EFFECTS OF FISCAL POLICY ON THE CONDUCT AND TRANSMISSION MECHANISMS OF MONETARY POLICY IN ZIMBABWE

BY

WILLIAM KAVILA

DEPUTY DIRECTOR, ECONOMIC RESEARCH DIVISION

RESERVE BANK OF ZIMBABWE

ABSTRACT

This paper provides an analysis of the effects of fiscal policy on the monetary policy transmission mechanism in Zimbabwe under a dollarised environment. The analysis was conducted using an Unrestricted Vector Autoregression model to identify shocks to fiscal variables and their impact on the monetary policy transmission mechanism. The variables analysed are interest rates, budget deficit, inflation, money supply and a proxy for economic activity over the period 2009 to 2014. The impulse response functions and variance decompositions are used to study the effects of identified shocks. The results suggest that nominal interest rates respond positively to a fiscal deficit shock. Furthermore, the results suggest that the response of inflation and money supply are muted, reflecting the limited role played by fiscal policy in influencing money supply and inflation under the dollarized environment.

Keywords: Structural VAR, Fiscal deficit, Monetary Policy, Transmission Mechanism

JEL classification: C32, E52, E62

Table of Contents

1.INTRODUCTION42.TRENDS IN FISCAL PERFORMANCE IN ZIMBABWE7Revenue Performance7Expenditure Performance8Fiscal and Monetary Policy Interaction in Zimbabwe103.LITERATURE REVIEW11Theoretical Literature11Empirical Literature144.METHODOLOGY18Data and Estimation Method195.EMPIRICAL RESULTS206.CONCLUSION AND POLICY RECOMMENDATIONS27

INTRODUCTION

The efficient coordination of fiscal and monetary policies is a pre-requisite for sustainable economic growth in the context of achieving both internal and external balance. Prudent macroeconomic management allows for mutually reinforcing objectives of both fiscal and monetary policies. On the contrary, inefficient coordination give rise to sub-optimal economic outcomes. As highlighted by Balino and Enoch (1998), the necessary condition for effective coordination between monetary and fiscal policies is that each policy should be on a sustainable path. Even with effective coordination, unsustainability in one policy has negative spillover effects on the other, making the entire macroeconomic framework unsustainable. In addition, coordination also looks at the credibility of the overall policy mix. In this regard, the effectiveness of monetary and fiscal policies is dependent upon significant coordination.

The coordination of fiscal and monetary policy is crucial since the two policies operate in different time frames. Monetary policy can be adjusted more frequently and is normally used in fine tuning the economy. On the other hand, it takes a long time to change the fiscal stance. In this regard, the issue of coordination of fiscal and monetary policies had been prominent in the context of macroeconomic stabilization programmes (Niemann, 2008). The need for fiscal and monetary policy coordination has become pertinent especially given that most countries have established independent central banks. As a result, central banks around the globe have moved to primarily focus on price stability through inflation targeting (Sehovic, 2013). Central bank independence has resulted in increased disassociation between fiscal and monetary goals, implying that economic policy management increasingly focuses on the coordination of fiscal and monetary policies.

The importance of coordination between fiscal and monetary policy also came to the fore during the global financial crisis of 2008. The crisis showed that financial instability and weak fiscal policies can have a negative impact on each other. Crucially, the financial-fiscal feedback loop negatively affects the smooth operation of the monetary policy mechanism. The crisis highlighted that sound fiscal and monetary policies are critical for sustainable growth (European Central Bank, 2012). The coordination of fiscal and monetary policies also gained prominence as countries endeavoured to deal with the global financial crisis. Several countries carried out unconventional monetary and fiscal policies. Notably, monetary authorities turned to quantitative easing, while fiscal policies were highly expansive characterised by increased government spending and reduced taxes. Against this background, efficient coordination of monetary and fiscal policy becomes a necessity to ensure a sustainable policy mix in the aftermath of the crisis (Liborioa, 2011).

The euro area sovereign debt crisis also showed that if fiscal and monetary policies are operating at cross purposes, the overall policy mix would be unsustainable. In the euro area, in particular, unsustainable fiscal policy including high debt levels, adversely impacted on the monetary policy transmission mechanism (ECB, 2012). In this regard, fiscal and monetary policy should be in harmony. The euro area crisis highlights that fiscal and monetary coordination should be an integral part of countries moving towards or are in a monetary union. In this regard, as the Common Market for Eastern and Southern Africa (COMESA) strides towards a currency union it becomes imperative to review and examine the state of fiscal and monetary coordination in the respective member countries.

The need for fiscal and monetary coordination increases under monetary union arrangements. As highlighted by Suarez and Panico (2007), in a monetary union without fiscal federation, fiscal policy is the only policy instrument which can be deployed to deal with asymmetric shocks. Under a monetary union, the existence of only one monetary authority with several fiscal authorities requires significant measures to ensure adequate monetary and fiscal policy coordination. In a monetary union, coordination is required at two levels, that is, coordination among fiscal authorities of member states and in the coordination among monetary and fiscal policy authorities (Tirelli and Muscatelli, 2005).

It is against this heightened requirement for greater coordination of fiscal and monetary policy for countries moving towards or in a monetary union that it becomes imperative to assess the interaction of fiscal and monetary policy in Zimbabwe. The assessment of fiscal and monetary coordination in Zimbabwe is, however, an interesting case since the country adopted the multicurrency system in 2009. In the multicurrency system, the country uses an array of foreign currencies, in which the principal currencies include the United States of America dollar (US$), British pound, South Africa rand, Botswana Pula and the Euro. It should be noted that while Zimbabwe is under a multicurrency system, the US$ is the unit of account and the majority of the transactions (over 90%) are in US$. All goods and services are priced in US$. The adoption of the multicurrency system resulted in the loss of monetary policy autonomy. This implies that the country is unable to use traditional monetary policy and exchange rate instruments to fine tune the economy. In this regard, the role of monetary policy has become limited, implying that the interaction between monetary and fiscal policies in Zimbabwe takes a different dimension. Fiscal policy is dominant under the multicurrency system, therefore there is need for the Zimbabwean Authorities to ensure that there is fiscal sustainability.

Historically, Zimbabwe faced significant fiscal challenges as exhibited by huge fiscal deficits averaging more than 9% of GDP for the period 1980 to 2008. The country adopted the multicurrency system in 2009 to stabilise the economy and this resulted in economic activity rebounding, on the back of an improved business environment. In this regard, growth in gross domestic product rebounded to an overage of 10.6% over the period 2009 to 2012, while annual inflation was below 5%. Fiscal performance also improved since the inception of the multicurrency system, with fiscal deficits averaging less than 3%. This was aided by the concomitant implementation of the cash budgeting framework since 2009.

In the absence of a local currency, the impact of fiscal policy on the smooth functioning of the monetary policy is expected to be minimal. It should, however, be noted that fiscal policy can affect monetary policy through its impact on interest rates and financial stability. Despite adopting a cash budgeting system in 2009, Government of Zimbabwe (GoZ) has since 2013 turned to domestic borrowing on the back of declining revenues. The increased recourse to domestic borrowing, may have resulted in higher market lending rates and the crowding out of private investment.

There are few studies on the interaction between fiscal and monetary policy in Zimbabwe and these have mainly concentrated on the impact of fiscal deficits on inflation. Most of the studies were done for the period prior to 2008. Makochekanwa (2011) examined the causality between government deficits and inflation and observed that there exists a causal link from the budget deficit to the inflation rate. He concluded that the monetisation of the budget deficit impacted negatively on inflation. Kararach et al (2010) also argued that the prime source of Zimbabwe’s hyperinflation was excessive money printing to finance huge budget deficits.

The rest of the study is organised as follows: Section II, provides an overview of trends in fiscal developments including institutional arrangements. Section III reviews theoretical and empirical literature, while methodological issues are addressed in Section IV. Section V analyses the results based on the empirical findings. Section VI proffers policy recommendations.

TRENDS IN FISCAL PERFORMANCE IN ZIMBABWE

This section reviews fiscal trends in Zimbabwe since independence in 1980. In addition, the section also analyses the observed relationship between fiscal and monetary variables as a prelude to the econometric analysis of the effects of fiscal policy on the conduct and transmission mechanism of monetary policy in Zimbabwe.

Zimbabwe’s fiscal performance was largely poor over the last 3 decades, starting in 1980, with fiscal deficits averaging well above 5% of GDP. The high fiscal deficits were mainly attributed to elevated Government expenditures. Figure 1 shows developments in Government revenues, expenditures and deficits since 1979.

Figure 1: Developments in Government revenue, expenditure and fiscal deficit as a % of GDP from 1980 to 2014.

Source: Ministry of Finance and Economic Development, Zimbabwe (Various Publications)

Revenue Performance

Government revenue averaged 26% of GDP between 1980 and 2014. Value-Added Tax (VAT) dominated the revenues, accounting for about 30% of the total revenue collected between 1980 and 2014. Equally important were individual and corporate taxes which also contributed about 28% of total revenues over the same period.

In a bid to improve revenue collection, GoZ made several institutional changes. Notably, the GoZ established the Zimbabwe Revenue Authority (ZIMRA) in 2001 a semi-autonomous institution, which merged the former Department of Taxes and Department of Customs and Excise. This resulted into a leaner organisation and boosted revenue collections.

To increase the contribution of indirect taxes as well as to expand the tax base, the country introduced value-added tax (VAT) in 2004. The introduction of VAT at a 15% standard rate improved the performance of indirect taxes. Over the years, the GoZ has been introducing and refining tax policy with the view to improve revenues. In light of the increasing informalisation of the economy, government introduced presumptive tax to cater for business that do not keep proper books of accounts such as informal and cross border traders, transport operators, hair dressing saloon operators and small scale miners.

Government also introduced the Large Client Office in 2010 aimed at providing a one-stop-shop service to large clients in the administration of Income Tax, Pay As You Earn (PAYE) and Value Added Tax (VAT). In the same year, the GoZ also introduced VAT fiscalisation process for operators with a certain threshold. This involved the configuration of fiscal devices to enable them to record sales and other tax information on the read-only fiscal memory at the time of sale for use by the tax authorities in Value Added Tax (VAT) administration.

Expenditure Performance

Government expenditures have been elevated, averaging about 36% of GDP between 1980 and 2014. Recurrent expenditure has dominated Government spending since 1980, with expenditure on social spending and employee compensation accounting for an average of 80% of total expenditure. The huge recurrent expenditures crowded out productive capital expenditures such as spending on infrastructure. Figure 2 below shows the composition of government expenditure since 1980.

Figure 2: Composition of Government Expenditure: 1980-2014

Source: Ministry of Finance and Economic Development, Zimbabwe (Various Publications)

Salaries and wages have been the largest single expenditure head since 1980. The wage bill increased from around 39% of total expenditures in 1980 to about 70% in 2014. Figure 3 below shows the proportion of employee compensation to recurrent expenditure.

Figure 3: Employee compensation versus other Government expenses

Source: Ministry of Finance and Economic Development, Zimbabwe, (Various Publications)

With government spending dominated by recurrent expenditures, capital expenditure received low allocations, impacting negatively on infrastructure development over the years. Government expenditure performance has also been affected by expenditure overruns by respective line Ministries. With a view to control expenditure overruns, Government set up the Implementation and Control of Expenditure Unit which validates expenditure requests from line Ministries and also ensures that the ministries do not overshot their budgetary allocations.

In 2009, Government adopted the cash budgeting system in a bid to foster fiscal discipline among line Ministries. This went a long way in reigning in expenditures by line Ministries and resulted in lower deficits. While adoption of multicurrency in 2009 improved revenue collection, it did not alter Government’s spending pattern, as expenditure remained tilted towards employee compensation. Wages and salaries have remained the most dominant component of expenditure from 2009 to 2014.

Fiscal and Monetary Policy Interaction in Zimbabwe

The GoZ’s fiscal deficits reached peaks of 20% and 22%, of GDP in 1998 and 2000, respectively. The deficits were difficult to address since the main expenditure head was in the form of salaries and wages. During the 1980s and 1990s the budget deficit was financed through both domestic and external sources. As a result, the country contracted huge domestic and external debt. Government faced challenges in meeting external debt obligations since 1999, resulting in the country accumulating external payment arrears.

Faced with huge budget deficits and limited financing options, the GoZ made recourse to the monetisation of fiscal deficits. The excessive recourse to bank finance by the fiscus fuelled money supply growth, which led to an upsurge in inflation. The recourse to central bank financing impaired the smooth functioning of monetary policy, with the central bank recording significant losses as a result of financing fiscal deficits. Kovanen (2004) and Kramarenko (2010) found the prevalence of fiscal dominance in Zimbabwe prior to 2008. Munoz (2007) highlighted that as a result of money printing central government losses reached 75% of GDP in 2006. The negative impact of the fiscal deficits on monetary policy were more evident during the period 2000 to 2008, when inflation reached a peak of 231 million per cent in July 2008.

The GoZ’s failure to service its external debt led to the accumulation of external payment arrears, which were estimated at 86% of public and publicly guaranteed debt in 2012. The perceived unsustainability of fiscal policy and debt could have had a negative impact on the credibility and confidence in monetary policy and the overall policy mix. In 2007 and 2008, the lack of confidence in monetary policy manifested itself through unofficial dollarisation and the emergence of a parallel market for foreign exchange which affected the efficiency of monetary policy. The lack of confidence in monetary policy also negatively impacted on financial stability.

The adoption of the multicurrency system in 2009 subordinated the role of monetary policy to fiscal policy. Under the multicurrency regime GoZ can no longer seek recourse to central bank financing. This effectively means that the government has to finance its deficits by borrowing from other financial institutions other that the central bank and from non-bank domestic sectors.

Since 2009, Government has been pursuing cash budgeting in a bid to nurture fiscal discipline. Cash budgeting was critical for fiscal consolidation between 2009 and 2011, when the economy was recovering at a fast pace. The cash budget system, however, exhibited greater vulnerabilities as the economy slowed down in 2012. Reflecting the slowdown in the economy, the GoZ increased borrowing to finance fiscal expenditure overruns.

The limited fiscal space that characterised the study period forced Government to seek alternative sources of finance such as issuance of TBs to finance deficits. The issuance of TBs impacts on monetary policy variables such as interest rates. In this regard, there is need for close coordination between fiscal and monetary authorities to ensure that fiscal deficits are financed on a sustainable basis.

LITERATURE REVIEW

Theoretical Literature

Fiscal and monetary policies are the traditional tools used by governments to achieve macroeconomic stability. Fiscal policy refers to the control of government revenue collections and expenditures to influence economic activity. Monetary policy on the other hand refers to the control of money supply or interest rates by the central bank to achieve stated macroeconomic objectives. Monetary and fiscal policy are implemented by two different bodies and, therefore, coordination of the policies is required.

A change in either fiscal or monetary policy will influence the effectiveness of the other, thereby, affecting overall policy direction. Fiscal policy affects the conduct of monetary policy through several channels, notably interest rates and exchange rates. Under fiscal dominance, for example, fiscal policy sets the general environment in which the central bank conducts monetary policy. Fiscal dominance implies that even when the central bank is independent, monetary policy can be severely limited by the stance of fiscal policy.

Sargent and Wallace (1981) focused on the impact of fiscal indiscipline on monetary policy. They argued that monetary policy and price level stop being exogenous when the fiscal deficit is predetermined and unsustainable. In this regard, fiscal sustainability is a precondition for monetary stability. The authors also introduced the concept of fiscal dominance, a scenario in which an extreme case of fiscal indiscipline has significant negative implications for monetary policy. In a broad sense, fiscal dominance occurs when it is the fiscal authorities who determine the extent to which budget deficits are financed through bond issuance and seignorage. In the face of fiscal dominance monetary authorities lose their ability to control inflation, whenever the real interest rate exceeds the growth rate of the economy (Sargent and Wallace 1981).

Leeper (1991); Sims (1994); and Woodford (1994) popularized the ‘Fiscal Theory of the Price Level’ which emphasizes the role of fiscal policy in macroeconomic stabilisation. According to the Fiscal Theory of the Price Level, government’s inter-temporal budget constraint is important in the determination of the price level. The theory posits that there is a set of unique prices that tend to equate the present value of future budget surpluses with the current stock of government debt. Leeper (1991) categorized policies into “active” and “passive” policies. Passive policies are also known as Ricardian fiscal policy, which ensures the satisfaction of the government’s intertemporal budget constraint. An active monetary policy is the one that pursues its inflation target notwithstanding the Government's financial position, but passive monetary policy accommodates fiscal policy.

Davig and Leeper (2009) argued that monetary and fiscal policies fluctuate between active and passive behavior. Lack of fiscal discipline results in increases in debt and inflation. Under such a case, even if the central bank raises interest rates aggressively, it is not able to reduce aggregate demand and inflation.

The “perverse effect of fiscal policy” (Beetsma and Bovenberg, 1999) is another theoretical strand on the interaction and coordination of monetary and fiscal policy. Beetsma and Bovenberg (1999) assert that a more anti-inflationary oriented central bank has a perverse effect on the incentive of the fiscal authorities to reduce the level of debt.

The other strand of literature on monetary and fiscal policy coordination focuses on the distortions that may emerge on the conduct of monetary and fiscal policy based on either rules or discretionary policy. Beetsma and Uhlig, (1999) found that a distortionary fiscal policy causes blockage between the natural and actual output forcing the monetary authority that would otherwise want to stabilize output around the natural level, to resort to inconsistent policies that can be inflationary. Dixit and Lambertini (2003) tested the relation between the monetary and fiscal policy and showed that fiscal policy authorities who have discretionary powers can undermine monetary policy authorities by running own policy based on rules. This, constrains the use of monetary commitment and monetary policy based on rules.

Buti et al. (2001) posited that the relationship between monetary and fiscal policy depends on the type of shock which the economy is facing. Coordination is particularly desirable in cases when the economy is faced with shocks on the supply side, while the opposite is true for shocks occurring on the demand side.

Hilbers (2004), also states that there are direct and indirect channels in which fiscal policy may influence monetary policy. For instance, if a country is running an expansionary fiscal policy, which usually results in deficits, there are two possibilities which the government may resort to, in order to carter for its deficits. First, government can finance the deficit through money printing or borrowing from the market. In many instances the government may resolve to finance the deficit through the printing of money which implies monetary policy expansion. Expansion in monetary policy results in inflationary pressures in an economy which may lead to a devaluation of a nation’s currency, balance of payments challenges as well as a banking crisis.

Second, Government may resort to finance the deficits through the domestic banking market, thus affecting the monetary policy’s credit transmission channel. High budget deficits are often associated with the crowding out of the private sector in the money market, as fiscal authorities finance budget deficits by borrowing from the banking sector. This results in an increase in lending rates as demand for credit outstrips supply. As the cost of credit increases, so does the cost of production and the general price level (Hilbers, 2004). In addition, fiscal measures, such as introducing or changing a consumption tax or value added tax, have a direct effect on inflation. A once off rise in indirect taxes may put pressure on prices and this could lead to a price-wage spiral which could trigger adverse inflationary expectations and eventually lead to high inflation. Furthermore, perceptions or expectations about government activities, may have an indirect impact on monetary policy. Expectations that the government may struggle to sustain its financial position may constrain the potency of monetary policy.

Perceptions and expectations of large and on-going budget deficits and resultant huge borrowing requirements may also trigger a lack of confidence in the economic prospects of a country. This may become a risk to stability in financial markets. Such lack of confidence in the sustainability of the financial position of the government may become a potential destabilising factor on bond and foreign exchange markets, eventually leading to the collapse of the monetary regime, (Hilbers, 2004).

Empirical Literature

Several studies have been done on the interaction of between monetary and fiscal policy, particularly in the aftermath of the Global Financial Crisis. Most of the studies, for example, Sehovic (2014), Lanmann (2014), Schroth (2013), Mortensen (2013) and Galí and Monacelli (2008), have focused mainly on the coordination of fiscal and monetary policy in the European Monetary Union (EMU).

Tomšík (2012) ascertained that fiscal policy has an impact on the monetary policy’s interest rate channel as noted in the case of the Czech Republic, whose government bond yields have a significant impact on long-term interest rates. When government bond yields rise, the risk of a sovereign debt crisis increases, leading to an escalation in long-term lending rates. This relationship, however, was weakened by the Global Financial Crisis, especially when it came to credit advances to large corporations and deposits. Dunn et al. (2011) investigated the monetary policy transmission mechanism in Pacific Island Countries (PICs) and found that lower fiscal deficits, coupled with lower public debt are correlated with lower average inflation and higher output growth. Furthermore, lower inflation was related to lower interest rates and lower costs of production.

Rukelj (2010) examined the interactions of fiscal policy, monetary policy and economic activity in Croatia using monthly data for the period 1997 to 2008. The researcher used a structural Vector Error Correction Model (VECM) to identify permanent and transitory shocks on government expenditures, money aggregate M1 and the index of economic activity. The main conclusion made was that fiscal and monetary policy move in the opposite direction, which indicates that they can be used as substitutes.

Deskar-Škrbić and Šimović (2013), employed a structural Vector Autoregressive (VAR) model to analyse the dynamic effects of discretionary fiscal shocks on economic activity of the private sector in Croatia from 2000Q1-2012Q2. They showed that government spending had a positive and statistically significant effect on private aggregate demand and private consumption which affects inflation and therefore, the conduct of monetary policy.

There are, however, few studies on the coordination of fiscal and monetary policy in Africa and even developing countries in general. Nyamongo et al. (2008) studied the monetary-fiscal policy interactions in Kenya for the period 1979 to 2007 and concluded that the fiscal and monetary policies were coordinated on a number of years but there were also several years with no evidence of coordination between the two policies. The study also shows a greater degree of monetary policy dominance in Kenya using a non-structural VAR analysis. The study also estimated the output gap as a way to gauge the cyclical behaviour of both the fiscal and monetary policies and it was observed that fiscal and monetary policy displayed both procyclical and countercyclical behaviour.

Frankel et al. (2008) showed that South Africa’s fiscal policy had been predominantly procyclical, while monetary policy had been mildly countercyclical. They concluded that fiscal policy should be made more countercyclical to ensure macroeconomic stability. Swanepoel (2004) found that monetary policy had been mainly anti-cyclical in South Africa but highlighted the challenge of coordination between fiscal and monetary policy in the country. The results were also confirmed by Du Plessis et al. (2007) using a structural vector-autoregression approach to assess the cyclicality of fiscal and monetary policy in South Africa since 1994. The study concluded that monetary policy had contributed markedly to the stabilisation of the South African economy. Specifically, Du Plessis et al. (2007) concluded that monetary policy had been largely countercyclical since 1994, while fiscal policy had been largely pro-cyclical.

Chukwu (2010) examined the monetary and fiscal policy interactions in Nigeria using quarterly data between 1970 and 2008. The interactions of monetary and fiscal policy was analysed using both VAR model and State-space with Markov-switching. Using a VAR model, Chukwu (2010) simulated generalised impulse responses and observed that there is evidence of a non-Ricardian fiscal policy in Nigeria. As a step further, the study applied a State-space model with Markov-switching to estimate the time-varying parameters of the relationship between monetary and fiscal policies. The State-space model showed that monetary and fiscal policies in Nigeria have interacted in a counteractive manner for most of the sample period (1980-1994). The study also observed some of form of accommodativeness of monetary policy between 1998 and 2008. Overall, Chukwu (2010) found the existence of fiscal dominance in Nigeria, implying that inflation, predominantly results from fiscal problems, and not from lack of monetary control.

Obinyeluaku and Viegi (2009) examined the relationship between fiscal balances and monetary stability in ten SADC countries based on the dynamic response of inflation to different shocks. The study showed evidence of fiscal dominance in five out of ten countries throughout the period 1980-2006, while the remainder revealed monetary dominance. Crucially, the study also observed that fiscal policy affects price variability through aggregate demand. The main conclusion from the study was that fiscal policy matters for achieving and maintaining price stability in the SADC region.

There are also few studies on the interaction of fiscal and monetary policy in Zimbabwe. Munoz (2007) highlighted that high government fiscal deficits led to increased central bank quasi-fiscal losses which interfered with monetary management from 2003 to 2007. Munoz (2007) estimated the quasi-fiscal losses at about 75 percent of GDP in 2006. The deficits were financed by money creation or the issuance of RBZ securities, resulting in high inflation.

Makochekanwa (2008) argued that the relatively high fiscal deficit experienced by Zimbabwe was the root cause of the high inflationary environment in the years 2005 to 2008. The study found a causal link running from budget deficit to the inflation rate using Johansen co-integration technique over the period 1980 to 2005. Makochekanwa (2008) concluded that the monetization of budget deficits led to hyperinflation.

Easterly and Schmidt-Hebbel (1993) also studied the relationship between fiscal deficits, inflation and interest rates for developing countries including Zimbabwe for the period 1978 to 1989. For Zimbabwe, the authors concluded that a percentage point increase in the deficit to GDP financed through money creation increased inflation by 10 percent. Despite Zimbabwe maintaining interest rates control in the 1980s, Easterly and Schmidt-Hebbel (1993) found that a percentage point increase in the deficit to GDP financed through domestic financing increased interest rates by 2.7% through simulations. This implied a negative impact on the operation of monetary policy.

Kramarenko (2010), and Kovanen (2004) found evidence of fiscal dominance in Zimbabwe, particularly in the 2000s. They argued that the high fiscal deficits experienced by the country since 2000 impacted negatively on the economy, including impeding the normal functioning of monetary policy.

METHODOLOGY

1.1 Model Specification

A review of empirical literature on African countries shows that most studies used variants of Vector Autoregression (VAR) to examine effects of fiscal policy on the conduct and transmission mechanisms of monetary policy (Chukwu, 2010; Nyamongo et al. 2008; and Du Plessis et al. 2007).

In light of the above, this study applies an Unrestricted Vector Autoregression model to assess the effects of fiscal policy on the monetary policy transmission mechanism in Zimbabwe. The VAR model is specified, following Sims (1980) and expressed as follows:

(1)

Where is a vector of endogenous variables with linear dynamics, is a vector of autoregressive coefficients and is an n-dimensional Gaussian white noise with covariance matrix, is an n– dimensional vector of constants. To keep the model parsimonious, five variables, namely fiscal deficit, money supply, interest rates, inflation and index of economic activity are simulated to assess their response to a fiscal deficit shock. Precisely the model is described as follows:

where: Mt is represents money supply, Gt, budget deficit, Yt, economic activity, Rt interest rates and It, inflation.

The VAR model isolates purely exogenous shocks and gets the responses of the endogenous variables after the economy is hit by these shocks. Getting the structural model is also called identification. According to Sims (1980), identification is the interpretation of historically observed variation in data in a way that allows the variation to be used to predict the consequences of an action not yet undertaken. The VAR, therefore, allows for identification of shocks to a variable, which are then used to assess the impulse response of other variables from the identified shock.

The impact of fiscal policy is represented by a shock to fiscal deficit, while that of monetary policy is represented by a shock to money supply and interest rates. In the case of a dollarized economy like Zimbabwe, where the country does not have monetary control, a significant foreign capital inflow or outflow not related to the national output, which increases money in the system, can be taken as a typical example of a monetary policy shock.

1.2 Data and Estimation Method

The analysis is conducted using monthly seasonally adjusted data for the fiscal deficit, consumer price index, money supply, interest rates and a proxy for economic activity for the period 2009 to 2012. The VAR requires all variables to be either stationary or cointegrated to ensure unbiased coefficients. As such, the unit root tests and Johansen cointegration tests are conducted to test for stationarity of variables as well as the cointegrating properties of the data. The lag length also matters and is determined using both the Akaike information criterion (AIC) and Final Prediction Error (FPE).

The variables used were obtained from Ministry of Finance and Economic Development and Reserve Bank of Zimbabwe. To enable the interpretation of estimated coefficients as elasticity variables were expressed in logarithms. The analysis was only limited to the multi-currency era to avoid bias in estimated coefficients emanating from distortions caused by the transition from hyperinflation to the multi-currency regime.

EMPIRICAL RESULTS

1.3 Unit Root Tests

As a preliminary analysis, the statistical properties of the data were assessed using unit root tests and Johansen cointegration tests. The number of lags was automatically selected by the Akaike Information Criterion (AIC) and Final Prediction Error (FPE). The unit root test results obtained from Augmented Dickey Fuller tests are shown in Table 1 below.

Table 1: Unit root tests

Variable

Level

First Difference

Economic activity

-5.376***

(0.000)

-6.5496***

(0.000)

Money supply

-3.1562**

(0.0267)

-9.3339***

(0.000)

Inflation

-0.6489

(0.8523)

-6.4464***

(0.000)

Interest rate

-3.8716***

(0.0037)

-5.4761***

(0.000)

Budget deficit

-8.9793***

(0.000)

-9.9827***

(0.0001)

Source: Researcher’s own Computations

The unit root test results in Table 1 above shows that economic activity, money supply interest rate, and budget deficit variables are stationary in their levels, while inflation, measured by consumer price index is only stationary after first differencing. The appropriate lag length was determined to be 6 using both the AIC and FPE approaches. Table 2 below shows the results from lag length tests.

Table 2: Determination of appropriate lag length

 Lag

LogL

LR

FPE

AIC

1

 684.5354

NA 

 2.80e-16

-21.62411

2

 720.3050

 59.81140

 1.99e-16

-21.97721

3

 748.2863

 42.20139

 1.87e-16

-22.07496

4

 770.9199

 30.42548

 2.18e-16

-21.99737

5

 813.2494

  49.96269*

 1.41e-16

-22.56555

6

 845.4358

 32.71406

  1.37e-16*

 -22.80117*

Source: Researcher’s own Computations

Note:  * indicates lag order selected by the criterion, LR: sequential modified LR test statistic (each test at 5% level), FPE: Final prediction error, AIC: Akaike information criterion, SC: Schwarz information criterion, HQ: Hannan-Quinn information criterion

1.4 Impulse Responses

The impulse response functions and variance decompositions for the length of 24 periods for all three cases were considered and the response of individual variables to the identified fiscal policy shocks in all three cases are presented in Figure 4 below.

Figure 4: Impulse response functions

Source: Researcher’s own Computations

The results in Figure 4 above suggest that the nominal interest rates respond positively to a fiscal deficit shock. Specifically the results indicate that a 1% fiscal deficit shock leads to a 0.02% increase in nominal interest’s rates over a period of four months, with the impact disappearing after 10 months. In addition, output increases in the short term, following a fiscal deficit shock. The results, therefore, suggests that a shock in government budget deficit has a transitory positive impact on interest rates and output. The inflation rate and money supply are, however, not responsive to a fiscal deficit shock.

The results confirm the assertion that in dollarized economies, inflation developments mainly mirror that of a country whose currency is being used. As such, domestic policy becomes ineffective in influencing inflation developments. Fiscal policy affects interest rates through the crowding out effect. The positive response of interest rates to a budget deficit shock is expected since government has in most cases been financing the mismatches in its revenues and expenditure through the issuance of Treasury bills. Money supply in a dollarized economy is mainly affected by changes in capital flows, implying that fiscal policy affects money supply in cases where government borrows externally. External borrowing by the Government was, however, limited during the period under review due to outstanding arrears to external creditors. As a result, the insignificant impact of fiscal policy on money supply was expected.

1.5 Variance Decomposition Results

The forecast error variance decomposition was applied to assess the relative importance of individual shocks in explaining forecast error variances of the observed variables. Specifically, the variance decomposition analysed are the decomposition of interest rates, inflation, money supply and economic activity to a fiscal deficit shock. The results are shown in Tables 5-8 below.

Table 3: Variance Decomposition of Interest Rates

 Period

S.E.

Deficit

Interest

Inflation

Money Supply

Output

 1

 0.185674

 0.050148

 99.94985

 0.000000

 0.000000

 0.000000

 2

 0.197201

 1.733573

 81.18590

 4.637394

 12.00760

 0.435534

 3

 0.202708

 8.883989

 64.32536

 7.646598

 17.60983

 1.534220

 4

 0.203312

 14.10107

 55.68852

 8.157283

 19.06936

 2.983768

 5

 0.203724

 17.93303

 51.21738

 7.851259

 19.38546

 3.612869

 6

 0.203766

 19.84094

 49.21157

 7.604188

 19.73783

 3.605467

 7

 0.203835

 20.68622

 48.16467

 7.453526

 20.16426

 3.531327

 8

 0.203858

 20.95296

 47.59824

 7.369404

 20.58465

 3.494740

 9

 0.203879

 21.00515

 47.26249

 7.318508

 20.93946

 3.474392

 10

 0.203893

 20.98315

 47.05654

 7.286137

 21.21397

 3.460205

 11

 0.203904

 20.94364

 46.92165

 7.263823

 21.42128

 3.449604

 12

 0.203912

 20.90354

 46.82815

 7.247699

 21.57893

 3.441669

Source: Researcher’s own Computations

The variance decomposition of interest rates in the Table 5 above suggests that about 21.6 percent of the variation in interest rates is explained by money supply, while 20.9 percent is explained by budget deficit. The interest rate variable itself explain a greater proportion of the variation, accounting for 46.8 percent. Inflation and output explains 7.2% and 3.4% of variation in interest rates respectively.

The variance decomposition of inflation suggests that about 93.5 percent of the variable is explained by the inflation variable itself as shown in Table 6 below. This suggests that inflation persistence has mainly been due to inflation expectations, with fiscal and monetary policy playing a limited role in explaining the inflation dynamics under a multiple currency regime.

Table 4: Variance Decomposition of Inflation

Source: Researcher’s own Computations

The budget deficit only explains a paltry 1.2 percent of the variation in inflation, while interest rates and money supply explain only 4.1 percent and 0.13 percent. The results suggest that inflation under the multiple currency regime has predominantly been influenced by other factors besides fiscal and monetary policy variables.

The variance decomposition of money supply suggests that the budget deficit only explained 0.37 percent of the variation in money supply, while inflation and interest rates explained 14.8 percent and 13.6 percent respectively. Money supply variable itself explain about 70.9 percent of the forecast error variation. The variance decomposition are shown in Table 7 below.

Table 5: Variance decomposition of money supply

Source: Researcher’s own Computations

Table 8 below shows the variance decomposition of output. It shows that about 22.6 percent of the variation in economic activity is explained by fiscal variable, 17.3 percent by inflation and 53.1 percent by the economic activity variable itself.

Table 6: Variance decomposition of output

Source: Researcher’s own Computations

CONCLUSION AND POLICY RECOMMENDATIONS

This paper attempted to assess the effects of fiscal policy on monetary policy transmission mechanism in Zimbabwe. Zimbabwe makes an interesting case to study, given its limited capacity to influence policy through monetary policy following the adoption of the multi-currency regime. The VAR model was applied to assess the response of relevant monetary policy variables, notably, interest rates and money supply to fiscal policy shocks.

The effects of fiscal policy shocks on monetary policy variables were examined using impulse response functions and variance decompositions. The results from the impulse response functions suggest that the effects of fiscal policy shocks on money supply and interest rates is positive.

The variance decomposition of monetary policy variables suggest that fiscal policy has to a lesser extent influenced interest rates and money supply under the multicurrency regime. Specifically the impact on money supply has been largely insignificant. The results are consistent with most empirical findings which suggest that in a dollarised economy, money supply becomes highly endogenous. The results also suggest that inflation dynamics have largely been influenced by inflation persistence and other factors besides fiscal and monetary policy variables. The large proportion of the variation in economic activity explained by fiscal policy shock, suggests that fiscal policy has been instrumental in influencing economic activity under the multiple currency environment.

The results suggest the need for Government to properly sequence its Treasury Bill issuance to avoid volatility on monetary conditions, explained by changes in real interest rates and real effective exchange rate, through the crowding out effect. Moreover the need for coordination between monetary and fiscal policy remains highly critical. Given the dominance of fiscal policy under the multicurrency regime, it is imperative that the government effectively implements its fiscal policy to impact positively on the economy. Future work on this topic could give a more precise definition of fiscal and monetary policy shocks. Moreover, a more sophisticated model is needed with additional variables, including the real effective exchange rate and government revenues to assess the implications of fiscal policy on the monetary policy transmission mechanism.

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Capital Expenditure198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320148.5593048607763192E-27.306007348174437E-20.104267424251143038.2671847730848916E-27.6470296471530974E-20.145166757988414946.0806490156268642E-27.4290191285914228E-20.10650858521414439.9901498786396092E-28.164083679041842E-20.105311973180916040.107338322945085180.108711839166046170.134768622990960650.137128450574557537.3507723418832729E-26.603194103194103E-24.0161068136060192E-27.8553615960099757E-21.5122873345935728E-26.1595615419243001E-27.1733561058923992E-27.7226444858740861E-20.12567332351456859.4139692226054658E-20.242693953448379660.284464218887164280.127239447873816254.908645500489954E-20.191231135026512010.122019609383556168.4622587126337689E-29.9326836949903685E-27.9000000000000001E-2Net Lending198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320145.3769852159945071E-23.4375023464930252E-23.6909442278033604E-23.4029361437939214E-23.3517404487760208E-24.3148982861424878E-22.911815845412849E-23.2632923357187163E-23.0552892279494384E-23.0005421683692961E-23.3488552936113775E-23.2625369841930131E-20.111806322276417184.5420699925539834E-27.9121119388089287E-20.103107688944002245.6145131296226801E-26.1117936117936117E-21.2715905478435943E-23.2418952618453865E-21.9533711405166982E-23.1738592488638907E-31.5371477369769428E-23.8505664706725944E-25.127043144201951E-27.9762536481825415E-32.4160920692772769E-31.7369563078733104E-22.565786814686729E-127.7879272366200583E-27.0451691338442812E-21.4455964837692292E-22.4898345253080267E-21.7968777834474203E-20.01Recurrent Expenditure198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320140.860637099232292040.892564903053325360.85882313347082340.883298790831211770.890012299040708780.811684259150160180.910075351389602830.893076885356898550.862938522506361270.870093079529910880.884870610273467810.86206265697715390.780855354778497550.845867460908414030.786110257620949990.759763860481440290.87034714528494050.872850122850122870.947123026385503830.889027431421446360.965343415248897330.935230525331893330.912894961571306560.884267890434533240.823056245043412020.897884054125762780.754889954482343080.698166218034102610.872760552123617810.873034272628899880.738317173635045230.863524425778751550.890479067620582040.882704385215622110.91100000000000003

Salaries and Wages 198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320140.392872908046343840.392872908046343950.374755885824113680.404867526784261130.450423929309221040.650074571210849110.410005881949112190.463429233191689830.380436966540452780.37365899981812040.512879467470666150.34252806269850450.379106849969627180.36997743938361460.362569682044117210.397302723031087880.37056606692776850.474461626575028660.442394366197183090.461024227095677420.439801610120759080.409220023134968640.475921885995777620.369739315283061090.480511921458625530.473381201044386470.449819004524886880.471342376052385440.513154395069737260.597562414931697370.505866436868314450.630215532712577240.703067389292320380.695667768675076180.75Other Expenses198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320140.607127091953656220.6071270919536560.625244114175886320.595132473215738810.549576070690778960.349925428789150890.589994118050887860.536570766808310170.619563033459547220.626341000181879660.487120532529333850.657471937301495450.620893150030372820.63002256061638540.637430317955882790.602697276968912070.62943393307223150.525538373424971340.557605633802816910.538975772904322530.560198389879240870.590779976865031360.524078114004222330.630260684716938970.519488078541374470.526618798955613480.550180995475113120.528657623947614620.486845604930262740.402437585068302630.494133563131685550.369784467287422760.296932610707679620.304332231324923820.25

Expenditure 1980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201422.40891182795698834.91359844248528134.67415294230769337.95580324881140741.47852364062499926.04912081732965135.11616742592412535.22151611607142732.27265349067970130.67697926209378429.98836884712012827.49108450190730232.50769817108630431.61413337727454528.13184553757616536.94226845605086931.52024177733797230.03219052362636963.42666648743833234.87305252264356950.43090854682034134.16051680520418930.27636455797686630.58116530777378439.36573722480066148.41037716915749243.041161607772374444411.323.726.428.628.927.5Revenue1980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201419.64227422260970727.75784223481033725.71261448076922627.97165110935023730.36914864062499918.44221744259072828.58859483640574726.38122384821428725.93716909773902724.36261342738020724.69526379454731622.10101597407420126.29746360490812423.53993550057672517.75681547036089821.00012911972629922.88002757986669924.23051735428945738.86790423830199625.48080895046026524.57078062883990626.20859825535280126.2171081654897924.22825021975554432.15190833180842835.42782408584309938.763694745821489363411.424.827.1228.0226.826.6Deficit19801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011201220132014-2.7666376053472801-7.1557562076749397-8.9615384615384706-9.9841521394611696-11.109375-7.6069033747389199-6.5275725895183836-8.8434252493601129-6.3354843929406766-6.3143658347135769-5.2931050525728098-5.390068527833102-6.2102345661781779-8.0741978766978217-10.375030067215301-15.942139336324599-8.6402141974712698-5.8016731693369117-24.558762249136336-9.3922435721833057-25.8601279179804-7.9519185498513902-4.0592563924870779-6.3529150880182401-7.2138288929922298-12.9825530833144-4.2774668619508818-8-109.9999999999999603E-21.06-0.7-0.6-2.1-0.9

31

-.02

-.01

.00

.01

.02

.03

.04

24681012141618202224

-.004

-.002

.000

.002

.004

.006

24681012141618202224

Response of inflation to budget deficit shock

Response of interest rates to budget deficit shock

-.015

-.010

-.005

.000

.005

.010

.015

24681012141618202224

Response of money supply to budget deficit shock

-.04

-.02

.00

.02

.04

.06

24681012141618202224

Response of output to budget deficit shock