and absorb the demand fluctuations. Size of the export sector also represents the

export share in the world market. Higher per capita income shows flexibility where a

country is better able to shift the resources among products as a result of demand

fluctuations. Exchange rate volatility reduces trade volume and increases the trade

variability by inducing the risk.

We conclude that available literature on export instability discusses some common factors

as commodity concentration, geographical concentration, size of export sector and

composition of exports. There is only one study that discusses the relationship of export

instability with exchange rate uncertainty while there are level studies available in this

respect. Moreover available literature also ignores external factors as determinants of

export instability. Therefore while explaining our result we will get empirical support from

level studies for some variables.


99

Regarding the determinants of fiscal policy volatility empirical literature examines the

political, institutional macroeconomic and demographic variables as a cause of volatility.

Moreover policy persistence is also included as a lag of dependent variable. Literature

ignores the role of external factors in explaining the fiscal policy volatility. In a globalized

world external factors are an important source of policy volatility in domestic economy.

Political and institutional factors include political constraints, constraints on the executive,

political system, electoral system and number of elections, political instability, democracy,

rule of law etc. Volatility of fiscal policy increases in countries with proportional as

opposed to majoritarian electoral systems and with presidential regimes. Governments that

face political constraints on decision making like checks and balances, from parliament or

from the judiciary, cannot use fiscal policy too aggressively with higher discretion. It

generates policy which is highly predictable and this predictability reduces the volatility.

Macroeconomic variables include per capita GDP, inflation, trade openness and level of

fiscal variables. Poor countries have more volatile budget deficits as a result of their larger

output voariability, less developed financial markets, poor institutions and weak automatic

stabilizers while richer countries are characterized with stable deficits. Higher inflation

increases the fiscal volatility as it brings economic uncertainty making volatile the

spending and revenue. Trade openness increases the volatility of budget deficit as it

exposes the countries to external shocks. Higher public deficit increases the instability due

to unanticipated changes in government expenditures and taxation.

Demographic variables include population size, urbanization and dependency ratio. Large

population spreads the cost of financing over a large pool of tax payers and brings less

volatility in budget deficits. Urbanization and dependency ratio increases the volatility.

Regarding the volatility of monetary policy or interest rate empirical literature is scant.

General tradition is to use high frequency data of different short term interest rates using


100

time series properties and measure the volatility through different methods and then

compare the magnitude of volatility. It just provides the information that the method

which provides the lowest magnitude of volatility is better. We have just one study that

describes the link between institutional quality and cyclicity of monetary policy and its

volatility. It shows positive co-movement between output and the interest rate

(countercyclical monetary policy) at relatively high levels of institutional quality. There is

an inverse association between volatility of interest rates and the institutional quality.

As we have described above that empirical literature is scare regarding the volatility of

monetary policy or interest rate and the available literature discuss only the magnitudes of

volatility through different measures therefore we will get literature support from the level

studies while explaining our results because we are not interested in magnitudes of

volatility through different measures but in determinants of monetary volatility.

2.8 Literature gap:

As discussed in the previous sections that policy volatility reduces the economic growth

mainly through investment channel therefore it is important to explore the factors that can

reduce the volatility. In this regard there is a lot of literature relating the level of policies to

different macroeconomic factors but literature is scarce regarding the volatility of policy.

Moreover there are only few studies that incorporate institutional quality as an important

determinant to reduce the uncertainty or volatility of policy. So it leaves the gap for

identifying the effect of different domestic macroeconomic, institutional and global factors

on policy volatility. Present study fills the gap by addressing the policy volatility and

identifying the factors contributing to it specifically institutional quality. This establishes

the link between institutional quality and policy instability or uncertainty.

We have described in concluding remarks of previous section (2.7.2) that the determinants

of fiscal policy have been extensively empirically examined but unluckily the literature on


101

fiscal volatility is scant. Similarly an increasing body of literature has highlighted the

importance of the level of capital flows by incorporating pull and push factors. In

contrast, relatively few empirical studies have tried to identify the factors that shape

volatility of capital flows. Regarding the volatility of monetary policy or interest rate

empirical literature is also scant. General tradition is to use high frequency data of

different short term interest and measure the volatility through different methods and then

compare the magnitude of volatility. While we are not interested in magnitude of volatility

but in domestic macroeconomic and external factors that determine monetary volatility

specifically institutional quality. Regarding the volatility of trade flows there are only few

studies and they ignore institutional and external factors as determinants of export

instability.

103

102

An Overview of Selected Developing Countries

The chapter is divided into four sections; the first section gives a brief overview of the

economies of selected countries, the second section discusses the dynamics of institutions

and policies of selected countries and the third section provides an overview of

institutional reforms in developing countries. The last section draws the conclusion from

the preceding sections.

3.1 An overview of the economies of selected countries:

We will start this section by giving a synoptic view of the economic performance of

selected countries, in a tabular form to compare the state of their economies. Table 3.2

shows the comparison of per capita growth rates, population growth, inflation rate, human

development and perception of corruption among the selected countries in year 2000 and

2014. Comparison of per capita growth rate shows that in year 2000 growth rate of

Srilanka was highest (6%) while of Kenya was lowest (-1.87%). In year 2014 again

Srilankas’ growth rate was highest (7.36%) while it was lowest in Brazil (-0.73%). During

2000 to 2014 the percentage increase in growth was highest in Kenya (237%), India

ranked second after Kenya having (203 %) increase in growth, while maximum reduction

in growth rate between these two years was in Brazil (91%). Second, population growth

rate in 2000 was highest in Maldives (3.99%) while lowest in Srilanka (0.93%). In 2014

population growth rate was highest in Kenya (2.88%) while it was lowest in Brazil (0.3%).

During 2000-2014 population growth rate was increased in Nepal (20%) while reduced in

all other countries, with maximum reduction in Thailand (81%)

Chapter # 3

103

Table 3.1 Main economic indicators of selected countries

Indicators years Pakistan India Bangladesh Srilanka Maldives Nepal Philippines Vietnam Thailand brazil Mexico Kenya

GDP per capita

growth

2000 1.92 2.01 3.26 6 2.96 4.29 2.20 5.36 3.54 2.81 3.71 -1.87

2014 3.21 6.10 4.86 7.36 5.66 4.20 4.41 4.79 0.30 -0.73 0.78 2.57

%

change 67.19 203.48 49.08 22.67 91.22 -2.10 100.45 -10.63 -91.53 -125.98 -78.98 237.43

Population

growth

2000 3.10 2.18 2.81 0.93 3.99 2.10 2.56 2.60 1.63 2.15 2.02 3.33

2014 2.48 1.73 1.95 0.42 2.05 2.52 1.92 1.07 0.30 0.88 1.83 2.88

%

change -20.00 -20.64 -30.60 -54.84 -48.62 20.00 -25.00 -58.85 -81.60 -59.07 -9.41 -13.51

Inflation rate 2000 4.4 4 2.2 6.2 -1.17 2.5 4 -1.7 1.6 7 9.5 10

2014 7.2 6.4 7 3.3 2.1 8.4 4.1 4.1 1.9 6.3 4 6.9

%

change 63.64 60.00 218.18 -46.77 279.49 236.00 2.50 341.18 18.75 -10.00 -57.89 -31.00

Human

development

index

2000 0.45 0.48 0.45 0.67 0.59 0.44 0.61 0.56 0.64 0.68 0.69 0.45

2014 0.53 0.60 0.57 0.75 0.70 0.54 0.66 0.66 0.72 0.75 0.75 0.54

%

change 17.78 25.00 26.67 11.94 18.64 22.73 8.20 17.86 12.50 10.29 8.70 20.00

Corruption

perception

index

2000 23 27 4 37 24 22 29 26 32 40 37 20

2014 29 38 25 38 27 29 38 31 38 43 35 25

%

change 26.09 40.74 525.00 2.70 12.50 31.82 31.03 19.23 18.75 7.50 -5.41 25.00

Source: World Bank and Transparency international.

Note: Human Development Index lies between 0-1 while Corruption perception index lies between 1-100, where 100 shows no corruption.

Chapter # 3 An Over View of Selected Developing Countries

104

Third, comparison of inflation rate in 2000 shows that it was highest in Kenya (10%)

while lowest in Maldives (-1.17). In year 2014 inflation was highest in Nepal (8%) while

lowest in Thailand (1.9%). Highest percentage increase between these two years was in

Vietnam (341%) while maximum reduction during these years was in Mexico (57%).

Fourth, Human development, represented by (HDI), was highest in Mexico (0.69) while

lowest in Nepal (0.44) in the year 2000. In 2014 it was highest in Mexico, Brazil and

Srilanka with equal score (0.75) while lowest in Pakistan (0.53). Percentage increase

during 2000-2014 was highest in Bangladesh (26%) while lowest in Philippines (8%).

Last, perception of corruption, represented by corruption perception index, was highest in

Bangladesh (4) while lowest in Brazil (40) in 2000. In 2014 it was highest in Bangladesh

and Kenya with an index value of (25) for both countries while it was lowest in Brazil

again (43). Percentage increase in corruption perception during these two years was only

in Mexico with a (5%) increase while reduction took place in all other countries, with

maximum reduction Bangladesh (525%) and least reduction in Maldives with a (12% )

reduction.

We may now proceed with a country wise explanation of the absolute positions of each of

the twelve countries.

3.1.1 Pakistan:

Pakistan is a developing country having population over 190 million and with a nominal

GDP per capita of $1,561 according to 2016 estimates20

. Pakistan has undergone a process

of economic liberalization including privatization, financial and trade liberalization and

fiscal reforms. Until a few years ago Pakistan's economy was highly unstable and exposed

to global and domestic shocks. Though the economy proved to be resistant against the

20

World Bank country reports, The World Factbook. Central Intelligence Agency, Pakistan economic

survey, various issues, Ministry of finance.


105

adverse shocks during (1998-2002) which include the Asian financial crisis, economic

sanctions , the global recession, a severe famine, military operation in Afghanistan, after

9/11, which caused a huge inflow of immigrants.

Government has made substantial economic reforms since 2000 for poverty reduction and

job creation under medium-term projections. Pakistan is continuously cutting tariffs and

encouraging the exports by improving the infrastructure. Fall in money-market interest

rate and a greater expansion in bank credit as a result of monetary policy stability is

changing consumption and investment patterns. The government is following an export-

led strategy of economic growth following South East Asia and China. Financial sector

reforms have improved the financial sector.

Pakistan's economic outlook has deteriorated since the beginning of 2008. Greater

instability has created by security concerns and Pakistan is playing a major role in the War

on Terror. These security concerns have created imbalance in financial resources by

reducing the social sector expenditure and has led to a decline in Foreign Direct

Investment from approximately $8 billion to $3.5billion. Higher global commodity prices

have increased the trade deficit, induced higher inflation and a continuous decline in the

value of the currency. Pakistan has a low tax to GDP ratio which is far below other

countries of the region such as India and Sri Lanka.

The sectoral share of agriculture in GDP has declined over time. There is rapid growth in

industrial (such as apparel, textiles, and cement) and services sector (such as

telecommunications, transportation, advertising, and finance). Industrial sector growth has

accelerated due to the policies of the government to diversify the industrial sector and

boost export industries.

https://en.wikipedia.org/wiki/Asian_financial_crisis

https://en.wikipedia.org/wiki/Economic_sanctions

https://en.wikipedia.org/wiki/Economic_sanctions

https://en.wikipedia.org/wiki/Global_recession

https://en.wikipedia.org/wiki/War_in_Afghanistan_(2001%E2%80%93present)


106

Figure 3.1 Governance indictors (percentile score):

Source: World Governance Indicators (World Bank)

Figure 3.2 Indicators of financial liberalization (% of GDP):

Source: Lane and Ferretti (2007).

Table 3.2 Indicators of fiscal and monetary policy and trade liberalization

Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures

(% of GDP) Current expenditures

Capital expenditures

29.17 26.05 25.56 19.93 19.89 21.05 21.5

21.79 20.95 21.36 16.89 15.49 16.75 16.75

7.38 5.1 4.2 3.05 4.4 4.31 4.75

Tax revenue

(% of GDP) 13.32 12.75 12.83 10.31 8.75 9.98 10.2

Interest rate 7.64 11.52 4.16 4.63 10.98 14.04 11.73

Average tariff rate tariff rate capital goods

tariff rate consumer goods

60.58 52.87 45.61 17.17 14.79 14.8 13.63

30.56 32.56 28.45 26.96 23.97 22.23 22.64

40.36 36.41 32.41 27.14 21.42 22.52 21.79

Trade openness

(% of GDP) 38.909 35.327 34.012 30.538 35.682 32.869 31.168

Import tax revenue (% of imports)

65.459 39.441 25.312 10.073 6.65 3.516 2.451

Source: Asian Development Bank (ADB) and World Development Indicators (World Bank).

0

10

20

30

40

1996 2000 2004 2008 2012

control of corruption

govt. effectiveness

political stability

regulatory quality

rule of law

voice & accountability

0

50

1990 1994 1998 2002 2006 2010 2014

portfolio assets & liabilities

FDI assets & liabilities

Debt assets & liabilities


107

3.1.2 India:

India is a newly industrialized country, a member of BRICS and one of the G-20 major

economies, with an average growth rate of approximately 7% over the last two decades21

.

After the end of British subjugation the India was governed by protectionist policies with

little or no liberalization. Indian economy was characterized by widespread regulation,

protectionism, public ownership, extensive corruption and slow growth. Economic

liberalization has led the country towards a more liberal and market friendly economy

since 1991. Liberalization has lower down the trade barriers including tariff rates and the

policies of deregulation and privatization have shattered public monopolies by

encouraging foreign investment in many sectors. By reducing the state control and

improved financial liberalization India has moved towards a free-market economy by the

21st century.

With an annual growth rate of above 9%, India has one of fastest growing service sectors

in the world. India has also become a major exporter of information technology (IT) and

software services. India has one of the largest auto mobile industries in the world.

The value of India's international trade has increased sharply since liberalization. As a part

of financial sector reforms India's relaxed its FDI policy in 2005 by allowing up to a 100%

FDI stake in ventures. Industrial reforms have significantly lower the restrictions and

enabled easy access to foreign technology and foreign investment. Though India has put

controls on short term capital inflows in order to avoid the currency crisis. The

government has also approved significant banking reforms since liberalization.

A major and widespread problem affecting the Indian economy is corruption. India was

ranked at 95th place in public sector corruption in 2011 by the Transparency International.

By reducing the corruption India enhanced the ranking to 85th place in 2014. The Indian

21

World Bank – India Country Overview, CIA – The World Factbook – India, Reserve Bank of India.


108

economy has a huge underground economy, Swiss Bankers Association recommended

India topped the worldwide list for black money.




Source: Lane and Ferretti (2007)





19.08 16.33 15.81 18.27 15.39 16.52 14.56

14.27 13.2 13.39 14.98 13.58 14.36 12.89

4.81 3.13 2.42 3.3 1.81 2.16 1.67

Tax revenue

(% of GDP) 9.82 8.83 7.97 8.53 11.03 10.19 9.21

Interest rate 16.5 14.75 13.54 11.91 11.18 8.33 10.25



81.56 52.98 28.23 28.18 10 8.31 9.37

72.72 36.45 22.15 20.79 4.99 4.59 4.89

25.28 16.58 26.85 30.04 10.13 9.77 8.35

Trade openness

(% of GDP) 15.239 19.732 23.291 29 52.269 48.308 49.558


78.212 54.49 33.536 18.832 2.601 2.517 1.803

Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)

0

10

20

30

40

50

60

70

1996 2000 2004 2008 2012


govt. effectiveness

political stability

regulatory quality

rule of law


0

20

40

1990 1994 1998 2002 2006 20102014



debt assets & liabilities

https://en.wikipedia.org/wiki/Underground_economy

https://en.wikipedia.org/wiki/Swiss_Bankers_Association

https://en.wikipedia.org/wiki/Indian_black_money


109

3.1.3 Bangladesh:

By purchasing power parity the economy of Bangladesh is the 32nd largest in the world.

Bangladesh has an average GDP growth rate of 6.5%, throughout last decades. Per-capita

income remained at US$3,840 (PPP) and US$1,466 (Nominal) in 201622

.

Inefficiency and economic stagnation in early period was the result of static policies

adopted by early leaders which included the nationalization of much of the industrial

sector. Government slowly moved to liberal policies by allowing and encouraging the

private sector in the economy in late 1975. Privatization and liberalization led the

economy towards progress in the mid-1980s The government successfully followed an

enhanced structural adjustment facility (ESAF) with the International Monetary Fund

(IMF) from 1991 to 1993 but remain unsuccessful to follow it completely because of

domestic political distresses.

Textile industry of Bangladesh has an important contribution in export sector which

includes knitwear and ready-made garments along with other textile products. Bangladesh

is second in world textile exports, behind China, which exported $120.1 billion worth of

textiles in 2009. It is an important source of employment and earnings for the female

sector. More than one million formal sector jobs for women are created by the garment

industry, contributing to the high female labour participation in Bangladesh.

Government has provided a large number of inducements to investors comprising 10-year

tax holidays, tariff and non-tariff reductions on import of capital goods, raw materials and

dividend tax exceptions. Bangladesh has improved the climate for foreign investors by

liberalizing the capital markets. Reforms were aimed at development of financial

22

Bangladesh Economy - Asian Development Bank, The World Factbook. Central Intelligence Agency.

Bangladesh Economic Review, various issues, Ministry of finance.


110

institutions and regulations. Millions of investors have been rendered bankrupt due to the

capital market crash during 2010.









12.42 15.05 12.92 14.92 14.69 12.7 13.68

6.71 6.72 7.1 8.3 8.8 9.17 9.3

5.7 8.32 5.81 6.61 5.88 3.53 4.38

Tax revenue

(% of GDP) 6.75 9.22 9.5 10.2 10.78 9.51 10.4

Interest rate 16 14.5 14 16 15.33 13 13



27.52 24.36 22.26 21.01 15.21 13.91 12.56

55.23 42.86 26.34 12.45 9.63 6.66 7.18

126.23 62.85 38.25 29.86 27.55 15.1 14

Trade openness

(% of GDP) 18.967 22.866 27.88 28.967 38.112 37.803 44.988


94.25 85.839 56.006 43.948 22.121 10.048 6.879

Source: Asian Development Bank (ADB) and World Development Indicators (World Bank).

0

10

20

30

40

50

1996 2000 2004 2008 2012


govt. effectiveness

political stability

regulatory quality

rule of law


0

50

1990 1994 1998 2002 2006 20102014





111

3.1.4 Srilanka:

Sri Lanka has mostly strong growth rates in recent years with $233.637 billion GDP at

purchasing power parity and a per capita GDP of about $11,068.996 (PPP) in 201523

.

During the last decade robust annual growth rate was 6.4 percent. In Sri Lanka tax-to-GDP

ratios are lowest in the world. Sri Lanka is now concentrating on long-term strategic and

development challenges since the end of the three-decade civil war.

The economy of Sri Lanka has been affected by natural disasters such as the 2004 Indian

Ocean earthquake. Internal conflicts also destabilized the economy such as the 1971, the

1987-89and the 1983-2009 civil wars. Since 1977, the move away from a socialist

orientation the, the government has taken many steps towards deregulation, privatization

and encouraging the foreign competition. Country moved from import substitution

towards free market policies and export-led growth.

The key sectors include tourism, tea export, textile, rice production and other agricultural

products. In Srilanka overseas employment contributes greatly in foreign exchange as

large number of emigrants lives in Middle East. Tourism is one of the main industry of

Srilanka and an important source of finance. Due to Indian Ocean Tsunami and the

instabilities caused by internal conflicts this industry suffered greatly however beginning

in early 2008 tourists visiting have been recently increasing.

Sri Lanka is on track to meet most of the MDGs, overtaking other South Asian countries;

Sri Lanka has met the target of halving extreme poverty and moving ahead towards other

targets. Between 2002 and 2009 Sri Lanka witnessed a huge drop in poverty, from 23

percent to 9 percent of the population.

23

Sri Lanka Overview - World Bank, Sri Lanka: Economy - Asian Development Bank , CIA Factbook,

Central Bank of Sri Lanka.

https://en.wikipedia.org/wiki/Tourism

https://en.wikipedia.org/wiki/Tea_Industry_of_Sri_Lanka

https://en.wikipedia.org/wiki/Apparel_industry_of_Sri_Lanka

https://en.wikipedia.org/wiki/Rice

https://en.wikipedia.org/wiki/Agriculture_in_Sri_Lanka

https://en.wikipedia.org/wiki/Agriculture_in_Sri_Lanka


112









28.72 27.19 24.27 23.8 24.17 22.11 18.22

22.58 21.94 19.09 20.22 18.65 16.72 13.52

6.14 5.25 5.18 3.58 5.52 5.39 4.7

Tax revenue

(% of GDP) 19.02 17.17 14.48 13.56 14.58 12.93 10.73

Interest rate 13 18.12 15.02 13.17 12.85 10.21 7.83



26.54 24.3 16.23 9.86 11.29 9.39 9.33

13.76 16.99 8.25 6.65 7.29 5.18 4.5

29.98 32.64 18.36 12.85 13.16 13.96 12.01

Trade openness

(% of GDP) 68.244 79.431 78.495 76.335 71.261 53.062 53.211


64.181 29.896 20.225 13.132 7.527 4.116 7.726


0

10

20

30

40

50

60

70

1996 2000 2004 2008 2012


govt. effectiveness

political stability

regulatory quality

rule of law


0

50

100

1990 1994 1998 2002 2006 20102014

portfolio assets & liabilitiesFDI ssets & liabilitiesdebt assets & liabilities


113

3.1.5 Maldives:

Main sectors of the economy of the Maldives are tourism, fishing and shipping. Tourism

accounted for 28% of GDP and more than 60% of the Maldives' foreign exchange

receipts24

. Tourism is the largest industry and Maldives has successfully promoted it.

Tourism-related taxes account for 90 % of government tax revenue.

Second leading sector in the Maldives is fishing. In 1989 as a result of economic reforms

the government reduced the trade barriers and allowed the private sector to participate in

this sector’s exports. Later on government further relaxed the regulations to permit more

foreign investment. Dried or canned fish consist of 42%, frozen fish consists of 31% and

the remaining fresh fish consists of 10% of total fish exports. The contribution of this

sector in GDP is 10% and provides the employment to 20% of the labour force. Due to the

unavailability of enough cultivable land and lack of domestic labour agriculture and

manufacture sector do not play a major role in the economy.

The banking industry of Maldives dominates the small financial sector. The Maldives has

been considered to have the simplest tax code in the world, no income, sales, property, or

capital-gains taxes. As for as economic assistance is concerned different multilateral

organizations have contributed in this regard such as United Nations Development

Programme, Asian Development Bank and the World Bank have played a major role in

the economy of Maldives.

Regarding the Millennium Development Goal (MDG), Maldives has successfully

achieved the target of poverty reduction by reducing the percentage of people living below

poverty line to one half according to the estimates of 2011. Malaria has been removed,

Starvation is non-existent and HIV rates have dropped.

24

CIA World Factbook Maldives, Maldives Overview - World Bank, Ministry of Finance and Treasury,

Maldives.

https://en.wikipedia.org/wiki/Tourism

https://en.wikipedia.org/wiki/Fishing

https://en.wikipedia.org/wiki/Shipping


114









14.9 19.57 23.85 23.21 42.36 40.26 41.74

7.257 9.976 14.64 15.62 33.61 30.85 34.3

7.64 9.6 9.21 7.6 8.74 9.4 7.44

Tax revenue

(% of GDP) 13.96 13 14.2 10.3 14.21 10.73 25.02

Interest rate 19 12 15 13.54 13 10.37 11.41



21.39 21.26 21.38 21.98 21.21

24.34 24.64 23.74 22.38 22.65

21.3 19.81 22.09 20.43 16.74

Trade openness

(% of GDP) 168.08 156.946 161.091 104.41 123.665 158.656 195.604


90.175 93.659 64.372 62.89 29.796 24.985 11.017


0

20

40

60

80

100

1996 2000 2004 2008 2012


govt. effectiveness

political stability

regulatory quality

rule of law


0

50

100

1990 1994 1998 2002 2006 20102014





115

3.1.6 Nepal:

Since 1950s Nepal has made progress toward sustainable economic growth. Nepal is

devoted to the program of privatization and deregulation. Many state enterprises have been

privatized and its currency has been made convertible. Foreign assistance from different

multilateral and bilateral donor agencies plays an important part in the development

budget of Nepal. To develop the transportation and communication sector and to increase

the efficiency and productivity of industrial sector have remained the priorities of the

government over the years.

Agriculture is the key sector of the economy, contributing 37% of GDP and providing

employment to 70% of the population according to 2013 estimates25

. In recent years

industrial sector has grown rapidly and contribute to nearly 70% of merchandise exports.

Remittances of foreign workers are a big source of income in Nepal. Overall balance of

payments and international reserves have improved due to increased productivity of export

sector and income from tourism sector. Tourism plays an important role in the economy of

Maldives.

Foreign investment is taking place mostly in real estate and tourism. Having huge

capacity of Hydroelectricity in Nepal large many foreign firms are in line but the process

has stopped due to political instability. Numerous multilateral organizations also provide

assistance such as the World Bank, the Asian Development Bank and the UN

Development Programme.

Development in infrastructure and social services has not made remarkable progress.

Country wide universal education system is not well developed also. In Nepal the Cost of

Living Index in is relatively smaller as compared to many other countries. In recent years

25

Nepal Overview - World Bank, Nepal: Economy - Asian Development Bank, Economic Review - Central

Bank of Nepal.

https://en.wikipedia.org/wiki/Gross_domestic_product


116

the quality of life has deteriorated. Out of 81 ranked worst countries Nepal was ranked

54th

.









17.72 15.65 17.35 17.43 14.54 19.04 19.6

6.012 5.78 8.4 10.58 10.25 15.64 16.31

11.7 9.87 8.95 6.85 4.3 3.4 3.29

Tax revenue

(% of GDP) 7 7.73 8.64 8.56 8.78 13.4 16.1

Interest rate 14.41 7.31 14 6.77 8 8 6.13



22.56 20.88 21.69 14.57 12.51 12.62 11.82

32.56 42.58 21.45 13.96 14.23 11.16 8.56

35.58 34.25 33.55 28.63 20.85 19.2 18.63

Trade openness

(% of GDP) 32.189 50.432 56.71 46.231 44.762 45.985 52.445


86.536 42.684 40.198 33.013 16.047 6.433 4.765

Source: Asian Development Bank (ADB) and World Development Indicators (World Bank

0

10

20

30

40

50

60

70

1996 2000 2004 2008 2012

control of corruptiongovt. effectivenesspolitical stabilityregulatory qualityrule of lawvoice & accountability

0

20

40

60

80

1990 1994 1998 2002 2006 20102014

portfolio assets & liabilitiesFDI assets & liabilitiesdebt assets & liabilities


117

3.1.7 Thailand:

Thailand is a newly industrialized country and export sector play a major role in the

economy. Exports account for more than two-thirds of its gross domestic product (GDP).

Average growth rate of the economy is 6.5 percent with an inflation rate of 3.02 percent26

.

Industrial and service sectors play an important role in the economy of Thailand,

contributing to 39.2 and 54.4 percent of GDP respectively according to 2012 estimates.

Thailand’s trade balance has improved much with the help of automobile exports since

2005, with over one million cars produced annually. About 15 percent of total exports

electronics is Thailand's largest export sector. Trade in services has emerged as a source of

industrial expansion and economic competitiveness. Thailand has pursued many free-trade

agreements. Tourism is an important sector significantly contributing to the Thai

economy, around 8.5 percent of GDP.

Thai economy collapsed confronted with the 1997 financial crisis. The crisis was the result

of over investment in the real estate and share market. As a result of crisis the Stock

Exchange of Thailand fell from a peak of 1,753.73 in 1994 to a low of 207.31 in 1998.

Foreign debt increased due to sharp decline in the value of baht. Many financial

institutions undergo bankruptcy.

The country has confronted a number of internal and external challenges since 2007; in

late 2006 having a military coup, from 2008 to 2011 political disorder, from 2008 to 2009

the US financial crisis, floods in 2010 and 2011 and Eurozone crisis of 2012.

Through the collaboration of state and foreign-owned institutions the government has

attempted to strengthen the financial sector. The reforms of the financial sector, corporate-

26

Thailand Overview - World Bank, Thailand: Economy - Asian Development Bank, Economic Reports,

Ministry of Finance Thailand.


118

debt restructuring, stimulus to foreign investment and exports have improved the

economy.









13.94 15.96 22.36 24.06 18.52 19.73 19.87

11.41 10.55 16.37 21.19 16.52 17.83 18.58

2.53 5.41 5.99 2.87 2 1.9 1.29

Tax revenue

(% of GDP) 16 12.86 15.25 13.68 16.52 14.57 15.31

Interest rate 14.41 10.89 14.41 6.87 7.35 5.93 6.77



41.22 24.36 32.05 13.76 10.81 11.1 8.42

38.35 20.56 26.52 7.69 4.55 5.39 2.57

45.76 36.54 32.14 17.85 10.16 13.48 5.58

Trade openness

(% of GDP) 75.782 82.587 101.868 121.697 143.804 135.142 142.731


54.821 25.03 23.424 13.658 3.432 1.944 0.728


0

10

20

30

40

50

60

70

1996 2000 2004 2008 2012

controll of corruption

govt. effectiveness

political stability

regulatory quality

rule of law


0

50

100

1990 1994 1998 2002 2006 2010 2014





119

3.1.8 Vietnam:

Vietnam's economy is a developing market economy. Vietnam has moved from a highly

centralized economy to a mixed economy since the mid-1980s. The economy has

experienced rapid growth over that period. The nominal GDP reached to US$198.8 billion

with nominal GDP per capita of US$2,073 in 201527

.

The economy of Vietnam experienced a slowdown in productivity and growth after the

end of the Cold War. Country has moved towards a more market-oriented economy as a

result of liberalization, though government has still control over the key sectors such as

financial sector, state-owned enterprises and foreign trade.

Vietnam is one of the largest exporters of rice in the world market followed by coffee.

Manufacturing sector experienced rapid growth including food processing, electrical

goods, chemicals, cigarettes and tobacco. Real estate sector has contributed greatly in the

economy over the last 2 decades but also caused "bubble" to the economy. Share of the

services sector to the GDP increased to an average annual rate of 6.0% from 1994 to 2004.

Vietnam is also an attractive destination for tourists.

The economy of Vietnam depends greatly on foreign investment. In this regard Vietnam

encourages and facilitates the foreign direct investment to attract the capital from overseas.

Industry and construction are the largest sectors for licensed FDI. Important channels of

investments in the economy are mergers and acquisitions especially after 2005.

There are three objectives of World Bank's support program for Vietnam; to encourage

Vietnam’s switch to a market economy, to support good governance and to enhance

equitable and sustainable development. Major obstacles to investment include Corruption,

lack of transparency, poor property rights to investors and bureaucracy.

27

Vietnam Overview - World Bank , Viet Nam: Economy -Asian Development Bank, Vietnam country

statistics by Ministry of Finance and State Bank.


120









21.89 25.01 20.34 24.16 25.28 27.17 25.61

16.83 18.68 14.65 15.72 16.96 18.68 20.33

5.06 6.33 5.68 8.44 8.32 8.49 5.28

Tax revenue

(% of GDP) 14.7 22 19.6 22.3 26.8 26.71 21.76

Interest rate 26.4 18.9 14.4 9.06 11.17 13.13 8.66



21.68 14.5 15.45 14.21 11.9 7.29 6.7

11.25 9.58 12.56 11.44 6.22 3.3 1.56

26.53 24.25 22.96 22.32 15.5 10.19 6.35

Trade openness

(% of GDP) 81.316 77.473 97.001 107.829 138.314 152.217 165.094


0

10

20

30

40

50

60

1996 2000 2004 2008 2012


govt. effectiveness

political stability

regulatory quality

rule of law


0

50

100

150

1990 1994 1998 2002 2006 20102014





121

3.1.9 Philippines:

The Economy of the Philippines is one of the emerging markets. The GDP estimates for

2016 are $811.726 billion at Purchasing power parity. Political instability aggrieved the

country and the economy. Currently it is one of Asia's fastest growing economies.

The Philippines is a newly industrialized economy, transitioning from agriculture to

services and manufacturing. Services sector has become the dominant sector of the

economy. The industrial sector consists of processing and assembly processes in the

manufacturing of electronics and other high-tech components. Tourism plays an important

role by sector contributing 7.8% to the gross domestic product (GDP) according to 2014

estimates. Tourism sector is major source of employment as it provided employment to 3.8

million people in 201428

. Overseas workers are a significant contributor to the economy.

Business process outsourcing (BPO) is regarded as one of the fastest growing industries in

the world. Many reputed BPO firms of the United States operate in Philippines. BPO

industry continues to show significant improvements. Philippines is regarded as choice of

location owing to less expensive labour and operational costs and a highly educated labor

pool. Government provides the incentives to further encourage the investors such as tax

holidays, tax exclusions, and easy business processes.

Both tourism and foreign investment play an important role in the development of the

economy. To improve and encourage the tourism industry certain policies are introduced

such as Holiday Economics, encourage celebrating certain holidays.

28

Philippines: Economy- Asian Development Bank, CIA World Factbook, Economic statistics, Central

Bank of Phillipines.


122









20.4 18.85 19.22 19.84 17.31 16.9 18

17.28 16.38 17.56 18.57 16.81 16.88 16.98

3.12 2.47 1.66 1.27 0.5 0.02 1.02

Tax revenue

(% of GDP) 14.08 16.03 14.11 11.82 13.71 12.15 13.6

Interest rate 24.11 15.05 16.77 9.13 9.77 7.67 5.52



19.54 21.22 10.4 5.29 5.4 4.84 2.76

10.53 6.32 3.94 0.67 0.88 1.37 1.23

26.53 22.75 18.42 9.15 8.93 11.37 3.85

Trade openness

(% of GDP) 60.8 73.96 98.662 102.435 94.941 71.419 60.573

Import tax revenue

(% of imports) 80.872 46.134 21.449 17.473 15.78 15.012 12.142


0

10

20

30

40

50

60

1996 2000 2004 2008 2012


govt. effectiveness

political stability

regulatory quality

rule of law


0

100

200

1990 1994 1998 2002 2006 2010 2014





123

3.1.10 Mexico:

Mexican economy grew at an annual rate of 2.5 % through 2015 and 2016. Government

has improved the country's macroeconomic fundamentals since the 1994 crisis. Mexico

was most affected by the 2008 recession relative to other Latin American nations with a

6% decline in the GDP growth.

Since 1998 exchanged rate has remained stable under the reforms commenced after the

1994 peso crisis. The tax revenue is also lowest at 19.6 percent of GDP in 2013 among the

34 OECD countries29

. Human development index of Mexico was reported at 0.75, ranked

74th in the world, within the group of high-development according to 2014 estimates.

Services sector contribution to GDP is 60% followed by the industrial sector at 37%

according to 2013 estimates. Trade liberalization has improved the industrial sector.

Automotive industry is among the major industrial manufacturers, whose quality standard

is internationally recognized. The electronics industry of Mexico ranks sixth largest in the

world after China, Japan, Taiwan, South Korea and United States. Many foreign firms

have business set up in Mexico such as Phillips, Vizio and LG.

The financial sector is dominated by either foreign firms or mergers. The process of

institution building in the financial sector has developed with the efforts of financial

liberalization and integration. After the 1994–95 financial crisis Mexico’s monetary policy

was reconsidered, price stability was set as the main goal of monetary policy to sustained

growth.

More than 90% of Mexican trade is under free trade agreements. Remittances are the

largest source of foreign income. Tourism is an important industry and a largest source of

foreign exchange earnings.

29

Mexico Overview - World Bank, Mexico Economic Review.


124









18.82 15.92 16.71 17.59 13.58 14.59 15.7

14.38 12.52 11.59 11.47 10.5 11.66 12.28

4.44 3.4 5.12 6.12 3.08 2.93 3.42

Tax revenue

(% of GDP) 12.01 11.9 12.23 15.84 16.46 14.63 16.95

Interest rate 22.56 19.3 26.35 8.21 7.51 5.28 3.55



14.78 13.57 14.72 15.29 8.04 7.73 6.5

20.65 7.56 10.22 3.91 1.74 1.58 1.23

18.56 10.74 16.11 6.49 3.81 8.47 9.56

Trade openness

(% of GDP) 38.306 29.297 51.776 48.371 56.362 60.947 66.394

Import tax revenue

(% of imports) 33.722 18.475 7.616 4.17 2.19 1.169 1.006


0

10

20

30

40

50

60

70

1996 2000 2004 2008 2012

controll of corruption

govt. effectiveness

political stability

regulatory quality

rule of law


0

50

100

1990 1994 1998 2002 2006 20102014





125

3.1.11 Brazil:

Brazil is one of the ten largest markets in the world with a population of over 204 million

and abundant natural resources. With respect to nominal GDP Brazil has the world's

seventh largest economy. It’s a moderately free market and inward looking economy.

Brazil was regarded as one of the largest economy in the world based on growth rate

during 2000 to 2012 with a 5% average annual GDP growth rate. However in 2013

Brazil’s economic growth declined and also showed no liquid growth throughout 201430

.

Since the 1990s measures taken towards liberalizing the economy and fiscal sustainability

provided a better environment for private-sector development by boosting country's

competitiveness. Industrial sector constitutes a major sector of the economy. High foreign

direct investment is attracted by scientific and technological development, which has

averaged US$30 billion per year. Trade surplus also allowed for currency gains and

external debt pay down.

The contribution of the services sector to GDP is 76 percent while the share of the

industrial sector is 18.5 percent of GDP according to 2016 estimates. Out of total labour

force 66 percent is occupied in the service sector according to 2013 estimates. Brazil's

industries consist of automobiles, consumer durables, steel and petrochemicals, computers

and aircraft. Important sources of industrial raw materials and export earnings are large

iron and manganese reserves.

Under the liberalization program besides providing the local businesses Brazil's financial

sector is attracting several new entrants, including U.S. financial firms. To improve its

social security (retirement pensions) and tax system Brazil carried out reforms. Policies

were also formed to create windows of opportunity for local and international investors, to

encourage the exports, industry and trade. Administrative efficiency was also improved.

30

Brazil Overview - World Bank, Economic Survey of Brazil. CIA World Factbook.


126

Brazil has reduced its vulnerability with these reforming efforts; domestic debt has

decreased and exports grew on average by 20% a year.









24.19 26.21 21.82 22.59 26.75 25.89 26.96

19.29 17.63 19.89 19.67 18.81 19.01 20.19

4.9 8.58 1.93 2.92 7.94 6.88 6.77

Tax revenue

(% of GDP) 12.01 11.9 12.23 15.84 16.46 14.63 16.65

Interest rate 88 82 86.36 62.87 50.8 39.99 32



33.5 14.46 17.15 14.56 12.2 13.44 12.01

32.46 19.16 17.72 12.06 9.1 9.48 9.58

28.57 16.68 21.67 11.74 8.47 9.32 10.96

Trade openness

(% of GDP) 15.162 19.333 16.38 27.576 26.04 22.512 25.792

Import tax revenue

(% of imports) 10.155 7.176 5.281 4.016 1.575 1.171 0.992


0

10

20

30

40

50

60

70

1996 2000 2004 2008 2012


govt. effectiveness

political stability

regulatory quality

rule of law


0

20

40

60

80

1990 1994 1998 2002 2006 20102014





127

3.1.12 Kenya:

Kenya is considered a market-based and liberalized economy with a few state-owned

enterprises. Regarding financial, communication and transportation services Kenya is

usually considered as Eastern and central Africa's hub. Kenya had a GDP of $69.977

billion while Per capita GDP was estimated at $1,587 according to 2015 estimates31

.

Import substitution policy of Kenya made its manufacturing sector uncompetitive and

inefficient. Domestic environment for investment has been less attractive due to absence

of export inducements, foreign exchange controls and tight import controls. The

government of Kenya undertook a reform program in 1993 with the support of the World

Bank and the International Monetary Fund. Under this program a series of measures were

undertaken which include the removal of price and foreign exchange controls,

privatization of several public owned enterprises and introduction of conservative fiscal

and monetary policies.

Services sector of Kenya is dominated by tourism and contributes about 61 percent of

GDP according to 2015 estimates. Tourism sector faced downfall in late 1990s due to

security concerns, blasting of the U.S Embassy in Nairobi in 1998. After the service sector

the share of agriculture sector is largest in Kenya’s gross domestic product. Agriculture

accounted for about 24 percent of GDP and 50 percent of export revenue in 2005.

Manufacturing contributes only 14 percent of gross domestic product. The trade balance

fluctuates extensively because of major share of primary exports in total exports which

face unstable prices in the world market. Remittances by non-resident Kenyans are a

significant portion of Kenya's foreign inflows. For future economic growth vision 2030 is

Kenya's current program. The vision is divided into three different parts: economic, social

31

Kenya Overview - World Bank, Kenya Economic Outlook - African Development Bank.


128

and institutional. The long-term goals of this vision are to move towards a successful and

globally competitive nation by the year 2030.









18.69 19.58 18.36 18.98 17.21 18.04 19.96

13.64 15.15 16.25 17.08 14.35 14.16 14.01

5.05 4.43 2.11 1.9 2.86 3.88 5.95

Tax revenue

(% of GDP) 16.21 14.94 15.06 17.29 17.38 19.4 20.89

Interest rate 18.75 36.24 29.49 18.45 13.63 14.37 16.51



33.53 31.23 24.93 20.45 12.27 12.12 11.52

30.25 15.23 10.58 9.39 4.03 3.73 4.58

24.56 18.56 15.74 15.65 11.04 12.89 13.25

Trade openness

(% of GDP) 57.021 71.266 48.897 55.173 55.236 54.227 50.277

Import tax revenue

(% of imports) 25.659 17.722 17.127 14.592 3.124 2.125 1.2


0

10

20

30

40

50

1996 2000 2004 2008 2012


govt. effectiveness

political stability

regulatory quality

rule of law


0

20

40

60

80

1990 1994 1998 2002 2006 20102014





129

3.2 Dynamics of institutions and policies of selected countries:

We will discuss the characteristics of institution and policies of selected countries with the

help of country tables and graphs given in previous section. We will also discuss volatility

and cyclical behaviour of policies given in appendix IV and V respectively.

3.2.1 Institutional dynamics:

In previous section percentile score of each individual indicator of governance provides

the dynamics of governance in each country. Pakistan has highest score on government

effectiveness and least on political stability. India has highest score on voice and

accountability followed by rule of law and government effectiveness and least on political

stability. Bangladesh has highest score on voice and accountability and least on control of

corruption and political stability. Srilanka has highest score on rule of law followed by

control of corruption and regulatory quality where both have more or less same score

while political stability has least score. Maldives has highest score on political stability

then comes regulatory quality and government effectiveness both having same magnitude

and least on voice and accountability. Nepal has highest score on control of corruption

followed by rule of law and least on political stability. In Philippines government effective

has highest score followed by regulatory quality and voice and accountability both having

same magnitude and least on political stability. Thailand has highest score on government

effectiveness followed by regulatory quality and rule of law and least on political stability.

Vietnam has highest score on political stability followed by government effectiveness and

least on voice and accountability. Brazil has highest score on control of corruption

followed by regulatory quality and voice and accountability and least on political stability.

Mexico has highest score on regulatory quality followed by government effectiveness and


130

least on political stability. Kenya has highest score on regulatory quality and lowest on

control of corruption and political stability.

3.2.1 Dynamics of stabilization policies:

Regarding the fiscal policy government expenditures show increasing trends in Maldives

and Vietnam while declining trends in Pakistan, Philippines and Srilanka. All other

countries show mixed trends. While the composition of government expenditures show

that current expenditures are greater than capital expenditures in all the countries, mainly

due to higher expenditures regarding security concerns worldwide and higher debt

servicing payment as developing countries are highly indebted etc., moreover total

government expenditures and current expenditures follow the same trends. In appendix IV

table IVA shows that government expenditures are less volatile in India, Bangladesh and

Mexico while more volatile in all other countries. In appendix V table VA shows that

government expenditures show the procyclical and acyclical behavior in Pakistan, Kenya,

Nepal, Thailand and Vietnam. Government expenditures show countercyclical behaviour

in all other countries. Countries with procyclical or acyclical expenditures show higher

volatility. Higher volatility in some countries with countercyclical expenditures shows the

effect of non-cyclical factors. Tax revenues show increasing trends in Nepal, Mexico,

Brazil and Kenya while declining trends in Srilanka, Pakistan and Philippines. All other

countries show mixed trends. Table IVB shows that tax revenues are less volatile in

Bangladesh while more volatile in all other countries. Table VB shows that tax revenues

are procyclical and acyclical in Brazil, India, Maldives, Mexico, Srilanka and Vietnam,

Bangladesh, Kenya, Pakistan, Philippines and Thailand while they show countercyclical

behaviour only in Nepal. Almost all the countries show the acyclical or procyclical

behavior along with higher volatility.


131

Regarding the monetary policy interest rate shows declining trends in Brazil, India,

Philippines and Thailand while mixed trends in all other countries. In appendix IV table

IVC shows that interest rate is less volatile in all countries except Brazil. In appendix V

table VC shows that monetary policy shows procyclical and acyclical behaviour in

Bangladesh, India, Philippines, Thailand, Vietnam., Brazil, Kenya, Mexico, Nepal and

Srilanka while countercyclical behaviour in Maldives and Pakistan. Most of the countries

show acyclical or procyclical behavior along with less volatility therefore non-cyclical

factors are playing their role in reducing the volatility.

3.2.3 Dynamics of liberalization policies:

In previous section indicators of trade liberalization are represented by average tariff

rate, trade openness and import tax revenue. As a result of globalization average tariff rate

shows declining trends in all countries except Maldives where it shows mixed trends.

Composition of the tariff rate shows that tariff rate on consumer and capital goods both are

declining but tariff on consumer goods is greater than capital goods. Trade openness

shows that increasing trends in Bangladesh, India, Thailand, Mexico and Vietnam while

all other countries show mixed trends. Table IVD in appendix IV shows that trade flows

are less volatile in India, Bangladesh and Brazil while more volatile in all other countries.

In previous section indicators of capital account liberalization are represented by

portfolio assets and liabilities, FDI assets and liabilities and debt assets and liabilities.

Gross capital flows show increasing trends in India, Nepal, Pakistan, Maldives and Brazil

while other countries show mixed trends. Disaggregated data shows that in almost all the

countries debt flows are highest while in non-debt flows FDI flows are greater than

portfolio flows moreover portfolio flows show more swings and are considered more

volatile. FDI inflows show increasing trend, as a result of incentive provided by the

countries to foreign investors, in almost all countries except Vietnam, Philippines and


132

Bangladesh where they show mixed trend. Table IVE in appendix IV shows that FDI

inflows are more volatile in Srilanka, Thailand, Vietnam and Philippines while less

volatile in all other countries. Table VD in appendix V shows that FDI inflows are counter

cyclical in Brazil, India, Srilanka and Thailand. They are procyclical and acyclical in

Kenya and Nepal, Bangladesh, Maldives, Mexico, Pakistan, Philippines and Vietnam.

Countries with acyclical or procyclical behavior are less volatile therefore non-cyclical

factors are playing their role in reducing volatility. Brazil and India show countercyclical

behavior along with less volatility while Srilanka and Thailand show higher volatility

along with countercyclical behavior therefore other factors are responsible for higher

volatility.

Portfolio inflows show increasing trend in Kenya, Nepal, India and Maldives and mixed

trends in other countries. Table IVF in appendix IV shows that portfolio inflows are more

volatile in Srilanka, Thailand, Philippines and Mexico while they are less volatile in all

other countries. Table VE in appendix V shows that portfolio inflows are countercyclical

in Brazil, India and Srilanka while they are procyclical and acyclical in Bangladesh,

Kenya, Mexico, Nepal and Vietnam, Maldives, Pakistan, Philippines and Thailand. In

most of the countries portfolio inflows show the acyclical or procyclical behavior but only

few shows the evidence of higher volatility therefore non-cyclical factors are important in

reducing the volatility. Brazil and India show the counter cyclical behaviour with less

volatility therefore cyclical fluctuations are source of volatility.

3.3 Institutional reforms in developing countries:

3.3.1 South Asia:

There are cultural and institutional resemblances in most South Asian countries due to

their common political past and history of colonial rule. There was an increased demand of

institutional reforms throughout South Asia during 1990s. The main intentions behind this


133

demand include institutional reforms as a consequence of Asian crisis; the consolidation of

democracy in Bangladesh, Nepal and Pakistan; economic liberalization; the movement

toward decentralization, inefficient judicial system and massive administrative corruption.

World Bank has supported the South Asian governments to enhance the performance of

public institutions. Beside the Bank assistance the region has also commenced reforms.

There are three main objectives of the assistance for public institutional reform: public

sector reorientation, forming regulatory frameworks, reforming key government functions.

Reorienting the public sector:

In order to encourage the private sector South Asian governments have taken many steps

though, privatization process has been slow due to the resistance of vested interests.

Beside other institutional changes power sector reforms are notable. Many Indian states

have initiated reforms to privatize power sector with the Bank support. In Bangladesh also

the Bank has started efforts for the power sector reform while except this sector

privatization has also been commenced. Nepal, Pakistan, and Sri Lanka are making efforts

to encourage privatization to continue. Bank has supported the privatization process in

Srilanka beginning from tea estates and the national airline to the telecommunications. The

Bank has also provided the support to privatize the financial sector in Pakistan.

Privatization experience in Bangladesh has not remained very successful and Bank has to

be cancelled a large structural adjustment credit

Establishing regulatory frameworks:

To help the governments establish effective and appropriate regulation the Bank has given

considerable attention. With a poor regulatory framework privatization can be ineffective

causing abuses. South Asia’s banking system demonstrates the dangers of inadequate

regulation. Weak banking regulations and poor implementation has allowed undue loans

to be too high in Bangladesh and Nepal. In India, Pakistan, and Sri Lanka, improvement


134

has also been made with Bank support. Bank is also assisting the sovereign regulations in

power, environment, water management and telecommunications.

Reforming key government functions:

Bank has made extensive efforts to improve key government functions including financial

systems and financial controls in many countries; civil service reform and tax

administration in Sri Lanka, Pakistan, Bangladesh and some Indian states. Bank has

provided the assistance through both structural adjustment loans and technical assistance.

3.3.2 East Asia and Pacific:

Before the economic crisis it was misconception that public institutions were working

efficiently in the region whereas crisis exposed institutional weaknesses. It also exposed

the poor management and regulatory practices of the financial sector. Beside the crisis

increased globalization has elevated the desire for responsible governance.

Before the crisis the Bank had focused mainly on stimulating public policy rather than

restructuring institutions. With the growing importance of the institutional agenda Bank

faces the challenge to assist the countries regarding institutional restructurings. These

reforms comprise four areas: financial sector management, reinforcing the administrative

and civil service, regulatory and legal improvement and governance and anticorruption

reforms.

Emerging market economies:

Indonesia, Korea, Malaysia, Philippines and Thailand are generally wealthier and more

competitive economies as compared to other countries of the region however, the crisis

has raised debt levels and deficits. These countries have common wide goals for

institutional transformation supported by the Bank. These include better fiscal

management to achieve the macroeconomic objectives, spending and debt management,


135

improved service delivery to achieve long term development objectives and encouraging

the anti-poverty programs, struggle to reduce the opportunities for corruption through

deregulation, development of special watchdog agencies and resilient judicial system,

strong civil society institutions and last, decentralization.

To achieve these objectives the region is using both lending and non-lending sources. In

Indonesia, Korea and Thailand Technical assistance (TA) loans have stimulated an

institutional agenda. The Bank has also collaborated with other institutions in the region

for specific projects; with the UNDP, USAID and the Asia Foundation for anticorruption

reforms in the Philippines. To restructure the financial sector Bank has also worked

together with Asian Development Bank.

Small economies:

Bilateral donors play an important role in the resource transfers in the smaller economies

of the region (Cambodia, Laos, Mongolia, Papua New Guinea and Pacific Islands). In

smaller countries progress has been mixed. With steady implementation of reforms Fiji is

one of the countries that have tried to restructure its expenditures. Other countries of the

region, such as the Papua New Guinea and Laos, have made less improvement, as

inefficient governance has reversed wider reforms.

3.3.3 Latin America and Caribbean region:

In the 1980s with the consolidation of democracy, there was strong demand for change by

the civil society including higher transparency and accountability on the part of the

government. Beside this demand the debt crisis of 1980s, due to poor performance of most

governments, also initiated the need for reform by political leaders.

The Bank initiated institutional reforms in the early 1980s for fiscal adjustment and

economic liberalization. Bank provided assistance to many countries in the form of


136

structural adjustment. By the late 1980s and early 1990s, Bank adopted a modernization

approach. The ultimate objective of this approach has been to enhance the efficiency of

financial system by implementing modern information technology. In enhancing the

efficiency of existing bureaucratic institutions these projects invested heavily on

modernizing the legal framework.

Considerable success of the economic stabilization programs in the 1990s led governments

to look for Bank assistance in new areas. Later in the mid-1990s, the Bank has initiated

judicial reform, decentralization and anticorruption efforts. Bank reforms also support

sectoral decentralization, provision of safety nets and social service delivery. Judicial

reforms help providing anticorruption measures by refining legal processes and discipline.

Moreover the Bank has initiated efforts to incorporate more participatory (voice)

approaches.

3.3.4 Sub Saharan Africa:

Africa has deep rooted institutional development problems. The high levels of aid

dependence that complemented reform weaken the capability of governments regarding

management of public spending. This institutional weakness was an already fragile basis

of accountability and legitimacy for many governments. In some countries rent-seeking

absorbed much of the energy of African elites at the cost of development measures.

In 1980s African region moved from investment-oriented development projects to policy

reform and adjustment lending. The region invested heavily on reform efforts of public

sector management. 70 of 102 civil service reform projects were in sub-Saharan Africa

between 1987 and 1997. But the experience of region regarding public sector management

has been uneven. During 1990s attention turned towards participation and building local

capacity. The public sector management program was accompanied by participation and

building local capacity.


137


We start this chapter by providing an overview of economies of selected countries on main

economic indicators; per capita growth, population growth, inflation rate, human

development and corruption perception. We compare their relative performance on these

indicators between 2000-2014. We conclude that percentage increase in per capita growth

was highest in Kenya, India stood next to Kenya. Percentage reduction in population

growth was highest in Thailand between these two periods. Percentage reduction in

inflation was highest in Mexico. Percentage increase in human development was highest

in Bangladesh and percentage reduction in corruption perception was also highest in

Bangladesh. Then we provide a snapshot of the economy of each country showing their

absolute position. We also provide a view of different indicators representing institutional

quality, stabilization and liberalization policies for selected countries which deliver the

dynamics of these variables. Regarding governance we conclude that among all the six

indicators the percentile score of political stability is lowest in all the countries except

Maldives and Vietnam where it is highest. Most of the countries have highest score on

regulatory quality and government effectiveness. Srilanka, Brazil and Nepal have highest

scores on control of corruption and rule of law while Bangladesh and Kenya have lowest

score on control of corruption. India and Bangladesh have highest scores on voice and

accountability while Maldives and Vietnam have lowest. Regarding stabilization policies

we conclude that government expenditures and revenue show increasing, declining and

mixed trends in different countries. Composition of government expenditures shows that

current expenditures are higher than capital expenditures in all countries mainly due to

higher expenditures regarding security concerns worldwide and higher debt servicing

payment as developing countries are highly indebted etc. Interest rate show declining and

mixed trends in different countries. Regarding trade liberalization average tariff rate and


138

import tax revenue show declining trends in almost all countries as a result of

globalization, trade openness show increasing trends. Regarding capital account

liberalization FDI flows, portfolio flows and debt flows show increasing trends in some

countries while in some countries mixed trends. In most of the countries FDI inflows show

increasing trends as a result of incentives provided by countries to foreign investors.

Composition of capital flows show that debt flows are larger than non-debt flows. In non-

debt flows FDI flows are larger than portfolio flows moreover portfolio flows show more

swings and are considered more volatile. We have also discussed the volatility of fiscal,

monetary and liberalization indicators by calculating mean volatility for each country.

Similarly we have also discussed the cyclical behaviour of these indicators. In some

countries cyclical fluctuation are responsible for higher volatility while in others countries

non-cyclical factors are playing their role. At the end we provide a brief over view of

institutional reforms in developing countries by the World Bank. These include better

fiscal management to achieve the macroeconomic objectives, spending and debt

management, improved service delivery, struggle against corruption, privatization,

deregulation, strong judicial system, strong civil society institutions and decentralization.

139

Model Specification

This chapter derives the theoretical/empirical specification of growth model in first

section, second section provides the description of variables in detail, third section

describes the estimation methodology and the last section concludes the chapter.

4.1 Theoretical model:

Growth models are formulated into two main strands; Neoclassical models, whose bases

stem from Solow (1956), and other is endogenous growth models, initiated by Romer

(1989). Researchers traditionally focused on the former because of easy data availability

and cross country implications such as convergence. Neoclassical models assume constant

returns to scale and diminishing returns to capital. Countries reach their steady state in the

long run based on their exogenous steady state variables, population growth and savings.

There are several variants of neoclassical growth model (Cass 1965; Koopmans 1965). We

use the version of Neoclassical growth model that was empirically estimated and

augmented by Mankiw et al. (1992). Mankiw finds that adding the human capital results

in more reasonable factor shares and convergence. We use the same general empirical

methodology but make slight modification by adding institutional and policy variables, the

findings could be considerably different from those obtained by Mankiw et al. (1992). The

approach is very much comparable with the work of Barro and Sala-i- Martin (1991),

Islam (1995), Gundlach (2007), Freire-Seren (1999), Cellini (1997).

Chapter # 4

Chapter # 4 Model Specification

140

1

Following Mankiw et al. (1992) we use human capital augmented Cobb-Douglas

production function with constant returns to scale, where production in each period takes

place as follows;

Here K and H is the physical and human capital stock respectively in period t, AL is the

effective labour in period t, Y is output in period t while α and β are the coefficients

representing the elasticity or share of each input in output. We use Harrod neutral

technical progress where for a given capital output ratio the relative input shares remain

unchanged. Moreover the function exhibits diminishing returns to scale, allowing for the

steady state values to be constant. It is assumed that labour grows exogenously at constant

rate (n).

nt

t eLL )0(

“A” represents the economic and technological efficiency, the level of technological

progressed is assumed to grow exogenously at rate (g), X is a vector of variables

(institutions and policies) that represents the level of economic efficiency in the economy

and θ is the vector of coefficients associated to these variables.

P

m

mm Xgt

t eAA 1)0(

“A” in our study is different from Mankiw et al. (1992) and bears a resemblance to Erich

Gundlach (2007). “A” is assumed to grow for each country with the same constant rate (g)

over time [as in Menkiw, Romer and Weil (1992)] but at different levels determined by

several factors (Xm), like institutional framework of a country that differ considerably

across countries. A(0) stands for initial level of narrow concept of technology that is same

for all the countries and Xm may capture the factors that differ across countries but remain

)1()( 1 eqLAHKY ttttt


141

fairly stable over time (m=1………….p). For simplicity we take constant exogenous rate

of growth of technology (g) while the constant growth rate of labour (n) shows that when

new labour enters in the market at the same time some labour retires and leaves the market

(inflow and outflow of labor in the labour market).

Taking the production function in labour intensive form we get;

tt

tttt

tt

t

LA

LAHK

LA

Y

1)(

)2(eqhky ttt

Where ,tt

tt

LA

Yy ,

tt

tt

LA

Kk

tt

tt

LA

Hh

A fraction of output is saved which is spent on either the accumulation of physical and

human capital or consumption. The net increase in the stock of physical capital at a point

in time equals gross investment less depreciation.

ttt KIK .

KYsK tKt .

10 s

Here .

K denotes differentiation with respect to time. I is gross investment while δ shows

rate of depreciation, Ks is the share of capital in output. Dividing both sides of equation

by effective labour gives;

tt

t

tt

tK

tt

t

LA

K

LA

Ys

LA

K

.

ktk

tt

t ysLA

K

.

The right hand side represents per capita variables in order to convert left hand side in per

capita form we take derivative of AL

Kk with respect to time;


142

t

tt

ttttt kgn

LA

K

dt

LAKdk )(

)/(.

.

Where (n+g) is the growth rate of effective labour, substituting the value of AL

K.

from

previous equation gives the evolution of physical capital;

)3()(.

eqkgnysk ttkt

Growth rate of technology is assumed to be constant (g) as described earlier, in the same

way depreciation rate is also assumed to be constant, share of output to physical capital

(sk) is also constant.

In the same way as described above the evolution of human capital takes the following

form;

)4()(.

eqhgnysh ttht

hs shows the proportion of output devoted to human capital, δ shows the rate of

depreciation of human capital, n and g are described earlier. For simplicity we postulate

that both the physical and human capital depreciate at the same rate (δ).

Allocation of savings between physical and human capital depends on rates of returns of

both. As marginal productivity theory says that factors are paid according to their marginal

product. We will equate the marginal product of both capitals. First we calculate the

marginal product of physical capital by taking derivative of production function, in labour

intensive form, with respect to capital per effective worker.

As

ttt hky

tt hkMPk

1

t

t

k

yMPk .

In the same way marginal product of human capital is;


143

t

t

h

yMPh .

Rate of return to physical capital is t

t

k

y. while Rate of return to human capital is

t

t

h

y. .Equating the rate of return of both capitals;

tt kh

)(Aeqkh tt

The equality between both capitals shows one to one relation between them. This

relationship is used to calculate the steady state values of physical and human capital. We

write the equation of .

k again.

ttkt kgnysk )(.

kgnhksk ttkt )(

.

We use equation (A) to eliminate h from above equation.

tttkt kgnkksk )(.

t

k

httkt kgn

s

skksk )(

.

tthkt kgnkssk )(1

.

Steady state implies that 0.

k

thkt ksskgn

1)(

After solving for k we get steady state value of k;

)5(1

11

*

eqgn

ssk hk

t

In the same way steady state value of h will be;

t

t

t

t

h

y

k

y..


144

)6(1

11*

eqgn

ssh hk

t

Substituting steady state values of k and h into the production function we get;

1

111

11

gn

ss

gn

ssy hkhk

t

After simplifying the above equation we get;

1

11

)(

)()(

gn

ssy hk

t

We get the equation of income per capita as follows;

)7(

)(

)()(

1

11*

eq

gn

ssAy hk

t

Where t

tt

L

Yy *

By taking logs we get

)ln(1

)ln(1

)ln(1

lnln*

gnssAy hktt

m

P

m

mtt XgAA

1

0lnln

)8()ln(1

)ln(1

)ln(1

lnln1

0

*

eqgnssXgAy hkm

P

m

mtt

To find the convergence around the steady state we need the growth rate of physical and

human capital.

)9()(1

.

eqgnhksk

kttk

t

t

ttt hky


145

Log linearization of above equation implies;

In the same way we get the log linear equation of human capital;

)11()(ln)1(ln

.

eqgneesh

h hk

h

t

t

The growth rate of y is a weighted average of the growth rate of the two inputs;

t

t

t

t

t

t

h

h

k

k

y

y...

If we use log linear equations of physical and human capital and take a two dimensional

first order Taylor series expansion we get;

)ln)]](ln1([[

)ln](ln)]1([[

*ln)1(lnlnln)1(

*ln)1(lnlnln)1(

.

****

****

tt

hk

h

hk

k

tt

hk

h

hk

k

t

t

hheesees

kkeeseesy

y

At the steady state **

lnln)1( hk

k ees and **

ln)1(ln hk

h ees is equal to gn with the

assumption that rate of depreciation is same for both types of capital and k is closer to *

k

and similarly h is closer to*

h .

)12()ln(ln*

.

eqyyy

yttt

t

t

))(1( gn

or

)ln(lnln *

.

tt

t

tt yyy

y

dt

yd

)]ln(ln)ln(ln)[)(1(**

.

tttt

t

t hhkkgny

y

)10()(lnln)1(

.

eqgneesk

k hk

k

t

t


146

Here λ is the convergence coefficient which shows the speed of convergence to the steady

state.

If we integrate above differential equation with respect to time from t0 to t1 we get;

)13()(lnln)1(ln 0

*

eqyeyey tt

t

Subtracting lny0 from both sides

00

*

0 ln)(lnln)1(lnln yyeyeyy tt

t

)14()ln)(ln1(lnln 0

*

0 eqyyeyy t

t

0

1

0

0

ln

)ln(1

)ln(1

)ln(1

ln)1(lnln

y

gnssXgAeyy

hkm

P

m

mtt

t

Formally our empirical specification, for the i-th country in the t-th period, for the panel

data can be written in the reduced form as under;

)15(ln11

110 eqZcXbyaagy itititj

q

j

jitm

p

m

mitit

Where gy is the growth rate of GDP per capita of ith country at time (t) and yt-1 is the

lagged value of GDP per capita, Xm shows vector of institutions and policies, Zj is a vector

of control variables; physical capital, human capital and population growth. Equation

shows that growth rate of GDP per capita is determined by physical and human capital,

population growth, initial level of GDP per capita and vector of institutions and policies

determined by “A”. Above equation is the basic empirical specification of the model.

εit is the error term with constant variance and zero mean while νi and µt represent both

country and time specific factors. They represent unobserved characteristics that are either

country specific and time invariant (e.g. geography, culture, religion, language, distance

etc.) or time specific and country invariant (e.g. global economic cycles).


147

We can further expand/explain last equation according to our objectives, as our first

objective is to assess the effect of policies (both stabilization and liberalization policies)

and institutions on economic growth so we will estimate the above equation directly or we

can further explain the equation as follows;

)15(ln 111

1

21110 aeqZcPbIQbyaagyitititj

q

j

jitititit

Here Zj includes vector of traditional or control variables (physical capital, human capital

and population growth). Our first objective will provide us the empirical significance of

alternative policies and institutions in economic growth.

Regarding our second objective we will analyze the effect of policy volatility on economic

growth. As there is problem of policy volatility, uncertainty or policy switching in

developing countries that lead to lower rates of investment and economic growth by

causing uncertainty to investors both foreign and domestic (Fatas and Mihov, 2008;

Aizenman and Marion, 1991; Sirimaneetham Vatcharin, 2006).

)15(ln 222

1

43132 beqVdPVbIQbyaagyitititn

r

n

nitititit

Here Vn includes traditional factors of production; physical capital, human capital and

population growth and some external factors (foreign growth volatility, term of trade

volatility and foreign interest rate volatility).

Given the importance of institutions our last objective is to empirically investigate the

effect of institutions on policy volatility as better institutions reduce the policy volatility

by putting constraints on the policy makers (Henisz, 2004; Albuquerque Bruno, 2010;

Agnello and Sousa, 2014).

)15(333

1

5154 ceqWfIQbPVaaPVititits

v

s

sititit


148

Here Ws consist of control variables inflation volatility representing macroeconomic

volatility, GDP per capita representing level of development of a country, previous

period’s debt, exchange rate volatility, export concentration, financial development and

some external factors which include foreign growth volatility, term of trade volatility and

foreign interest rate volatility.

4.2 Description of variables:

4.2.1 Economic Growth (GDP per capita growth):

Economic growth is represented by annual percentage growth rate of real GDP per capita

based on current U.S. dollars. There are many studies in the literature that use growth of

output per capita to represent the economic growth, Kappler (2004), Islam (1995), Mankiw

et al. (1992), Zhang (2001), Dalgaard and Strulik (2013), Aiello and Scoppa (2007), Li

and Zhou (2011), Ali (2002). Data is collected from World Development Indicators

(WDI).

4.2.2 Initial GDP per capita (Convergence):

It is one of the key implications of the Neoclassical growth model that growth rate is

influenced by the initial condition of the economy. Higher the distance from the steady

state higher will be speed of convergence and hence higher the growth. The rationale

behind is that poor countries have the capability to grow faster than rich ones due to the

proposition of diminishing returns. Absolute or unconditional convergence hypothesis

states that assuming same economic characteristics of economies the lower the initial

income the higher will be the growth rate whereas conditional convergence accounts for

heterogeneity across countries. It allows countries to converge not towards a common

steady state but towards their own steady state. We control for the initial state of the

economy by including the level of real per capita GDP in previous period.


149

4.2.3 Capital stock (% of GDP):

Capital stock represented by gross fixed capital formation comprises expenditures on

additions to the fixed assets of the economy. Gross fixed capital formation is commonly

used in empirical studies, Kappler (2004), Mankiw et al. (1992), Bassanini et al. (2001),

Ali (2002), Gundlach (2007), Dalgaard and Strulik (2013). Data is collected from World

Development Indicators (WDI).

4.2.4 Human capital:

Human capital represents all the knowledge, talents, skills, abilities, experience,

intelligence and training possessed individually and collectively by individuals in an

economy. To account for differences in human capital we have used human capital index

per person, which uses the data on the average years of schooling (primary, secondary and

tertiary) from Barro and Lee (2010) and rates of return for completing different sets of

years of education (primary, secondary and tertiary) by Psacharopoulos (1994). Data is

collected from Pen World Table (8.0) given for 135 countries.

4.2.5 Population growth:

It represents annual population growth rate (15-64). It include all residents irrespective of

legal status excluding refugees not invariably settled and are generally regarded as part of

the population of the source country. Data is collected from World Development

Indicators (WDI).

4.2.6 Stabilization policies:

Stabilization policies are macroeconomic policies executed by the government and central

banks in order to keep economic growth stable along with price stability. There are two

common devices available to stabilize the economy: fiscal and monetary policy. Fiscal

policy is the policy of central government concerning outlays and taxation. Monetary


150

policy is the policy of the central bank to control money supply and interest rate within the

parameters of monetary policy.

4.2.6.1 Government expenditures (% of GDP):

It includes both the current and capital expenditures of the central government.

Consumption expenditure consist of all government current expenditures for the provision

of goods and services, reward to employees (wages and salaries), interest and subsidies,

grants, social benefits, defence and other outlays such as rent and dividends. Capital

expenditures include expenditures on additions to the fixed assets of the economy for

future benefits such as expenditures on physical and social infrastructure etc. We have

used both the aggregated and disaggregated expenditures. Data is collected from Asian

Development Bank (ADB).

4.2.6.2 Tax revenue (% of GDP):

Tax revenue denotes necessary transfers to the central government for public purposes

from both the direct and indirect sources. Direct taxes comprise income, profits and capital

taxes (as a liability to individuals and enterprises) whereas indirect taxes comprise taxes

on goods and services (general taxes, sales tax, value added taxes), excise duties, taxes on

trade (custom and other import duties, taxes on exports) etc. Data is collected from Asian

Development Bank (ADB).

4.2.6.3 Interest rate:

Interest rate is represented by lending rate, the rate that fulfills the short and medium term

financing needs of the private sector. Data is collected from World Development

Indicators (WDI).

4.2.7 Liberalization Policies:

Economic liberalization refers to the reduction of government regulations and restraints to

encourage the contribution of the private sector in order to stimulate economic


151

development. Liberalization policies include larger labour market flexibility, fewer

restrictions on domestic and foreign capital, open markets, etc. In developing countries,

economic liberalization mentions to further opening up of their respective economies to

foreign capital and trade.

4.2.7.1 Trade liberalization:

Trade liberalization denotes fewer restrictions on trade in the form of tariff and non-tariff

barriers. There is no unified measure of trade liberalization, literature provides few

measures; average tariff rate, revenue collected from imports, trade openness as a common

measure and trade liberalization index by Sachs and Warner (1995)32

. Index is available

only from 1950-92 for 152 countries. Since, due to the unavailability of the index for

recent years we have used average tariff rate for all products subject to tariffs33

weighted

by the product import shares analogous to each partner country. We have also used

disaggregated measure of tariff for capital and consumer goods as most of the imports of

sample countries consist of these goods. Moreover we also have used trade openness as an

indicator of liberalization mostly used in the literature. Data of tariff rate is collected from

World Integrated Trade Solutions (WITS) given by the World Bank while the data of trade

openness is collected from World Development Indicators (WDI).

4.2.7.2 Financial liberalization:

Financial liberalization denotes to ease restrictions on capital flows across a country’s

borders by domestic residents and foreigners. There are two type of measures used for

financial liberalization in empirical literature; de-jure and de-facto measures. A traditional

approach to measure financial liberalization is De- jure measure, declaring to the legal

32 Sachs and Warner (1995) developed a measure of movement towards a liberal trade policy regime. 33 Capital goods, consumer goods, intermediate goods and raw material.


152

status of financial liberalization34

. All these measures are based on the information

available in the IMF's Annual Report on Exchange Arrangements and Exchange

Restrictions (AREAER). We use Chinn and Ito (2008) index35

, based on principal

component analysis an average measure of four binary indicators; multiple exchange rates,

current account, capital account and export proceeds from (AREAER). Data is available

from 1970 to recent for 182 countries. However, de jure measures are not true measure of

liberalization as they only capture the presence or absence of restrictions.

An alternative measure is the use of de facto approach which measures the actual openness

of financial market transactions. One of the most reliable data sources for de facto

measures of financial liberalization has been offered by Lane and Milesi-Feretti (2007).

They have computed the accumulated stock of foreign assets and liabilities as a percentage

of GDP for a broad sample of 178 countries from 1970 to recent. The composition of

international financial position is distinguished on the basis of foreign direct investment,

foreign portfolio investment, external debt (portfolio debt and other investments) and

others (financial derivative and total reserves minus gold)36

. We have also used net FDI

inflows being long term and stable flows while portfolio equity and debt inflows being

short term flows. Data is collected from World Development Indicators (WDI).

4.2.8 Institutional Quality:

The World Bank has collected the data for governance usually known as World

Governance Indicators (WGI). There are six compound measures representing wide

aspects of governance covering 215 countries from 1996 to recent; voice and

34 Chinn and Ito (2008), Quinn (1997), Schinlder (2009) etc. 35 It is a scale measure (0-1) of capital account openness; it takes value of one when capital account is fully liberalized

and zero with full restrictions on capital transactions.

36

For accounting framework see Lane and Milesi-Feretti (2007).


153

accountability, political stability and absence of violence, government effectiveness,

regulatory quality, rule of law and control of corruption. These indicators are based on

numerous indicators from different sources; survey respondents, business sector, public

and nonpublic sector organizations all over the world. Index ranges between (-2.5 weak) to

(2.5 strong). We can explain these broad dimensions as;

Voice and Accountability; is the degree to which the citizens have right to elect their own

government and representatives, and while media is free from censorship and enjoys

independence.

Political Stability and Absence of Violence; refers to the probability that a political

dispensation will be undermined by resort to violence or unlawful means.

Government Effectiveness; measures the capacity of an administration to ensure public

service delivery, conception and execution of a policy framework, and the evidence of

probity in such processes.

Regulatory Quality; looks at instances of comprehensive policy frameworks that

spearhead development and advancement of private sector enterprises.

Rule of Law; explains the prospects of reasonable and foreseeable rules and regulations

that will govern commercial and social exchanges such as enforcement of contracts,

protection of property rights, judicial processes, as well as the probability of wrongdoing

and violence.

Control of Corruption; refers to the impression generated by practices of abusing public

authority for private benefit.

We have used all the six indicators individually for a broader view and comprehensive

policy implication and also a single governance indicator by taking average of all.

We have also used data of institutional constraints as a measure of checks and balances on

the decision power of policy makers. Henisz (2002) provides a measure of political


154

constraint which measures the possibility of policy change using the number of

independent veto players. Data is collected from POLCONIII. Index ranges from 0 to 1,

where a higher score represents stronger constraints.

As a measure of monetary institutions we have used data on central bank independence.

Published data at annual frequency is available by Polillo and Guillen (2005) but with low

frequency and less country coverage. Therefore we have used governor turnover as an

indicator of central bank independence. It is a dummy variable where 1 is being assigned

to all those years where governor turnover is taking place (Cukierman et al. 1992, Dreher

et al. 2010, Haider et al. 2011). We have collected the information regarding the turnover

of the governor from the web site of each country’s central bank.

4.2.9 Inflation:

Inflation as measured by the consumer price index reveals the annual percentage change in

the price of attaining a basket of goods and services, such as yearly (base 2010=100). Data

is collected from World Development Indicators (WDI).

4.2.10 Exchange rate:

Official exchange rate denotes to the exchange rate that is determined by the legally

authorized exchange market. Usually it is the average of monthly exchange rate and

defined as the ratio of local currency units to the corresponding foreign currency (usually

US dollar). Data is collected from World Development Indicators (WDI).

4.2.11 Export concentration:

Export concentration refers to a limited export structure of a country where a lower range

of the goods is produced which is closely related. Most commonly used measure is

Herfindahl-Hirschmann Index. It is calculated by taking the square of export shares of all

export categories in the market. It varies between zero and one, index value nearer to 1

specifies that exports are highly concentrated on a few commodities whereas closer to 0


155

reflect less concentration. We use data from World Bank where export concentration is

measured through Herfindahl-Hirschmann Index. It includes the number of products

exported at the three-digit SITC, Rev. 3 level.

4.2.12 Financial development:

Financial development is usually defined as a process that makes improvement in quantity,

quality, and efficiency of financial intermediary services. Commonly used measure of

financial development in the literature is domestic credit to private sector by financial

institutions. It denotes to financial resources provided to the private sector by financial

institutions, such as loans, purchases of securities, trade credits and others, which create a

claim for repayment. Data is collected from World Development Indicators (WDI).

4.2.13 External debt stocks, long-term public sector (% of GDP):

Long-term external debt refers to debt that has maturity of more than one year and that is

payable to nonresidents by residents of a country. Data is collected from World

Development Indicators (WDI).

4.2.14 Volatility:

Volatility refers to the fluctuations in any economic activity, the pace at which the

economic activity moves up or down and how widely they swing. Less volatility shows

stability, it shows minor fluctuations/consistent behavior of economic variables. Higher

volatility is harmful for an economy which leads to instability.

There are different methods to measure volatility such as standard deviation of the residual

through an autoregressive process, conditional variance through ARCH and GARCH

model. ARCH and GARCH models are used with high frequency data mostly weekly and

monthly. Most widely used measure is standard deviation method with annual frequency.

The volatility of any variable can be measured by fitting a first-order autoregressive

process of the form:


156

ttt YY 110 )(

where α1 is the autoregressive parameter. The standard deviation of the residual (ε)

measures the volatility or the uncertainty associated with changes in variable “Y”. The

standard deviation measures the dispersion of a variable around its mean value.

Observations on a variable tend to be far away from the variable’s mean value if the

standard deviation is high while these clustered around the average value if standard

deviation is low.

4.2.15 External shocks:

Due to globalization and more integrated economies the extent of external shocks also

affects the domestic economy upon which they have little control. To capture the effect of

external shocks we have incorporated term of trade shock, fluctuations in foreign interest

rate and foreign growth rate. The Term of trade is calculated as the percentage ratio of the

export unit value index to the import unit value index, measured relative to the base year

(2010=100). For foreign growth we have used the data of US growth, being a major

trading partner of countries included in the sample. Data of term of trade index and US

growth is collected from World Development Indicators (WDI). For the foreign interest

rate we have used Federal Funds Rate, the rate banks claim each other to borrow funds,

data is collected from International Financial Statistics (IFS).

157

Table 4.1 Description of variables

variable description unit Source

Economic Growth The rate of change of real per capita GDP. Annual percentage World Development

Indicators (WDI).

convergence Previous period’s GDP per capita in logs. Current US dollars World Development

Indicators (WDI).

Capital stock

(private sector)

Gross fixed capital formation, entails expenditures on additions to the

fixed possessions of the economy by the private sector.

Percentage of GDP World Development

Indicators (WDI).

Human capital Human capital index per person, which uses the data on the average

years of schooling from Barro and Lee (2010) and rate of return to

education from Psacharopoulos (1994).

Index Pen World Table

(8.0)

Population growth Annual population growth rate (15-64). Rate of growth of population

from year t-1 to t, expressed as a percentage.

Annual percentage World Development

Indicators (WDI).

Inflation Annual percentage change in consumer price index (CPI) Index

2010=100

World Development

Indicators (WDI).

Real exchange rate Ratio of local currency units to the U.S. dollar deflated by price index of

both countries.

Index

World Development

Indicators (WDI).

Export

concentration

Export shares of all export categories in the market. Index (0-1) World Development

Indicators (WDI).

Financial

development

Domestic credit to private sector. Percentage of GDP World Development

Indicators (WDI).

External debt stock

(long-term public

sector)

Debt that has a maturity of more than one year and that is payable to

nonresidents by residents of a country.


Indicators (WDI).

Volatility Standard deviation of the residual of AR(1) process Own calculation

Stabilization policies (fiscal and monetary policy)

Government

expenditures

It includes all the current and capital expenditures of the central

government.

Percentage of GDP Asian Development

Bank (ADB).

Tax revenue Tax revenue denotes compulsory transfers to the central government for

public purposes from both the direct and indirect taxes.

Percentage of GDP Asian Development

Bank (ADB).

158

Interest rate Interest rate is represented by lending rate, rate that generally fulfills the

short and medium term financing requirements of the private sector.

Annual percentage World Development

Indicators (WDI).

Liberalization policies (trade and financial liberalization)

Average tariff rate Average tariff rate for all products. Annual percentage World Development

Indicators (WDI).

Trade openness Sum of exports and imports of goods and services measured as a share

of gross domestic product.


Indicators (WDI).

Financial

liberalization

(De jure measure)

Measure of restrictions on capital account. Index (0-1) Chinn and Ito

(2008)

Gross capital flows

(De facto measure)

Sum of gross inflows and outflows. Percentage of GDP Lane and Ferretti

(2007)

Institutional quality

Governance

Political

constraints

Central bank

independence

Six composite indicators of governance; voice and accountability,

political stability and absence of violence, government effectiveness,

regulatory quality, rule of law and control of corruption.

It measures the checks and balances on the policy makers.

It represents the governor turnover.

Index (-2.5 to 2.5)

Index (0-1).

A dummy variable

(0/1)

World Governance

Indicators (WGI)

POLCONIII.

External shocks

Term of trade

(TOT)

Percentage ratio of export prices to import prices Index

2010=100

World Development

Indicators (WDI).

Foreign growth

rate

Rate of change of real GDP of US Annual percentage World Development

Indicators (WDI).

Foreign interest

rate

US federal funds rate, the rate banks claim each other to borrow funds. Annual percentage International

Financial Statistics

(IFS)


159

4.3 Methodology:

The general regression equation that we will estimate for economic growth as described in

theoretical model eq (15) is the following;

)15(lnlnln11

1101eqZcXbyaayy itititj

q

j

jitm

p

m

mittiti

Here left hand side is the growth rate of GDP per capita of ith country at time (t) and yt-1 is

the lagged value of GDP per capita, Xm shows vector of institutions and policies, Zj is a

vector of traditional control variables. εit is the error term while νi and µt represent both

country and time specific factors. After accounting the time specific affects we can write

the above equation as;

)16(lnln11

110 eqZcXbyjay itiitj

q

j

jitm

p

m

mitti

There are some estimation concerns related to above regression equation. The first is the

existence of unobserved country-specific effects. Country specific effect combines factors

that influence the GDP per capita and are correlated with the explanatory variables. The

second is the possibility of most explanatory variables to be endogenous with economic

growth, so there is need to control for the biases resulting from simultaneity or reverse

causation. The last is to control for the econometric problems resulting from the inclusion

of the initial per capita GDP as an explanatory variable. The above concerns provide the

motivation for the use of econometric methodology in a dynamic model of panel data.

We use the generalized method of moments (GMM) established for dynamic models of

panel data, initiated by Holtz-Eakin, Newey and Rosen (1988), Arellano and Bond (1991),

and Arellano and Bover (1995). These estimators control the unobserved effects through

differencing. There is possibility of correlation between the levels variables and the


160

country specific effect (vi) in equation (16) while differencing eliminates this possibility.

This can be illustrated as:

)17()(

)(()ln(lnlnln

1

1

1

1

1

21101

eq

ZZcXXbyyjayy

itit

itjitj

q

j

jitmitm

p

m

mitittiti

There is need of instruments to handle the possible endogeneity of the explanatory

variables and the correlation of the new error term, 1 itit , with the lagged dependent

variable, 21 lnln itit yy . The instruments comprise preceding values of the explanatory

and lagged-dependent variables. Following the supposition that the error term, ε, is not

serially correlated and that the explanatory variables (X and Z) are weakly exogenous,

GMM dynamic panel estimator uses the following moment conditions:

Here s ≥2; t=3…….T

The GMM estimator based on the moment conditions described above (18a) and (18b) is

known as the difference estimator. For the level equation lagged differences of the

explanatory variables are used as instruments. It ensures that though there may be

correlation between the levels of explanatory variables and the country specific effect (vi)

in equation (16), there is no correlation between those variables in differences and the

country specific effect (vi). The moment conditions for the regression in level are;

The reliability of the GMM estimators depends on the validity of instruments/moment

conditions. We use two specification tests for this purpose, first is the Sargan test of over

identifying restrictions, which tests the validity of the instruments. We test the null

)18(0)([,0)([

)18(0)([ln

11

1

beqZEXE

aeqyE

ititsitititsit

ititsit

)19(10))([(0))([(

)19(10))([(

11

1

beqforsvZZandEvXXE

aeqforsvyyE

itisitsititisitsit

itisitsit


161

hypothesis that restrictions are valid against the alternative; rejection of the null shows the

presence of hetroskedasticity. This test is valid only for homoscedastic errors; rejection of

the null implies that we need to reconsider the model or instruments unless we attribute the

rejection of hetroskedasticity. The second test examines whether the original error term εit

(eq 16) is serially correlated. We test the null hypothesis of no second order serial

correlation against the alternative. The model is, therefore, supported when the null

hypothesis is not rejected. First-order serial correlation of the differenced error term is

expected even if the original error term (in levels) is uncorrelated. Serial correlation of

order higher than one implies that moment conditions used are not valid.


In this chapter we have derived a dynamic panel data model to study the role of

institutions and policies in economic growth, following Mankiw et al. (1992), in the

empirics of Neoclassical growth model. Derived model shows the effect of institutions and

policies (stabilization and liberalization policies) on economic growth along with

traditional factors and convergence. Traditional determinants of growth are physical

capital, human capital and population growth. We have further manipulated the equation

according to our objectives.

Economic growth is measured by annual growth rate of GDP per capita. For physical

capital we have used gross fixed capital formation for private sector, for human capital we

have used human capital index per person which uses the data of average years of

schooling and rate of returns to schooling from Pen World Table (0.8), population growth

is measured by annual population growth from (15-64). To measure the convergence we

have used log of previous year’s GDP per capita.


162

For institutional quality we have used the data of World Bank, World Governance

Indicators, which defines governance in six broad dimensions; voice and accountability,

political stability and absence of violence, government effectiveness, regulatory quality,

rule of law and control of corruption. For stabilization policies we have used fiscal and

monetary policy. For fiscal indicator we have used total government expenditure and also

disaggregated current and capital expenditures and tax revenue, for monetary policy

indicator we have used interest rate as a policy variable. For liberalization policy we have

used trade liberalization and financial liberalization. For trade liberalization we have used

average tariff rate for all commodities and also disaggregated tariff rate for capital and

consumer goods. We have also used trade openness as an indicator of trade liberalization.

For financial liberalization we have used both the De jure (Chinn and Ito (2008) and De

facto measure (Milesi-Feretti (2007)). We have used these alternate measures of

stabilization and liberalization policies for comprehensive and broader policy implications.

Moreover we are also interested in analyzing the role of policy volatility in economic

growth and last, the factors affecting the policy volatility where we emphasize on the

importance of institutions in reducing the policy volatility.

The standard deviation of the residual of first-order autoregressive process measures the

volatility. Factors affecting the policy volatility are classified into some domestic and

global factors; domestic factors include macroeconomic volatility measured by inflation

volatility, level of development of a country (represented by GDP per capita), previous

period’s debt, exchange rate volatility, export concentration, financial development and

institutional quality and some global factors; foreign growth volatility, term of trade

volatility and foreign interest rate volatility. Inflation is measured through annual

percentage change in general price level using consumer price index. Debt shows long-


163

term public sector external debt. Exchange rate denotes to official exchange rate (ratio of

local currency units to US dollars). Financial development is measured through domestic

credit to the private sector. Export concentration is measured through Herfindahl-

Hirschmann Index. Foreign growth is measured by the growth rate of US GDP, Term of

trade (TOT) is represented by an index of export to import price ratio, foreign interest rate

is represented by US Federal Funds Rate.

Main sources of the data are the World Bank (World Development Indicators),

International Financial Statistics (IFS), Pen World Tables (8.0), Asian Development Bank

(ADB), World Governance Indicators (WGI), Chinn and Ito (2008) and Lane and Ferretti

(2007).

Next we discuss the methodology used; to control the unobserved country specific effects

and due to the possible endogeniety of explanatory variables with the growth we use

dynamic panel data GMM method of estimators initiated by Holtz-Eakin, Newey, and

Rosen (1988), Arellano and Bond (1991), and Arellano and Bover (1995). The

methodology consists of the level as well as differencing the equation to control for

country specific effects. For the level equation the lagged differences of the variables are

used as instruments whereas for differenced equation level of the preceding observations.

Last we explain two specification tests to check the reliability of GMM estimators; first is

the Sargan test of over identifying restrictions and second is the test of second order serial

correlation.

164

Results and Discussion

This chapter provides the empirical evidence of the model derived in previous chapter. We

estimate the model using panel data of twelve developing countries included in the sample

by GMM methodology. The objective is to analyze and explain the dynamics of

relationships. First of all we test the reliability of our data using summary statistics or

descriptive statistics. Next we see the relationships between variables through pair wise

correlation matrix. Last section provides the results of GMM. We estimate the equations

according to our objectives and discuss the results in detail with empirical support from

the literature.

5.1 Descriptive statistics:

Descriptive statistics provide an understanding and analysis of the data before estimation.

It tests the reliability of data both through numerical and graphical procedure by giving a

summary of the data. The main objective of data analysis is to draw valuable

conclusions from the data, which can further be used to make logical decisions.

Commonly used measures of data analysis are measures of central tendency and measures

of variability or dispersion. Mean, median and mode are used as a measure of central

tendency while measure of dispersion includes standard deviation, range, quartile,

derivative and mean derivative. Mean represents the average while median is the central

value and mode is the repeatedly occurring value. In case of normal distribution mean and

median are equal to each other showing the symmetry of data or no skewness. Standard

deviation is commonly used as a measure of dispersion or variability. If variation is small

standard deviation will be small, less variation shows consistency.

Chapter # 5

https://en.wikipedia.org/wiki/Central_tendency

https://en.wikipedia.org/wiki/Statistical_dispersion

https://en.wikipedia.org/wiki/Mean

https://en.wikipedia.org/wiki/Median

https://en.wikipedia.org/wiki/Mode_(statistics)

https://en.wikipedia.org/wiki/Standard_deviation

Chapter # 5 Results and Discussion

165

Table 5.1 Descriptive Statistics

Variable Mean Median Std. Dev.

Economic growth 3.137768 3.146415 3.302225

Income per capita 2.992272 2.73348 0.994312

Private capital stock 24.24362 22.945 6.239235

Human capital 2.178215 2.101236 0.455816

Population growth 2.14666 2.192232 0.860336

Institutional quality -0.372571 -0.355 0.573965

Government expenditures 20.22351 18.93862 6.11414

Tax Revenue 13.33183 13.505 3.37175

Interest rate 2.992272 2.73348 0.994312

Trade openness 66.77416 54.17934 41.58757

Average tariff rate 15.60543 14.17 7.820966

Gross capital flows 0.904347 0.840569 0.325011

External debt 25.01145 22.85242 13.38216

Financial development 31.41746 29.06498 22.84897

Inflation volatility 1.687431 1.603041 1.413896

Exchange rate volatility 1.29125 1.231465 0.917792

Export concentration 0.164004 0.163896 0.090217

Political constraints 0.506203 0.445961 0.416059

Foreign growth volatility 0.61892 0.504591 0.492058

Term of trade volatility 0.058762 0.05222 0.037583

Foreign interest rate volatility 0.035309 0.025603 0.034395

Results in the above table show that mean and median of almost all the variables is more

or less same which further provide the evidence of symmetry of data or no skewness.

Normal distribution is always symmetric. Moreover trade openness shows higher variation

as standard deviation of this variable is higher.

5.2 Pair wise correlation matrix:

Correlation explains the linear relationship between two variables; like correlation

between trade and growth, inflation and interest rate, interest rate and capital flows etc. it

does not show causality. It lies between -1 and +1, a positive value shows a direct

relationship between variables while negative value shows inverse relationship. -1 and +1


166

shows perfect negative or positive relationship while zero shows no relationship.

Coefficient closer to either -1 or +1 shows stronger correlation between two variables.

Table 5.2 Pair wise correlation matrix

Note: gy shows economic growth, PG represents population growth rate, H and K show human and physical

capital stock respectively. TE, CE and KE represent total government expenditures, current and capital

expenditures respectively. TR represents tax rate and R is interest rate. TO shows trade openness. TF, TFK

and TFC represent total tariff rate, tariff rate for capital and consumer goods respectively. GFC and FDI

show gross capital flows and net FDI inflows. IQ represents institutional quality.

Results of the correlation matrix show that population growth has weak negative

correlation with economic growth while human and physical capital both have positive

correlation with economic growth. Aggregate and current expenditures have negative

correlation with economic growth while capital expenditures and tax revenue are

positively correlated with economic growth. Interest rate is negatively correlated with

economic growth. Trade openness has positive correlation with economic growth while

tariff rate has negative correlation. Gross capital flows and net FDI inflows both show

positive correlation with economic growth. Institutional quality is also positively

correlated with economic growth. Results show that most of the relationships are

according to economic theory. Further there is evidence of high correlation between total

government expenditures and current expenditures. There is also high correlation between

gy PG H K TE CE KE TR R TO TF TFK TFC GCF FDI IQ

gy 1.00

PG -0.14 1.00

H 0.52 -0.48 1.00

K 0.48 -0.51 0.49 1.00

TE -0.34 0.10 0.03 -0.31 1.00

CE -0.38 0.07 0.15 -0.19 0.91 1.00

KE 0.24 0.11 -0.24 0.36 0.56 0.17 1.00

TR 0.39 -0.04 0.27 0.21 0.36 0.32 0.23 1.00

R -0.38 -0.01 0.05 -0.30 0.23 0.24 0.04 0.03 1.00

TO 0.31 -0.07 0.15 0.49 0.48 0.55 0.28 0.53 -0.33 1.00

TF -0.34 0.36 -0.51 -0.06 0.18 0.10 0.23 0.23 0.04 -0.15 1.00

TFK -0.36 0.43 -0.61 -0.08 0.26 0.13 -0.35 0.41 0.06 -0.15 0.79 1.00

TFC -0.44 0.33 -0.60 -0.01 0.00 -0.16 0.32 0.36 -0.08 -0.18 0.73 0.47 1.00

GCF 0.36 -0.16 0.35 0.27 0.53 0.52 0.03 0.44 -0.13 0.62 -0.29 -0.28 -0.37 1.00

FDI 0.39 -0.02 0.06 0.44 0.57 0.49 -0.40 0.48 0.05 0.78 0.00 0.06 -0.13 0.62 1.00

IQ 0.40 0.38 0.47 0.54 -0.10 0.13 0.00 0.01 0.17 0.11 0.14 0.02 -0.12 0.15 0.17 1.00


167

total tariff rate and tariff rate for consumer goods similarly a high correlation exists

between total tariff rate and tariff rate for capital goods. There is also evidence of high

correlation between trade openness and net FDI inflows.

5.3 Results of GMM:

5.3.1 Effect of institutions and policies on economic growth:

Our first objective is to analyze the effect of policies (both stabilization and liberalization

policies) and institutions in economic growth. We again write the equation here which we

have already explained in previous chapter in section 4.1 as follows;

)15(ln 111

1

21110 aeqZcPbIQbyaagyitititj

q

j

jitititit

Here Zj represents vector of traditional or control variables (physical capital, human capital

and population growth). IQ shows institutional quality while P represents policies, both

stabilization and liberalization policies. yt-1 is the lagged value of GDP per capita which

represents convergence. To represent institutional quality we have used the data of World

Bank which explains six dimensions of the governance, we have used the aggregate index

in this equation. The detail is mentioned in previous chapter section 4.2. For stabilization

policies we have used fiscal and monetary policy. We have used government expenditures

and tax revenue as indicators of fiscal policy while we have used interest rate as a

monetary policy instrument. For liberalization policies we have used trade liberalization

and financial liberalization. Trade liberalization is represented by trade openness index

and average tariff rate. To represent the financial liberalization we have used De- jure

measure [Chinn and Ito (2008)] and De facto measure, gross assets and liabilities as a

percentage of GDP [Milesi-Feretti (2007)]. Moreover we have also used net FDI inflows

as a long term and stable source of foreign capital flows.


168

Institutional quality is hypothesized to have a positive effect on economic growth by

providing an environment conducive to investment. We would test the null hypothesis that

institutional quality is unrelated to economic growth against the alternative. Regarding the

fiscal policy we would test the null hypothesis that fiscal policy does not contribute to

economic growth (Classical hypothesis) against the alternative (Keynesian hypothesis).

Regarding monetary policy we assume that it affects the economic growth through

aggregate demand, we would test the null hypothesis that monetary policy does not affect

economic growth (Keynesian hypothesis) against the alternative (Monetarist). Trade

liberalization is also assumed to have a positive effect on economic growth through

positive externality. We would test the null hypothesis that trade liberalization has no

association with economic growth against the alternative. Financial liberalization is

assumed to have a positive effect on economic growth by relaxing the borrowing

constraint and providing more investment opportunities while on the other hand there is

also opposing view that financial liberalization increases the risk of crisis in economies

where financial sector is week thereby reducing the growth. We would test the null

hypothesis of no association between financial liberalization and economic growth against

the alternatives. Physical and human capital both are hypothesized to have a positive effect

on economic growth while population growth is assumed to have a negative effect. It is

hypothesized that higher initial income reduces the steady state growth (convergence).

Estimation of this equation will provide the significance of institutions and alternative

policies in economic growth.


169

Table 5.3 Effect of institutions and policies on economic growth

Dependent variable: Economic growth variables Eq1 Eq2 Eq3 Convergence -.098229*

(0.002)

-.064413*

(0.000)

-.048807*

(0.011)

Private capital stock .1916751*

(0.012)

.0420228

(0.540)

.1415328**

(0.067)

Human capital 1.423672*

(0.050)

1.184211**

(0.065)

1.166283*

(0.021)

Population growth - .506445

(0.374)

-1.04926**

(0.067)

-1.954578 **

(0.083)

Institutional quality .25147*

(0.049)

.1269705**

(0.081)

.1928122**

(0.063)

Stabilization policies ( Fiscal and monetary policy) Aggregate govt. expenditures -.2308414*

(0.043)

Current expenditures -.1467202**

(0.062)

Capital expenditures .3285581*

(0.031)

Tax revenue

.0930385*

(0.044)

Interest rate -.1040991*

(0.023)

-.1353151*

(0.007)

Liberalization policies ( Trade and financial liberalization) Trade openness .1138372*

(0.042)

Tariff rate total - .1834675*

(0.020)

Tariff rate consumer goods -.0346299

(0.329)

Tariff rate capital goods -.2844151*

(0.014)

Financial liberalization

(De jure measure)

-.126968**

(0.075)

Gross capital flows

(De facto measure)

-.344006*

(0.043)

Net FDI inflows .626968*

(0.025)

Portfolio inflows

(equity and debt securities)

-0.0869**

(0.06718)

constant .0666723

(0.993)

17.3845*

(0.016)

-3.591562

(0.619)

No. of countries 12 12 12

No. of observations 210 210 210

Wald chi2(prob) 0.0000 0.0000 0.0014

Sargan (prob. chi2) 0.2577 0.2267 0.2240

AR1(prob. Z)

AR2(prob. Z)

0.0197

0.1202

0.0911

0.1918

0.0010

0.1403

Note: Values in the parentheses show the probability of „Z‟ statistics. * shows the significance at 1% and 5

% level of significance while ** shows the significance at 10 %. Wald test check the joint significance of the

model, Sargan test checks the reliability of instruments while AR test checks the presence of autocorrelation.


170

Convergence:

We have described the concept of convergence as one of the key implications of the

Neoclassical growth model in previous chapter in section 4.2. Following the Neoclassical

tradition many researchers have tested the convergence hypothesis using different

methodologies, sample and data sets and some studies have strongly rejected the

hypothesis and some have accepted. According to Mankiw (1995) most of the studies

show estimates of speed of convergence around 2%. The consistency of 2% reflects same

economic structures across countries while in reality economic structures vary across the

countries and hence cannot be the source or 2 % uniformity. As the level of technology is

assumed to be constant among countries in cross section estimates, so these estimates of

rate of convergence are considered biased [Islam (1995)]. Owing to the technological

differences across countries researchers adopted a panel data approach providing different

estimates from cross country estimates because economies are supposed to converge more

quickly towards their own steady state than to common one.

Our results show that initial GDP is inversely related to economic growth in all the

equations providing the proof of conditional convergence. Speed of convergence lies

between 5% to 10%; in first equation speed of convergence is 10%, in second equation 6%

and 5% 37

in last equation. Our results are consistent with previous economic literature.

Conditional convergence estimates by Islam (1995) for OECD and non-oil countries

ranges from 4.6% to 10.7%, Caselli, Esquivel and Lefort (1996) replicate the previous

models using cross country and panel data and provide the estimates of rate of

convergence between 2% to 10%, Edwards (1991) provide the estimates from 5% to 17%

in different specifications in a cross section of developing countries. McLean and Shrestha

(2002) provide the estimates for developed and developing countries from 4% to 6%. Li et

37

Speed of convergence is calculated as λ = - ln (1+ coefficient of initial GDP).


171

al. (2016) provide estimates of conditional convergence for 120 world economies with the

speed ranging from 0.03 percent to 22 percent. Speed of convergence for Europe is 22 %,

Asia 25 %, Latin America 23 % while there is evidence of no convergence for Africa.

Mathur (2005) measures the speed of conditional convergence for EU, East Asian and

South Asian regions together and there is evidence of conditional convergence from 0.2 %

in a year to 22%.

Traditional determinants of growth (Human capital, physical capital and population

growth):

In the theoretical literature the role of human capital has been extensively analyzed. The

literature identifies the role of human capital in economic growth in two ways; human

capital can directly affect the growth by including in production function as an additional

factor and secondly human capital indirectly affect the economic growth through

technological progress. Mankiw, Romer and Weil (1992) develop an extension of the

Solow growth by human capital augmented growth model.

We have used human capital index which uses the data on the average years of schooling

and rates of return to schooling, which we have discussed in detail in description of

variables. Higher the average years of schooling and rate of returns to schooling higher

the accumulation of human capital and therefore the economic growth. Results show that a

1 % increase in human capital index leads to an increase in economic growth by 1.424%,

1.18% and 1.16% respectively. Our findings have empirical support such as Levine and

Renelt (1992), Islam (1995), Harrison and Hanson (1999), Freire-Seren (1999), Bosworth

and Collins (2003), Chang et al. (2009) and Falvey et al. (2013) find a significant role of

human capital in economic growth by using different indicators.

Investment in physical capital is considered an important factor of economic growth in

the neoclassical growth model with the assumption of diminishing returns. An increase in


172

the physical capital stock (plant, machinery, and infrastructure investment) enhances the

economic activities and hence economic growth through increase in productivity,

employment opportunities, scale economies and by raising the overall welfare of

countries. Our Results show that a 1% increase in private investment increases the

economic growth by 0.19%, and 0.14% respectively. Our results follow the empirical

literature such as Edwards (1989, 1991), Levine and Renelt (1992), Harrison and Hanson

(1999), Freire-Seren (1999), Greenaway et al. (2002), Bosworth and Collins (2003) and

Falvey et al. (2013).

Higher population growth reduces the per capita growth as both have inverse

relationship. In two equations coefficient of population growth is negative and significant

(-1.04 and -1.95) respectively while in first equation this variable is insignificant. Our

findings are in line with Mankiw, Romer and Weil (1992), Levine and Renelt (1992),

Greenaway et al. (2002), Bosworth and Collins (2003), Salinas et al. (2006), Falvey et al.

(2013).

Institutional quality:

Most of the literature provides the evidence that institutions promote the economic growth

by creating an environment for capital creation. They reduce the risk of doing the business

thereby increasing the investment return. Some studies highlight the role of institutions in

attracting the capital flows particularly FDI and portfolio investment. In the same way

institutions play a significant role in attracting the aid flows. Control of corruption,

secured property rights and the rule of law all enhance the economic growth. Poor

institutions impede the economic growth by reducing economic activity and also induce

lower investment returns

Our findings are consistent with the earlier studies that institutional quality positively

affects the economic growth. In the first equation a 1% increase in institutional quality


173

increases the economic growth by 0.25 %. Second equation shows that a 1 % increase in

institutional quality increases the economic growth by 0.12%. Last equation shows that a 1

% increase in institutional quality promotes the economic growth by 0.19%. Our findings

have support of the empirical literature. Kaufmann et al. (1999) and Al Bassam (2013)

explain that better governance leads to growth and development. Chong et al. (2004) and

Fayissa et al. (2013) conclude that all the aggregated and disaggregated measures of

institutional quality positively contribute to economic growth. Siddique and Ahmed (2010)

provide the evidence of long run relationship between institutions and economic growth.

Ahmad and Marwan (2012) illustrate that property right protection appears the most

important institutional measure in affecting the economic growth.

Fiscal policy:

Regarding the fiscal policy and growth association there is extensive empirical research

using different fiscal measures, using cross-sectional, panel, and time-series methods. The

existing empirical findings are mixed regarding the role of fiscal policy, either positive,

negative or indeterminate. Supporters of government intervention believe that such

intervention can increase the long term growth by productive investment, law and order,

provision of public goods and services, research and development both in the short- and

long-run Opponents hold the view that government brings inefficiency and therefore

reduce the growth.

For fiscal policy we have used aggregate and disaggregate government expenditure,

current and capital expenditures. Moreover we have also used tax revenue as an indicator

of fiscal policy (revenue includes from both the direct and indirect sources). Our results

show that aggregate government expenditures negatively affect the economic growth with

a coefficient (-0.230). Capital expenditures positively contribute to economic growth with

a coefficient (0.328) while current expenditures adversely affect the economic growth with


174

a coefficient (-0.146). Tax revenue positively affects the economic growth as suggested by

the literature, with a coefficient (0.093). Our finding are supported by empirical literature

as Barro (1990) and Gallo and Sagales (2011) find that government investment raises the

growth while government consumption brings distortions, such as high tax rates, without

providing a stimulus to investment and growth. Easterly and Rebelo (1993) provide the

evidence that government investment expenditure on transportation and communication

enhance economic growth by raising the return to private investment. Gupta et al. (2002)

illustrate that expenditures on wages and salaries are negatively related to economic

growth while expenditures on other goods and services and capital expenditures foster the

growth. Kukk Kalle (2007) explains that current expenditures are inversely related to

economic growth while investment expenditures are directly related. Moreover spending

on employees, consumption spending or social benefits and interest spending are

negatively related to economic growth. Ali and Ahmad (2010) explain that the

unproductive expenditures become the main cause of persistent deficit in Pakistan.

Ormaechea and Morozumi (2013) find that increase in capital spending financed through

reduction in current spending is positively associated with economic growth. Engen and

Skinner (1992) and Guseh (1997) provide the evidence that government size reduces the

economic growth.

Regarding the tax and tax revenue Easterly and Rebelo (1993), Kukk Kalle (2007), Gallo

and Sagales (2011), Acosta Ormaechea and Yoo (2012) provide the evidence that tax

revenue positively contribute to economic growth while the disaggregated analysis show

that in developing countries indirect taxes positively contribute to economic growth while

direct taxes specifically income tax reduce the economic growth.

Our findings are in contrast to some studies such as Sattar (1993) find that government

consumption expenditures positively contribute to economic growth for Asian developing


175

countries therefore efficiency enhancing role of government outweighs the efficiency

reducing role. Devarajan et al. (1996) find positive relationship between current

expenditures and economic growth, negative relationship between capital expenditures

and economic growth. Gong and Zou (2002) find that current expenditures positively

contribute to economic growth while capital expenditures remain insignificant. He further

explains that higher infrastructure spending may deteriorate the economic growth if

spending on basic economic services is ignored. Gangal and Gupta (2013) and Morozumi

and Veiga (2014) find that aggregate public expenditures are positively associated with

economic growth.

Monetary policy:

Conventionally monetary policy affects the real economy through aggregate demand. The

interest rate is regarded as a most important transmission channel. Higher interest rate

decreases the consumption expenditures by increasing the opportunity cost of

consumption. In the same way it also reduces the investment expenditures by the firms by

raising the cost of capital. It leads to decrease the aggregate demand in both cases which

decreases economic growth.

Findings show that monetary policy does affect the economic growth therefore supporting

the Monetarists hypothesis. An increase in interest rate, a tight monetary policy, reduces

the economic growth by 0.10% and 0.13% respectively. Results of our study are in line

with earlier studies that provide the evidence of an inverse relationship between interest

rate and the growth. Fatima and Iqbal (2003), Ali et al. (2008), Hussain and Siddiqi (2012)

and Younus (2013) explain that in case of developing countries monetary policy is

effective in enhancing the economic activity. Gul et al. (2012), Coric et al. (2012) and

Kandil (2014) explain that contractionary monetary policy is negatively associated to

economic growth by discouraging the private investment.


176

In contrast to our findings Cheng (2006) and Buigut (2009) explain that monetary policy

remains insignificant in African countries due to underdeveloped financial and regulatory

framework. It is also argued that a lower interest rate policy in developing countries

encourages the unproductive investment in luxury consumer goods, real estate and gold

rather than on fixed capital goods having no effect on real activity.

Trade liberalization:

Trade liberalization affects economic growth through various channels. It creates more

employment opportunities by expanding the market size, provides benefits of economies

of scale and better resource allocation, technological spillover, increases variety, increases

international competitiveness through elimination of government trading monopolies,

provides the consumers the access to cheaper commodities and also enables firms to get

access to cheaper inputs by expanding the market for their output. Many developing

countries adopted import-substitution policy in the 1970s but this inward oriented policy

proved to be inefficient and caused a shift from inward oriented policy towards outward

oriented.

As a measure of trade liberalization we have used average tariff rate38

. We have also used

the tariff rate for capital and consumer goods separately for a comprehensive policy

implication39

. Additionally as a traditional measure of trade liberalization we have also

used trade openness. Results show that trade liberalization boost the economic growth as a

1% reduction in average tariff rate increases the economic growth by 0.18 % points.

Moreover liberalization of capital goods positively contributes to economic growth with a

coefficient (0.2844) while liberalization of consumer goods is unrelated to economic

growth. Higher imports of capital goods stimulate the investment while consumer goods

38 Aggregate of consumer goods, capital goods, intermediate goods and raw material as a proxy of trade liberalization. 39 We have chosen tariff rate of capital and consumer goods because a large proportion of imports of developing

countries (included in sample) consists of these goods.


177

stimulate the consumption. Imports of capital goods increase the industrial sector

efficiency through technology transfer and boost the exports thereby improving the trade

balance. Trade openness as another indicator of trade liberalization positively affects the

economic growth with coefficient (0.1138) as common in the literature. Our findings have

empirical support from the literature. Greenaway et al. (2002) and Morgan and S.

Kanchanahatakij (2008) empirically analyze that trade liberalization positively contributes

to economic growth. Goldar and Kumari (2003) explain that import liberalization has

increased industrial productivity in India. Wacziarg and Welch (2003), Aksoy Ataman

(2006) and Falvey et al. (2013) explain that trade liberalization also increases capital

formation and manufacture exports by increasing export diversification in developing

countries. Dollar and Kraay (2004) find that globalization contributes to higher growth

rate and decline in poverty.

There is also some evidence in contrast to our results which shows that trade liberalization

may reduce economic growth. Harrison and Hanson (1999) find that trade liberalization

amplify wage inequality in less developed countries. Yasmin et al. (2006) conclude the

trade liberalization makes income distribution more worse.

Financial liberalization:

According to financial liberalization literature the association between financial

liberalization and growth is weak in developing countries. Stiglitz et al. (1994) criticize

the financial liberalization due to the increased market imperfections prevalent in

developing countries. Moreover financial liberalization in countries with weak financial

structure increase the risk of crisis, Mexican and Asian crisis in particular provide this

evidence40

. Excess capital inflows are associated with appreciation of the domestic

currency which is harmful for trade balance and divert the resources from trade able to

40

Both the crises witnessed the potential risks of short-term capital flows that lead to balance-of-payments

crises.


178

non-trade able sectors (construction, housing etc.). Furthermore huge and unanticipated

inflows encourage the consumption growth and lead to high inflation.

For financial liberalization we have used two measures; De jure and De facto measures

(detail is given in the previous chapter section 4.2). Both measures show that financial

liberalization negatively affects the economic growth with coefficients (-.1269) and (-

.3440) respectively. Our findings are in line with empirical literature. Kim et al. (2012)

find that capital account liberalization is inversely related to economic growth in the short

run both in the developed and developing countries. Eichengreen and Leblang (2003)

explain that capital account liberalization hurts the growth in the presence of crisis.

Alesina, Grilli and Milesi-Ferretti (1993, 1995) find that capital account liberalization

significantly contributes to economic growth in developed countries while it retards the

growth in developing countries. Klein and Olivei (2001), Arteta et al. (2001) and Edwards

(2000) depicts that capital account liberalization negatively contributes to growth in

countries having weak financial and institutional structure and lower level of development.

The negative sign of financial liberalization actually contradict the proposition advocated

by supporters of financial liberalization that liberalization enhances the growth rate of

economies. Bekaert et al. (2005) find that liberalization decreases the cost of capital

thereby increasing the investment and the efficiency of investment which leads to higher

growth. Quin (1997, 2008) explains that capital account liberalization contributes to

economic growth equally in developed and developing countries. Kim et al. (2012)

explains that capital account liberalization is helpful to economic growth in the long run

only.

There are certain weaknesses of both the De jure and De facto measures. De jure measure

only declares the legal status of financial liberalization of countries. De facto measure is

the sum of gross assets and liabilities; it includes both the short term and long term


179

flows41

. Aggregate measures of capital flows could conceal the individual effect of

different types of capital flows. Therefore we also use disaggregated measures

representing net FDI inflows being long term and stable investment while portfolio equity

and debt being short term investment.

Results show that net FDI inflows positively contribute to economic growth with

coefficient (.6269). Foreign investment plays an important role in developing countries

which are characterized by lack of capital and technology. This is also shown by Singh

(2003), McLean and Shrestha (2002), Reisen and Soto (2001), Mody and Murshid (2005).

Short term capital inflows negatively contribute to economic growth with a coefficient

(0.0869). They are highly volatile42

and bring macroeconomic and financial instability as

discussed above. Singh (2003), Mody and Murshid (2005) and Demir Firat (2009) provide

the evidence that short term capital flows negatively contribute to economic growth in

developing countries while they positively affect the growth in developed countries.

5.3.1.1 Diagnostic tests:

As described in the methodology in previous chapter section 4.3 that the validity of GMM

estimators depend on two specification tests; first the Sargan test of over identifying

restrictions, it tests the reliability of instruments, the second is the serial correlation test.

The null hypothesis of Sargan test explains that restrictions are valid against the

alternative. The second test examines whether there is higher order or second order serial

correlation. We test the null hypothesis of no serial correlation against the alternative.

Results of all equations show that we fail to reject both hypotheses. Chai square

probability shows that instruments are valid and errors are homoscedastic. Probability of Z

statistics in autocorrelation test shows that there is no evidence of second order serial

correlation. Moreover the Wald test checks the joint significance of all estimators in an

41

FDI being long term flows while loans and bonds are short term flows. 42

There reversal rate is higher as compared to other capital inflows.


180

equation. The results show that chai square probability is highly significant indicating that

overall goodness of the fit is satisfactory.

5.3.1.2 Concluding remarks:

To fulfill our first objective we analyze empirically the effect of institutions and policies

on economic growth. The results provide the proof of conditional convergence. Traditional

growth variables; physical and human capital and population growth also follow the

empirical literature. Physical capital increases the growth rate by increasing the economic

activities; increase in productivity, employment opportunities and economies of scale.

Human capital affects the economic growth through quality improvements in labour.

Population growth reduces the economic growth by increasing the consumption and

reducing the savings. Institutional quality promotes the economic growth by creating an

environment for capital creation. They reduce the risk of doing the business thereby

increasing the investment return. Results regarding the fiscal policy support the Keynesian

hypothesis. Capital expenditures positively contribute to economic growth by providing

necessary infrastructure for the encouragement of private sector investment. Current

expenditures adversely affect the economic growth by reducing the incentive for

investment, higher tax-finance outweighs the utility derived from it. Tax revenues also

positively affect the economic growth by increasing the ability of the government to

finance its expenditures. Results regarding the monetary policy support the Monetarists

hypothesis, monetary policy do affect the economic growth through aggregate demand.

Results show that contractionary monetary policy reduces the investment and economic

growth. Trade openness as a proxy for trade liberalization positively affects the economic

growth through externality as common in the literature. Reduction in the tariff rate also

positively contributes to economic growth. Disaggregated analysis shows that

liberalization of capital goods increases the economic growth by stimulating the


181

investment while liberalization of consumer goods is unrelated to economic growth.

Regarding the financial liberalization both De jure and De facto measure show that it

negatively affects the economic growth. In developing countries financial liberalization

brings macroeconomic and financial instability. Disaggregated analysis shows that FDI

inflows positively contribute to economic growth being long term and stable investment

while short term investment (portfolio equity and debt) negatively contribute to economic

growth due to higher reversal rate.

5.3.2 Disaggregated analysis of institutions

For a detailed analysis of institutional quality and for more comprehensive policy

implication we have also taken disaggregated measure of the institutional quality; voice

and accountability, political stability, government effectiveness, regulatory quality, rule of

law and control of corruption. We test the null hypothesis of no effect of each institutional

variable on economic growth against the alternative. Other independent variables are

initial GDP which captures the convergence, traditional determinants of growth; physical

capital, human capital and population growth. As an indicator of fiscal policy we use

government investment expenditures. We use interest rate as an instrument of monetary

policy. For trade liberalization we use average tariff rate and for financial liberalization we

use net FDI inflows.

Except the institutional variable, which we have taken in disaggregated form, results of

other variable; including convergence, traditional growth variables, indicators of fiscal and

monetary policy, indicators of trade and financial liberalization, have been discussed

already in detail in the previous section 5.3.1 with empirical evidence from previous

studies. Here again the detail will show only repetition so to avoid repetition we will only

explain the direction of relationship between the variables. We will discuss the results of

each institutional indicator with detail and support of empirical evidence.


182

Table 5.4 Disaggregated analysis of institutions

Dependent variable: Economic growth variables Eq1 Eq2 Eq3 Eq4 Eq5 Eq6

Convergence -.0340781*

(0.001)

-.0790415*

(0.001)

-.1170197*

(0.033)

-.0912243*

(0.000)

-.0450525*

(0.035)

-.0587423*

(0.003)

Capital stock .2267513*

(0.006 )

.1378771*

(0.043)

.1779449*

(0.016)

.1997953*

(0.010)

.1990583*

(0.008)

.157573

(0.283)

Human capital 1.293482

(0.249)

.7308444*

(0.023)

1.842145*

(0.046)

1.783189

(0.491)

.6684316*

(0.000)

1.018186*

(0.037)

Population growth -.5233922*

(0.050)

-.2684542

(0.268)

-.1813858

(0.204)

.4088777*

(0.047)

-1.855763*

(0.008)

.5466093

(0.217)


voice and

accountability

.214876*

(0.031)

political stability

and absence of

violence

.1370642

(0.418)

government

effectiveness

.09379**

(0.069)

regulatory quality .1623408**

(0.080)

rule of law .3316861*

(0.003)

control of

corruption

.257809*

(0.042)

Stabilization policies (Fiscal and monetary policy)

Govt. investment

expenditures

.5098117*

(0.000)

.5676061*

(0.000)

.4370075 *

(0.001)

.5399704*

(0.000)

.4349869*

(0.001)

.602409*

(0.000)

Interest rate -.0545692

(0.279)

-.1258617*

(0.009)

-.1080105*

(0.024)

-.0552043

(0.251)

-.1090939*

(0.022)

-.0643816**

(0.056)

Liberalization policies (Trade and financial liberalization)

Tariff rate -.0993893*

(0.041)

-.0869403**

(0.081)

-.1457545*

(0.007)

-.1453519*

(0.044)

-.1392638*

(0.008)

-.1108772**

(0.066)

Net FDI inflows

.4329936*

(0.030)

.178682

(0.430)

.4492691*

(0.038)

.2171839

(0.256)

.4444044*

(0.040)

.2058977*

(0.006)

constant .0194078

(0.998)

8.488722

0.298

19.67251*

(0.032)

11.04793

(0.391)

19.52491*

(0.034)

-.9370931

(0.960)

No. of countries 12 12 12 12 12 12

No. of

observations

210 195 195 213 195 195

Wald chi2(prob) 0.0013 0.0100 0.0058 0.0000 0.0009 0.0007

sargan (prob. chi2) 0.0874 0.0763 0.1775 0.1221 0.0711 0.0745

AR1(prob. Z)

AR2(prob. Z)

0.0182

0.4985

0.0685

0.2554

0.0853

0.5336

0.0263

0.2122

0.0392

0.2248

0.0889

0.1537

Note: Values in the parentheses show the probability of „Z‟ statistics. * shows the significance at 1% and 5

% level of significance while ** shows the significance at 10 %. Wald test check the joint significance of the

model, Sargan test checks the reliability of instruments while AR test checks the presence of autocorrelation.

Results show that there is evidence of conditional convergence, speed of convergence

ranges between 3% to 12%. Again as discussed in previous section traditional factors of

production follow empirical findings. Physical and human capital both are positively


183

associated to economic growth while population growth is inversely related to economic

growth. Government investment expenditures as an indicator of fiscal policy positively

affect the economic growth. Interest rate as a measure of contractionary monetary policy

negatively affects the economic growth. Average tariff rate as a measure of trade

liberalization shows inverse relationship with economic growth indicating that higher the

liberalization higher will be growth. Net FDI inflows as an indicator of financial

liberalization has direct relationship with economic growth implying that higher the

financial liberalization higher will be growth. Next we discuss the effect of each

institutional variable on economic growth in detail.

Voice and accountability:

As described in the previous chapter section 4.2 the World Bank defines the voice and

accountability as the extent to the possibility that the people of a country have freedom of

expression or choice. Economic as well as political freedom is regarded an important pillar

of institutional structure of a country. Higher economic freedom increases the rate of

private investment in GDP, productivity of private investment and growth of countries.

Our results show that a 1% increase in voice and accountability index increases the

economic growth by 0.21%. Our results follow the find empirical support as Kaufmann et

al. (1999), Fayissa et al. (2013), Yerrabati and Hawkes (2015) and Bhattacharjee et al.

(2015) conclude that voice and accountability is positively correlated with economic

growth. Gwartney et al. (2003) describe that countries with higher degree of economic

freedom achieved higher economic growth. Azman Saini et al. (2010) provide the

evidence that the effect of FDI on economic growth is conditional on the degree of

economic freedom.

In contrast to our findings Bjornskov (2014) provide the evidence that higher economic

freedom is associated with high crime rates.


184

Political stability:

Relationship between political stability and economic growth depends on how we define

political stability. Literature uses different indicators for this variable. Executive turnover

represents the frequency of government collapses, Polity II democratization score,

assassinations and war casualties, occurrence of strikes, violence and coup etc. Mostly it is

observed through democratic and non-democratic governments and we also explain this

variable with this aspect. Research regarding the role of democracy in economic growth

provides ambiguous findings. The opponents argue that democracy impedes the growth

especially in less developed countries through creating consumption pressures which

hampers capital accumulation. Supporters emphasize that democracy increases economic

growth by providing civil liberties and political rights creating an environment beneficial

to economic growth. The skeptical view argues that both democracy and economic growth

are unrelated. A democratic system alone is not enough to effect on economic growth,

institutional structure and government development strategies are important factors

without which we cannot relate democracy to economic growth.

Most of the empirical studies provide the evidence of insignificant or negative association

between both variables. Our results show that political stability is unrelated to economic

growth as this variable becomes insignificant. Moreover the political stability has the

lowest percentile rank over time in nearly all the countries included in the sample which

shows that this indicator is not an important indicator of institutional quality (chapter 3

section 3.1).

Bhattacharjee et al. (2015) find that political stability has no relationship with economic

growth. Ahmad and Marwan (2012) find the evidence of negative effect of political rights,

favouring the strong authoritarian in the East Asian countries to pursue the pro-growth


185

policies. Yerrabati and Hawkes (2015) argue that if political stability is achieved through

oppression or if it produces stagnation then it negatively contributes to economic growth.

In contrast to our findings some empirical studies find positive relationship between both

variables as Goldsmith (1995), Chong et al. (2004), Gani (2011), Fayissa et al. (2013)

provide the evidence of positive relationship.

Government effectiveness:

Effective state has an important role for the provision of goods and services, public

welfare, maintaining law and order, creating an enabling policy environment for

productive activities. United Nations43

defined governance as “the process of decision-

making and the process by which decisions are implemented.” Literature provides the

evidence of a significant association between improved quality of governance and

economic growth. Findings infer that government effectiveness is positively related to

economic growth having a coefficient 0.09 which follows the empirical studies. A cross

section analysis of developing countries shows that countries having poor governance

experience a lesser growth per year relative to other countries. The work of Kaufmann et

al. (1999) provides the same conclusion about the importance of governance to economic

growth. Similar findings are provided by Gani (2011), Fayissa et al. (2013) and

Bhattacharjee et al. (2015).

Regulatory quality:

The relationship between regulatory quality and economic growth is of considerable

interest for the researchers in recent years. Through regulatory framework state affects the

behavior of the private sector. Regulatory policy in developing countries has transformed

from interventionist state to deregulation. It highlights the role of private sector for

production decision, which also ensures well-functioning competitive markets, and

43

United Nations Economic and Social Commission for Asia and the Pacific [UNESCAP], 2009.


186

emphasizes the role of state regulations to correct the market failures44

. World Bank has

emphasized the importance of improving the regulatory framework for better investment

climate for the private sector.

Our findings are consistent with the regulatory theory that effective regulation is related to

higher economic growth, which is conducive to the development of international business.

Results show that a 1% increase in regulatory quality index increases the economic growth

by 0.16%. Kaufmann et al. (1999) and Fayissa et al. (2013) explain that regulatory quality

increases the growth and development.

Rule of Law:

World Bank defines the rule of law as the contract enforcement, property rights protection,

the police and the courts, control of crime and violence. A better judicial system fosters

the economic growth by enforcing the property rights which are necessary for the increase

in private investment, moreover it keeps the checks and balances on the government,

controls the corruption. There is evidence that many African countries have shown poor

performance in terms of economic growth while they are rich in natural resources because

in the absence of property rights, these resources are exploited by power-full interest

groups45

.

Our results support the empirical literature as a 1% increase in rule of law index increases

the economic growth by 0.33% which is also highly significant. Campos and Nugent

(1999) and Kaufmann et al. (1999) explain that rule of law significantly contributes to

growth and development. Knack and Keefer (1995), Goldsmith (1995) and Ahmad and

Marwan (2012) describe that property rights increase the investment and economic

growth.

44

World Bank, 2001: 1 45

See Lane and Tornell (1996).


187

In contrast to our findings Yerrabati and Hawkes (2015) explain that rule of law is

negatively correlated to growth for South Asia, East Asia and Pecific regions. Negative

effect of rule of law indicates the less developed legal system of the region which does not

contribute to economic growth.

Control of Corruption:

World Bank defines the corruption as the use of public power for the private gain. There is

broad consensus in the literature that corruption impedes the economic growth by

lowering the rate of investment both domestic and foreign, reducing trade flows, creating

uncertainty and lowering the quality and efficiency of public projects. Corruption is

treated as detrimental to economic growth because it reduces the efficient allocation of

resources because individuals engage in rent-seeking activities rather than socially

productive activities.

Our results show that less corruption enhances the economic growth as a 1% increase in

control of corruption index boost the economic growth by 0.25 %. Mauro (1995) and

Mauro (2002) explain that corruption reduces the economic growth through reduction in

private investment. Drury and Lusztig (2006) and Gani (2011) also provide the evidence

of an inverse relationship between corruption and economic growth.

There is also evidence in sharp contrast to our results which describes that corruption

contributes to economic growth. Yerrabati and Hawkes (2015) explain that corruption

reduces the bureaucratic delays and facilitate investment and hence economic activity.


As described in previous section that to check the validity of the GMM estimators we use

two specification tests; first the Sargan test of over identifying restrictions the second is

the serial correlation test. Chai square probability of the Sargan test shows that instruments

are valid. Probability of Z statistics in autocorrelation test shows that there is no evidence


188

of second order serial correlation. Wald test checks the joint significance of all estimators

in an equation. The results show that chai square probability is highly significant all

equations, indicating that overall goodness of the fit is satisfactory.


Disaggregated analysis of institutional measures demonstrates that voice and

accountability positively contribute to economic growth. Economic as well as political

freedom is regarded an important pillar of institutional structure of a country. Political

stability is unrelated to economic growth as it alone cannot affect economic growth,

institutional set up and government development strategies are important factors without

which we cannot relate political stability to economic growth. Results show that there is a

positive relationship between improved quality of government services and economic

growth. Effective state has an important role for the provision of goods and services,

public welfare, maintaining law and order, delivering public services, creating an enabling

policy environment for productive activities. Regulatory quality is also positively related

to economic growth. Through regulatory framework state affects the performance of the

private sector. Rule of law and economic growth are also positively related. A better

judicial system fosters the economic growth by enforcing the property rights which are

necessary for the increase in private investment, moreover it keeps the checks and

balances on the government, controls the corruption. Lesser corruption significantly

contributes to economic growth. Corruption retards the economic growth because it

reduces the efficient allocation of resources.

5.3.3 Effect of policy volatility on economic growth:

First objective examines the level effect of policies whereas second objective examines

volatility effect of domestic macroeconomic policies on economic growth. We again write


189

the equation here which we have already explained in previous chapter in section 4.1 as

follows;

)15(ln 222

1

43132 beqVdPVbIQbyaagyitititn

r

n

nitititit

Here Vn includes traditional factors of production; physical capital, human capital and

population growth and some external factors (foreign growth volatility, term of trade

volatility and foreign interest rate volatility). IQ shows institutional quality while PV

represents policy volatility. yt-1 is again the lagged value of GDP per capita which

represents convergence.

Volatility refers to the fluctuations in any economic activity, less volatility shows stability,

while higher volatility is harmful for an economy which leads to instability. To measure

the volatility we have used the first-order autoregressive process where the standard

deviation of the residual measures the volatility. We have also discussed the measurement

of volatility in previous chapter section 4.2. For fiscal policy volatility we have used

volatility of aggregate government expenditures. Interest rate volatility represents the

volatility of monetary policy. Volatility of financial liberalization is represented by FDI

inflows volatility. For volatility of trade policy we have used volatility of trade flows. We

have already discussed all other variables in detail in previous section 5.3.1 here again

discussion will be just repetition. Both the volatility of domestic macroeconomic policies

and external factors affect the investment and economic growth. We hypothesize that

policy volatility reduces the economic growth thus we will test the null hypothesis that

policy volatility does not affect the economic growth

Except the policy volatility which we have taken in this equation results of other variables;

including convergence, traditional growth variables and institutional quality, we have

already discussed in detail in previous section 5.3.1 with empirical evidence from the


190

literature. Here again the detail will show only repetition therefore to avoid the repetition

we will only explain the direction of relationship between these variables. We will discuss

the results of policy volatility with detail and support of empirical literature.

Table 5.5 Effect of policy volatility on economic growth

Dependent variable: Economic growth variables Eq1 Eq2 Eq3 Eq4

Convergence -.0425199*

(0.000)

-.0976269

(0.224)

-.0721738

(0.200)

-.0271405*

(0.031)

Capital stock .1469909*

(0.021)

.1504829*

(0.049)

.1482574**

(0.091)

.1959927*

(0.035)

Human capital 2.271369*

(0.023)

2.051568**

(0.095)

1.889191*

(0.016)

1.977229*

(0.038)

Population growth -.5207025

(0.440)

-.4406616*

(0.046)

.4672669**

(0.084)

-.881823

(0.760)

Institutional

quality

.1487524**

(0.076)

.3259461

(0.137)

.1276399*

(0.043)

.0673953**

(0.092)

Fiscal policy

volatility

-.138725**

(0.069)

Monetary policy

volatility

-.098406*

(0.046)

Trade flows

volatility

-.170112**

(0.092)

Capital flows

volatility

-.0351274*

(0.033)

External shocks Foreign growth

volatility

-.0852388**

(0.052)

-.1497384*

(0.001)

-.1013687

(0.214)

-.0117363*

(0.000)

TOT volatility -.5109134*

(0.020)

-.6786726**

(0.060)

-.2893842*

(0.033)

.4122176

(0.759)

Foreign interest

rate volatility

-.0611558

(0.281)

-.0376918*

(0.007)

-.0966214*

(0.013)

-.0148586*

(0.038)

constant -14.07357*

(0.036)

-13.4263*

(0.047)

-13.65986*

(0.045)

-8.666981

(0.647)

Number of obs 201 201 201 201

Number of

countries

12 12 12 12

Wald chi2(prob) 0.0014 0.0013 0.0013 0.0000

sargan (prob. chi2) 0.8142 0.3861 0.4482 0.4850

AR1(prob. Z)

AR2(prob. Z)

0.0828

0.4563

0.0485

0.3539

0.0267

0.9152

0.0670

0.2600 Note: Values in the parentheses show the probability of „Z‟ statistics. * shows the significance at 1% and 5

% level of significance while ** shows the significance at 10 %. Wald test check the joint significance of

the model, Sargan test checks the reliability of instruments while AR test checks the presence of

autocorrelation.

Results show that there is evidence of conditional convergence implying the negative

association between initial GDP and economic growth. Again as discussed in previous


191

section traditional factors of production follow empirical literature. Physical and human

capital both are positively related to economic growth while population growth is

inversely related to economic growth. Institutional quality positively affects the economic

growth. Next we discuss the effect of policy volatility on economic growth in detail.

Volatility of domestic policies:

Developing countries face the problem of uncertainty or frequent switches in their

macroeconomic policies due to some internal and external factors which reduces the rate

of economic growth and investment. Consistency of the policy is most important because

inconsistent decisions loose the public confidence, creating uncertainty for investors, reducing

the investment and growth. Investors become sensitive to policy changes and the associated

risks because of irreversible nature of certain investments. In an uncertain environment

firms delay investment and it takes a long time to investors to assure themselves that

changes of policies are permanent.

Our results show that a 1% increase in fiscal policy volatility as represented by

government expenditures reduces the economic growth by 0.13%. Our results follow the

empirical literature. Empirical literature shows that predictability or certainty of the fiscal

policy is important for the decision to invest. Uncertainties regarding future behavior of

fiscal parameters reduce the growth rate by making investment riskier. In poor countries a

combination of discretionary fiscal policy and procyclical fiscal policy increases the

volatility and harms long-term growth. Aizenman and Marion (1991), Ramey and Ramey

(1995), Ali M. Abdiweli (2005) and Fatas and Mihov (2008) explain that volatility of the

fiscal policy, uncertainty about future taxes and the future behavior of fiscal parameters,

negatively affect the behavior of economic agents altering the investment patterns. Davide

Furceri (2007) find that government expenditures volatility is negatively associated to

long-run growth for developing countries while it has a small effect for OECD countries.


192

Afonso and Jalles (2012) explain that both the discretionary and transitory variations in

fiscal policy raise the output volatility and decrease the economic growth. Moreover with

a financial crisis government spending is less flexible than revenues in developing

countries.

Regarding the volatility of monetary policy as represented by short term interest rate our

results show that a 1% increase in monetary policy volatility reduces the economic growth

by 0.09%. Uncertainty of the interest rate affects the firm‟s profitability by reducing the

corporate investment especially when there is irreversibility. Firms delay investment in

order to get information regarding the future stance of monetary policy. Findings are also

supported by empirical literature. Peterson (1998) finds that an unstable money supply

growth has contributed to slower growth in developing countries. Gulen and Ion (2013)

and Bretscher et al. (2016) explain that policy uncertainty reduces the industry and firm

investment with a substantial magnitude. Relationship is stronger for firms having higher

degree of irreversibility, have more financial constraints and those who are less

competitive. Bo and Sterken (2002) show that an increase in interest rate volatility

increases the interest rate burden and decreases the real value of debt holdings and the

effect is larger for highly indebted firms.

Regarding the volatility of capital inflows as represented by net FDI inflows our results

show that it negatively affects the economic growth, a 1 % increase in the volatility of

capital inflows reduce the economic growth by 0.03%. Volatility of capital inflows is a

proxy for country specific risk, given the higher risk foreign investors might delay or even

reverse the investments. Increasing volatility of capital flows affects domestic investment

through interest rates, exchange rate, inflation expectations and risk and uncertainty

regarding future profitability. FDI volatility is detrimental to economic growth by

discouraging the innovation and technology adaption. There is growing body of literature


193

indicating that unstable short-term capital flows have deteriorated the long-term growth

prospects in developing countries. Our findings are supported by empirical literature.

Choong et al. (2011) explain that FDI volatility is negatively associated with all ASEAN

countries while it has a marginal effect on Singapore because the financial system of

Singapore is well developed having the ability to alleviate the variability of FDI inflows.

Demir Firat (2009) conclude that volatility of the short term capital inflows is negatively

associated with economic growth. Neanidis (2015) find that volatility of all the capital

flows aggregated and disaggregated (FDI, equity and debt flows) is negatively related to

economic growth.

Volatility associated with trade flows as represented by export instability also reduces

the economic growth. Our results show that a 1% increase in the volatility of trade flows

reduces the economic growth by 0.17%. Economic literature provides the evidence that

trade flows are more volatile in less developed economies as compared to developed

countries as global integration has exposed these countries to external shocks and the

difficulty to manage these shocks has made their trade flows more volatile thereby

reducing the growth. Volatility of export earnings bring instability in foreign reserves that

reduce the imports of capital goods and hence decrease the efficiency of industrial sector.

Our findings follow the empirical literature. Ozler and Harrigan (1988) find that largest

negative effects of export instability are on countries who are more open and whose

exports are concentrated in capital intensive sectors. Love (1989) concludes that export

instability brings instability in capital goods imports and, in turn, investment and growth.

Gyimah-Brempong (1991) and Rashid et al. (2012) explain that export instability

negatively affect the economic growth in Asian and African countries.

In contrast to our findings Yotopoulos and Nugent (1976) and Sinha (1999) infer that

export instability reduces the marginal propensity to consume, thereby increasing savings


194

and higher growth. While Chaudhary and Qaisrani (2002) explain that export instability

does not affect economic growth and investment in Pakistan because the trade deficit is

met through foreign borrowings.

Volatility of external factors:

With the increased globalization and integration of world market economies are greatly

influenced by the growth volatility of their trading partners such as the financial crisis of

2008. Terms of trade shocks affect in particular growth of small open economies. Interest

rate shocks make the credit and investment more expensive bringing the firms towards

bankruptcy. Results show that volatility of foreign growth, term of trade volatility and

foreign interest rate volatility all inversely related to economic growth. Literature provides

the empirical support to our findings. Mendoza (1997) and Andrews and Rees (2009)

explain that term of trade volatility reduces the economic growth by increasing the

volatility of consumption, exports and imports. Olaberria and Rigolini (2009) explain that

besides the volatility of domestic factors volatility of external factors has also contributed

to the slow growth of emerging economies. Abaidoo (2012) conclude that external

macroeconomic volatility has larger effect on macroeconomic performance of African

countries than domestic volatility.


Sargan and auto correlation test both check the reliability of GMM estimates. Results of

the Sargan test show that instruments are valid and results of autocorrelation test provide

the evidence of no second order serial correlation. Results of the Wald test the joint

significance of the model implying that overall significance of the model is satisfactory.


195


Our second objective examines the association between policy volatility and economic

growth. Results show that volatility of domestic macroeconomic policies brings the

uncertainty regarding investment decisions therefore reducing the growth. A predictable

policy is an important factor that affects the behaviour of investors. Volatility makes the

investors sensitive to policy change and the associated risks because of irreversible nature

of certain investments. Volatility of the fiscal policy creates uncertainty about future taxes

and the future behavior of fiscal parameters which negatively affects the behavior of

economic agents. Uncertainty of the interest rate affects the firm‟s profitability by

reducing the corporate investment especially when there is irreversibility. Access to the

external market has destabilized the economies of less developed countries because of

volatility associated with trade and capital flows. Volatility of both negatively affects the

economic growth by reducing the domestic and foreign investment.

5.3.4 Determinants of policy volatility:

Our last objective is to analyze the effect of institutions on policy volatility. We again

write the equation here which we have already explained in previous chapter in section 4.1

as follows;

)15(333

1

5154 ceqWfIQbPVaaPVititits

v

s

sititit

Here Ws consist of control variables including domestic macroeconomic and external

factors; inflation volatility representing macroeconomic volatility, GDP per capita

representing level of development of a country, previous period‟s debt, exchange rate

volatility, export concentration, primary exports, financial development and some external

factors which include foreign growth volatility, term of trade volatility and foreign interest

rate volatility.


196

As explained in previous chapter section 4.2 and also in previous section 5.3.2 that

volatility refers to the fluctuations in any economic activity. To measure the volatility we

have used the first-order autoregressive process where the standard deviation of the

residual measures the volatility. As explained in previous section 5.3.2 that for fiscal

policy volatility we have used volatility of aggregate government expenditures, for

monetary policy volatility we have used interest rate volatility. Volatility of capital flows

is represented by FDI inflows volatility and for volatility of trade policy we have used

volatility of trade flows.

Developing countries are more volatile and their volatility stems from three sources. First,

they experience more domestic shocks due to macroeconomic instability second, they face

bigger exogenous shocks due to global integration third ,they have weak shock absorbers46

due to which exogenous factors have strong influence on their macroeconomic volatility.

Institutions play an important role to reduce policy volatility by putting restrictions or

check and balances on policy makers. We hypothesize that institutions reduce the policy

volatility hence we will test the null hypothesis that institutions does not affect policy

volatility against the alternative.

46

Financial markets and macroeconomic stabilization policies are regarded shock absorbers. Financial

markets diversify the risk and stabilization policies help to absorb the shocks.


197

Table 5.6 Determinants of policy volatility

Dependent variable: Policy volatility variables Fiscal policy

volatility

Monetary policy

volatility

Capital flows

volatility

Trade flows

volatility

Previous period‟s policy

volatility

.1471345*

(0.000)

.0931952**

(0.075)

.0534053*

(0.014)

.0269583*

(0.005)

Inflation volatility .09235722*

(0.000)

.0174039*

(0.039)

.0475569*

(0.030)

GDP per capita -.2252021*

(0.000)

-.0127363*

(0.291)

-.0689597*

(0.001)

-.0449205**

(0.076)

Previous period‟s debt .0553092*

(0.035)

0.312784*

(0.043)

Exchange rate volatility .0215541*

(0.025)

.075566**

(0.063)

.1289132*

(0.004)

Financial development -.290425*

(0.008)

-.2651632**

(0.052)

Export concentration .0858227*

(0.002)


Fiscal institutions (Political constraints)

- .0834411*

(0.048)

Economic institutions (rule of law and control of

corruption)

-.1300039**

(0.076)

-.1614577*

(0.031)

Monetary institutions (Central Bank independence)

.0282034*

(0.046)

External shocks

Foreign growth volatility .0358045*

(0.000)

.0137612

(0.543)

-.1573719*

(0.049)

.0725686*

(0.042)

TOT volatility .416788

(0.422)

.654213

(0.631)

.22249

(0.230)

.850552*

(0.007)

Foreign interest rate

volatility

.0865999

(0.171)

.1565321*

(0.026)

-.0888771*

(0.005)

.1520388

(0.530)

constant .2302051

(0.116)

.8180584*

(0.000)

.5367057*

(0.000)

2.101226*

(0.001)

Number of obs 204 204 204 204

countries 12 12 12 12

Wald chi2(prob) 0.0140 0.0029 0.0001 0.0337

sargan (prob. chi2) 0.1134 0.1034 0.6959 0.1928

AR1(prob. Z)

AR2(prob. Z)

0.0069

0.1132

0.0845

0.1460

0.0125

0.9843

0.0845

0.1848 Note: Values in the parentheses show the probability of „Z‟ statistics. * shows the significance at 1% and 5

% level of significance while ** shows the significance at 10 %. Wald test check the joint significance of

the model, Sargan test checks the reliability of instruments while AR test checks the presence of

autocorrelation.


198

5.3.4.1 Determinants of fiscal policy volatility:

Volatility of fiscal policy is associated with cyclical fluctuations or some exogenous

factors, exogenous factors bring fluctuations in fiscal policy that are not associated to

economic or business cycle fluctuations; politically motivated changes in taxes or

spending and changes in fiscal policy caused by exogenous shocks. For the empirical

analysis of fiscal policy volatility we have used government spending because it is less

volatile, reacts much less to the cyclical fluctuations in general.

Previous period’s fiscal volatility increases the volatility in current period because it

becomes difficult to reverse certain spending due to some political constraints. Results

show that a 1% increase in volatility of the previous period increases the volatility in

current period by 0.14%.

Fatas and Mihov (2008), Agnello and Sousa (2014) and Attiya et al. (2011) explain that

fiscal policy volatility has persistence effect.

GDP per capita represents the level of development of the countries. As the level of

development increases it reduces the volatility of fiscal policy. Results show that GDP per

capita and fiscal policy volatility are inversely related. It indicates that rich countries have

more stable fiscal policy with lower volatility of fiscal discretion and larger automatic

stabilizers. While poor countries are likely to have more volatile business cycle and more

prone to discretionary fiscal policy. Fatas and Mihov (2008, 2013), Agnello and Sousa

(2009) and Bleaney and Halland (2009) explain that higher level of development

represented by GDP per capita reduces the volatility of fiscal policy.

Higher inflation volatility represents the macroeconomic instability which is positively

associated with the fiscal policy instability. A 1 % increase in the inflation volatility

increases the fiscal policy by 0.09%. Higher inflation increases the fiscal volatility as it

brings economic uncertainty making volatile the spending and revenue. Agnello and Sousa


199

(2009) and Attiya et al. (2011) explain that inflation and inflation volatility increases the

volatility of capital flows.

Higher external debt in developing countries, due to higher fiscal deficits, increases the

volatility of fiscal policy. Our results also follow the empirical literature indicating a direct

relationship between external debt and fiscal policy volatility with a coefficient of 0.05.

Large fiscal adjustments are required for the accumulation of debt which affects the

country‟s long run fiscal sustainability. Higher external debt reduces the efficiency of

fiscal policy in controlling economic fluctuations due to increase in taxes, generating a

more procyclical fiscal policy. Fatas and Mihov (2008), Attiya et al. (2011) and Agnello

and Sousa (2008, 2014) explain that higher public debt and deficits lead to higher fiscal

instability due to frequent taxes and spending variations.

Regarding the institutional quality our results show a significant negative effect of the

quality of institutions on government spending volatility with a coefficient 0.08. Empirical

literature provides the evidence that institutional constraints make it hard for the

governments to frequently change the policy. Strong budgetary institutions provide the

rules to govern the budget process and checks and balances over public finances. Also the

checks and balances by the parliament or judiciary put constraints on the governments and

generate the fiscal policy which is highly predicable. Our results follow the empirical

literature. Fatas and Mihov (2008, 2013) and Henisz (2004) explain that institutional

quality represented by political constraints significantly and robustly contributes to fiscal

policy volatility. Agnello and Sousa (2009, 2014) explain that higher political instability

increases the volatility of public deficit while higher democracy and parliamentary

systems reduces volatility. Bruno (2010) finds that institutions, both the explicit and

implicit constraints, reduce the volatility of fiscal policy significantly. Attiya et al. (2011)

depicts that political and institutional constraints reduce the volatility of budget deficit.


200

Results show that external factors also enhance the volatility of fiscal policy. Foreign

growth volatility increases the fiscal policy volatility with a coefficient 0.03. With

increased globalization, integration and external competitiveness economies are therefore

more exposed to external shocks, which put an upward pressure on domestic

macroeconomic policy making it more volatile, as documented by Agnello and Sousa

(2009, 2014).

5.3.4.1.1 Diagnostic tests:

Sargan test provides the evidence of the reliability of instruments while the auto

correlation test provides the evidence of no second order serial correlation. In both tests

we fail to reject the null hypothesis. Wald test provides the overall significance of the

model which is satisfactory.

5.3.4.1.2 Concluding remarks:

We conclude that volatility of the fiscal policy is affected by some domestic and external

factors. We determine the fiscal policy volatility by its past behaviour, previous period‟s

volatility induces volatility in the current period. GDP per capita represents the level of

development of the countries. With higher level of development countries have more

stable fiscal policy with lower volatility of fiscal discretion and larger automatic

stabilizers. Inflation volatility which represents the macroeconomic instability induces

economic uncertainty which makes fiscal policy highly volatile. Higher external debt, due

to higher fiscal deficits, increases the volatility of fiscal policy inducing large fiscal

adjustment for the accumulation of debt leading to frequent changes in spending and

taxation. Institutional checks and balances by the parliament or judiciary put constraints on

the governments and generate the fiscal policy which is highly predicable. With increased

globalization, integration and external competitiveness economies are therefore more


201

exposed to external shocks, which put an upward pressure on domestic macroeconomic

policy.

5.3.4.2 Determinants of monetary policy volatility:

Less volatility of monetary policy is closely associated with the transparency of monetary

authority‟s actions and decisions. There are certain internal and external factors affecting

the volatility of monetary policy. External factors explain the degree of market integration.

Since the last two decades trade and foreign investment barriers have reduced in

developing countries due to deregulation, accompanied by high interest rate volatility.

Monetary policy volatility is represented by short term interest rate though short term

interest rate is considered highly volatile but due to data constraints its common practice in

empirical literature.

Previous period’s volatility increases the volatility of monetary policy in current period.

Results show that a 1% increase in previous period‟s volatility increases the volatility in

current period by 0.09%. Previous period‟s volatility makes the profits of investors

uncertain so they delay their investment decisions also in the current period by assuming

that previous pattern will prevail in current period which increases the volatility further.

As described in previous equation that GDP per capita represents level of development of

a country. Results show that GDP per capita and volatility of monetary policy are

inversely related. A 1% increase in GDP per capita reduces the monetary policy volatility

by 0.01%. Higher level of development show macroeconomic stability, less market

imperfections or distortions, financial market stability and autonomy of the central bank

will reduce the volatility of monetary policy.

Our results show that inflation volatility and interest rate volatility are directly related

with a coefficient 0.01. Inflation is a major determinant of interest rate according to

Fischer‟s theory, loanable funds and liquidity preference. There are many studies that


202

investigate this relationship at levels. Payne and Ewing (1997) and Ahmad (2010) provide

the evidence of positive association between expected inflation and interest rate in

developing countries. Berument and Malatyali (2001) and Berument et al. (2007) also

consider inflation uncertainty and provide the evidence that both inflation and inflation

uncertainty positively contribute to interest rate in developed and developing countries.

Noula (2012) explain that uncertainty in inflation affects the investor‟s welfare, for a given

level of risk they want to have higher return.

Management of public sector deficit or debt is an important aspect of fiscal policy. In

many developing countries unsustainable fiscal deficits and public debt lead towards high

and volatile inflation therefore making monetary policy more volatile. Though financial

liberalization policies have been executed in many developing countries, government

interventions still remain significant in many countries. Empirical literature provides

mixed results regarding the relationship between government debt or deficits and interest

rate. Some studies support the non Ricardian47

hypothesis, public debt and deficits

increase interest rates while others support the Ricardian equivalence48

hypothesis, no link

between the both because private savings fully offset the effect of a higher deficit. It is

also argued that sensitivity of interest rate to deficit has decreased due to the globalization

and financial market integration, due to increasing flow of foreign capital to finance the

deficit.

Our results show that a 1 % increase in previous periods‟ debt increases the volatility of

monetary policy in current period by 0.31%. Our results support the non Recardian

hypothesis that fiscal policy distortions caused by higher deficit or debt bring distortions in

monetary policy. Our results are supported by empirical literature. Lal et al. (2001)

47

In a non-Ricardian regime fiscal policy becomes active and monetary policy passive, monetary policy

accommodates higher fiscal deficits. 48

In a Ricardian regime monetary policy is active which determines the prices and fiscal policy is passive.


203

explain that the higher fiscal deficit and debt have led to higher interest rates and crowding

out of private investment in India. Kwon et al. (2006) explain that a higher public debt is

strongly related with higher inflation and interest rate in countries under higher debt

obligations. Claeys et al. (2012) explain that only in OECD countries the effect of public

debt on interest rate is small due to globalization while emerging markets are not well

integrated so the effect is larger there.

In contrast to our results Gale and Orszag (2002) and Chakraborty (2012) argue that fiscal

expansion does not increase the interest rate due to availability of foreign savings

replacing domestic savings and due to interest rate deregulation.

The relative strength of the domestic currency affects the inflation and interest rate. A

decline in the value of domestic currency raises the cost of imported inputs and final goods

via the cost push inflation. It not only increases price of imported goods but also indirectly

increases the price of domestic goods which are under competitive pressure from imported

goods, via demand pull inflation. Opposite holds in case of appreciation of domestic

currency so the volatility in exchange rate brings inflation volatility which is associated

with interest rate volatility. Results show that a 1% increase in exchange rate volatility

increases the interest rate volatility by 0.02%. Hol (2006) and Aisen and Hauner (2008)

explain that devaluation leads to higher domestic interest rate in small semi open

economies. Chakraborty (2012) explains that a higher exchange rate attracts the demand

for domestic financial assets from abroad, by making the domestic currency less valuable,

which may lead to increase the interest rate.

Institutional quality plays an important role in the effectiveness and consistency of

monetary policy. Results show an inverse association between central bank independence

and volatility of monetary policy. A 1% decrease in central bank autonomy increases the

volatility of monetary policy by 0.02%. Institutions affect the transmission of monetary


204

policy through their effect on the elasticity of investment demand to changes in interest

rates. An independent central bank can provide more consistent policy by reducing the

uncertainty, in addition to lower inflationary outcome. Independent central banks are much

less sensitive to political influence and are more concerned about price stability while

higher political influence changes central bank laws randomly within short time spans.

Krause and Rioja (2006) provide the evidence that higher institutional quality and central

bank independence contribute towards a more efficient monetary policy outcome in both

developed and developing countries. Burdekin et al. (2011) provide the evidence of

central bank independence and inflation consistency both for developed and developing

countries. Duncan (2013) provides the evidence that strong institutional quality reduces

the volatility of interest rate and brings a positive co-movement between output and the

interest rate (countercyclical monetary policy).

Over the past two decades the global integration (through trade and financial channels)

has resulted in a higher degree of business cycle co-movement by faster transmission of

shocks. This has reshaped the monetary policy framework in developing countries, short

and long term interest rates have become more responsive to global conditions. Monetary

policy volatility in the world or large countries has significant effect on monetary policy in

developing countries. Results show that volatility of foreign interest rate increases the

volatility of monetary policy by 0.15%. Lorde et al. (2008) and Aisen and Hauner (2008)

provide the evidence of a positive correlation between domestic interest and US interest

rate. Hol (2006) provide the evidence that external factors have more influence on

domestic interest rate as compared to domestic macroeconomic factors. Noula (2012) and

many other studies explain that with higher openness interest rate is determined by

external factors, interest rate parity relationship.


205


Sargan test provides the evidence of validity of instruments while serial correlation test

provides the evidence of no higher order serial correlation. Wald test provides the

evidence that level of significance of the model is satisfactory.


We conclude that there are some domestic and global factors that affect the volatility of

monetary policy. Previous period‟s volatility increases the volatility of monetary policy in

current period by making uncertain the profits of the investors. Higher level of

development shows macroeconomic stability, financial market stability and independence

of the central bank causing more stable monetary policy. Increased inflation uncertainty

increases the unanticipated inflation which is associated with anticipated and uncertainty

effects on interest rate. Regarding the previous period‟s debt our results support non

Ricardian hypothesis. We conclude that distortions in fiscal policy caused by public debt

or deficit bring distortions in monetary policy. The relative strength of the domestic

currency affects the inflation and interest rate. Institutions play an important role in the

consistency of monetary policy. An independent central bank can provide more consistent

policy by reducing the uncertainty. Due to global integration and a greater business cycle

co-movement monetary policy volatility in the world or large countries has significant

effect on monetary policy in developing countries.

5.3.4.3 Determinants of capital flows volatility:

Literature shows that there are certain external (push) and internal (pull) factors that are

accountable for the volatility of capital flows in developing countries. Prior to financial

crisis 1997-98 many developing countries observed a significant increase in net capital

inflows, mainly driven by the banking sector capital flows, these short term flows reversed

during crisis. Again prior to global financial crisis 2007-08 developing countries


206

experienced large short term inflows, during the crisis larger reversal lead to financial

market instability in developing countries. An effective management of these capital flows

has been a major policy concern for many developing countries. In this respect,

understanding the factors that drive capital flows is vital for the effective management of

such flows. We use net FDI inflows to represent volatility of capital flows because these

are considered more stable as compared to other flows.

Results show that previous period’s volatility positively affects the volatility of capital

flows in current period because it increases uncertainty and the risk on the part of

investors. Results show that a 1% increase in previous period‟s volatility increases the

volatility in current period by 0.05%. (Broner and Rigobon, 2005).

Results show an inverse relationship between GDP per capita and volatility of capital

flows with a coefficient 0.06. Countries with higher development level exhibit lower

volatility of capital flows due to fewer distortions in the capital market. It is argued that

the presence of market imperfections such as information asymmetry, moral hazard and

herding destabilize the capital flows in both developed and developing countries. There

are a number of studies finding these distortions as a key factor behind destabilized capital

flows to developing countries. Alfaro et al. (2005), Broner and Rigobon (2005), Mercado

and Park (2011), Waqas et al. (2015) explain that level of development reduces the

volatility of capital flows. While Broto et al. (2008) provide the evidence of nonlinear

relationship between both variables.

Inflation volatility represents macroeconomic uncertainty which is positively related with

volatility of capital flows. Findings indicate that a 1 % increase in inflation volatility

increases the volatility of capital flows by 0.04%. Capital flows respond to the

macroeconomic uncertainty because the foreign investor bears the risk, and uncertainty of

inflation is detrimental to the profitability of investors. Countries having lesser inflation


207

volatility incline to experience lower levels of volatility in terms of the net foreign flows

of capital. Alfaro et al. (2005) and Waqas et al. (2015) explain that volatility of capital

flows increases in countries with higher inflation and inflation volatility rates as it reflects

unpredictable and distortionary monetary conditions.

Regarding the Exchange rate volatility results indicate a direct relationship between both

variables with a coefficient of 0.07. Volatility of exchange rate creates uncertainty about

the profits, by putting the investors into dilemma of how to infer these changes, by

restricting the international capital flows. Our results follow the empirical literature.

Gerardo and Felipe (2002) conceal that a stable exchange rate is essential to stabilize FDI

flows. Mercado and Park (2011) and Ullah Sami et al. (2012) explain that devaluation of

host country currency encourages the foreigners to invest due to higher return thereby

decreasing their volatility while higher exchange rate volatility increases the volatility of

capital flows.

Financial development provides more efficient risk diversification. More developed

financial system contributes to financial integration by attracting foreign investment. Our

results follow the empirical literature indicating an inverse relationship between financial

sector development and volatility of capital flows having coefficient 0.29. Chinn and Ito

(2006) provide empirical evidence that the benefits from financial integration are possible

only if financial system is well developed. Broner and Rigobon (2005), Broto et al. (2008)

and Mercado and Park (2011) explain that a developed financial system lessens the

instability of capital inflows. Countries with underdeveloped financial system experience

more volatile capital flows and also the risk of crises

Institutional quality plays an important role in reducing the volatility of capital flows.

Results show that a 1% increase in institutional quality index reduces the volatility of

capital flows by 0.13%. A strong legal system for financial transactions is especially


208

important. When the legal system in an economy does not clearly define the property

rights and guarantee the contract enforcement the incentives for credit activities become

limited. Legal safeties for creditors and the reliability and transparency of accounting

procedures are also likely to affect investor‟s financial decisions. Higher corruption

represents country specific risk and distorts the persistence of capital inflows. Corruption

may also weaken domestic financial system and increases the chance of a financial crisis.

Lambsdorff, J. G. (2003) explains that corruption reduces the persistence of capital flows

as investors prefer to export their capital to safe havens. Broto et al. (2008) explain that

economic and political stability reduces the volatility of portfolio flows. Broner and

Rigobon (2005) and Mercado and Park (2011) describe that institutional quality lowers the

volatility of capital flows. Beck Ronald (2001) finds that regulatory environment

represented by rule of law matters more than macroeconomic indicators in reducing the

volatility of capital flows.

Regarding the volatility of external factors our findings show that volatility of foreign

growth rate and interest rate reduces the volatility of capital flows. Literature also provides

the empirical evidence that changes in global economic conditions also bring changes in

capital flows to developing countries. Global conditions also work as push factors to

capital flows in developed countries. Demir Firat (2006), Neumann and Tanku (2009)

conclude that volatility of US interest rate and growth rate is inversely related to the

volatility of capital inflows to domestic market. By examining the volatility of different

type of capital flows in emerging economies Broto et al. (2008) explain that global

conditions significantly affect the volatility of portfolio and other investment flows but

less the FDI flows. Mercado and Park (2011) conclude that global factors significantly

contribute to volatility of capital flows.


209


Both the Sargan and serial correlation tests provide the evidence that instruments are valid

and there is no second order serial correlation and Wald test indicates the overall

significance of the model.


We conclude that there are some domestic and global factors that contribute to the

volatility of capital flows. Previous period‟s volatility increases the volatility in current

period by creating the uncertainty and risk on the part of investors. At higher level of

development there is expectation of less market distortions, information asymmetry and

moral hazard etc., hence capital flows will be less volatile. Inflation and exchange rate

volatility makes the investor‟s profits uncertain which increases the uncertainty of the

foreign capital flows. While the exchange rate stability is positively associated with

stability of capital flows. Financial market development reduces the volatility of capital

flows by providing more efficient risk diversification. Institutional quality plays an

important role to stabilize the capital flows. A strong legal system for financial

transactions and the reliability and transparency of accounting procedures affects the

investor‟s financial decision. Due to world integration and globalization changes in global

economic conditions also bring changes in capital flows to developing countries. External

shocks affect the volatility of capital flows in developing countries and work as push

factors.

5.3.4.4 Determinants of trade flows volatility:

Importance of trade flows in determining the competiveness of the economy is

incontestable. As a result of liberalization and world integration trade flows have become

responsive to changes in internal and global economic scenario and show frequent


210

changes, especially in less developed countries. We use volatility of exports to represent

trade flows as is common in empirical literature.

Previous period’s volatility increases the volatility of trade flows in current period. It

creates uncertainty on the part of investors regarding their profits. They delay their

investment decisions assuming that previous period‟s pattern of volatility will continue in

the current period. Results show that a 1% increase in GDP per capita reduces the

volatility of trade flows by 0.02%

GDP per capita indicates the level of development of the country. Results show that a 1%

increase in GDP per capita reduces the volatility of trade flows by 0.04%. Countries with

higher level of development exhibit lower volatility of trade flows due to less market

imperfections, more competitiveness, macroeconomic stability, exchange rate stability,

financial market stability and higher export diversification. Our findings are in line with

the previous literature Massell (1970), Aslam (1985) and Sarada et al. (2006).

Exchange rate is an important indicator of trade flows. Exchange rate volatility can affect

the trade both directly and indirectly. At the one hand it raises the uncertainty and

adjustment cost whereas on the other hand it deteriorates the production and investment

decisions. Results show a positive association between exchange rate instability and

export instability with a coefficient 0.12. Our findings are supported by empirical

literature. Baum and Caglayan (2009) provide the evidence of a positive association

between exchange rate uncertainty and volatility of trade flows. Many studies are available

that discuss the impact of exchange rate or its volatility on trade performance at levels

while empirical evidence regarding volatility of trade flows is scarce. Arize et al. (2000),

Chit et al. (2008), Demir (2012) and Khan (2014) all provide the evidence that exchange

rate uncertainty or volatility adversely affect the trade both export and import volumes in

developing and emerging economies.


211

Financial development relaxes the liquidity constraints facing by the firms. Economies

with developed financial sectors enjoy comparative advantage in sectors with high scale

economies. Firms are more likely to export when they enjoy lower credit constraints and

higher productivity levels. Credit constraints also matter for export patterns therefore

literature supports that financial development promotes the production and trade. Our

results support the empirical findings and show a negative relationship between financial

development and exports instability also supported by Beck (2002; 2003) and Hur et al.

(2006).

Regarding export concentration our results show that a 1 % increase in the export

concentration index increases the volatility or instability of exports by 0.08%. A country

with a large share of its exports by producing a single good or closely related goods

experience more instability in exports than a country with diversified export base. Higher

the diversification, the larger the number of goods a country exports, the more evenly

resources are spread over the different goods which reduces the instability. Our results are

supported by empirical literature. Massell (1970), Sheehey (1977), Aslam (1985), Sarada

et al. (2006) and Neena (2015) provide the empirical evidence that there is higher export

concentration in developing countries which increases the instability of exports.

Findings show a1% increase in institutional quality index decreases the volatility of trade

flows by 0.16%. Institutions increase the transparency of trading system through greater

predictability which reduces the trading cost. Besides their direct effect institutions also

indirectly affect the trade through their effect on investment and productivity. Sound

regulation, efficient administration, low corruption and effective law enforcement

facilitate the trade flows. Contract enforcement, property rights and investor protection

also matter by allowing the investors to overcome distortions. Our findings are supported

by empirical literature. Anderson and Marcouiller (2002), Groot et al. (2004), Levchenko


212

(2007) and Helble et al. (2007) provide the evidence that institutional quality (contract

enforcement, secured property rights, shareholder protection and the like) and quality of

governance determine the bilateral trade flows between the countries. Moreover higher

transparency of the trading system has an important impact on trade costs in developed

and developing countries.

Access to external market has exposed less developed countries to volatilities prevalent in

the global market. These volatilities have significant impact on country‟s trade flows.

Global financial crisis of 2008 provides the evidence of shortage of finance for trade

because of bankruptcy of financial institutions which also increased the cost of capital by

lowering the trade volume. Moreover global crises resulted in significant change in

countries‟ terms of trade. Our results show that external shocks positively affect the

volatility of trade flows. Foreign growth volatility and term of trade volatility increase the

volatility of trade flows by 0.07% and 0.85% respectively. Shelburne (2010) examine the

effect of global financial crisis of 2007-10 on the world and European emerging

economies. Crisis severely affected the trade of the European emerging economies and the

world as the terms of trade deteriorated significantly.


Sargan test and serial correlation test provide the evidence of reliability of instruments and

no higher order serial correlation respectively while Wald test provides the evidence of

overall significance of the model.

5.3.4.4.2 Concluding remarks

There are certain domestic and global factors that are responsible for the volatility of trade

flows. Previous period‟s volatility increases the volatility of trade flows in current period

by creating uncertainty on the part of investors regarding their profits. Higher the level of

development lower the volatility of trade flows due to less market imperfections, more


213

competitiveness, macroeconomic stability, exchange rate and financial market stability

and more diversified exports. Exchange rate volatility positively affects the volatility of

international trade flows. at the one hand it raises the uncertainty and adjustment costs and

on the other hand it deteriorates the production and investment decisions. Financial sector

development relaxes the liquidity constraints facing by the firms and reduces the volatility

of trade flows. Economies with developed financial sectors enjoy comparative advantage

in sectors with high scale economies. Higher export concentration increases the volatility

of trade flows. A country with a large share of its exports by producing a single good or

closely related goods experience more instability in exports than a country with diversified

export base. Institutions increase the transparency of trading system through greater

predictability which reduces the trading cost. Sound regulation, efficient administration,

low corruption and effective law enforcement facilitate the trade flows. Access to external

market has exposed less developed countries to volatilities inherent in the global market.

These volatilities have significant impact on country‟s trade flows.

214

Conclusions and Policy Recommendations

This chapter discusses the summary of the whole thesis moreover it also draws some

important policy recommendations based on empirical findings and last it discusses the

limitations of the study and provides the direction for future research. First section

discusses the conclusions of the study, second section discusses important policy

recommendations and last section discusses limitations and future research directions.

6.1 Conclusions:

Policy failures in many developing countries were caused by weak institutions structure;

the failure of price reform and privatization in Russia, failure of market-oriented reforms

in Latin America and the financial crisis of Asia were all the results of the lack of helpful

legal, regulatory and political framework. Moreover the monetary transmission

mechanism is weak in developing countries due to weak monetary, financial and fiscal

institutions. Government finances in many developing countries are also weak which lead

to high deficits, debts and debt-servicing obligations. The lack of political stability and an

inefficient bureaucracy allow rent-seeking to continue. Financial sector distortions have

historically lead to financial crises. All it provides the rationale for the importance of

institutions and their strengthening in developing countries for policy effectiveness. The

second generation reforms focus on restructuring the state and institutions.

Given the importance of institutions this study tries to discover the relatively unexplored

areas on the relationship between institutions, policies and economic growth. As there is

extensive literature so far on institutions-growth relationship as well as macroeconomic

policies-growth relationship therefore the study contributes by filling the gap on

Chapter # 6

Chapter # 6 Conclusions and Policy Recommendations

215

institutions-policies link for developing countries specifically the role of institutions in

reducing policy instability. Choice of the countries is based on the governance status or

percentile rank of the countries provided by the World Bank, World Governance

Indicators. Choice of the time period is relevant to policy initiatives in developing as an

agenda of neoliberal approach. Our empirical analysis employs annual data for a set of 12

developing countries, according to the World Bank classification, from South Asia, East

Asia and Pacific, Latin America and Sub Saharan Africa. The sample period spans from

1990–2014. In the light of motivation and significance of the study there are three main

objectives and also sub objectives. Main objectives discuss the role of policies (both

stabilization and liberalization policies) and institutions on economic growth. In addition

to the level effect of domestic macroeconomic policies on economic growth the study also

evaluates the volatility effect and last the indirect effect of institutions on economic

growth through reducing the policy instability or volatility which contributes to the

literature as an unexplored area.

First chapter discusses background and motivation of the study, review of institutions

and policies in developing countries which establishes an institution policy link,

significance and contribution and objectives of the study, which we have already discussed

above in a summarized way.

Second chapter discusses the review of theoretical and empirical literature according to

our objectives. Moreover it also discusses the unexplored areas regarding institutional

policy link.

Third chapter provides an overview of the economies of selected countries. It also

discusses the dynamics of their institutions and policies and institutional reforms in

developing countries. It provides a view of different indicators representing institutional

quality, stabilization and liberalization policies for selected countries which delivers the


216

dynamics of these indicators. We have discussed the volatility of fiscal, monetary and

liberalization policies for each country. We have also discussed the cyclical behaviour of

fiscal and monetary policy and also of FDI and portfolio inflows as literature discusses

that one of the reasons for high volatility of these policies is their procyclical behaviour in

most developing countries.

Fourth chapter discusses the derivation of theoretical model, description of variables and

methodology. We have derived a dynamic panel data model to study the role of

institutions and policies in economic growth, following Mankiw et al. (1992), in the

empirics of neoclassical growth model. Derived model shows the effect of institutions and

policies (stabilization and liberalization policies) on economic growth along with

traditional factors and convergence. We have further manipulated our equation according

to our objectives.

Main sources of the data are the World Bank (World Development Indicators),

International Financial Statistics (IFS), Pen World Tables (8.0), Asian Development Bank

(ADB), World Governance Indicators (WGI), Chinn and Ito (2008) and Lane and Ferretti

(2007).

Considering the unobserved country specific effects and econometric problems related to

the possible endogeniety of explanatory variables with the growth we use dynamic panel

data GMM method of estimators developed by Holtz-Eakin, Newey, and Rosen (1988),

Arellano and Bond (1991), and Arellano and Bover (1995).

Fifth chapter provides the detailed empirical results and discussion. Before the empirical

estimation we have tested the reliability of the data through descriptive statistics.

Moreover the pair wise correlation explains the linear relationship between two variables.

We have also tested the stationarity properties of the data through Im, Pesaran and Shin


217

(IPS) test. Regarding the empirical results of GMM we explain these according to our

objectives below.

6.1.1 Effect of institutions and policies on economic growth:

To fulfill our first objective we examine empirically the effect of institutions and policies

on economic growth. The result provides the evidence of conditional convergence.

Traditional growth variables; physical and human capital and population growth also

follow the empirical literature. Physical capital increases the growth rate by increasing the

economic activities. Human capital affects the economic growth through quality

improvements in labour. Population growth reduces the economic growth by increasing

the consumption and reducing the savings. Institutional quality promotes the economic

growth by creating an environment for capital creation. Results regarding the fiscal policy

support the Keynesian hypothesis. Capital expenditures positively contribute to economic

growth by providing necessary infrastructure for the encouragement of private sector

investment. Current expenditures adversely affect the economic growth by reducing the

incentive for investment, higher tax-finance outweighs the utility derived from it. Tax

revenues also positively affect the economic growth by increasing the ability of the

government to finance its expenditures. Results regarding the monetary policy support the

Monetarists hypothesis, monetary policy do affect the economic growth through aggregate

demand. Results show that contractionary monetary policy reduces the investment and

economic growth. Trade liberalization positively contributes to economic growth. Trade

openness as a proxy of trade liberalization positively affects the economic growth through

externality as common in the literature. Reduction in the tariff rate also positively

contributes to economic growth. Disaggregated analysis shows that liberalization of

capital goods increases the economic growth by stimulating the investment while

liberalization of consumer goods is unrelated to economic growth. Regarding the financial


218

liberalization both De jure and De facto measure show that it negatively affects the

economic growth. In developing countries financial liberalization increases the risk of

crisis. Additionally large and unanticipated inflows induce higher consumption, inflation

and unmanageable current account deficits. Disaggregated analysis shows that FDI

inflows positively contribute to economic growth being long term and stable investment

while short term investment (portfolio equity and debt) negatively contribute to economic

growth due to higher reversal rate.

6.1.2 Disaggregated institutions:

Disaggregated analysis of institutional variables show that higher economic and political

freedom increases the rate of private investment, productivity and growth. Political

stability is unrelated to economic growth as political stability alone cannot affect

economic growth without institutional set up and government development strategies.

There is direct association between improved quality of government services and

economic growth. Regulatory quality is also positively related to economic growth.

Through regulatory framework state affects the performance of the private sector. Rule of

law and economic growth are also positively related. A better judicial system fosters the

economic growth by enforcing the property rights which are necessary for the increase in

private investment, moreover it keeps the checks and balances on the government, controls

the corruption. Corruption retards the economic growth because it reduces the efficient

allocation of resources.

6.1.3 Effect of policy volatility on economic growth:

Our second objective evaluates the link between policy volatility and economic growth.

Results show that volatility of domestic macroeconomic policies brings uncertainty

regarding investment decisions therefore reducing the growth. Volatility makes the

investors highly sensitive to policy change and the associated risks because of irreversible


219

nature of certain investments. Volatility of the fiscal policy creates uncertainty about

future taxes and the future behavior of fiscal parameters which negatively affects the

behavior of economic agents. Uncertainty of the interest rate affects the firm’s profitability

by reducing the corporate investment especially when there is irreversibility. Access to the

external market has destabilized the economies of less developed countries because of

volatility associated with trade and capital flows. Volatility of both negatively affects the

economic growth by reducing the domestic and foreign investment.

6.1.4 Determinants of policy volatility:

Our last objective is to emphasize on the role of institutions in enhancing the policy

stability. Institutions play an important role to reduce policy volatility by putting controls

or check and balances on policy makers and providing an environment favorable to good

policies. Regarding the fiscal policy volatility institutional constraints make it difficult for

the governments to frequently change the policy. Regarding monetary policy volatility an

independent central bank can provide more consistent policy by reducing the uncertainty,

in addition to lower inflationary outcome. Furthermore, high institutional quality enables

countries to apply counter-cyclical monetary and fiscal policies. As for as the volatility of

capital flows is concerned it is argued that low institutional quality has less ability to deal

with economic shocks. High institutional quality enables countries to stabilize financial

markets and capital flows. Good institutions make the trade flows stable through greater

predictability which reduces the trading cost. Sound regulation, low corruption and

effective law enforcement facilitate the trade flows.

Above and beyond the institutions there are some other domestic and global factors that

affect the volatility of domestic macroeconomic policies; these include per capita income

which embodies the level of development of a country, inflation volatility which

represents the macroeconomic uncertainty, financial sector development work as shock


220

absorber, external debt, exchange rate instability, export concentration and some external

factors which include foreign growth volatility, term of trade volatility and foreign interest

rate volatility.

Higher the level of development lower the volatility of domestic macroeconomic policies

due to less market imperfections, macroeconomic stability, exchange rate and financial

market stability, larger automatic stabilizers and independence of the central bank etc.

Higher inflation volatility makes the domestic macroeconomic policies more volatile.

Higher external debt increases the volatility of fiscal policy inducing large fiscal

adjustment. Fiscal deficits and debt lead towards high and volatile inflation therefore

making monetary policy more volatile. Exchange rate instability makes the profits

uncertain which increase the uncertainty of the foreign capital flows and trade flows.

Financial market development reduces the volatility of capital flows by providing more

efficient risk diversification. Financial sector development also relaxes the liquidity

constraints facing by the firms and reduces the volatility of trade flows. Higher export

concentration increases the volatility of trade flows. A country with a large share of its

exports by producing a single good or closely related goods experience more instability in

exports than a country with diversified export base. World integration has increased the

exposure of lees developing countries to volatilities of global market. Access to external

market has exposed developing countries to volatilities prevailing in the world market.

These volatilities significantly affect the macroeconomic policies of the countries.

6.2 Policy recommendations:

The results presented in this study emphasize the importance of sensible long run growth

oriented policies. The important policy recommendations that stems from our analysis are

regarding the role of institutional quality, fiscal and monetary policies, trade and financial

liberalization in economic growth. Moreover, as we have also addressed the issue of


221

policy volatility in developing countries so we will also discuss some policy implications

regarding policy volatility or uncertainty. Keeping in view the findings of the study we

propose some specific policy recommendations.

6.2.1 Institutions:

The subject matter of good governance and institutional reforms received attention in

developing countries in 1990s due to emergence of political and economic disorders.

Moreover increased globalization has raised the need for transparent, efficient and

responsive institutions. Institutional reforms lead to restructuring state institutions so that

they respect human rights, rule of law and are accountable to their constituents. To

encourage the private investment it is the responsibility of the state to create a suitable

legal and economic environment that ensure protection of property rights, strong judiciary

and improved transparency. There is also a role of external support as the World Bank and

the IMF are giving a great deal of attention to issues concerning the governance and

institutions. Regarding the institutional reforms it is needed to divide the reform areas into

basic and advanced reforms49

. The objective is to provide the guideline to authorities

towards the choice of a few specific areas in which reform would be both beneficial and

practicable given the political, institutional and capacity constraints facing the countries.

6.2.2 Fiscal policy:

Findings regarding government expenditures lead to the implication that given the

resource constraint a reallocation of government expenditures from current to capital

expenditures will increase the economic growth. It is needed to formulate the expenditures

such as to reduce the unproductive expenditures while enhancing public investment.

Developing countries already lack infrastructure like transport and communications, roads,

railways, electricity, gas etc. that help promote private capital accumulation. The

49 So-called “platform approach” proposed by Brooke (2003).


222

government should increase its investment in areas that facilitate the private sector and

avoid from those that crowd it out. It is also argued that with capital expenditures there

comes rent seeking while current expenditure have less probability of this as these are on

fixed outlays. Institutional checks and balances can prevent this rent seeking behavior. As

tax revenue significantly contributes to economic growth therefore if a government wishes

to increase its revenue it should reduce the tax evasion and greater emphasis on collection

moreover to increase the tax base by reducing the tax exemptions.

6.2.3 Monetary policy:

Through its stabilizing role monetary policy plays a significant role in the welfare of an

economy. The interest rate channel of the monetary policy transmission mechanism

associates the fluctuations in in monetary aggregates to the economy. An expansionary

monetary policy decreases the financial constraints of private enterprises thus encouraging

the private investment. However, the financial redundancy following from expansionary

monetary policy leads to inefficient or unproductive investments by private enterprises;

investment in luxury consumer goods, real estate, gold and jewellery etc. Policy makers

should focus on improving corporate investment efficiency and to avoid over-investment.

Continuous fluctuations in interest rate bring uncertainty about return on investment and

may also decrease the confidence of investors.

6.2.4 Trade liberalization:

The policies should be emphasized towards more free trade and the abolition of trade

barriers. Corruption and rent-seeking associated with trade interventions can be reduced

with a free-trade regime. This will make the trade and investments opportunities more

attractive in a country. The government has to focus on motivating the development

through technology transfers to high growth sectors in developing countries because low

growth sectors have very little potential of productivity growth. Primary objective of


223

relaxing the trade barriers should be to encourage the exports of less developed countries.

Liberalizing the imports of capital goods will increase the industrial efficiency and also the

manufacture exports.

6.2.5 Financial liberalization:

Given the harmful consequences of financial liberalization there is need to adopt

restrictive policy. Relative restrictive capital account regime of India and China provided

the protection against the East Asian crisis in 1997. The Indian policy placed emphasis on

encouraging larger non-debt flows, particularly foreign direct investment and longer-

maturity debt flows while having restrictions on short-term capital flows. Controls on

capital inflows can also serve to stabilize outflows. While discussing the effectiveness of

controls on inflows, there is also evidence of Chilean experience. During 1978-82 Chile

has imposed tax on short-term inflows which has stabilized these flows, without any

harmful effects on long-term flows of productive capital. The main purpose of the control

is to slow down the size of capital inflows and to change the structure of capital inflows

towards longer maturities. Certain pre conditions are also required to stabilize the capital

flows; a stable exchange rate policy, macroeconomic stability and a better institutional

framework which ensures transparency and accountability, regulatory quality and rule of

law. The Asian crisis highlighted the importance of the financial system.

6.2.6 Policy volatility:

As described in previous chapter that developing countries are more volatile and there are

three sources of their volatility first, the domestic factors or shocks second, exogenous

shocks and last, weak shock absorbers due to which exogenous factors have strong

influence on their macroeconomic volatility. Findings imply that domestic policy induced

volatility or uncertainty can be reduced by reducing macroeconomic instability indicated

by inflation volatility, achieving the exchange rate stability, higher export diversification,


224

controlling the external debt or deficit, increasing the level of income and improving the

institutional quality. External shocks are beyond the control of domestic economies but

their affect can be minimized by strengthening the economy’s shock absorbers, stable

macroeconomic policies and improved financial sector.

As our central concern is related to the role of institutions in reducing policy volatility

therefore there is need of strong fiscal, monetary and economic institutions. Fiscal

institutions put constraints on the governments and generate the fiscal policy which is

highly predicable. Monetary institutions provide more consistent policy in addition to

lower inflationary outcome. Sound regulation, low corruption and effective law

enforcement stabilize the financial and trade flows.

6.3 Limitations and future research directions:

All the studies have some limitations which should be regarded while explaining the

results and present study is no exception. Limitations will provide some directions for

future research. Like in most empirical studies there are the issues of the quality or

reliability of data which can affect the reliability of results. There is limitation of the data

of institutional quality, which is subjective and more prone to measurement error as it

depends upon the rating of experts. Subjective measures of capital account liberalization,

de jure measures, also increase the possibility of measurement error. Regarding

institutional quality variable we have considered only formal institutions while ignoring

the informal institutions thus by allowing the other category of institutions will provide the

significance of each in economic growth. Regarding fiscal policy indicator we have

disaggregated the government expenditures by type not by function which can provide a

more comprehensive analysis regarding each functional category. Moreover we have also

taken total tax revenue as an indicator of fiscal policy. We can further disaggregate the tax

into its direct and indirect tax components which will provide the significance of different


225

taxes in economic growth. Regarding the effect of capital account liberalization on

economic growth the study can also test the hypothesis about sequencing of capital

account by introducing the interaction term regarding trade openness, financial

development, institutional quality, level of development etc. to determine the most

effective channel of capital account liberalization. Regarding monetary policy we have

used interest rate as one of the channel of monetary transmission mechanism. We can also

include other channels of monetary transmission mechanisms to determine the most

reliable one. Regarding the data of physical capital stock we have used gross fixed capital

formation of the private sector which is commonly used in the literature. We can improve

our study in the future by using capital stock itself. We could update our data set including

more countries. Study can be extended by adding different regions which will provide

more insight on the comparative significance of alternative government policies in

different regional context. Last, we could also apply additional estimation methods

commonly used in empirical literature for robustness analysis.

It is not possible to include everything in a single study hence limitations are definite. By

incorporating these limitations we can further extend the study in future.

226

References

Abaidoo, R. (2012). Macroeconomic Volatility and Macroeconomic Indicators among

Sub-Saharan African Economies. International Journal of Economics and Finance,

4(10), 1- 14.

Acosta Ormaechea, S., and Morozumi, A. (2013). Can a Government Enhance Long-Run

Growth by Changing the Composition of Public Expenditure? IMF Working Papers,

WP/13/162.

Acosta-Ormaechea, S. and J. Yoo. (2012). Tax Composition and Growth: A Broad Cross-

Country Perspective. IMF Working Paper 12/257. Washington, DC: International

Monetary Fund.

Afonso, A., and Furceri, D. (2008). Government Size, Composition , Volatility and

Economic Growth. European Central Bank, Working Paper No.849.

Afonso, A., and Jalles, T., J. (2012). Fiscal Volatility, Financial Crises and Growth.

School of Economics and Management, Technical University of Lisbon. WP

06/2012/DE/UECE.

Aggarwal, M. R. (1982). Export Earning Instability and Economic Development in Less

Developed Countries: A Statistical Verification. Indian Economic Journal, 29, 60-70.

Agnello, L., and Sousa, R. (2009). The Determinants of Public Deficit Volatility.

University of Palermo, Department of Economics, Business and Finance, Italy.

____________________ (2014). The Determinants of the Volatility of Fiscal Policy

Discretion. Fiscal Studies, 35(1), 91–115.

Ahmad, M., and Marwan, F.N. (2012). Economic Growth and Institutions in Developing

Countries: Panel Evidence. Munich Personal RePEc Archive, MPRA Paper No.

42293.

Ahmad, S. (2010). The Long-Run Fisher Effect in Developing Economies. Studies in

Economics and Finance, 27(4), 268–275.

Aiello, F., and Scoppa, V. (2005). Convergence and Regional Productivity Divide in Italy :

Evidence from Panel Data. University of Calabria, Department of Economics and

Statistics.

Aisen, A., and Hauner, D. (2008). Budget Deficits and Interest Rates: A Fresh Perspective.

IMF Working Paper. WP/08/42.

Aizenman, J., and Marion, N. (1991). Policy Uncertainty, Persistence and Growth.

NBER Working Paper No. 3848.

Alam, S., A. Sultana, and M. Butt. (2010). Does Social Expenditure Promote Economic

Growth? A Multivariate Panel Cointegration Analysis for Asian Countries. European

Journal of Social Sciences, 14 (1), 44–54.

227

AlBassam, B. A. (2013). The Relationship between Governance and Economic Growth

during Times of Crisis. European Journal of Sustainable Development, 1–18.

Albuquerque, B. (2010). Fiscal Institutions and Public Spending Volatility in Europe.

Banco de Portugal, Working Papers 17/2010.

Alesina, A. F., Grilli, V., and Milesi-Ferretti, G. M. (1993). The Political Economy of

Capital Controls. NBER Working Paper Series.

Alfaro, L., Kalemli-Ozcan, S., and Volosovych, V. (2005). Capital Flows in a Globalized

World: The Role of Policies and Institutions, NBER Working Paper No. 11696.

Ali, M. Abdiweli. (2005). Fiscal Policy and Economic Growth: The Effect of Fiscal

Volatility. Journal of Business and Economics Research, 3(5), 17-28.

Ali, S., and Ahmad, N. (2010). The Effects of Fiscal Policy on Economic Growth: Time

Series Evidenc from Pakistan. The Pakistan Development Review, 49(4), 497–512.

Ali, S., Irum, S., and Ali, A. (2008). Whether Fiscal Stance or Monetary Policy is

Effective for Economic Growth in Case of South Asian Countries? The Pakistan

Development Review, 47(4), 791–799.

Alvarez, Luis HR, Vesa K., and Jan S. (1998). Tax Policy Uncertainty and Corporate

Investment: A Theory of Tax-Induced Investment Spurts. Journal of Public

Economics, 69 (1), 17-48.

Anderson, J., and D. Marcouiller (2002). Insecurity and the Pattern of Trade: An

Empirical Investigation. The Review of Economics and Statistics, 84, 342-352.

Andrews, D., and Daniel R. (2009). Macroeconomic Volatility and Terms of Trade

Shocks. Reserve Bank of Australia, Research Discussion Paper 2009-05.

Arellano, M., and Bond, S. (1991). Some Tests of Specification for Panel Data: Monte

Carlo Evidence and an Application to Employment Equations. The Review of

Economic Studies, 58 (2), 277-297.

Arellano, M., and Bover, O. (1995). Another Look at the Instrumental Variable Estimation

of Error Components Models. Journal of Econometrics, 68(1), 29–51.

Arize, A. C., Osang, T., and Slottje, D. J. (2008). Exchange-Rate Volatility in Latin

America and its impact on Foreign Trade. International Review of Economics and

Finance, 17(1), 33–44.

_______________________________ (2000). Exchange-rate Volatility and Foreign

Trade: Evidence from Thirteen LDCs. Journal of Business and Economic Statistics,

18, 10-17.

Arnott, R., Greenwald, B., and Stiglitz, J., E. (1994). Information and economic

efficiency. Information Economics and Policy, vol. 6(1), 77-82.

228

Arteta, C., B. Eichengreen, and C. Wyplosz (2001). When Does Capital Account

Liberalization Help More than It Hurts? National Bureau of Economic Research,

Cambridge.

Aslam, N. (1985). Export Instability, Growth and Concentration in Pakistan: A Time

Series Analysis. Pakistan Institute of Development Economics Islamabad, Research

Report Series No. 143.

Azman-Saini, W. N., Baharumshah, A., Z. and Law, S., H. (2010). Foreign Direct

Investment, Economic Freedom and Economic Growth: International Evidence.

Economic Modelling, 27 (5), 1079–89.

Badinger, H. (2008). Cyclical Fiscal Policy, Output Volatility , and Economic Growth.

CESIFO Working Paper NO. 2268.

Baker, S. R., Bloom, N., and Davis, S. J. (2012). Measuring Economic Policy Uncertainty.

AEA Annual Meeting Working Paper, 1–57.

Baldacci, E., Clemens, B., Gupta, S., and Mulas-Granados, C. (2002). Expenditure

Composition, Fiscal Adjustment and Growth in Low Income Countries. IMF

Working Paper, WP/02/77.

Ball, C. a, and Torous, W. N. (1999). The Stochastic Volatility of Short-Term Interest

Rates: Some International Evidence. Journal of Finance, 54(6), 2339–2359.

Barro, J. R., and Sala-i-Martin, X. (2004). Economic Growth.

Barro, R. J. (1989). A Cross-Country Study of Growth, Saving, and Government. NBER

Working Paper Series (Vol. w2855).

_________ (1991). Economic growth in a cross section of countries. Quarterly Journal of

Economics, 106(2), 407.

Barro, R. R. J., and Lee, J. J.-W. (1993). International Comparisons of Educational

Attainment. Journal of Monetary Economics, 32, 363-394.

Barro, R.J. and Sala-I-Martin, X. (1991). Convergence across States and Regions.

Brookings Papers on Economic Activity, 22(1), 107-182.

_________________________ (1992). Convergence. Journal of Political Economy

100(2), 223-251.

__________________________(1997). Technological Diffusion, Convergence, and

Growth. Journal of Economic Growth, 2(1), 1-26.

Baum, C., and Caglayan, M. (2009). The Volatility of International Trade Flows and

Exchange Rate Uncertainty. Department of Economics, Boston College, USA.

Beck, R. (2001). The volatility of capital flows to emerging markets and the financial

services trade. Russian and East European Finance and Trade, 37(3), 5–24.

229

Beck, T. (2002). Financial Development and International Trade: Is There a Link? Journal

of International Economics, 57, 107–131.

_______ (2003). Financial Dependence and International Trade. Review of International

Economics, 11, 296–316.

Bekaert, G., C. R. Harvey and C. Lundblad (2001). Does Financial Liberalization spur

Growth? NBER Working Paper 8245, National Bureau of Economic Research,

Cambridge.

__________________________________ (2005). Does financial liberalization spur

growth? Journal of Financial Economics, 77(1), 3–55.

Ben-David, D. (1993). Equalizing Exchange: Trade liberalization and Income

Convergence. Quarterly Journal of Economics, 108(3).

Bernanke, B. S., Boivin, J., and Eliasz, P. (2005). Measuring the Effects of Monetary

Policy. Quarterly Journal of Economics, 120, 387–422.

Berument, H., and Malatyali, K. (2001). Determinants of Interest Rate in Turkey. Russian

and East European Finance and Trade, 37 (1), 5-16.

Berument, H., Ceylan, N. B., and Olgun, H. (2007). Inflation Uncertainty and Interest

Rates: Is the Fisher Relation Universal? Applied Economics, 39(1), 53–68.

Bhagwati, J. (1998). The Capital Myth: The Difference Between Trade in Widgets and

Trade in Dollars. Foreign Affairs, 77, 7-12.

Bhattacharjee, J., and Kr, S. (2015). Economic Growth of Selected South Asian countries:

Does Institution Matter? Asian Economic and Financial Review, 5(2), 356–370.

Blanchard, Olivier and Roberto Perotti (2002). An Empirical Characterization of the

Dynamic Effects of Changes in Government Spending and Taxes on Output.

Quarterly Journal of Economics, 117(4), 1329-1368.

Bleaney, M., Halland, H., and Bleaney, M. F. (2009). The Resource Curse and Fiscal

Policy Volatility, CREDIT Research Paper No. (09).

Bloom, N., Bond, S., and Reenen, V., J. (2007). Uncertainty and Investment Dynamics,

Review of Economic Studies, 74, 391–415.

Blundell, R., and Bond, S. (1998). Initial Conditions and Moment Restrictions in Dynamic

Panel Data Models. Journal of Econometrics, 87(1), 115–143.

Bo, H., and Sterken, E. (2002). Volatility of the Interest Rate, Debt and Firm Investment:

Dutch Evidence. Journal of Corporate Finance, 8(2), 179–193.

Bogdan Bogdanov (2014). Liberalized Capital Accounts and Volatility of Capital Flows

and Foreign Exchange Rates. European Economy. Economic Papers 521.

230

Bonfiglioli., A. (2005). How Does Financial Liberalization affects Economic Growth?

Seminar Papers 736, Stockholm University, Institute for International Economics

Studies.

Bose, N., H. M. Emranul, and D. R. Osborn. (2007). Public Expenditure and Economic

Growth: A Disaggregated Analysis for Developing Countries. The Manchester

School, 75 (5), 533–556.

Bosworth, B. P. (2014). Interest Rates and Economic Growth: Are They Related? Journal

of Chemical Information and Modeling, 53(9), 1689–1699.

Bosworth, B., and Collins, S. M. (2003). The Empirics of Growth: An Update. Brookings

Papers on Economic Activity, (2), 113–206.

Bretscher, L., Schmid, L., and Vedolin, A. (2016). Interest Rate Uncertainty , Hedging ,

and Real Activity. Arne Ryde Finance Workshop, the CEPR ESSFM in Gerzensee

Broner, F., and R. Rigobon (2005). Why are Capital Flows so Much More Volatile in

Emerging than in Developed Countries? Central Bank of Chile Working Papers No.

328.

Brooke, P., (2003). Study of Measures Used to Address Weaknesses in Public Financial

Management in the Context of Policy-Based Support. Final report for the Public

Expenditure and Financial Accountability (PEFA) Secretariat (Washington: PEFA

Secretariat).

Broto, C., Diaz-Cassou, J., and Erce- Domínguez,, A. (2011). Measuring and explaining

the volatility of capital flows to emerging countries. Journal of Banking and Finance,

35(8), 1941–1953.

Buigut , S., (2009). Monetary Policy Transmission Mechanism: Implications for the

Proposed East African Community (EAC) Monetary Union. mimeo.

Burdekin, Richard C. K., King Banaian, Mark Hallerberg and Pierre L. Siklos (2011).

Fiscal and Monetary Policy Institutions and Policies: Onward and Upward? Journal

of Financial Economic Policy, 3 (4), 340-354.

Campos, N. F., and Nugent, J. B. (1999). Development Performance and the Institutions of

Governance: Evidence from East Asia and Latin America. World Development,

27(3), 439- 452.

Carp, L. (2014). Financial Globalization and Capital Flows Volatility Effects on Economic

Growth. Procedia Economics and Finance, 15(14), 350–356.

Caselli, F., Esquivel, G., and Lefort, F. (1996). Reopening the Convergence Debate: A

New Look at Cross-Country Growth Empirics. Journal of Economic Growth, 1(3),

363–389.

Cass David (1965). Growth in an Aggregative Model of Capital Accumulation. The

Review of Economic Studies, 32 (3), 233-240.

231

Cellini, R. (1997). Growth Empirics: Evidence from a Panel of Annual Data. Applied

Economic Letters, 4, 347-351.

Chakraborty, L., S. (2012). Interest Rate Determination in India: Empirical Evidence on

Fiscal Deficit – Interest Rate Linkages and Financial Crowding Out. Levy Economics

Institute of Bard College. Working Paper No. 744.

Chan, K. C., Karolyi, G. A., Longstaff, F. A., and Sanders, A. B. (1992). An Empirical

Comparison of Alternative Models of the Short-Term Interest Rate, Journal of

Finance, 52 (1), 209–227.

Chang, R., Kaltani, L., and Loayza, N. V. (2009). Openness can be good for growth: The

role of policy complementarities. Journal of Development Economics, 90(1), 33–49.

Charette, M., F. (1985). Determinants of Export Instability in the Primary Commodity

Trade of LDC‟s. Journal of Development Economics, 18, 13-21.

Chaudhary, M. A., and Qaisrani, A. A. (2002). Trade Instability , Investment and

Economic Growth in Pakistan. Pakistan Economic and Social Review, 40(1), 57–73.

Cheng, K. C. (2006). A VAR Analysis of Kenya‟s Monetary Policy Transmission

Mechanism: How Does the Central Bank's REPO Rate Affect the Economy? IMF

Working Papers.

Chinn, Menzie D. and Hiro Ito (2006). What Matters for Financial Development? Capital

Controls, Institutions, and Interactions. Journal of Development Economics, 81(1),

163-192.

_________________________ (2008). A New Measure of Financial Openness. Journal of

Comparative Policy Analysis, 10 (3), 309 – 322.

Chit, M. M., Rizov, M., and Willenbockel, D. (2008). Exchange Rate Volatility and

Exports: New Empirical Evidence from the Emerging East Asian Economies. Munich

Personal RePEc Archive (MPRA), (MPRA Paper No. 9014).

Chong, A., and Zanforlin, L. (2004). Inward-Looking Policies, Institutions, Autocrats, and

Economic Growth in Latin America: An Empirical Exploration. Public Choice,

121(3-4), 335–361.

Choong, C., Liew, V., Chan, S., and Chang, H. (2011). Foreign Direct Investment

Volatility and Economic Growth In Asean-Five Countries. International Journal of

Academic Research, 3(4), 221–224.

Christian Bjornskov( 2015). Does Economic Freedom Really Kill? On the Association

between „Neoliberal‟ Policies and Homicide Rates. European Journal of Political

Economy, 37, 207–219.

Christiano, j., L., Eichenbaum, M., and Evans, C. (1996). The Effects of Monetary Policy

Shocks: Evidence of the Flow of Funds. The Review of Economics and Statistics,

78(1), 16-34.

232

Claeys, P., Moreno, R., and Surinach, J. (2012). Debt, Interest Rates, and Integration of

Financial Markets. Economic Modelling, 29(1), 48–59.

Coric, B., Perovic, M., L. and Simic, V. (2012). Monetary Policy Effects on Output and

Prices  International Evidence. University of Split.

Crowley, J. (2007). Interest Rate Spreads in English-Speaking African Countries. IMF

Working Paper No. 07/10.

Cukierman, A. (1992). Central Bank Strategy, Credibility, and Independence. Cambridge,

MIT Press.

Dalgaard, C. J., and Strulik, H. (2013). The History Augmented Solow Model. European

Economic Review, 63, 134–149.

De Groot, H. L. F., Linders, G.-J., Rietveld, P. and Subramanian, U. (2004). The

Institutional Determinants of Bilateral Trade Patterns. Kyklos, 57, 103-123.

De Vaal, A., and Ebben, W. (2011). Institutions and the Relation between Corruption and

Economic Growth. Review of Development Economics, 15(1), 108–123.

Dean, J., Desai, S., and Riedel, J. (1994). Trade Policy Reform in Developing Countries

Since 1985: A Review of the Evidence. World Bank Discussion Paper, Number 267.

Demir, F. (2006). Volatility of Short Term Capital Flows and Socio-Political Instability in

Argentina, Mexico and Turkey. MPRA Paper No. 1943.

_______ (2009). Volatility of Short-term Capital Flows and Private Investment in

Emerging Markets. Journal of Development Studies, 45(5), 672-692.

Devarajan, S., V. Swaroop, and H. Zou. (1996). The Composition of Public Expenditure

and Economic Growth. Journal of Monetary Economics, 37 (2), 313–344.

Dollar, D. (1992). Outward-Oriented Developing Economies Really Do Grow More

Rapidly: Evidence from 95 LDCs, 1976-85. Economic Development and Cultural

Change, 523-544.

Dollar, D., and Kraay, A. (2004). Trade, Growth, and Poverty. The Economic Journal,

114(493).

Dreher, A., Sturm, J.-E., and Haan, J. De. (2010). When is a central bank governor

replaced? Evidence based on a new data set. Journal of Macroeconomics, 32(3), 766–

781.

Drury, A. C., Krieckhaus, J. and Lusztig, M. (2006). Corruption, Democracy and

Economic Growth. International Political Science Review, 27( 2), 121 – 136.

Duncan, R. (2013). Institutional Quality, the Cyclicality of Monetary Policy and

Macroeconomic Volatility. Federal Reserve Bank of Dallas. Globalization and

Monetary Policy Institute, Working Paper No. 163.

233

Easterly, W. and S. Rebelo. (1993). Fiscal Policy and Economic Growth: An Empirical

Investigation. NBER Working Paper No. 4499. Cambridge, MA: National Bureau of

Economic Research.

Easterly, William, (1989). Policy Distortions, Size of Government, and Growth. NBER

Working Paper No. 3214.

Edison, H. J., and Warnock, F. E. (2008). Cross-border listings, capital controls, and

equity flows to emerging markets. Journal of International Money and Finance,

27(6), 1013–1027.

Edison, H., R. Levine, L. Ricci, and T. Slok (2002). International Financial Integration and

Economic Growth. Journal of International Monetary and Finance, 21( 6):749–76.

Edward, S. (2000). Capital Mobility and Economic performance: Are Emerging

Economies Different? University of California, Los Angeles and National Bureau of

Economic Research.

_________ (1989). Openness, Outward Orientation, Trade Liberalization and Economic

Performance in Developing Countries. National Bureau of Economic Research,


_________ (1991). Trade Orientation, Distortions and Growth in Developing Countries.

National Bureau of Economic Research, Working Paper No. 3716.

_________ (1996). A tale of two crises: Chile and Mexico. NBER Working Paper 5794.

Edwards, S. and Susmel, R. (2003). Interest-Rate Volatility in Emerging Markets. The

Review of Economics and Statistics, 85(2), 328–348.

Edwards, S., (1993). Openness, Trade Liberalisation and Growth in Developing Countries.

Journal of Economic Literature, 31, 1358–1393.

Edwards, S., and Khan, M. S. (1985). Interest Rate Determination in Developing

Countries: A Conceptual Framework, IMF Staff Paper, 377-403.

Eichengreen, B. (2001). Capital Account Liberalization: What Do Cross-Sections Studies

Tell Us? World Bank Economic Review, 15(3), 341–365.

Eichengreen. B, and D.Leblang (2003). Capital Account Liberalization and Growth: Was

Mr. Mahathir Right? NBER Working Paper No. W9427 (Cambridge, MA: National

Bureau of Economic Research).

Engen, E. M., and Skinner, J. (1992). Fiscal Policy and Economic Growth. NBER Working

Paper Series, WP No. 4223.

Engen, E., and Hubbard, R., G. (2004). Federal Government Debts and Interest Rates.

National Bureau of Economic Research. Working Paper No. 10681.

Engle, R., F., and Gonzalo, R., J. (2009). High and Low Frequency Correlations in Global

Equity Markets. Working Papers 2009-17, Banco de Mexico.

234

Erba, S. D., and Sola, S. (2011). Expected Fiscal Policy and Interest Rates in Open

Economy. Graduate Institute of International and Development Studies. Working

Paper No. 07.

Falvey, R., Foster-McGregor, N., and Khalid, A. (2013). Trade liberalisation and growth:

A threshold expectation, Journal of the Asia Pacific Economy, 18(2) 230-252.

Fatas, A., and Mihov, I. (2008). Fiscal Discipline, Volatility, and Growth. Fiscal Policy,

Stabilization, and Growth:Prudence or Abstinence, 43–74.

__________________ (2013). Policy volatility, institutions, and economic growth.

Review of Economics and Statistics, 95(May), 362–376.

Fatima, A., and Iqbal, A. (2003). The relative effectiveness of monetary and fiscal

policies: An Econometric Study. Pakistan Economic and Social Review, 41(1/2), 93–

116.

Fayissa, B., and Nsiah, C. (2013). The Impact of Governance on Economic Growth in

Africa. The Journal of Developing Areas, 47(1), 91–108.

Ferreira, M. A., and Laux, P. A. (2009). Journal of International Money Portfolio flows,

volatility and growth. Journal of International Money and Finance, 28(2), 271–292.

Fetai, B., (2013). The effectiveness of fiscal and monetary policy during the financial

crisis. East-West Journal of Economics and Business, 16(2), 53-66.

Finn E. Kydland and Edward C. Prescott (1982).Time to Build and Aggregate

Fluctuations. Econometrica, 50 (6), 1345-1370.

Firat Demir and Mustafa Caglayan and Omar S. Dahi (2012). Trade Flows, Exchange Rate

Uncertainty and Financial Depth: Evidence from 28 Emerging Countries. Munich

Personal RePEc Archive. MPRA Paper No. 37400.

Forbes, B. K. (2012). Capital Flow Volatility and Contagion : A Focus on Asia. MIT-

Sloan School of Management and NBER.

Fosu, A. K. (1992). Effect of Export instability on Economic Growth in Africa. Journal of

Developing Areas , 26, 323-32.

Frankel, J., and D. Romer. (1999). Does Trade Cause Growth? American Economic

Review, 89(3), 379-399.

Freire-Seren, M. J. (1999). Human Capital Accumulation and Economic Growth. Working

Paper No. 435.99.

Fu, D., Taylor, L.L. and Yucel, M.K. (2003). Fiscal policy and growth. Research

Department Working Paper 0301, Federal Reserve Bank of Dallas.

Furceri, D. (2007). Is Government Expenditure Volatility Harmful for Growth? A Cross-

Country Analysis. Fiscal Studies, 28(1), 103–120.

235

Gabriele, A. (2000). Instability and Volatility of Capital Flows to Developing Countries.

World Economy, 23(8), 1031-1056.

Gale, W. G., and Orszag, P. R. (2002). The Economic Effects of Long-Term Fiscal

Discipline. Urban-Brookings Tax Policy Center Discussion Paper.

Gallo, M., L, and Sagales, R., O. (2011). Economic Growth and Inequality: The Role of

Fiscal Policies. Australian Economic Papers, 50(2‐3), 74-97.

Gangal, V. L. N., and Gupta, M. H. (2013). Public Expenditure and Economic Growth A

Case Study of India. Global Journal of Management and Business Studies, 3(2), 191–

196.

Gani, A. (2011). Governance and Growth in Developing Countries. Journal of Economic

Issues, 45, (1).

Gemmell, N. and J. Au. (2012). Government Size, Fiscal Policy and the Level and Growth

of Output: A Review of Recent Evidence. Working Paper in Public Finance, 10/12.

Wellington: Victoria Business School.

Gerardo E. and L.B. Felipe (2002).The impact of G-3 Exchange Rate Volatility on

Developing Countries. United Nations Conference on Trade and Development

(UNCTAD). G-24 Discussion Paper No. 16.

Ghani, G. M. (2011). The impact of trade liberalisation on the economic performance of

OIC member countries. Journal of Economic Cooperation and Development, 32(1),

1–18.

Ghatak, S., and Sánchez-Fung, R., J. (2007). Is Fiscal Policy Sustainable in Developing

Economies? Review of Development Economics, 11(3), 518-530.

Gilbert, N. (2004). Trade Openness Policy, Quality of Institutions and Economic Growth.

CERDI, France, (33).

Glezakos, C. (1973). Export Instability and Economic Growth: A Statistical Verification.

Economic Development and Cultural Change, 3, 815 – 828.

Globan, T. (2012). Capital flow reversals during a financial crisis: Does the pre-crisis

composition matter? Ekonomski Pregled, 63 (11) 587-607.

Goldar, B., and Kumari, A. (2003). Import Liberalization and Productivity Growth in

Indian Manufacturing Industries in the 1990s. The Developing Economies, XLI(4),

436–460.

Goldsmith, A. A. (1995). Democracy, Property Rights and Economic Growth. The Journal

of Development Studies, 32(2), 157-174.

Gong, L., and Zou, H. (2002). Effects of Growth and Volatility in Public Expenditures on

Economic Growth : Theory and Evidence. Annals of Economics and Finance, 3, 379–

406

http://www.tandfonline.com/loi/mjei20?open=45&repitition=0#vol_45

http://www.tandfonline.com/toc/mjei20/45/1

236

Gourinchas, P-O. and and Jeanne, O. (2006). The Elusive Gains from International

Financial Integration. Review of Economic Studies, 73 (3), 715–741.

Greenaway, David; Morgan, Wyn; and Wright, Peter. (1998). Trade Liberalization and

Growth in Developing Countries. Journal of Development Economics, 67, 229-244.

Greenaway, David; Morgan, Wyn; Wright, P. (2002). Trade Liberalisation and Growth in

Developing Countries. Journal of Development Economics, 67, 229-44.

Griffith-Jones, S. (1998). How to Protect Developing Countries from Volatility of capital

flows? Institute of Development Studies Sussex University, England.

Grilli, G., and Ferretti, M., (1995). Economic Effects and Structural Determinants of

Capital Controls. Staff Papers (International Monetary Fund), 42( 3), 517-551.

Gul, H., Mughal, K., and Rahim, S. (2012). Linkage between Monetary Instruments and

Economic Growth. Journal of Management and Social Sciences, 2(5), 69–76.

Gulen, H., and Ion, M. (2015). Policy Uncertainty and Corporate Investment. Review of

Financial Studies, (765), 1–47.

Gundlach Erich (2007). The Solow Model in the Empirics of Growth and Trade .Oxford

Review of Economic Policy, 23 (1), 25-44.

Guseh, J. S. (1997). Government Size and Economic Growth in Developing Countries: A

Political Economy Framework. Journal of Macroeconomics, 19(1), 175–192.

Gwartneya, J., and Lawson, R. (2003). The Concept and Measurement of Economic

Freedom. European Journal of Political Economy, 19, 405 – 430.

Gyimah-Brempong, K. (1991). Export instability and economic Growth in Sub- Saharan

Africa. Economic Development and Cultural Change, 39, 815-28.

Haider, A., Din, M-U. and Ghani, E. (2011). Consequences of Political Instability,

Governance and Bureaucratic Corruption on Inflation and Growth : The Case of

Pakistan. The Pakistan Development Review, 50(4):2, 773–807.

Hansen, B. E., and Seshadri, A. (2013). Uncovering the Relationship between Real

Interest Rates and Economic Growth. Working Paper, University of Michigan

Retirement Research Center, (WP 2013-303).

Hansson, P. and M. Henrekson. (1994). A New Framework for Testing the Effect of

Government Spending on Growth and Productivity. Public Choice, 81, 381-401.

Harrison, A., and Hanson, G. (1999). Who gains from trade reform? Some remaining

puzzles. Journal of Development Economics, 59(1), 125–154.

Helble, Matthias; Ben Shepherd and John S. Wilson (2007). Transparency and Regional

Integration in the Asia Pacific. World Bank Policy Research Paper 4401. Washington

DC: World Bank.

237

Henisz, W. J. (2004). Political Insitutions and Policy Volatility. Economics and Politics,

16(1), 1–27.

__________ (2002). The Institutional Environment for Infrastructure Investment.

Industrial and Corporate Change, 11 (2), 355–89.

Henry, P. B. (2003). Capital Account Liberalization, the Cost of Capital, and Economic

Growth. American Economic Review, 93(2), 91–96.

Holtz-Eakin, D., Newey, W., and Rosen, S., H. (1988). Estimating Vector

Autoregressions with Panel Data. Econometrica, 56 (6), 1371-1395.

Hur, J., M. Raj and Y. Riyanto (2006). Finance and Trade: A Cross-Country Empirical

Analysis

on the Impact of Financial Development and Asset Tangibility on International

Trade. World Development 34, 1728-41.

Hussain, T., and Siddiqi, M. W. (2012). Fiscal, Monetary Policies and Institutions‟ Role

(Political, Social and Economic) in Pakistan. Theoretical and Applied Economics,

19(6), 33–50.

________________ (2013). Fiscal Policy, Institutions and Governance in Selected South

Asian Countries. Pakistan Journal of Commerce and Social Sciences, 7 (2), 331-345.

Islam, N. (1995). Growth Empirics: A Panel Data Approach. The Quarterly Journal of

Economics, 110 (4), 1127- 1170.

Ismail, G., A., Karim, A., Z., Zaidi, A., M., and Wahid, H. (2006). Interest Rate

Uncertainty, Spread and Economic Activity: Empirical Evidence in Malaysia. Jurnal

Ekonomi Pembangunan, 11(3), 187-199.

Ivrendi, M., and Yildirim, Z. (2013). Monetary Policy Shocks and Macroeconomic

Variables : Evidence from Fast Growing Emerging Economies. Discussion Papers,

No 2013-61, Kiel Institute for the World Economy.

Jankee, K. (2003). Interest Rate Determination in the Post- Liberalisation Period in

Mauritius. Journal of Law, Management and Social Sciences, 5, 1–18.

Javid, A., Y., Arif, U. and Arif, A. (2011). Economic, Political and Institutional

Determinants of Budget Deficits Volatility in Selected Asian Countries. The Pakistan

Development Review, 50(4):2, 649–662.

Jayaraman, TK and Sharma, Rajesh (2003). Why Is Interest Rate Spread High in Fiji?

Results From a Preliminary Study. A Journal of Contemporary Fiji, 1(1), 75-104.

Joshua Aizenman and Nancy Marion (1991). Policy Uncertainty, Persistence and Growth.

National Bureau of Economic Research (NBER), Working Paper No. 3848.

Kandil, M. (2014). On the effects of monetary policy shocks in developing countries.

Borsa Istanbul Review, 14(2), 104–118.

238

Kappel, R. (2003). Openness, Institutions, and Policies: Determinants of Globalization and

Economic Growth in Developing Countries. Pakistan Development Review, 42(4 I),

395 416.

Kaufmann, D. (2007). Governance matters VI : Aggregate and Individual Governance

Indicators, 1996-2006, 93.

Kaufmann, D., and Kraay, A. (2002). Growth without Governance. Economía, 3(1), 169–

229.

Kaufmann, D., and Zoido-lobaton, P. (1999). Governance Matters. The World Bank .

Kaufmann, D., Kraay, a, and Mastruzzi, M. (2004). Government Matters III: Governance

Indicators for 1996-2002. The World Bank Economic Review, 18(2), 253–287.

Kaushik, K.K., Arbenser L.N.A. and Klein, K.K. (2008). Export Growth, export

instability, investment and economic growth in India: A time series analysis. The

Journal of Developing Areas, 41(2), 155-170.

Keynes, J., M. (1936). The General Theory of Employment, Interest and Money.

Macmillan Cambridge University Press.

Khan, A., J., Azim, P., and Syed, S., H. (2014). The Impact of Exchange Rate Volatility

on Trade: A Panel Study on Pakistan‟s Trading Partners. The Lahore Journal of

Economics, 19 (1), 31–66.

Kim., D.H, S.C.Lin, and Y.B. Seun (2012). Dynamic Effects of Financial Openness on

Economic Growth and Macro Economic Uncertainity. Emerging Markets Finance

and Trade, 48(1):25-54.

Klein, M.W. and G.P.Olivei (2001). Capital Account Liberalization, Financial Depth and

Economic Growth. Tufts University and NBER.

Knack, S., and Keefer, P. (1995). Institutions and Economic Performance: Cross-Country

Tests using Alternative Institutional Measures. Economics and Politics, 7(3), 207–

227.

Kneller, R., Morgan, C. W., and Kanchanahatakij, S. (2008). Trade Liberalisation and

Economic Growth. The World Economy, 31(6), 701–719.

Koedijk, K. G., Nissen, F. G. J. a., Schotman, P. C., and Wolff, C. C. P. (1997). The

Dynamics of Short-Term Interest Rate Volatility Reconsidered. Review of Finance,

1(1), 105–130.

Koopmans, T. C. (1965). On the Concept of Optimal Economic Growth. Econometric

Approach to Development Planning, chap. 4, pp. 225–87. North-Holland Publishing

Co., Amsterdam.

Krause, S., and Rioja, F. (2006). Financial Development and Monetary Policy Efficiency.

Department of Economics, Georgia State University.

239

Krueger, A. (1997). Trade Policy and Economic Development: How We Learn. American

Economic Review, 87 (1), 1-22.

__________ (1997). Trade policy and Economic Development: How we Learn. American

Economic Review 87, 1–22.

Kukk, K. (2007). Fiscal Policy Effects on Economic Growth: Short Run vs Long Run.

Department of Economics, Tallinn University of Technology, 77–96.

Kwon, G.; McFarlane, L.; Robinson, W. (2006). Public Debt, Money Supply, and

Inflation: A Cross-Country Study and Its Application to Jamaica. IMF Working

Paper No. 06/121.

Lal, D., Bhide, S., and Vasudevan, D. (2001). Financial Exuberace: Savings Deposits,

Fiscal Deficits and Interest Rates in India. Economic and Political Weekly, 36 (44),

4196-4203.

Lambsdorff, J. G. (2003). How Corruption Affects Persistant Capital Flows? Econnomics

of Governance, 4, 229–243.

Landau, D. (1986). Government and Economic Growth in the Less Developed Countries:

An Empirical Study for 1960-88. Economic Development and Cultural Change, 35,

35-75.

Lane, P. R. and G. M.M. Ferretti (2007). The External Wealth of Nations Mark II: Revised

and Extended Estimates of Foreign Assets and Labilities. Journal of International

Economics, 73(2), 223-250.

Lane, R., P. and Tornell, A. (1996). Power, Growth, and the Voracity Effect. Journal of

Economic Growth, 1 (2), 213-241.

Leahy, John V., M.Whited, T. (1996). The Effect of Uncertianty on Investment: Some

Sylized Facts. Journal of Money, Credit and Banking 28(1), 65-83.

Lensink, R., and Morrissey, O. (2001). Foreign direct investment: Flows, volatility and

growth in developing countries, University of Groningen.

Levchenko, A. (2007). Institutional Quality and International Trade. The Review of

Economic Studies, 74 (3), 791-819.

Levchenko, A. A., and Mauro, P. (2007). Do some forms of financial flows help protect

against “sudden stops”? World Bank Economic Review, 21(3), 389–411.

Levine, R., and Renelt, D. (1992). Analysis of Cross-Country Growth Regressions. The

American Economic Review, 82 (4), 942-963.

Li, K. W., Zhou, X., and Pan, Z. (2016). Cross-Country Output Convergence and Growth:

Evidence From Varying Coefficient Nonparametric Method. Economic Modelling,

55, 32–41.

240

Loayza, N. V., Ranciere, R., Serven, L., and Ventura, J. (2007). Macroeconomic Volatility

and Welfare in Developing Countries: An Iintroduction. World Bank Economic

Review, 21(3), 343–357.

Long Jr., J. B., and Plosser, C. I. (1983). Real Business Cycles. Journal of Political

Economy, 91 (1), 39-69.

Lorde, T., Francis, B., Waithe, K., and Taylor, G., T.(2008). Interest Rate Determination

in Developing Countries. Savings and Development, 32 (1), 31-50.

Love, J. (1992). Export Instability and the Domestic Economy: Questions of Causality.

Journal of Development Studies, 28, 735 – 742.

Lucas, E., R. (1988).On the Mechanics of Economic Development. Journal of Monetary

Economics, 22, 3-42.

MacBean, A., and Nguyen, D. (1980). Commodity Concentration and Export earnings

Instability: A Mathematical Analysis. The Economic Journal, 90(358), 354–362.

Mahajan, N., and Verma, S. (2015). International Financial Integration and Economic

Growth in India: An Empirical Investigation. Eurasian Journal of Business and

Economics, 8(16), 121–137.

Mankiw, G., N., Romer, D., and Weil, N., D.(1992). A Contribution to the Empirics of

Economic Growth. The Quarterly Journal of Economics, 107( 2), 407-437.

Mankiw, N. G., Phelps, E. S., and Romer, P. M. (1995). The growth of nations. Brookings

Papers on Economic Activity, 275–326.

Mankiw, N. Gregory. (2000). The Savers-Spenders Theory of Fiscal Policy. American

Economic Review, 90(2), 120-125.

Manni, U. H., and Afzal, M. N. I. (2012). Effect of Trade Liberalization on Economic

Growth of Developing Countries: A Case of Bangladesh Economy. Journal of

Buisness, Economics and Finance , 1(2), 37–44.

Martin, L., S. (1960). Political Man: The Social Bases of Politics. United States.

Martin, P., and Rey, H. (2006). Globalization and Emerging Markets: With or Without

Crash? American Economic Review, 96 (5), 1631-1651.

Martin, R. and M. Fardmanesh. (1990). Fiscal Variables and Growth: A Cross-Section

Analysis. Publi Choice, 64, 239-259.

Massell, B., F. (1970). Export Instability and Economic Structure. The American

Economic Review, 60 (4), 618-630.

Mathur, S. K. (2005). Economic Growth and Conditional Convergence: Its Speed for

Selected Regions for 1961-2001. Indian Economic Review, 40(2), 185–208.

241

Mauro, P. (1995). Corruption and Growth. The Quarterly Journal of Economics, 110(3),

681 712.

________ (2004). The Persistence of Corruption and Slow Economic Growth. IMF Staff

Papers, 51 (1): 1–18, 1–18.

McLean, B., and Shrestha, S. (2002). International Financial Liberalization and Economic

Growth. Research Discussion Paper. Economic Research Department, Reserve Bank

of Australia.

Mendoza, E. G. (1997). Terms-of-trade uncertainty and economic growth. Journal of

Development Economics, 54(2), 323–356.

Mercado, R. and Park, C-Y. (2011). What Drives Different Types of Capital Flows and

Their Volatilities in Developing Asia? ADB Working Paper Series on Regional

Economic Integration. No. 84.

Mishkin, F. (2009). Globalization, Macroeconomic Performance, and Monetary Policy.

Journal of Money, Credit and Banking, 41(1), 187-196.

_________ (2002). The Role of Output Stabilization in the Conduct of Monetary Policy.

NBER Working Paper, 9291.

Mishra, P., and Montiel, P. (2012). How Effective is Monetary Transmission in Low-

Income Countries?: A Survey of the Empirical Evidence, 1–40.

Mody, Ashoka, and Antu Panini Murshid, (2005). Growing Up With Capital Flows.

Journal of International Economics, 65(1), 249–66.

Moran, C. (1983). Export Fluctuations and Economic Growth: An Empirical Analysis.

Journal of Development Economics, 12, 195-218.

Morozumi, A., and Veiga, J., F. (2014). Public Spending and Growth: The Role of

Institutions. NIPE WP 11/ 2014.

Mundell, R. (1963). Inflation and Real Interest. Journal of Political Economy, 71 (3), 280-

283.

Munir, K., and Qayyum, A. (2014). Measuring the Effects of Monetary Policy in Pakistan:

A Factor-Augmented Vector Autoregressive Approach. Empirical Economics, 46 (

3), 843-864

Neanidis, K. C. (2015). Volatile Capital Flows and Economic Growth : The Role of

Macro-prudential Regulation. University of Manchester and Centre for Growth and

Business Cycle Research, Manchester M13 9PL, United Kingdom.

Neena, M. (2015). Sources of Export Instability in India. Journal of International

Economics, 6 (1), 58-72.

Neumann, R. M., Penl, R., and Tanku, A. (2009). Volatility of capital flows and financial

liberalization: Do specific flows respond differently? International Review of

Economics and Finance, 18(3), 488–501.

242

Ngeny, L. K., and Mutuku, C. (2014). Impact of Foreign Direct Investment Volatility on

Economic Growth in Kenya: EGARCH Analysis. Economics , 3(4), 50-61.

Niemann, R. (2007). The Impact of Tax Uncertainty on Irreversible Investment. CESIFO

Working Paper NO. 2075.

North, C., D. and Thomas, P., R. (1975). The Rise of the Western World: A New

Economic History. The Business History Review, 49 (2 ), 237-239.

North, D. C. (1990). Institutions, Institutional Change, and Economic Performance.

Cambridge University Press, 5(1), 1–153.

Noula, Armand G. (2012). Fiscal Deficits and Nominal Interest Rates Determination in

Cameroon: An Application of the Loanable Funds Models. Global Advanced

Research Journal of Management and Business Study, Vol. 1(1), 006-029.

Olaberria, E., and Rigolini, J. (2009). Managing East Asia‟s Macroeconomic Volatility.

The World Bank, East Asia and Pacific Region, Policy Research Working Paper,

WPS4989.

Oladipo, O. S. (2011). Does Trade Liberalization Cause Long Run Economic Growth in

Mexico? An Empirical Investigation. International Journal of Economics and

Finance, 3(3), 63–75.

Olson, M. (1994). Who Gains From Policies that Increase Poverty? IRIS Center Working

Paper #137. Center for Institutional Reform and the Informal Sector, University of

Maryland College Park.

Olweny, T. (2011). Modelling Volatility of Short-term Interest Rates in Kenya.

International Journal of Business and Social Science, 2 (7), 289-303.

Owens, E., (1987). The Future of Freedom in the Developing World. Pergamon Press.

Ozler, S. and Harrigan, J. (1988), Export Instability and Economic Growth. Department of

Economics. Working Paper No. 486, University of California, Los Angeles.

Paudel, R. C. (2014). Trade Liberalisation and Economic Growth in Developing

Countries : Does Stage of Development Matter ? Crawford School Research Paper

No. 14-13.

Payne, J. E., and Ewing, B. T. (1997). Evidence From Lesser Developed Countries on the

Fisher Hypothesis : A cointegration analysis. Applied Economics Letters, 4, 683–687.

Peterson, W. (1998). Monetary Instability and Economic Growth. Bulletin Number 98-6,

Economic Development Center, University Of Minnesota.

Polillo, S., and Guillen, M. (2005). Globalization Pressures and the State: The Global

Spread of Central Bank Independence. American Journal of Sociology. 110(6), 1764-

1802.

243

Prasad, E. S., and Rajan, R. G. (2008). A Pragmatic Approach to Capital Account

Liberalization. Journal of Economic Perspectives, 22(3), 149–172.

Prasad, E., Rogoff, K., Wei, S.J., and Kose, M. A. (2003). Effects of Financial

Globalization on Developing Countries: Some Empirical Evidence. IMF Working

Paper.

Pritchett, L., Sethi, G., (1994). Tariff rates, Tariff Revenue, and Tariff Reform: Some New

Facts, The World Bank Economic Review, 8 (1), 1– 16.

Psacharopoulos, G. (1994). Returns to Investments in Education: A Global Update. World

Development, 22(9), 1325–1343.

Quinn, D. (1997). Correlates of Changes in International Financial Regulation. American

Political Science Review, 91(3):531-551.

Quinn, D. P., and Toyoda, A. M. (2008). Does capital account liberalization lead to

growth? Review of Financial Studies, 21.

Qureshi, M. N., K. Ali, and I. R. Khan (2010). Political Instability and Economic

Development: Pakistan Time-Series Analysis. International Research Journal of

Finance and Economics, 56, 179–192.

R., Nazir, M., Anwar, M., Irshad. (2013). Does Fiscal Policy Matter for Growth?

Empirical Evidence from Pakistan. International Journal of Economics and Finance,

5(3).

Raddatz, C. (2007). Are External Shocks Responsible for the Instability of Output in Low

Income Countries? Journal of Development Economics, 84(1), 155–87.

Ram, R. (2007). IQ and Economic Growth: Further Augmentation of Mankiw-Romer-

Weil Model. Economics Letters, 94(1), 7–11.

Ramey, G., and Ramey, V. a. (1995). Cross-Country Evidence on the Link between

Volatility and Growth. American Economic Review, 85(5), 1138–51.

Rashid, F., Ullah, S., and Zaman, B. (2012). Effects of Exports Instability on Economic

Growth in SAARC Region Countries. Pak. J. Commer. Soc. Sci, 6(1), 97–120.

Reisen, H. (1996) „Managing volatile capital inflows: the experience of the 1990s‟ Asian

Development Review, 14(1) 72-96.

Reisen, Helmut, and Marcelo Soto, (2001). Which Types of Capital Inflows Foster

Developing- Country Growth? International Finance, 4(1), 1–14.

Rodriguez, F., and Rodrik, D. (2001). Trade Policy and Economic Growth: A Skeptic‟s

Guide to the Cross-National Evidence. Working Paper 7081, NBER.

Rodrik, D. (1991). Policy Uncertainty and Private Investment in Developing Countries,

Journal of Development Economics, 36, 229-242.

244

_________ (1998). Who Needs Capital-Account Convertibility? Essays in International

Finance, No. 207 (Princeton, New Jersey: Princeton University).

________ (2004). Institutions and Economic Performance - Getting Institutions Right.

CESifo DICE Report, Ifo Institute - Leibniz Institute for Economic Research at the

University of Munich, 2(2), 10-15.

________ (2006). Goodbye Washington Consensus, Hello Washington Confusion? A

Review of the World Bank's Economic Growth in the 1990s: Learning from a Decade

of Reform. Journal of Economic Literature, 44 (4), 973-987.

Rodrik, D., and Velasco, A. (1999). Short-Term Capital Flows. NBER Working Papers

7364, National Bureau of Economic Research, Inc.

Rodrik, D., Subramanian, A., and Trebbi, F. (2002). Institutions Rule: The Primacy of

Institutions over Geography and Integration in Economic Development. NBER


Romer, P. M. (1989). Human Capital and Growth: Theory and Evidence. National Bureau

of Economic Research, Working Paper No. 3173.

Sachs, J. D., and Warner, A. M. (1995). Economic Convergence and Economic Policies.

NBER Working Paper Series, 47.

Salinas, G., Aksoy, A., and Washington, D. C. (2006). Growth Before and After Trade

Liberalisation. World Bank Policy Research Paper No 4062 World Bank.

Santiso, C. (2001). Good Governance and Aid Effectiveness : The World Bank and

Conditionality. The Georgetown Public Policy Review, 7(1), 1–22.

Sarada, C., Ravisankar, T., Krishnan, M., and Anandanarayanan, C. (2006). Indian

Seafood Exports: Issues of Instability, Commodity Concentration and Geographical

Spread. Indian Journal of Agricultural Economics, 61(2), 238–252.

Sargent T.J., Wallace N. (1981). Some Unpleasant Monetarist Arithmetic. Federal Reserve

Bank of Minneapolis Quarterly Review.

Sattar, Z. (1993). Government Control and Economic Growth in Asia: Evidence from

Time Series Data. The Pakistan Development Review, 32 (2), 179-197.

Schindler, M. (2009). Measuring Financial Integration: A New Data Set. IMF Staff

Papers, 56(1), 222-238.

Sen, A. (1991). Welfare, Preference and Freedom. Journal of Econometrics, 50(1-2), 15-

29.

Shaheen, S., Ali, M. M., and Kauser, A. (2013). Impact of Trade Liberalization on

Economic growth in Pakistan. Interdisciplinary Journal of Contemporary Research

in Business, 5(5), 228–240.

245

Sheburne, R. C. (2010). The Global Financial Crisis and its Impact on Trade : The World

and the European Emerging Economies. United Nations Economic Commission for

Europe. Discussion Paper Series No. 2010.2, 1–30.

Sheehey, E. (1977). Levels and Sources of Export Instability : Some Recent Evidence,

Kyklos, 30, 319–324.

Siddiqui, A. D. and Ahmed, A. Q. (2010). The Causal Relationship between Institutions

and Economic Growth: An Empirical Investigation for Pakistan Economy. Munich

Personal RePEc Archive, MPRA Paper No. 19745.

Singh, A. (2003). Capital Account Liberalization, Free Long-Term Capital Flows,

Financial Crisis and Economic Development. Eastern Economic Journal, 29(2):

191-216.

Sinha, D. (1999). Export Instability, Investment and Economic Growth in Asian

Countries: A Time Series Analysis. Discussion Paper No. 799, Economic Growth

Center, Yale University.

Sirimaneetham, V. (2006). Explaining policy volatility in developing countries.

Department of Economics, University of Bristol, Discussion Paper No. 06/583.

Sohaib, S., and Corresponding, Z. (2014). Good Governance: Pakistan‟s Economic

Growth and Worldwide Governance Indicators. Pakistan Journal of Commerce and

Social Sciences, 8(1), 258–271.

Solow, M., R. (1956). A Contribution to the Theory of Economic Growth. The Quarterly

Journal of Economics, 70 (1 ), 65-94.

Stiglitz, J. (2000). Capital Market Liberalization, Economic Growth, and Instability.

World Development, 28, 1075-1086.

________ (2000). Capital market liberalization, economic growth, and instability. World

Development, 28(6), 1075–1086.

Sula, O., and Willett, T. D. (2007). Reversibility of Different Types of Capital Flows to

Emerging Markets. Department of Economics, Claremont Graduate University.

Suyuan, L., Wu, and Khurshid, A. (2015). Interest Rate Uncertainty, Investment and their

Relationship on Different Industries; Evidence from Jiangsu, China. Journal of

International Studies, 8 (2), 74-82.

Ullah, S., Haider, S. Z., and Azim, P. (2012). Impact of Exchange Rate Volatility on

Foreign Direct Investment A Case Study of Pakistan. Pakistan Economic and Social

Review, 50(2), 121–138.

Vinayagathasan, T. (2014). Monetary Policy and the Real Economy: A Structural VAR

Approach for Sri Lanka. Asian Journal of Empirical Research, 4.1(July), 1584–1607.

Wacziarg, R., and Welch, H., K. (2003). Trade Liberalization and Growth: New Evidence.

National Bureau of Economic Research, Working Paper10152.

246

Waqas, Y., Hashmi, S. H., and Nazir, M. I. (2015). Macroeconomic factors and foreign

portfolio investment volatility: A case of South Asian countries. Future Business

Journal, 1(1), 65–74.

Williamson, J., and Z. Drabek, (1999). Whether and When to Liberalize Capital Account

and Financial Services. Staff Working Paper ERAD-99-03. World Trade

Organization. Economic Research and Analysis Division.

Yasmin, B., Jehan, Z., and Chaudhary, A. M. (2006). Trade Liberalization and Economic

Development: Evidence from Pakistan. The Lahore Journal of Economics, 11 (1), 19-

34.

Yerrabati, S., and Hawkes, D. (2015). Economic Governance and Economic Growth in

South and East Asia Pacific Region: Evidence from Systematic Literature Reviews

and MetaAnalysis. Advances in Economics and Business. 3(1), 1 – 21.

Yotopoulos, P.J. and Nugent, J.B. (1976). Economics of Development. New York: Harpar

and Row.

Younus, S. (2013). Relative Effectiveness of Monetary and Fiscal Policies on Output

Growth in Bangladesh: A Co integration and Vector Error Correction Approach.

Policy Analysis Unit Research Department, Bangladesh Bank.

Zakaria, M. and B. A. Fida (2010). Democratic Institutions and Variability of Economic

Growth in Pakistan: Some Evidence from the Time-series Analysis. Pakistan

Development Review, 48, 269–289.

247

Appendix I: Percentile score of countries at governance index (2014)

sr # Country Name 2014 sr # Country Name 2014 sr # Country Name 2014 sr # Country Name 2014 sr # Country Name 2014

1 New Zealand 98.79 46 Virgin Islands (U.S.) 76.43 91 Tonga 55.13 136 Dominica 37.15 181 Cuba 21.87

2 Georgia 98.22 47 Benin 76.41 92 Trinidad and Tobago 55.07 137 Haiti 37 182 Pakistan 20.95

3 Switzerland 97.58 48 Angola 76.26 93 Serbia 54.4 138 Vietnam 36.81 183 Kenya 18.88

4 Norway 96.22 49 Reunion 76.17 94 Iraq 53.47 139 Malawi 36.64 184 Congo, Dem. Rep. 17.82

5 Sweden 95.57 50 Slovenia 75.9 95 Rwanda 52.14 140 Bangladesh 36.29 185 Chad 17.42

6 Lao PDR 95.5 51 Mauritius 75.81 96 Korea, Dem. Rep. 51.78 141 Swaziland 33.36 186 Tajikistan 16.49

7 Netherlands 95.08 52 Finland 75.53 97 Greece 51.77 142 Cayman Islands 33.26 187 Congo, Rep. 16.23

8 Colombia 94.68 53 Spain 74.28 98 Algeria 50.88 143 Nauru 33.23 188 Aruba 15.91

9 Equatorial Guinea 94.43 54 Slovak Republic 74 99 Antigua and Barbuda 50.87 144 Tanzania 33.22 189 Uzbekistan 15.45

10 Liberia 94.12 55 Macao SAR, China 73.95 100 Burkina Faso 50.48 145 West Bank and Gaza 33.12 190 Nigeria 14.79

11 Bermuda 93.7 56 Kyrgyz Republic 73.92 101 Palau 50.04 146 Guam 32.87 191 Turkmenistan 14.02

12 Albania 93.48 57 Croatia 72.8 102 Hong Kong SAR, China 49.75 147 Guinea-Bissau 31.75 192 Eritrea 13.58

13 Grenada 92.02 58 Puerto Rico 72.35 103 Turkey 49.53 148 Papua New Guinea 31.58 193 Hungary 13.52

14 Italy 91.87 59 Brunei Darussalam 72.34 104 Mongolia 49.47 149 Nicaragua 30.9 194 Guyana 10.69

15 Jersey, Islands 91.86 60 St. Vincent 72.11 105 Senegal 49.26 150 Paraguay 30.76 195 Myanmar 10.31

16 Iceland 89.79 61 Dominican Republic 71.63 106 Maldives 48.19 151 Mozambique 30.74 196 Zimbabwe 9.863

17 Iran, Islamic Rep. 89.75 62 Cabo Verde 71.18 107 Cote d'Ivoire 48.19 152 Libya 29.68 197 Venezuela, RB 9.32

18 Gambia, The 88.83 63 United Arab Emirates 71.03 108 Lesotho 47.96 153 Azerbaijan 29.68 198 Cambodia 8.951

19 Argentina 88.72 64 Samoa 69.98 109 Saudi Arabia 46.54 154 Uganda 29.31 199 Kazakhstan 8.473

20 Singapore 88.31 65 St. Lucia 69.78 110 Gabon 46.52 155 Guinea 29.29 200 Yemen, Rep. 8.457

21 United Kingdom 88.29 66 Qatar 69.69 111 Suriname 46.18 156 Ethiopia 29.03 201 Estonia 8.292

22 San Marino 88.18 67 Jamaica 69.37 112 Botswana 45.61 157 Russian Federation 28.8 202 Cook Islands 8.15

23 Indonesia 87.95 68 Ireland 69.05 113 Philippines 45.36 158 Bolivia 28.69 203 Afghanistan 7.84

24 Bahrain 86.39 69 Israel 66.91 114 Sri Lanka 44.72 159 American Samoa 28.6 204 Canada 6.546

25 Belize 85.37 70 Malaysia 66.43 115 Morocco 44.23 160 Czech Republic 28.2 205 Sudan 5.31

26 Fiji 84.35 71 Denmark 66.15 116 Jordan 44.01 161 Cyprus 27.87 206 Liechtenstein 4.72

27 United States 84.08 72 China 66.11 117 Thailand 43.96 162 Madagascar 27.71 207 Central African Republic 4.682

28 Malta 83.9 73 Bahamas, The 65.23 118 Tunisia 43.89 163 Ukraine 26.8 208 Syrian Arab Republic 3.778

29 Australia 83.86 74 Guatemala 63.74 119 Macedonia, FYR 43.85 164 India 26.7 209 Kosovo 3.628

30 Burundi 83.04 75 St. Kitts and Nevis 63.58 120 Mexico 43.49 165 Nepal 26.69 210 South Sudan 2.269

31 Ghana 82.66 76 Namibia 61.91 121 Djibouti 43.33 166 Niger 26.54 211 Somalia 0.726

32 Greenland 82.28 77 French Guiana 61.31 122 Brazil 43.15 167 Timor-Leste 26.47

33 Taiwan, China 81.34 78 Germany 61.08 123 Belarus 43.13 168 Comoros 25.78

34 Ecuador 79.67 79 Oman 60.2 124 Marshall Islands 43.02 169 France 25.71

35 Portugal 79.14 80 Bhutan 60.08 125 Peru 42.96 170 Mali 25.02

36 Austria 79.03 81 South Africa 59.88 126 Zambia 42.57 171 Sierra Leone 23.93

37 Uruguay 78.83 82 Romania 58.97 127 Moldova 42.01 172 Bosnia and Herzegovina 23.53

38 El Salvador 78.57 83 Seychelles 58.39 128 Barbados 41.61 173 Kuwait 23.49

39 Anguilla 78.44 84 Montenegro 58.08 129 Japan 41.29 174 Luxembourg 23.19

40 Kiribati 78.1 85 Korea, Rep. 57.48 130 Latvia 40.04 175 Egypt, Arab Rep. 22.75

41 Chile 78.03 86 Vanuatu 57.37 131 Bulgaria 39.41 176 Armenia 22.51

42 Martinique 77.37 87 Panama 57.23 132 Solomon Islands 38.39 177 Togo 22.28

43 Monaco 77.27 88 Cameroon 57.13 133 Belgium 38.21 178 Andorra 22.22

44 Poland 77.13 89 Tuvalu 56.49 134 Honduras 38.18 179 Lithuania 22.19

45 Lebanon 76.78 90 Micronesia, Fed. Sts. 55.84 135 Sao Tome and Principe 38.06 180 Mauritania 22.01


248

Appendix II: Summary of literature review

Institutions and economic growth author country technique institutional measures main objective main findings

Mauro (1995),

Mauro (2002)

67 countries

(1980-83)

OLS and

instrumental

variables

Data of Business International (BI)

indices on corruption, bureaucratic

inefficiency and judicial system.

Association between

corruption and economic

growth.

Corruption reduces the economic growth by

reducing the private investment.

Knack and

Keefer (1995)

Cross country

(1974-89)

OLS and

instrumental

variables

Expropriation risk and rule of law from

ICRG, contract enforcement from BERI.

Link between property rights

protection and economic

growth.

Property rights increase the investment and

economic growth.

Goldsmith

(1995)

59 less

developed

countries.

(1988-93)

OLS

regression

Freedom House and Heritage

Foundation

Correlation between

institutions and economic

growth.

Both the political freedom (democracy) and

property rights positively contribute to

economic growth.

Kaufmann et

al. (1999)

Cross country OLS and

instrumental

variables

six aggregate aspects of the governance;

voice and accountability, political

stability and violence, government

effectiveness, regulatory quality, rule of

law, and control of corruption developed

by Kaufmann et al. (1999)

Relationship between

governance and economic

growth.

Better governance is associated to higher

development, such as higher per capita

income, lower mortality rate and higher

literacy rate.

Campos and

Nugent (1999)

Panel of Latin

America and

East Asia

(1982-95)

OLS

regression

International Country Risk Guide

(ICRG), Business Environmental Risk

Intelligence (BERI), polity III

Effect of institutions on

development; per capita

income, infant mortality rate

and adult literacy.

For Latin America rule of law significantly

contributes to development in all

specifications while in East Asia bureaucratic

efficiency plays its role.

Kaufmann et

al. (2002)

Cross country

(2000-01)

OLS and

instrumental

variables

Kaufmann et al. (1999) Correlation between


growth.

A robust positive correlation between per

capita income and institutional quality while

a weak negative correlation running in the

opposite direction.

Glaeser et al.

(2004)

Cross country

(1960- 2000)

OLS and

instrumental

variables

risk of expropriation by the government

from the ICRG, government

effectiveness by Kaufmann et al.(2003),

restraints on the executive from the

Polity IV

Link between institutions and

economic growth.

Economic growth leads to institutional

development.

Chong et al.

(2004)

Panel of Latin

American

countries

(1970-1995)

Fixed effect International Country Risk Guide

(ICRG), Business Environmental Risk

Intelligence (BERI) and contract

intensive Money (CIM).

Association between


growth.

All the aggregated and disaggregated

indicators of institutional quality are

positively related to economic growth.

249

Drury and

Lusztig (2006)

More than

100 countries

(1982–97)

OLS

regression Freedom House Relationship between

corruption, democracy and

economic growth.

Democracy indirectly affects the economic

growth while corruption has direct and

negative impact on economic growth.

Siddique and

Ahmed (2010)

Pakistan

(1984-2006)

Johansen

cointegration,

Granger

causality

Index of institutionalized social

technologies.

Impact of institutional quality

on economic growth. There is long run relation between

institutions and economic growth moreover

causality goes from institutions to economic

growth.

Gani (2011) Panel of 84

developing

economies

(1996 – 2005)

OLS

regression

Worldwide Governance Indicators,

(Kaufmann et al., 2010).



growth.

Political stability and government

effectiveness are directly associated to

economic growth whereas voice and

accountability and corruption are inversely

related.

Haider et al.

(2011)

Pakistan regression Index of Corruption, Index of

Governance.

Outcome of political

instability, governance and

corruption on inflation and

growth.

High corruption and poor governance cause

high inflation and low growth. Both

corruption and weak governance coincide

with political instability during the

democratic regimes.

Ahmad and

Marwan

(2012)

69

developing

countries

(1985-2008)

GMM, Fixed

effect

International Country Risk Guide

(ICRG), Gastil index and polity II.



growth.

Property rights protection appears as the

highly significant institutional indicator to

affect the growth for whole sample as well as

for East Asia. Albassam

(2013)

All countries

listed on

(WGI)

(2006-11)

correlations Kaufmann et al. (1999) Whether the crisis and the

level of development affect

the relationship between

governance and growth?

Economic crisis has not affected the

relationship between governance and growth

but the level of development of the countries

does affect it.

Fayissa et al.

(2013)

Panel of 28

Sub Saharan

African

countries

(1990-2004)

Fixed effect

and random

effect, quintile

regression.



Link between governance

and economic growth. Both the aggregate and disaggregate

measures of governance positively

contributes to economic growth.

Yerrabati and

Hawkes

(2015)

South Asia,

East Asia and

Pecific.

(1980-2012)

Meta

regression

analysis.


(Kaufmann et al., 2010). Relationship between


growth.

Voice and accountability and corruption are

positively associated with economic growth.

Political stability, government effectiveness,

regulation and rule of law are negatively

correlated to growth. Bhattacharjee

et al.(2015)

Panel data of

South Asia

(1996-2010)

Fixed effect

and dynamic

panel GMM.





growth.

Voice and accountability and government

effectiveness contribute to economic growth

while others measures remain insignificant.

250

Financial liberalization and economic growth author country technique financial liberalization measures main objective main findings

Alesina, Grilli

and Milesi-

Ferretti (1993),

Grilli and

Milesi-Ferretti

(1995)

20 high-income

countries.

61 developing

countries from

1950s to the 1990s.

Instrumental

variables. Binary measure for capital account

liberalization constructed by the

IMF.

Relationship between capital

account openness and

economic growth.

Capital account openness is directly

associated to economic growth for

developed countries while there is

negative association for developing

countries.

Quin (1997)

Quin(2008) 65 developed and

developing

countries.

(1958-89)

Instrumental

variables. De Jure indicators of capital account

openness. Relationship between capital


economic growth.

Capital account openness positively

contributes to economic growth alike in

developed and developing countries.

Rodrik (1998) 100 industrial and

developing

countries.

(1975-1989)

Binary measure for capital account

liberalization constructed by the

IMF.



economic growth.

No relationship between capital account

liberalization and economic growth.

Edwards

(2000)

20 emerging

economies during

the 1980s.

Instrumental

variables.

Quinn’s indicator of capital account

liberalization.

Association between capital


economic growth.

The positive impact of an open capital

account depends on the level of

development.

Klein and

Olivei (2001)

Cross section of

developed and

developing

countries.

(1986-95)

Instrumental

variables.

De Jure indicators of capital account

liberalization; IMF capital account

openness.



economic growth through

financial development.

Capital account liberalization contributes

to economic growth through financial

deepening only in developed countries.

The relationship does not hold in

developing countries.

Arteta et al.

(2001)

61 developed and

developing

countries.

Instrumental

variables Quinn’s index and IMF capital

account openness measure.

Correlation between capital


economic growth.

Capital account openness contributes to

growth only in countries having strong

institutions.

Reisen and

Soto (2001)

Panel of 44

developing

countries.

(1986–97).

Instrumental

variables.

Disaggregated capital inflows. Association between capital

inflows and economic growth.

Foreign direct investment and portfolio

equity inflows contribute to economic

growth.

McLean and

Shrestha

(2002)

40 developed and

developing

countries

(1976-95)

Instrumental

variables.

Capital inflows also disaggregated

into FDI inflows flows, portfolio

inflows and bank inflows.

Effect of capital account

openness on economic growth.

FDI and portfolio flows positively

contribute to growth.

Edison et al.

(2002)

Panel of 57

countries

(1980-2000)

OLS,2SLS,

GMM

De Jure and de facto indicators of

capital account liberalization.

Impact of capital account

openness on economic growth. No robust association between financial

openness and economic growth.

251

Eichengreen

and Leblang

(2003)

21 countries.

(1880-1997)

Instrumental

variables.

Capital controls is captured by

presence or absence of control

during the initial year of each period

while for recent years, IMFs binary

indicator is utilized.



economic growth in the

presence of crisis.

Capital account openness hurts the

growth in the presence of crisis.

Singh (2003) 118 developed and

developing

countries.

(1972-98)

Instrumental

variables.

FDI flows, portfolio flows and debt

flows



economic growth.

Long run capital flows (FDI) positively

contributes to economic growth.

Bekaert et al.

(2005)

panel of 95

countries

(1980-97)

Fixed effects,

time effects,

GMM

De Jure indicators of capital account

openness; Bekaert and Harvey

(2002), IMF capital account

openness, Quinn (1997), first sign

indicator and capital intensity

measure.



economic growth.

Capital account openness positively

contributes to economic growth in

different specifications.

Bonfiglioli

(2005)

93 countries.

(1975 to1999)

Instrumental

variables. De jure measure for capital account

liberalization as well as for equity

market liberalization.

Effect of capital account

openness on economic growth

through productivity and

investment.

Financial openness has a little and non-

robust effect on investment while it

boosts productivity growth. Capital

account liberalization enhances the

possibility of banking crises in developed

countries only.

Mody and

Murshid

(2005)

60 developing

countries.

(1979-99)

Instrumental

variables. Aggregate capital flows and also

their components; foreign direct

investment, portfolio flows and

bank loans; liberalization dates.


flows and investment. FDI flows significantly contribute to

investment and their effect can be

enhanced through better policy

environment.

Kim et al.

(2012)

Panel of 70

developed and

developing

countries.

(1960-2007)

PMG,MG de facto measure of financial

liberalization; external financial

stocks and FDI stocks

Impact of capital account

openness on economic growth. In long run both are positively related but

in short run both are inversely related.

252

Trade liberalization and economic growth author country technique trade liberalization measures main objective main findings

Sachs and

Warner (1995)

Cross section of

117 countries

(1970-1989)

regression Sachs and Warner Index (1995) Relationship convergence and

economic policies.

Open trade regimes increase the growth and

convergence.

Harrison and

Hanson (1999)

Cross country

(1970-98)

regression Sachs and Warner (1995) Effect of trade liberalization on

economic growth, employment

and wages.

No association between trade liberalization

and economic growth. Liberalization has

very small impact on employment and it

increases the wage inequality.

Rodriguez and

Rodrik (2000) Trade liberalization and

economic growth.

There is no robust correlation between trade

liberalization and economic growth due to

misspecification and misleading proxies of

liberalization.

Zhang (2001) 10 East Asian

economies from

1960 to 1996

regression Exports as a ratio to GDP. Link between trade

liberalization, convergence and

economic growth.

There is evidence of weak convergence due

to world integration.

Greenaway et

al. (2002)

73 developing

countries from

1975-93.

GMM Sachs and Warner (1995), Dean et

al. (1994) and one based on World

Bank (1993).

Effect of trade liberalization on

economic growth.

Trade liberalization positively contributes to

economic growth.

Wacziarg and

Welch (2003)

141 countries.

(1970-99)

Fixed effect. Dummy variable approach as

developed by Sachs and Warner

(1995) but with extended data set,

liberalization dates.


economic growth.

Trade liberalization contributes to economic

growth, investment and trade openness.

Goldar and

Kumari (2003)

India

(1981-98)

Effective protection rate, non-tariff

barriers.

Relationship between import

liberalization and productivity

growth in manufacturing sector.

Import liberalization increases industrial

productivity.

Dollar and

Kraay (2004)

39 developing

countries

(1975-97)

regression Changes in trade volumes indicate

the liberalization.

Trade liberalization, poverty

and economic growth. Globalization leads to faster growth and

poverty reduction.

Aksoy Ataman

(2006)

39 developing

countries.

(1970-2004)

Fixed effects Dummy variables representing

liberalization dates from World

Bank’s Trade Assistance

Evaluation.


economic growth. Trade liberalization contributes to economic

growth. Moreover, trade liberalization also

increases investment and manufacture

exports by increasing export diversification.

Yasmin et al.

(2006)

Pakistan

(1960-2003)

2SLS Two measures of trade

liberalization; trade-GDP ratio and

import duties.


economic development; per

capita GDP, income inequality,

poverty and employment.

Liberalization has reduced the GDP per

capita. It has increased the employment

level while it has no effect on poverty and

distribution of income has become worse.

253

Morgan and S.

Kanchanahatakij

(2008)

37 liberalising

countries.

(1970-98)

Fixed effect. Dummy representing date of

liberalization, ratio of trade taxes

to GDP.

Relationship between trade

liberalization and economic

growth.

Positive relationship between trade

liberalization and economic growth.

Chang et al.

(2009)

Panel of 82

developed and

developing

countries.

(1960–2000)

GMM Two measure of outward

orientation; trade openness and

import duties.

Relationship between trade


growth.

Trade liberalization contributes to faster

growth but its effect can be enhanced by

undertaking macroeconomic and

institutional reforms.

Ghani (2011) 24 OIC

countries

(1970-2001)

regression Dummy variable that equals zero

before liberalization and one after

liberalization.


economic performance (GDP

per capita, exports and imports)

Liberalization increases the GDP per capita

but exports, imports and trade has not

improved much after liberalization.

Mani and Afzal

(2012)

Bangladesh

(1980-2010)

regression Liberalization is measured as trade

as a ratio to GDP.

Impact of trade liberalization

on economic performance;

growth, inflation, exports and

imports.

Trade liberalization boost economic growth,

real exports and imports. While

liberalization has no effect on inflation.

Falvey et al.

(2013)

Panel data for 58

developing

countries.

(1970-2005)

Sachs-Warner index of trade

Liberalization. Association between trade


growth.

Trade liberalization enhances economic

growth through four channels; investment,

government finance, trade openness and

price variations.

Paudel, R. C.

(2014)

panel data of

193countries

(1985-2010)

Fixed effects. Sachs and Warner Index updated

by countries and time period. Link between trade


growth.

Trade liberalization positively contributes to

economic growth but its effect also depends

on the level of development of countries.

254

Fiscal policy and economic growth author country technique fiscal policy measures main objective main findings

Barro (1989) Cross section of

120 countries.

(1960-85)

regression Disaggregated government

expenditures.


growth, savings and

government

expenditures.

Public investment increases the investment and

growth while public consumption reduces both.

Engen and

Skinner (1992)

107 developed

and developing

countries.

(1970-85)

Regression Change in government

expenditures as a ratio to

GDP, government

expenditures as a ratio to

GDP, change in tax rate,

average tax rate.

Effect of fiscal policy on

economic growth.

Government expenditures and taxation both are

negatively related to economic growth.

Easterly and

Rebelo (1993)

Cross section of

100 countries.

(1970-1988)

regression Aggregated and disaggregated

expenditures and revenues.

Impact of fiscal policy

on economic growth.

Government investment is positively correlated with

investment and growth. Investment on transportation

and communication is robustly related to growth. In

poor countries indirect taxes contribute to growth

while in developed countries direct taxes.

Sattar (1993) Asian developing

countries.

(1950-85)

regression Government consumption

expenditures.

Effect of government

expenditures on

economic growth

Government consumption expenditures positively

contribute to economic growth for Asian developing

countries. Efficiency enhancing role of government

outweighs the efficiency reducing role.

Devarajan et al.

(1996)

Panel of 43

developing

countries.

(1970-90)

Regression Disaggregated current and

capital expenditures.

Association between

public outlays and

economic growth.

Positive association between current expenditures

and economic growth while a negative association

between capital expenditures and growth. Defence,

infrastructure, education and health expenditures are

negatively related to growth. Guseh (1997) 59 middle income

developing

countries.

(1960–85)

fixed effects Growth of consumption

expenditure, growth in the

relative size of expenditure.

The effect of government

size on economic growth

across political and

economic systems.

Government size reduces the economic growth but

growth rate slows down more in nondemocratic and

socialist system.

Gupta et al.

(2002)

31 low income

countries.

(1990-2000)

Feasible

generalised

least squares

(FGLS),

GMM

Disaggregated current

expenditures, capital

expenditure, and tax and non-

tax revenues.


fiscal adjustment,

structure of expenditures

and economic growth.

Fiscal composition shows that expenditures on wages

and salaries are negatively related to growth while

expenditures on other goods and services and capital

expenditures foster the growth.

255

Bose et al.

(2003)

Panel of 30

developing

countries.

(1970-90)

Seemingly

unrelated

regression

(SURE).

Disaggregated current and

capital expenditures. Relationship between

public expenditures and

economic growth.

Capital expenditures positively contribute to growth

while current expenditures remain insignificant.

Expenditures on education contribute to growth

while expenditures in other sectors (transport and

communication, defence) do not remain robust.

Kukk Kalle

(2007)

Panel of 52

developed and

developing

countries.

regression Disaggregated expenditures

and taxes. Effect of fiscal policy on

economic growth. Current expenditures retard economic growth while

investment expenditures enhance economic growth.

Tax revenue and indirect taxes positively contribute

to economic growth.

Alam and Butt.

(2010)

Panel of

developing

countries.

(1970-2005)

GMM and

panel

cointegration.

Education, health and social

security expenses.

Correlation between

social expenditures and

economic growth.

Long run relationship among education, health and

social security expenses and economic growth.

Ali and Ahmad

(2010)

Pakistan

(1972-2008)

ARDL Fiscal deficit Effect of fiscal policy on

economic growth.

Fiscal deficit is inversely related to economic growth

in the long run.

Gallo and

Sagales (2011)

Panel of 43 upper,

middle and high

income countries.

(1972-2006)

Instrumental

variables.

Disaggregated expenditures

and taxes. Contribution of fiscal

policy in economic

growth and inequality.

Higher consumption expenditures and direct taxes

reduce the economic growth and inequality whereas

investment expenditures reduce the inequality

without reducing growth.

Acosta

Ormaechea and

Yoo (2012)

69 high, middle

and low income

countries.

(1970-2010)

Pooled Mean

Group (PMG)

Tax revenue as a percentage

of GDP, tax-composition

variables as a share of total tax

revenue.

Relationship between tax

composition and

economic growth.

Direct taxes specifically income tax negatively

contributes to economic growth while indirect taxes;

VAT and sales taxes significantly contribute to

growth.

Ormaechea and

Morozumi

(2013)

56 low, medium

and high income

countries.

(1970-2010)

GMM, fixed

effects.

Total expenditures and

disaggregated into defence,

education, health, social

protection and transport and

communication spending.

Link between public

expenditures and

economic growth.

Reallocation of expenditures, an increase in

education spending by a fall in social protection

significantly contributes to economic growth.

Aggregate spending negatively contributes to growth.

Gangal and

Gupta (2013)

India.

(1998-2012)

Cointegration

and Granger

Causality.

Aggregate public

expenditures.

Connection between

public expenditures and

economic growth.

Aggregate public expenditures are positively

associated with growth.

Morozumi and

Veiga (2014)

80 developed and

developing

countries.

(1970-2010)

GMM Aggregated and disaggregated


The role of institutions in

spending growth

relationship.

Findings show that capital expenditures significantly

contribute to economic growth when complement

with institutional quality. Current expenditure does

not show robust growth enhancing effect. Aggregate

spending and revenues positively contributes to

growth.

256

Monetary policy and economic growth author country technique Monetary policy measures main objective main findings

Christiano et al.

(1996)

US

(1960Q1-1992Q4)

VAR Federal funds rate, non-

borrowed reserves.

Effect of monetary policy

shocks on different sectors of

the economy.

Monetary shock affects the macroeconomic

aggregates; decline in real GDP, employment,

retail sales, non-corporate financial profits and a

sharp decline in prices. It increases the

unemployment and manufacturing inventories.

Fatima and

Iqbal (2003)

5 developing

countries from South

and East Asia.

(1970-2000)

Cointegration,

Granger

causality.

Money supply and

government expenditures as

indicators of monetary and

fiscal policy respectively.

Relative effectiveness of

fiscal and monetary policies.

In case of Indonesia, Pakistan and India only

monetary policy is powerful while in case of

Malaysia and Thailand both fiscal as well as

monetary is effective.

Cheng (2006) Kenya.

(1976-2005)

VAR Short term interest rate. Effect of the interest rate on

output, prices and exchange

rate.

A contractionary monetary policy shock reduces

the prices but has insignificant effect on output.

Moreover it appreciates the exchange rate.

Ali et al. (2008) South Asian

countries.

(1990-2007)

ARDL Fiscal balance and broad

money represent fiscal and

monetary policy

respectively.

Relative significance of fiscal

and monetary policies.

Monetary policy is an effective tool than fiscal

policy in order to boost economic growth.

Buigut (2009) East African

countries.

(1984-2005)

VAR Short term interest rate. Effect of the interest rate

channel on output and prices.

Interest rate channel does not seem to be appear

so important as the monetary policy shock

remains insignificant while it has a very small

effect on inflation.

Gul et al. (2012) Pakistan

(1995-2010)

regression interest rate Linkage between monetary

policy instruments and

economic growth.

Tight or contractionary monetary policy in terms

of higher interest rate is inversely related to

economic growth by discouraging the private

investment.

Hussain and

Siddiqi (2012)

Pakistan

(1976 to 2008)

ARDL Fiscal policy: government


Monetary policy: money

supply and interest rate.

Institutions: civil liberty,

political rights and polity.

Relationship between fiscal,

monetary policies,


growth.

Monetary policy is effective and economic

institutions play an important role in increasing

the per capita GDP growth. Fiscal policy,

political and social institutions have no

significant association with economic growth.

Coric et al.

(2012)

48 lower-middle,

upper-middle and

high-income

countries.

(1975-2009)

Regression,

Structural

VAR.

Money supply and domestic

interest rate.

Influence of monetary policy

shocks on output and prices.

In countries having more flexible exchange rate,

higher financial openness, larger financial sector

and greater share of trade in GDP a

contractionary monetary policy shock has a

larger negative effect on output and prices.

257

Younus (2013) Bangladesh (1980-

2011)

Cointegration

and Granger

Causality.

Broad money and

government expenditures

represent monetary and

fiscal policy.

Effectiveness of fiscal and

monetary policy on output

growth.

Monetary policy has relatively stronger impact

than that of fiscal policy on output growth.

Fetai (2013)

66 emerging

countries.

(1980 to 2010)

Regression,

GMM

Monetary policy: Discount

rate, international reserves.

Fiscal policy: budget

balance.

Relative effectiveness of

fiscal and monetary policies

during financial crises.

Fiscal policy is a more powerful tool than

monetary policy in the course of financial crisis.

Ivrendi and

Yildirim (2013)

Six emerging

economies.

(1995: M01-

2012:M08)

VAR Short term interest rate. Influence of monetary policy

shocks on macroeconomic

variables.

Contractionary monetary policy shock

appreciates the domestic currency, increases the

interest rate, controls the inflation, reduces the

output and trade balance.

Kandil (2014) 105 developing

countries.

(1968- 2008)

regression Money supply growth

represents monetary policy.

Effects of monetary policy

shocks on output and prices.

Positive monetary policy shocks increase the

real output growth, average trend growth and

reduce the variability of output. Demand side

channel portray a significant role.

258

Policy volatility and economic growth

author country technique measure of policy volatility main objective main findings

Fiscal policy volatility and economic growth Aizenman and

Marion (1991)

46 developing

countries.

(1970-85)

regression Standard deviation of the

residual through

autoregressive process

measures the volatility of

different measures of fiscal

and monetary policy.

Links between policy

uncertainty (fiscal and

monetary policy

uncertainty) and growth.

Policy volatility is inversely related to economic

growth.

Ramey and

Ramey (1995)

92 developed and

developing

countries (1960-

1985).

Fixed effects. Standard deviation of growth

rates of variables represents

volatility.

Analysis of government

spending volatility and

economic growth.

There is evidence of an inverse association

between government spending-induced volatility


Gong and Zou

(2002)

90 developed and

developing

countries.

(1970-1994)

regression Variance of the growth rate of

public expenditures measures

volatility.

Consequences of public

expenditure volatility on

economic growth.

Volatility of both the current and capital

expenditures is inversely related to economic

growth.

Ali., M.

Abdiweli (2005)

90 developed and

developing

countries.

(1975-1998)

regression The standard deviation of the

residual measures the

volatility of aggregated and

disaggregated expenditures

and revenues.

Effect of volatility of fiscal

policy on economic growth.

Almost all the fiscal volatility measures are

negatively associated with economic growth.

Sirimaneetham

Vatcharin (2006)

65 developing

countries.

(1970-99)

regression Policy volatility is measured

by standard deviation of the

residual.

Effect of volatility of

macroeconomic, fiscal and

development policies on

economic growth.

Only macroeconomic volatility is inversely

related to economic growth while fiscal and

development policy volatility remain

insignificant in explaining the growth.

Davide Furceri

(2007)

116 developed and

developing

countries.

(1970-2000)


government expenditure

measures the volatility.

Association between

cyclical volatility of

expenditures and long run

growth.

Government expenditure volatility is negatively

associated to long run growth of developing

countries whereas it has a smaller effect on

OECD countries.

Fatas and Mihov

(2008)

91 developed and

developing

countries.

(1960-2000).

Instrumental

variables.

Volatility of residual of

government spending

represents fiscal volatility.

Effect of fiscal policy

volatility on economic

growth, investment and

output volatility.

Volatility of fiscal policy leads to more volatility

of output, which in turn lowers investment and

leads to slower economic growth.

Afonso and

Jalles (2012)

Cross country.

(1970-2008)

GMM Standard deviation of

aggregate government


Link between fiscal

volatility, financial crisis


Fiscal policy volatility lowers the economic

growth.

259

Monetary policy volatility and economic growth

Peterson (1998) 87 developed and

developing

countries.

(1968-92)

Comparison of

growth rates in

different

periods.

Standard deviation of money

supply growth.

Effect of monetary instability

on economic growth.

Higher money supply instability contributes to

slower growth.

Ismail et al.

(1999)

Malaysia.

monthly data from

(1998-2002)

regression Volatility is measured by

conditional variance of 3

month Treasury bill rate from

the GARCH.

Relationship between interest

rate uncertainty and economic

activity.

There is an inverse correlation between

interest rate uncertainty and aggregate output.

Bo and Sterken

(2002)

82 listed Dutch

listed firms.

(1984–1995)

Fixed effects The ARCH model of volatility

and the variance of the

residual through AR(1).

Effect of interest rate volatility

and debt on firm investment.

Higher interest depresses the firm investment

while the interest rate volatility shows

ambiguous result. Joint effect of interest rate

volatility and debt increases the investment.

Bloom and Bond

(2007)

UK

manufacturing

firms.

(1972-91).

GMM Standard deviation of daily

stock returns measure

volatility.

Dynamics of uncertainty and

investment both at aggregate

and also firm level.

Higher interest rate uncertainty decreases the

effect of demand shocks on investment.

Gulen and Ion

(2013)

data of 7861 US

firms from (1987-

2011)

Fixed effects Uncertainty index by Baker,

Bloom, and Davis (2012).


uncertainty and corporate

investment.

Policy uncertainty reduces the industry and

firm investment. Effect is stronger for firms

having higher degree of irreversibility,

financial constraints and less competitive.

Bretscher et al.

(2016)

Cross section of

1600 firms.

(1994-2014)

regression Uncertainty is measured by

treasury implied volatility.

Consequences of interest rate

uncertainty on investment

behaviour.

Uncertainty adversely affects the investment

both at the aggregate and firm level. The link

is stronger in more financially constrained and

levered firms.

Capital flows volatility and economic growth Lensink and

Morrissey

(2001)

88 developed and

developing

countries.

(1975-1998)

OLS

regression,

instrumental

variables.

Volatility is measured by

standard deviation of residual

from the autoregressive

process.

Link between FDI flows,

volatility and economic

growth.

FDI volatility has a negative effect on

economic growth.

Sulla and

Willett (2007)

35 emerging

economies.

(1990-2003)

OLS, Seeming

unrelated

regression

(SUR)

Standard deviation of capital

flows.

Reversal of various type of

capital flows.

Excluding FDI, all other capital flows exhibit

large reversals throughout crises. Reversals of

capital inflows have severe consequences in

the form of output losses.

Demir Firat

(2009)

3 emerging

economies.

(1991-2001)

GMM Standard deviation of net short

term net capital inflows

represents volatility.

Link between volatility of

short term capital flows and

private investment.

Volatility of the short term capital inflows is

inversely related to economic growth.

260

Ferreira and

Laux (2009)

Panel of 50

countries.

Fixed effects Standard deviation of the

residual of portfolio flows.

Link between portfolio flows,

volatility and growth.

Volatility does not have any detrimental effect

on growth.

Choong et al.

(2011)

5 ASEAN

countries.

(1974-2005)

ARDL Standard deviation of the

residual through AR (1)

process and EGARCH

represents the volatility of

FDI.

Relationship between foreign

direct investment volatility


FDI volatility is negatively related to

economic growth in Indonesia, Malaysia,

Philippines and Thailand while it has a

negligible effect on Singapore.

Carp (2014) Emerging

economies.

(1991 – 2012)

Pearson

correlation.

Standard deviation of the

residual of capital flows.


flow volatility and economic

growth.

Volatile capital flows exert an adverse impact

on economic growth.

Neanidis (2015) 78 developed and

developing

countries.

(1973-2013)

Regression,

GMM

Standard deviation of capital

flows represents volatility.

Relation between volatile

capital flows and economic

growth.

Volatility of all the capital flows, aggregated

and disaggregated, (FDI, equity and debt

flows) are negatively related to economic

growth.

Trade flows volatility and economic growth Yotopoulos and

Nugent (1976)

Cross section of

38 developing

countries.

(1958-68)

regression Squared deviations represent

export instability.

Consequences of export

instability for economic

growth.

Export instability reduces the marginal

consumption thereby increasing savings and

higher growth.

Ozler and

Harrigan (1988)

26 developing

countries from

(1963-82)

regression Instability index is measured

by applying autoregressive

conditional heteroscedasticity

(ARCH) model.

Effect of export instability on

economic growth and

investment.

Findings exhibit that export instability is

negatively related to economic growth and

investment.

Love (1989) 20 developing

countries.

Granger and

Sims causality

Instability is measured by

absolute deviations from a

five-year moving average.

Impact of export instability on

income instability.

Export instability brings instability in capital

goods imports and, in turn, investment and

growth.

Gyimah-

Brempong

(1991)

34 Sab Saharan

African countries.

(1960-86)

regression The coefficient of variation

and the mean of the absolute

difference between actual and

estimated value.

Correlation between export

instability and economic

growth.

Export instability has a negative effect on

economic growth.

Sinha (1999) Nine Asian

countries.

(1950-97)

Johanson

cointegration.

Deviations of actual exports

from a five-year moving

average.

Reaction of export instability

to investment and economic

growth.

In some countries export instability is

negatively related to economic growth while

in others

there is evidence of a positive association.

Chaudhary and

Qaisrani (2002)

Pakistan

(1972-94)

regression Not mentioned. Association between trade


growth.

Export instability does not affect economic

growth and investment.

261

Kaushik et al.

(2008)

India

(1971 to 2005)

Johanson

cointegration.

Export instability is measured

through squared deviations.

Link between export


growth.

Export instability is inversely related to short-

run stability and directly related to longer-run

growth of income.

Rashid et al.

(2012)

SAARC

countries.

(1972-2008)

Johanson

cointegration.

Instability index is measured

through trend method.

Effect of export instability on

economic growth.

Export instability is inversely related to

economic growth for all countries.

External factors volatility and economic growth Mendoza (1997) 40 industrial and

developing

countries.

(1970-91)


residual through autoregressive

process measures volatility.

Association between term

of trade uncertainty and

economic growth

Term of trade volatility adversely affect the

economic growth through consumption growth.

Andrews and

Rees (2009)

71 countries.

(1971–2005)

Fixed effects Standard deviation term of

trade growth represents

volatility.

Correlation between term

of trade volatility and

macroeconomic volatility.

Term of trade volatility increases the volatility

of output growth. It also enhances the

consumption, exports and imports volatility.

Olaberria and

Rigolini (2009)

80 emerging

economies.

(1966-2005)

GMM Standard deviation of residuals

through AR (1) process

represents volatility of each

respective variable.

Effect of East Asia’s

macroeconomic volatility

on economic growth.

Findings show that beside the volatility of

domestic factors volatility of external factors or

shocks has also contributed to the slow growth

of emerging economies.

Abaidoo (2012) 39 Sub Saharan

African countries.

(1980-2011)

Fixed effects Volatility is measured by

standard deviation of specific

macroeconomic variable.

Effect of macroeconomic

volatility on

macroeconomic indicators.

External macroeconomic volatility has higher

impact on macroeconomic measures as

compared to domestic volatility.

262

Determinants of policy volatility

author country technique determinants of policy volatility main objective main findings

Determinants of capital flows volatility Beck Ronald

(2001)

54 emerging and

developing

countries.

(1990-98)

regression Share of foreign bank numbers

and share of foreign bank assets,

macroeconomic and institutional

variables.

Role of foreign banks and

trade liberalization regimes to

capital flow instability in

emerging markets.

Findings show that foreign bank penetration

enhances the volatility of capital flows.

Regulatory environment represented by rule of

law matters more than macroeconomic

indicators.

Alfaro et al.

(2005)

Sample of 97

countries.

(1970-2000)

regression Macroeconomic policy variables,

GDP per capita and institutional

quality.

Determinants of capital flows

volatility.

Institutional quality remains insignificant in

explaining the volatility of capital flows.

Inflation, inflation volatility and government

consumption increases the volatility. GDP per

capita reduces the volatility.

Broner and

Rigobon (2005)

58 countries.

(1965-2003)

regression Domestic macroeconomic factors,

external factors, income per

capita, financial development and

institutional quality.

Motives behind the higher

volatility of capital flows in

emerging countries.

Findings show that internal and external

macroeconomic factors contribute very little to

volatility of capital flows. Financial

development, good institutional quality and

higher per capita income reduce the volatility

of capital flows.

Broto et al.

(2008)

48 emerging and

developing

countries.

(1980-2006)


financial sector variables, global

factors, institutional variables.

Factors contributing to the

volatility of various capital

inflows (FDI, portfolio and

other inflows).

Financial sector do play a stronger role in

reducing the volatility of capital flows. Global

factors are important in reducing the volatility

as compared to domestic factors. Economic and

political stability discourages the capital flows

instability.

Neumann and

Tanku (2009)

22 developing and

developed

countries.

(1981–2000)

regression Financial liberalization, volatility

of domestic output growth and global factors.

To examine the volatility of

capital flows.

FDI flows show increase in volatility in

emerging markets as a result of liberalization.

Higher world growth volatility increases the

volatility of portfolio and other flows while

reduces the volatility of FDI inflows.

Mercado and

Park (2011)

50 emerging

market economies.

(1980–2009)


financial indicators, global

economic indicators, institutional

quality.

Factors that determine the

size and variability of various

capital inflows.

Trade openness and volatility of real exchange

rate contribute to the volatility of all capital

inflows. Per capita income, financial

development, institutional quality and global

liquidity lower the volatility of capital inflows. Globan (2012) 75 developed and

developing

countries.

regression FDI, loan and total capital

inflows, GDP per capita, debt.


reversals of capital flows

during global financial crisis.

Countries with higher dependence on foreign

loan rather than FDI financing observed higher

reversals of foreign capital during the crisis.

263

Waqas et al.

(2015)

South Asian

countries.

(2000-2012)

GARCH

methodology.

Macroeconomic variables

include; interest rate, exchange

rate, inflation, industrial

production, GDP growth rate,

foreign direct investment.

Determinants of volatility of

portfolio investment.

Inflation rate reduces the volatility only in case

of China and India. Real exchange increases

the volatility in case of China. In Pakistan and

India, higher interest rate raises the volatility.

Foreign direct investment, industrial production

and economic growth reduce the volatility in

all countries.

Determinants of trade flows volatility

Massell (1970) 55 developed and

developing

countries.

(1950-66)

regression Commodity concentration,

geographic concentration, food

and raw materials, domestic

consumption, size of the export

sector and per capita income.

Relationship between export

instability and a set of

variables that describe an

economy’s structure.

Less export diversification and higher domestic

consumption increases the instability. Higher

size of the export sector, specialization in food

items and higher level of development reduce

the instability.

Aslam (1985) Pakistan

(1961 to 1980)

regression Commodity and geographical

concentration, size of the export

sector, income per capita, share of

food and raw material exports.

Determinants of export

instability.

Geographical concentration reduces the

instability of exports while commodity

concentration remains insignificant. Size of the

export sector, higher per capita income, export

share of raw material reduces instability.

Charette (1985) 15 less developing

countries primary

commodity

markets.

(1960-1970's)

regression Geographical concentration,

Percentage of exports as a share

of domestic output.

Determinants of export

instability.

Higher share of exports out of domestic

production reduces the instability of exports

earnings, prices and output. Geographical

concentration reduces the instability also.

Sarada et al.

(2006)

India

(1981-2004)

Johansen

Cointegration

Commodity concentration and

geographical concentration,

shrimp production, fisheries and

non-fisheries GDP.

Determinants of Indian sea

food export instability.

Commodity concentration reduces the

instability. Geographical concentration, the

instability of fisheries and non-fisheries GDP

and instability of shrimp production increases

the instability of seafood export.

Baum and

Caglayan

(2009)

Eurozone countries

and newly

industrialized

countries.

(1980-2006)

GARCH Exchange rate uncertainty. Association between

exchange rate instability and

instability of trade flows.

Exchange rate instability significantly

contributes to the instability of bilateral trade

flows.

Neena (2015) India

(1987-2013)

regression Instability index of different

export categories, commodity

and geographic concentration.

Sources of export instability. Instability of textile and petroleum products

reduces the export instability while of primary,

chemical and engineering products and

geographical concentration increases the export

instability.

264

Determinants of fiscal policy volatility

Henisz (2004) 91 developed and

developing

countries.

(1971-92)

Fixed effect Checks and balances on policy

makers are represented by political

constraints index, macroeconomic

volatility.

Correlation between political

institutions and fiscal

volatility.

Findings show that higher political constraints

reduce the volatility of different categories of

capital and current expenditures as well as tax

and non-tax revenues. Macroeconomic

volatility is negatively associated with fiscal

policy volatility.

Fatas and

Mihov (2008)

&

Fatas and

Mihov (2013)

Ninety-one

developed and

developing

countries.

(1960-2000).

Instrumental

variables.

Institutional variables (political

constraints, constraints on the

executive, political and electoral

system and number of elections),

macroeconomic and demographic

variables.

Effect of fiscal policy

volatility and institutions on

economic growth and

investment.

Institutional quality considerably contributes to

fiscal policy volatility. Urbanization increases

the volatility while openness and GDP per

capita reduces the volatility of fiscal policy.

Agnello and

Sousa (2009)

Panel of 125

countries.

(1980-2006)

GMM Political instability, democracy and

macroeconomic determinants of

fiscal policy volatility.

Determinants of public

deficit volatility.

Higher political instability increases the

volatility of public deficit while democracy

reduces the volatility. GDP per capita reduces

the volatility of budget deficits. Higher

inflation, openness and fiscal deficit increase

the fiscal volatility.

Bleaney and

Halland (2009)

75 countries.

(1980-2004)

regression Institutional constraints, rule of

law, electoral system, per capita

income, primary product exports.

Effect of primary exports on

growth, growth volatility and

fiscal volatility.

Institutional constraints and per capita income

reduce the volatility of fiscal policy. Higher

share of primary exports enhances the fiscal

volatility.

Albuquerque

Bruno (2010)

25 EU countries.

(1980-2007)

fixed and

random

effects.

Political and institutional variables

(type of the polling system, the

number of elections, cabinet

changes), macroeconomic

variables.

Effect of institutional quality

on volatility of discretionary

fiscal policy.

Fiscal institutions reduce the volatility of fiscal

policy significantly. Bigger countries and larger

government reduce government spending

volatility.

Attiya et al.

(2011)

South Asian and

ASEAN countries.

(1984-2010)

GMM Macroeconomic factors, political

and institutional factors (political

stability, democracy, low level of

corruption, less conflict).

Determinants of fiscal deficit

volatility.

Income per capita, deficit to GDP, inflation and

openness increase the volatility of budget

deficit. Moreover budget deficit volatility has

persistence effect. Population growth and all

the political and institutional variables reduce

the volatility of budget deficit.

Agnello and

Sousa (2014)

113 countries.

(1980-2006)

GMM Political and institutional

determinants, macroeconomic

economic variables.

Factors contributing to the

volatility of fiscal discretion.

Higher democracy and parliamentary system

reduces volatility. Higher government turnover

increases volatility. Country size and less

flexible exchange rate decrease the volatility.

265

Determinants of monetary policy volatility

Koedijk et al.

(1997)

US

(January 1968–July

1996)

CKLS and

GARCH

model.

Short term interest rate. Dynamics of short term

interest rate volatility.

Interest rate volatility is determined by

GARCH and level effects.

Ball and Torous

(1999)

Cross country EGARCH

model

Variety of short term interest rates. Dynamics of short-term

interest rates.

Interest rate dynamics are influenced by

economic shocks.

Edwards and

Susmel (2003)

Latin American

and Asian

countries.

(weekly data 1994-

1999)

univariate

and bivariate

switching

volatility

model.

Short term interest rate. Behavior of interest rate

volatility.

There is evidence of interest-rate volatility co-

movement across countries due to domestic and

international shocks.

Olweny (2011) Kenya

(1991M8 to

2007M12)

ARCH and

GARCH

models

Short term interest rate. Relationship between level of

short term interest rate and its

volatility.

Volatility is positively associated with the level

of the short term interest rate.

Duncan (2013) 56 developed and

developing

countries.

(1984.Q -2008.Q4)

Instrumental

variables

Institutional quality, Financial

openness, central bank

independence, output volatility,

inflation.

Consequences of a better

institutional quality for the

cyclicity and volatility of

monetary policy.

The model shows a positive co-movement

between output and the interest rate at

relatively high levels of institutional quality.

Higher institutional quality reduces the interest

rate volatility.

266

11

12

13

14

15

16

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

21

22

23

24

25

26

27

28

29

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

14

15

16

17

18

19

20

90 92 94 96 98 00 02 04 06 08 10 12 14

India

16

17

18

19

20

21

22

23

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

10

15

20

25

30

35

40

45

50

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

12

13

14

15

16

17

18

19

20

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

14

15

16

17

18

19

20

21

22

23

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

16

18

20

22

24

26

28

30

32

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

15

16

17

18

19

20

21

90 92 94 96 98 00 02 04 06 08 10 12 14

Phillipines

18

20

22

24

26

28

30

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

12

14

16

18

20

22

24

26

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

14

16

18

20

22

24

26

28

30

90 92 94 96 98 00 02 04 06 08 10 12 14

Vietnam

Appendix III: Trends of the variables

Fiscal policy Government expenditures (% of GDP)

267

6

7

8

9

10

11

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

9

10

11

12

13

14

15

16

17

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

7

8

9

10

11

12

90 92 94 96 98 00 02 04 06 08 10 12 14

India

14

15

16

17

18

19

20

21

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

8

12

16

20

24

28

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

9

10

11

12

13

14

15

16

17

18

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

6

8

10

12

14

16

18

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

8

9

10

11

12

13

14

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

11

12

13

14

15

16

17

18

90 92 94 96 98 00 02 04 06 08 10 12 14

Philippines

10

12

14

16

18

20

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

12

13

14

15

16

17

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

12

16

20

24

28

32

90 92 94 96 98 00 02 04 06 08 10 12 14

Vietnam

Fiscal policy Tax revenue (% of GDP)

268

12.5

13.0

13.5

14.0

14.5

15.0

15.5

16.0

16.5

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

20

30

40

50

60

70

80

90

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

8

10

12

14

16

18

20

90 92 94 96 98 00 02 04 06 08 10 12 14

India

10

15

20

25

30

35

40

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

10

12

14

16

18

20

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

0

10

20

30

40

50

60

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

6

7

8

9

10

11

12

13

14

15

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

2

4

6

8

10

12

14

16

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

5

10

15

20

25

90 92 94 96 98 00 02 04 06 08 10 12 14

Philippines

6

8

10

12

14

16

18

20

22

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

4

6

8

10

12

14

16

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

5

10

15

20

25

30

35

90 92 94 96 98 00 02 04 06 08 10 12 14

Veitnam

Monetary policy

(Interest rate)

269

12

16

20

24

28

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

8

12

16

20

24

28

32

36

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

0

10

20

30

40

50

60

70

80

90

90 92 94 96 98 00 02 04 06 08 10 12 14

India

10

15

20

25

30

35

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

21.1

21.2

21.3

21.4

21.5

21.6

21.7

21.8

21.9

22.0

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

4

6

8

10

12

14

16

18

20

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

10

12

14

16

18

20

22

24

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

10

20

30

40

50

60

70

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

0

4

8

12

16

20

24

90 92 94 96 98 00 02 04 06 08 10 12 14

Philippines

8

12

16

20

24

28

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

8

12

16

20

24

28

32

36

40

44

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

4

8

12

16

20

24

90 92 94 96 98 00 02 04 06 08 10 12 14

Veitnam

Trade liberalization

(Average tariff rate)

270

15

20

25

30

35

40

45

50

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

14

16

18

20

22

24

26

28

30

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

10

20

30

40

50

60

90 92 94 96 98 00 02 04 06 08 10 12 14

India

45

50

55

60

65

70

75

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

100

120

140

160

180

200

220

240

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

20

30

40

50

60

70

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

30

35

40

45

50

55

60

65

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

28

30

32

34

36

38

40

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

50

60

70

80

90

100

110

90 92 94 96 98 00 02 04 06 08 10 12 14

Philippines

40

50

60

70

80

90

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

70

80

90

100

110

120

130

140

150

160

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

60

80

100

120

140

160

180

90 92 94 96 98 00 02 04 06 08 10 12 14

Vietnam

Trade liberalization

Trade openness (% of GDP)

271

40

45

50

55

60

65

70

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

30

40

50

60

70

80

90

100

110

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

10

20

30

40

50

60

70

80

90

90 92 94 96 98 00 02 04 06 08 10 12 14

India

60

70

80

90

100

110

120

130

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

60

80

100

120

140

160

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

50

60

70

80

90

100

110

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

20

30

40

50

60

70

80

90

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

40

44

48

52

56

60

64

68

72

76

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

80

90

100

110

120

130

140

150

90 92 94 96 98 00 02 04 06 08 10 12 14

Philippines

72

76

80

84

88

92

96

100

104

108

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

0

20

40

60

80

100

120

140

160

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

20

40

60

80

100

120

140

90 92 94 96 98 00 02 04 06 08 10 12 14

Vietnam

Financial Liberalization

Gross capital flows (% GDP)

272

3

4

5

6

7

8

9

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

5

10

15

20

25

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

0

2

4

6

8

10

90 92 94 96 98 00 02 04 06 08 10 12 14

India

6

7

8

9

10

11

12

13

14

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

0

5

10

15

20

25

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

4

8

12

16

20

24

28

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

0

4

8

12

16

20

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

0

10

20

30

40

50

90 92 94 96 98 00 02 04 06 08 10 12 14

Philippines

4

6

8

10

12

14

16

18

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

0

4

8

12

16

20

24

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

0

20

40

60

80

100

120

140

90 92 94 96 98 00 02 04 06 08 10 12 14

Vietnam


FDI inflows (% GDP)

273

-.1

.0

.1

.2

.3

.4

.5

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

-5

0

5

10

15

20

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

-8

-4

0

4

8

12

16

20

90 92 94 96 98 00 02 04 06 08 10 12 14

India

-8

-7

-6

-5

-4

-3

-2

-1

0

1

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

-.5

-.4

-.3

-.2

-.1

.0

.1

.2

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

-4

-2

0

2

4

6

8

10

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

-6

-5

-4

-3

-2

-1

0

1

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

-8

-4

0

4

8

12

16

20

24

28

90 92 94 96 98 00 02 04 06 08 10 12 14

Philippines

-0.8

-0.4

0.0

0.4

0.8

1.2

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

-8

-4

0

4

8

12

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

-4

-3

-2

-1

0

1

2

3

4

90 92 94 96 98 00 02 04 06 08 10 12 14

Vietnam


Portfolio inflows (% GDP)

274

-1.2

-1.1

-1.0

-0.9

-0.8

-0.7

-0.6

-0.5

90 92 94 96 98 00 02 04 06 08 10 12 14

Bangladesh

-.15

-.10

-.05

.00

.05

.10

.15

90 92 94 96 98 00 02 04 06 08 10 12 14

Brazil

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

India

-.85

-.80

-.75

-.70

-.65

-.60

-.55

90 92 94 96 98 00 02 04 06 08 10 12 14

Kenya

-.4

-.2

.0

.2

.4

.6

90 92 94 96 98 00 02 04 06 08 10 12 14

Maldives

-.4

-.3

-.2

-.1

.0

.1

90 92 94 96 98 00 02 04 06 08 10 12 14

Mexico

-1.1

-1.0

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

90 92 94 96 98 00 02 04 06 08 10 12 14

Nepal

-1.2

-1.1

-1.0

-0.9

-0.8

-0.7

90 92 94 96 98 00 02 04 06 08 10 12 14

Pakistan

-.6

-.5

-.4

-.3

-.2

-.1

.0

.1

90 92 94 96 98 00 02 04 06 08 10 12 14

Philippines

-.50

-.45

-.40

-.35

-.30

-.25

-.20

-.15

-.10

90 92 94 96 98 00 02 04 06 08 10 12 14

Srilanka

-.4

-.3

-.2

-.1

.0

.1

.2

.3

.4

90 92 94 96 98 00 02 04 06 08 10 12 14

Thailand

-.60

-.56

-.52

-.48

-.44

-.40

90 92 94 96 98 00 02 04 06 08 10 12 14

Veitnam

Institutional Quality

Governance index (-2.5 to 2.5)

275

0

2

4

6

8

10

12

14

50 100 150 200 250 300

fiscal policy volatility (govt. exp. vol)

0

10

20

30

40

50

60

70

50 100 150 200 250 300

trade flows volatility

0

10

20

30

40

50 100 150 200 250 300

monetary policy volatility (interest rate vol)

0

10

20

30

40

50

50 100 150 200 250 300

volatility of gross capital flows

0

4

8

12

16

20

24

50 100 150 200 250 300

portfolio inflows volatility

-40

-20

0

20

40

60

50 100 150 200 250 300

FDI inflows volatility

276

Appendix IV: Policy volatility in selected countries

Fiscal policy volatility:

Table IVA: Volatility of government expenditures:

Note: values highlighted show the highest and lowest mean volatility.

Countries with low volatility: India, Bangladesh and Mexico are less volatile. India has the lowest

volatility.

Countries with high volatility: Maldives, Thailand, Nepal, Vietnam, Brazil, Kenya and Pakistan, Srilanka

and Philippines are more volatile. Maldives has highest volatility.

Table IVB: Volatility of tax revenue:

countries mean st. dev conclusion

sample 0.371435 0.25176

Bangladesh 0.371435 0.256728

Brazil 0.639073 0.498674 More volatile

India 0.746015 0.637084 More volatile

Kenya 1.050356 1.140975 More volatile

Maldives 1.441895 1.688477 More volatile

Mexico 0.69162 0.659662 More volatile

Nepal 0.456427 0.393752 More volatile

Pakistan 0.577324 0.513079 More volatile

Philippines 0.49723 0.365531 More volatile

Srilanka 0.535333 0.402578 More volatile

Thailand 1.119483 0.82626 More volatile

Vietnam 0.992825 0.81804 More volatile


Countries with low volatility: Only Bangladesh is less volatile.

Countries with high volatility: All other countries are more volatile. Maldives has highest volatility.


sample 0.845557 0.724544

Bangladesh 0.845557 0.738841


India 0.675428 0.45284 Less volatile



Mexico 0.76428 0.62359 Less volatile







277

Monetary policy volatility: Table IVC: Volatility of interest rate: countries mean st. dev conclusion

sample 3.061241 4.68077

Bangladesh 3.061241 4.773135



Kenya 1.69735 2.039695 Less volatile

Maldives 1.426535 1.000072 Less volatile


Nepal 1.098336 0.992405 Less volatile

Pakistan 1.361078 1.346797 Less volatile

Philippines 1.475784 1.24348 Less volatile

Srilanka 2.182876 1.385985 Less volatile

Thailand 2.613641 4.102664 Less volatile

Vietnam 1.721329 1.677794 Less volatile


Countries with low volatility: All the countries are less volatile except Brazil.

Trade flows volatility:

Table IVD: Volatility of trade flows:


sample 2.43331 2.030559

Bangladesh 2.43331 2.070627

Brazil 1.415308 1.189719 Less volatile












Countries with low volatility: Brazil, India and Bangladesh are less volatile. Brazil has lowest volatility.

Countries with high volatility: Maldives, Vietnam, Thailand, Kenya, Srilanka, Pakistan, Philippines, Nepal

and Mexico are more volatile. Maldives has highest volatility.

278

Capital flows volatility:

Table IVE: Volatility of FDI inflows:


sample 2.313539 5.453756

Bangladesh 0.261717 0.202579 Less volatile













Countries with low volatility: Nepal, India, Bangladesh, Pakistan, Maldives, Brazil, Kenya and Mexico

are less volatile. Nepal has lowest volatility

Countries with high volatility: Vietnam, Philippines and Thailand are more volatile. Vietnam has highest

volatility.

Table IVF: Volatility of portfolio inflows:


sample 1.164023 2.443761

Bangladesh 0.221066 0.172438 Less volatile











Vietnam 0.699684 1.082116 Less volatile


Countries with low volatility: Nepal, Kenya, Maldives, Bangladesh, India, Brazil, Pakistan, and Vietnam

are less volatile. Nepal has lowest volatility.

Countries with high volatility: Philippines, Thailand and Mexico are more volatile. Philippines has highest

volatility.

279

Appendix V: Cyclical behaviour of policies in selected countries

Cyclical behaviour of fiscal policy (government expenditures):

Table VA: Cross Correlation between GDP and government expenditures at t+i and t-i (i = 0……2)

countries t-2 t-1 t t+1 t+2 Nature of co-movement conclusion

sample -0.0612 -0.1332 -0.3766 -0.1138 0.0189 countercyclical and coincident Stabilizing effect

Bangladesh -0.5753 -0.7424 -0.8859 -0.5862 -0.3516 countercyclical and coincident Stabilizing effect

Brazil -0.3415 -0.464 -0.5275 -0.3249 -0.1292 countercyclical and coincident Stabilizing effect

India -0.3058 -0.4589 -0.6388 -0.6002 -0.4962 countercyclical and coincident Stabilizing effect

Kenya -0.0866 -0.0542 -0.0051 -0.1002 -0.0526 acyclical No effect

Maldives -0.243 -0.2335 -0.3902 -0.2993 -0.1762 countercyclical and coincedent Stabilizing effect

Mexico -0.3527 -0.5325 -0.7537 -0.6294 -0.5452 countercyclical and coincedent Stabilizing effect

Nepal 0.0462 0.1291 0.1304 0.0871 0.0637 acyclical No effect

Pakistan 0.3398 0.5501 0.7636 0.6633 0.581 procyclical and coincedent Destabilizing

effect

Philippines -0.6436 -0.8183 -0.9045 -0.6273 -0.3707 countercyclical and coincedent Stabilizing effect

Srilanka -0.384 -0.5208 -0.6409 -0.4832 -0.3206 countercyclical and coincedent Stabilizing effect

Thailand -0.2457 -0.2272 -0.2597 -0.193 0.0286 acyclical No effect

Vietnam 0.1096 0.1841 0.1316 0.294 -0.2577 acyclical No effect

Note: Values highlighted show the coefficients those are statistically significant at 5% significance level.

Cyclical behaviour of fiscal policy (tax revenue):

Table VB: Cross Correlation between GDP and tax revenue at t+i and t-i (i = 0……2)


sample 0.1188 0.0408 -0.219 -0.0662 -0.0187 acyclical No effect

Bangladesh -0.1554 -0.0446 0.0821 0.0363 -0.0065 acyclical No effect

Brazil 0.0782 -0.054 -0.5608 -0.1036 0.0746 procyclical and coincident Destabilizing

effect

India -0.3911 -0.3911 -0.5196 -0.3619 -0.3056 procyclical and coincident Destabilizing

effect

Kenya -0.1811 -0.0803 0.1761 -0.0596 -0.0531 acyclical No effect

Maldives 0.0738 0.0258 -0.4954 -0.1062 -0.0278 procyclical and coincident Destabilizing

effect

Mexico -0.1356 -0.203 -0.1322 -0.4131 -0.3882 Procyclical and lags output by

one year.

Destabilizing

effect

Nepal 0.2954 0.4168 0.4289 0.4562 0.3199 countercyclical and coincident Stabilizing effect

Pakistan -0.2467 -0.2559 -0.2812 -0.289 -0.0845 acyclical No effect

Philippines 0.0227 -0.1445 -0.2997 -0.1101 -0.099 acyclical No effect

Srilanka -0.2505 -0.3213 -0.3049 -0.3253 -0.2972 Procyclical and lags output by

one year

Destabilizing

effect

Thailand -0.1321 -0.1019 -0.072 -0.0035 -0.026 acyclical No effect

Vietnam 0.2315 0.2708 0.2689 0.1204 -0.3337 procyclical and lags output by

two years

Destabilizing

effect


280

Cyclical behaviour of monetary policy (interest rate):

Table VC: Cross Correlation between GDP and interest rate at t+i and t-i (i = 0……2)


sample -0.2785 -0.2735 -0.3120 -0.3332 -0.3431 procyclical and lags output

by one year Destabilizing effect

Bangladesh -0.5292 -0.7439 -0.9859 -0.6558 -0.3942 procyclical and coincident Destabilizing effect

Brazil -0.3099 -0.1181 -0.0518 -0.0547 -0.0680 acyclical No effect

India -0.4263 -0.5656 -0.7237 -0.3816 -0.1835 procyclical and coincident Destabilizing effect

Kenya 0.1072 0.0470 -0.0888 -0.1684 -0.2248 acyclical No effect

Maldives 0.3235 0.4041 0.4696 0.3395 0.2400 countercyclical and

coincident Stabilizing effect

Mexico -0.0971 -0.1263 -0.1251 0.0007 0.1255 acyclical No effect

Nepal -0.2042 -0.2421 -0.3108 -0.1179 -0.0451 acyclical No effect

Pakistan -0.0464 0.1199 0.2167 0.3009 0.4413 countercyclical and lags

output by two years Stabilizing effect

Philippines -0.3253 -0.5216 -0.6494 -0.3723 -0.1810 procyclical and coincident Destabilizing effect

Srilanka -0.0382 -0.2077 -0.2004 -0.2502 -0.2093 acyclical No effect

Thailand -0.4001 -0.4625 -0.5445 -0.3081 -0.1618 procyclical and coincident Destabilizing effect

Vietnam -0.2254 -0.3491 -0.5328 -0.3344 -0.1440 procyclical and coincident Destabilizing effect


Cyclical behaviour of capital inflows (FDI inflows):

Table VD: Cross Correlation between GDP and FDI inflows at t+i and t-i (i = 0……2)


sample 0.0051 -0.0408 -0.1332 -0.0506 -0.0166 acyclical No effect

Bangladesh 0.008 -0.1227 -0.1391 0.0737 0.0541 acyclical No effect

Brazil -0.3189 -0.4185 -0.7562 -0.2599 -0.1193 countercyclical and


India -0.4171 -0.6513 -0.9296 -0.7108 -0.5026 countercyclical and


Kenya 0.0593 0.2238 0.7047 0.331 0.2773 procyclical and coincident Destabilizing effect

Maldives -0.0881 -0.1662 -0.2111 0.0502 0.1401 acyclical No effect

Mexico -0.0426 -0.0723 -0.0298 -0.144 -0.126 acyclical No effect

Nepal 0.4539 0.6185 0.8219 0.6622 0.498 procyclical and coincident Destabilizing effect

Pakistan 0.026 0.0482 0.0038 0.027 0.0122 acyclical No effect

Philippines -0.07 -0.0094 -0.122 -0.1862 -0.1832 acyclical No effect

Srilanka -0.2385 -0.3434 -0.6788 -0.3358 -0.2502 countercyclical and


Thailand -0.3267 -0.5693 -0.965 -0.5945 -0.3884 countercyclical and


Vietnam 0.1107 0.146 0.143 -0.0058 -0.2169 acyclical No effect


281

Cyclical behaviour of capital inflows (portfolio inflows):

Table VE: Cross Correlation between GDP and portfolio inflows at t+i and t-i (i = 0……2)


sample 0.0051 -0.0408 -0.1332 -0.0506 -0.0166 acyclical No effect

Bangladesh -0.0469 -0.0132 0.5508 0.1218 0.0999 procyclical and coincident Destabilizing effect

Brazil 0.0004 -0.095 -0.7668 -0.1946 -0.114 countercyclical and


India -0.1699 -0.2851 -0.4006 -0.305 -0.1803 countercyclical and


Kenya 0.3811 0.4581 0.5854 0.3044 0.1109 procyclical and coincident Destabilizing effect

Maldives 0.0456 0.0489 0.0682 0.1949 0.2285 acyclical No effect

Mexico 0.0433 0.0961 0.3403 0.0834 -0.0215 procyclical and coincident Destabilizing effect

Nepal 0.4808 0.6258 0.7863 0.5875 0.3812 procyclical and coincident Destabilizing effect

Pakistan 0.0383 -0.0721 -0.1149 -0.1484 -0.257 acyclical No effect

Philippines 0.017 0.1479 0.0846 -0.0655 -0.1373 acyclical No effect

Srilanka -0.057 -0.1868 -0.5454 -0.4006 -0.3857 countercyclical and


Thailand -0.115 -0.0632 0.1953 -0.0518 -0.1254 acyclical No effect

Vietnam 0.3586 0.5373 0.8192 0.5811 0.3427 procyclical and coincident Destabilizing effect

282

Table VF: Summary of cyclical behaviour of policies:

countries Govt. expenditures Tax revenue Interest rate FDI inflows Portfolio inflows conclusion

sample countercyclical acyclical procyclical acyclical acyclical

Bangladesh countercyclical acyclical procyclical procyclical procyclical Policy makers can use govt. expenditures as a hedge

against shock.

Brazil countercyclical procyclical

acyclical countercyclical countercyclical

Policy makers can use govt. expenditures, FDI inflows

and portfolio inflows as a hedge against shock.

India countercyclical procyclical procyclical countercyclical countercyclical Policy makers can use govt. expenditures, FDI inflows

and portfolio inflows as a hedge against shock.

Kenya acyclical acyclical acyclical acyclical procyclical

Maldives countercyclical procyclical countercyclical countercyclical acyclical Policy makers can use govt. expenditures, monetary

policy and FDI inflows as a hedge against shock.

Mexico countercyclical Procyclical acyclical countercyclical procyclical Policy makers can use govt. expenditures and FDI

inflows as a hedge against shock.

Nepal acyclical countercyclical acyclical procyclical procyclical Policy makers can use tax policy as a hedge against

shock.

Pakistan procyclical acyclical countercyclical acyclical acyclical Policy makers can use monetary policy as a hedge

against shock.

Philippines countercyclical acyclical procyclical acyclical acyclical Policy makers can use govt. expenditures as a hedge

against shock

Srilanka countercyclical Procyclical acyclical acyclical countercyclical Policy makers can use Govt. expenditures and portfolio

inflows as a hedge against shock

Thailand acyclical acyclical procyclical countercyclical acyclical Policy makers can use FDI inflows as a hedge against

shock.

Vietnam acyclical procyclical procyclical acyclical procyclical

283

-6

-4

-2

0

2

4

6

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt. exp

Bangladesh

-12

-8

-4

0

4

8

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt. exp

Brazil

-4

-2

0

2

4

6

8

10

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt exp.

India

-2

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt. exp

kenya

-8

-4

0

4

8

12

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt exp

Maldives

-10

-8

-6

-4

-2

0

2

4

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt exp

Mexico

-5

-4

-3

-2

-1

0

1

2

3

4

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt. exp

Nepal

-4

-3

-2

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt exp

Pakistan

-5

-4

-3

-2

-1

0

1

2

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt exp

Philippines

-3

-2

-1

0

1

2

3

4

5

6

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt exp

Srilanka

-4

-2

0

2

4

6

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt exp

Thailand

-8

-6

-4

-2

0

2

4

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP govt exp

Vietnam

Graphical analysis of cyclical behaviour of policies.

Cyclical behaviour of fiscal policy

Correlation between GDP and Government expenditures

284

-2

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Bangladesh

-10

-8

-6

-4

-2

0

2

4

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Brazil

-4

-2

0

2

4

6

8

10

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

India

-2

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Kenya

-4

-2

0

2

4

6

8

10

12

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Maldives

-4

-3

-2

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Mexico

-5

-4

-3

-2

-1

0

1

2

3

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Nepal

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Pakistan

-2

-1

0

1

2

3

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Philippines

-3

-2

-1

0

1

2

3

4

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Srilanka

-2

-1

0

1

2

3

4

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Thailand

-5

-4

-3

-2

-1

0

1

2

3

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP tax rev

Vietnam

Cyclical behaviour of fiscal policy

Correlation between GDP and tax revenue

285

-40

-30

-20

-10

0

10

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Bangladesh

-20

-10

0

10

20

30

40

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Brazil

-10

-5

0

5

10

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

India

-8

-4

0

4

8

12

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Kenya

-6

-5

-4

-3

-2

-1

0

1

2

3

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP intetrest rate

Maldives

-10

0

10

20

30

40

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Mexico

-4

-2

0

2

4

6

8

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Nepal

-6

-4

-2

0

2

4

6

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Pakistan

-8

-6

-4

-2

0

2

4

6

8

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Philippines

-6

-4

-2

0

2

4

6

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Srilanka

-8

-6

-4

-2

0

2

4

6

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Thailand

-8

-4

0

4

8

12

16

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP interest rate

Vietnam

Cyclical behaviour of monetary policy

Correlation between GDP and interest rate

286

-2

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Bangladesh

-12

-8

-4

0

4

8

12

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Brazil

-12

-8

-4

0

4

8

12

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

India

-2

-1

0

1

2

3

4

5

6

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Kenya

-6

-4

-2

0

2

4

6

8

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Maldives

-8

-4

0

4

8

12

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Mexico

-12

-10

-8

-6

-4

-2

0

2

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Nepal

-3

-2

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Pakistan

-20

-10

0

10

20

30

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Philippines

-2

0

2

4

6

8

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Srilanka

-15

-10

-5

0

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Thailand

-40

-20

0

20

40

60

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP FDI inflows

Vietnam

Cyclical behaviour of capital inflows

Correlation between GDP and FDI inflows

287

-1

0

1

2

3

4

5

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP Portfolio inflows

Bangladesh

-10

-5

0

5

10

15

20

90 92 94 96 98 00 02 04 06 08 10 12 14

GDP portfolio inflows

Brazil

-10

-5

0

5

10

15

20

90 92 94 96 98 00 02 04 06 08 10 12 14


India

-8

-6

-4

-2

0

2

4

90 92 94 96 98 00 02 04 06 08 10 12 14


Kenya

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

90 92 94 96 98 00 02 04 06 08 10 12 14


Maldives

-4

-2

0

2

4

6

8

90 92 94 96 98 00 02 04 06 08 10 12 14


Mexico

-6

-5

-4

-3

-2

-1

0

1

90 92 94 96 98 00 02 04 06 08 10 12 14


Nepal

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

90 92 94 96 98 00 02 04 06 08 10 12 14


Pakistan

-10

-5

0

5

10

15

20

25

30

90 92 94 96 98 00 02 04 06 08 10 12 14


Philippines

-0.8

-0.4

0.0

0.4

0.8

1.2

1.6

2.0

90 92 94 96 98 00 02 04 06 08 10 12 14


Srilanka

-8

-4

0

4

8

12

90 92 94 96 98 00 02 04 06 08 10 12 14


Thailand

-5

-4

-3

-2

-1

0

1

2

3

4

90 92 94 96 98 00 02 04 06 08 10 12 14


Vietnam

Cyclical behaviour of capital inflows

Correlation between GDP and portfolio inflows

288

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

0.0 0.4 0.8 1.2 1.6 2.0 2.4

fiscal policy volatility

econ

omic

gro

wth

Appendix VI: Scattered plots of variables (pair wise correlation)

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

3 4 5 6 7 8 9

govt. expenditures (% of GDP)

econ

omic

gro

wth

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

-1.1 -1.0 -0.9 -0.8 -0.7

institutional quality

econ

omic

gro

wth

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

2 4 6 8 10 12 14

interest rate

econ

omic

gro

wth

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

0 20 40 60 80 100 120 140

tariff rate

econ

omic

gro

wth

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

0.0 0.2 0.4 0.6 0.8 1.0 1.2

net FDI inflows (% of GDP)

econ

omic

gro

wth

289

0

2

4

6

8

10

-1.2 -1.1 -1.0 -0.9 -0.8 -0.7 -0.6 -0.5


trad

e flo

ws

voal

tility

.0

.1

.2

.3

.4

.5

-1.2 -1.1 -1.0 -0.9 -0.8 -0.7 -0.6 -0.5


capi

tal f

low

s vo

altil

ity

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

.40 .45 .50 .55 .60 .65 .70


fisca

l pol

icy

vola

tility

1.80

1.85

1.90

1.95

2.00

2.05

2.10

2.15

2.20

0.0 0.5 1.0 1.5 2.0 2.5

monetary policy volatility

econ

omic

gro

wth

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

.00 .01 .02 .03 .04 .05 .06 .07 .08

volatility of FDI inflows

econ

omic

gro

wth

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

0.0 0.4 0.8 1.2 1.6 2.0 2.4

trade flows volatilityec

onom

ic g

row

th

290

Appendix VII: Unit Root Test (Im, Pesaran and Shin (IPS))

Table VIIA Results of the unit root test:

Im, Pesaran and Shin W-stat

variables Level 1st Difference

Statistic Prob. Statistic Prob.

Economic growth -8.84783 0.0000* -15.3595 0.0000*

GDP per capita -4.13905 0.0000* -9.24540 0.0000*

Private capital stock -1.92892 0.0389* -12.0747 0.000*

Human capital -1.34802 0.0888** -4.21906 0.000*

Population growth -2.02781 0.0213* -3.10159 0.0010*

Institutional quality -3.16962 0.0008* -9.48141 0.0000*

Govt. expenditures -2.28235 0.0112* -14.0242 0.0000*

Tax revenue -1.43597 0.0501* -5.57544 0.0000*

Interest rate -1.49581 0.0474* -11.5019 0.0000*

Trade openness -2.43848 0.0074* -10.5498 0.0000*

Average tariff rate -1.56327 0.0490* -10.6388 0.0000*

Gross capital flows -1.18300 0.0784** -5.23312 0.0000*

Fiscal policy volatility -8.22254 0.0000* -19.0345 0.0000*

Monetary policy volatility -9.62713 0.0000* -24.4598 0.0000*

Trade flows volatility -10.8329 0.0000* -18.2460 0.0000*

Capital flows volatility -6.64604 0.0000* -18.3190 0.0000*

Inflation volatility -10.5538 0.0000* -15.3217 0.0000*

Financial development -9.15345 0.0000 0.0056* -4.42139 0.0000*

Exchange rate volatility -5.24132 0.0000* -15.9672 0.0000*

Export concentration -13.3802 0.0000* -19.2223 0.0000*

External debt -3.09266 0.0010* -12.1040 0.0000*

Central bank independence -9.54796 0.0000* -21.8706 0.0000*

Political constraints -4.59616 0.0000* -10.2196 0.0000*

Foreign growth volatility -7.30402 0.0000* -14.2082 0.0000*

Foreign interest rate volatility -10.0606 0.0000* -16.7115 0.0000*

TOT volatility -7.80977 0.0000* -17.3146 0.0000*

Note: To ensure that the residuals are white noise we have chosen lag length based on the Akaike Info

Criterion (0 to 4). Probabilities are computed assuming asympotic normality. * denote the rejection of null

hypothesis of unit root at 5 percent level of significance while ** denote the rejection of null hypothesis of

unit root at 10 percent level of significance.

Source: Authors’ calculation using Eviews-8 software.

291

Appendix VIII: Pairwise correlation matrix

Effect of policy volatility on economic growth

convergence

Human

capital

Physical

capital

Pop

growth

Institutional

quality

Fiscal

vol

Monetary

vol

Trade

vol

Capital

flows vol

Term of

trade vol

Foreign

growth vol

Foreign interest

rate vol

convergence 1.00

Human capital 0.39 1.00

Physical capital 0.27 0.49 1.00

Pop growth -0.31 -0.48 -0.51 1.00

Institutional quality 0.45 0.17 -0.54 0.38 1.00

Fiscal vol 0.04 -0.01 -0.07 -0.06 0.04 1.00

Monetary vol -0.06 0.43 0.39 -0.55 -0.44 0.30 1.00

Trade vol 0.01 0.27 0.25 -0.29 -0.41 -0.06 0.02 1.00

Capital flows vol -0.42 0.05 0.09 -0.14 -0.47 0.32 0.17 0.26 1.00

Term of trade vol 0.19 0.39 0.32 -0.53 -0.20 0.55 0.47 0.00 0.56 1.00

Foreign growth vol 0.06 0.13 0.03 -0.30 -0.16 0.42 0.55 -0.10 0.22 0.48 1.00

Foreign interest rate vol -0.35 -0.06 -0.02 -0.12 -0.22 0.48 0.43 0.06 0.39 0.43 0.40 1.00

292

Determinants of fiscal policy volatility

Previous

period vol

Inflation

vol

Per capita

income

Previous

period debt

Political

constraints

Foreign

growth vol

Term of

trade vol

foreign interest

rate vol

Previous period vol 1.00

Inflation vol -0.19 1.00

Per capita income 0.22 0.11 1.00

Previous period debt 0.29 0.14 0.11 1.00

Political constraints 0.06 0.25 -0.05 0.42 1.00

Foreign growth vol 0.42 -0.01 0.02 -0.14 -0.11 1.00

Term of trade vol 0.51 -0.25 0.10 -0.31 -0.25 0.48 1.00

Foreign interest rate vol 0.34 0.06 -0.24 0.17 0.33 0.27 0.24 1.00

Determinants of monetary policy volatility

Previous

period vol Inflation

vol Per capita

income Exchange

rate vol Previous

period debt Central bank

independence Foreign

growth vol Term of

trade vol foreign interest

rate vol


Inflation vol 0.03 1.00

Per capita income -0.20 0.11 1.00

Exchange rate vol 0.31 0.06 -0.26 1.00

Previous period debt -0.39 0.14 0.11 -0.25 1.00

Central bank independence 0.48 -0.19 -0.38 0.32 -0.17 1.00

Foreign growth vol 0.55 -0.01 0.02 -0.04 -0.14 0.15 1.00

Term of trade vol 0.42 -0.25 0.10 0.10 -0.31 0.22 0.48 1.00

Foreign interest rate vol 0.37 0.06 -0.24 0.37 0.17 -0.01 0.27 0.24 1.00

293

Determinants of capital flows volatility

Previous

period vol

Inflation

vol

Per capita

income

Exchange

rate vol

Financial

development

Economic

institutions

Foreign

growth vol

Term of

trade vol

Previous

period vol


Inflation vol -0.11 1.00

Per capita income -0.41 0.17 1.00

Exchange rate vol 0.39 -0.03 -0.17 1.00

Financial development -0.02 -0.05 0.17 0.05 1.00

Economic institutions -0.40 0.29 0.53 -0.43 0.00 1.00

Foreign growth vol 0.22 0.07 0.07 -0.02 0.03 -0.14 1.00

Term of trade vol 0.56 -0.06 0.20 0.20 0.11 -0.13 0.48 1.00

Foreign interest rate vol 0.38 -0.04 -0.34 0.42 -0.03 -0.22 0.39 0.43 1.00

Determinants of trade flows volatility

Previous

period vol

Per capita

income

Exchange

rate vol

Financial

development

Export

concentration

Economic

institutions

Foreign

growth vol

Term of

trade vol

Previous

period vol


Per capita income 0.02 1.00

Exchange rate vol 0.50 -0.17 1.00

Financial development 0.06 0.17 0.05 1.00

Export concentration 0.13 -0.23 -0.18 -0.07 1.00

Economic institutions -0.42 0.53 -0.43 0.00 -0.09 1.00

Foreign growth vol -0.10 0.07 -0.02 0.03 0.19 -0.14 1.00

Term of trade vol 0.00 0.20 0.20 0.11 0.10 -0.13 0.48 1.00

Foreign interest rate vol 0.06 -0.34 0.42 -0.03 0.18 -0.22 0.39 0.43 1.00

Documents

ROLE OF INSTITUTIONS AND POLICIES IN ECONOMIC GROWTH …prr.hec.gov.pk/jspui/bitstream/123456789/11849/1/azra khan_Eco_20… · Ihtisham ul Haq for their moral support. Dr. Sadia