International Research Journal of Finance and Economics ......International Research Journal of Finance and Economics - Issue 179 (2020) 17 is in view of these expected gains from

International Research Journal of Finance and Economics

ISSN 1450-2887 Issue 179 June, 2020

http://www.internationalresearchjournaloffinanceandeconomics.com

Financial Development, Trade Openness and Economic Growth:

The Evidence from West African Countries Revisited

Yaya KEHO

Ecole Nationale Supérieure de Statistique et d’Economie Appliquée (ENSEA) Abidjan

08 BP 03 Abidjan 08, Côte d’Ivoire

E-mail: [email protected]

Tel.: (+225) 22 44 41 24; Fax: (+225) 22 48 51 68.

Abstract

This study investigates the relationship among financial development, trade

openness and economic growth for a panel of 11 West African countries over the period

from 1985 to 2018. Contrary to most existing studies, the analysis makes use of the

Common Correlated Mean Group method and the Seemingly Unrelated Regression

Estimator (SURE) to cope with both heterogeneity and cross-sectional dependency across

countries. The study provides various pieces of evidence through whole-panel and country-

level analyses. The results from the panel analysis show that financial development and

trade openness have, on average, positive effects on economic growth both in the short and

long run. The Granger causality tests show that real GDP, financial development and trade

openness are mutually causal, implying that their simultaneous development should be

promoted. In the short run, however, there is unidirectional causality flowing from trade

openness to financial development. The results also show that investment is an important

channel through which financial development and trade feed economic growth. The

country-level results reveal, however, considerable heterogeneity across countries. The

long-run growth effect of financial development is positive in 8 countries while that of

trade openness is positive in 6 countries. The results have important policy implications for

the financial sector and trade development of West African countries.

Keywords: financial development; trade openness; economic growth; West African

countries

JEL Classification:C33, E44, F43, O55

1. Introduction The growth effects of financial development and trade have been subjects of intense debate in

macroeconomics. The debate has received increased attention in both theoretical and empirical

literature and remains inconclusive. The theoretical view about the finance-growth nexus suggests a

number of mechanisms through which financial development promotes economic growth. The

development of financial sector allows risk diversification and risk management, facilitates exchange

by reducing transaction costs, and improves resource allocation through the production of information

about investment opportunities (Goldsmith, 1969; Shaw, 1973; Bencivenga and Smith, 1991; King and

Levine, 1993a; Bencivenga, et al., 1995; De Gregorio and Guidotti, 1995). With respect to trade

openness, the theoretical literature on international trade advocates that trade contributes positively to

economic growth through efficient allocation of resources, dissemination of knowledge and

technology, and greater economies of scale (Grossman and Helpman, 1991; Markusen et al., 1995). It

International Research Journal of Finance and Economics - Issue 179 (2020) 17

is in view of these expected gains from trade and financial development that many developing

countries have adopted liberalization policies with the aim of opening up and integrating them into the

world market in order to boost their economic development. Recent financial crises, however, have

shown us that increase in the interdependence of economies across the world makes financial crises

more costly because countries are more exposed and vulnerable to external shocks. Breitenlechner et

al. (2015) showed that financial development has positive effect on economic growth in non-crisis

times, but larger financial sectors worsen growth during banking crises. The 2008 global financial

crisis which was mainly driven by subprime mortgage lending, brought the finance-trade-growth nexus

into question. This crisis indicates the failure of financial markets to allocate the large inflow of funds

into profitable ventures (Carré and L’oeillet, 2018).

On the empirical front, an overwhelming body of literature has examined the linkages between

financial development and economic growth, and between trade openness and economic growth.

Though the evidence from this literature is mixed and even conflicting, the general belief remains that

financial development and market openness are essential for economic development. On the one hand,

most of the studies revealing the significance of financial development and trade openness for

economic growth have been conducted in a bivariate framework. On the other hand, few studies have

investigated the causal links among financial development, trade openness and economic growth,

simultaneously in a multivariate framework. As financial development and trade are important drivers

of economic growth, understanding the causal connections between these three phenomena is

important for designing relevant strategies in developing countries. A sizeable empirical research has

been devoted, in recent years, to examine the effects of financial development and trade openness on

economic growth. These studies show mixed and controversial results depending on countries, data,

variables measurement, and econometric techniques used.

A serious shortcoming in previous studies is that they employed estimation methods that

assume parameter homogeneity and cross-sectional independence across countries with the hope that

the results from panel analysis could be applied to all countries. In addition, the problem of

endogeneity has not been satisfactorily addressed. Therefore, the results from existing studies based on

panel data may be questionable if models exhibit cross country dependency and heterogeneity. With

the increasing globalization of the world, countries become more and more interdependent. In addition,

findings reported by Demetriades and Hussein (1996), Agbetsiafa (2004), Ghirmay (2004), Enisan and

Olufisayo (2008), Akinlo and Egbetunde (2010), Were (2015), Khobai et al. (2017), and Guei and Le

Roux (2019) show that the role of financial development and trade openness in the economic growth

process is country specific. Therefore, more research is needed in this field of economics.

This study contributes to the empirical literature by employing recent developments in non-

stationary heterogeneous panel techniques to appraise the effect of financial development and trade

openness on economic growth in selected 11 West African countries. More precisely, the study

provides more reliable results than previous studies by running the Common Correlated Effects Mean

Group (CCEMG) estimator developed by Pesaran (2006). This estimator has been shown to be robust

to the problems associated with cross-country dependence and heterogeneity, and omitted variables. It

also takes care of the problem of endogeneity considered by Das and Paul (2011) as one possible

reason for disappointing results in the empirical literature. Our aim in this study is to contribute to the

ongoing debate on the growth effects of trade openness and financial development. To the best of our

knowledge the methodology and estimation strategy employed in this study have not yet been used

before for providing evidence for the joint effect of financial development and trade openness on

economic growth in the African context.

The remainder of the study is organized as follows. Section 2 reviews the theoretical and

empirical literature linking financial development, trade openness and economic growth. Section 3

outlines the empirical model and the estimation strategy of the study. The data description is provided

in Sector 4. Section 5 presents and discusses the empirical results. Finally, Section 6 concludes the

study and provides some key policy recommendations.

18 International Research Journal of Finance and Economics - Issue 179 (2020)

2. Literature Review The relationships between financial development and economic growth and between trade openness

and economic growth are subjects of intensive debate that has received substantial attention both in

empirical and theoretical economic literature. Yet these issues are far from being resolved. A

comprehensive survey of the literature on these topics is provided by Ang (2008), Acaravci et al.

(2009), Huang and Chang (2014), Saquib (2015), and Keho (2017). It is argued that the development

of the financial sector fosters economic growth in two ways. One is quantitative and runs through the

accumulation of physical capital. A well-developed financial sector stretches the range of financial

services available in the economy and increases the accessibility of financial services to the public. An

increasing use of financial services might stimulate savings, thereby increasing the availability of

resources for investment (Goldsmith, 1969; Shaw, 1973). The other is qualitative and operates through

productivity enhancement. By analyzing information and channeling savings to the most productive

uses, financial intermediaries help the efficient allocation of resources and reduce asymmetries

information and costs of investing in productivity enhancement (Greenwood and Jovanovic, 1990).

Also, financial development enhances productivity through the adoption of new technologies

(Schumpeter, 1911; Pagano, 1993; Bencivenga and Smith, 1991; De Gregorio and Guidotti, 1995;

Levine, 1997). These arguments suggest that in a financially underdeveloped economy, the allocation

of resources will not be optimized in the sense that they will not go to most productive uses.

Conversely, the development of the financial sector may follow economic growth. As the real economy

grows, the demand for credits and new financial products and services increases which enhances the

development of the financial sector (Robinson, 1952; Patrick, 1966; Goldsmith, 1969).

As regards the trade-growth nexus, the theory of comparative advantage contends that

international trade encourages specialization in sectors which have economies of scale that contribute

to improve the efficiency and productivity in long-run (Krueger, 1978; Bhagwati, 1978). New

endogenous growth models advocate that openness to trade enhances economic growth by improving

productivity through the diffusion of knowledge and advanced technologies (Rivera-Batiz and Romer,

1991; Grossman and Helpman, 1991; Ben-David and Loewy, 2000). A more open economy has a

greater ability to use advanced technologies, and this capability leads it to grow more rapidly than a

less open economy. It is therefore expected that outward-oriented economies will record higher

economic growth rates than inward-oriented economies. From this perspective, developing countries

have much to gain by trading with advanced countries. An opposite view claims, however, that

increase in trade openness may be detrimental to economic growth by increasing inflation,

vulnerability to terms of trade and financial crisis (Cooke, 2010; Jafari et al., 2012; Fosu, 2013). A

reverse causation flowing from economic growth to trade is also possible through an increase in the

exportable capacity of the economy and imports of goods and services.

These theoretical considerations have stimulated a growing empirical literature devoted to

ascertain the role of financial development and trade openness in supporting economic growth.

Unsurprisingly, the evidence from this literature remains mixed and inconclusive. The literature is rich

in studies that highlight the positive effect of financial development on economic growth (e.g., King

and Levine, 1993b; Gregorio and Guidotti, 1995; Odedokun, 1996; Beck et al. 2000; Levine et al.,

2000; Odhiambo, 2007; Ahmad and Malik, 2009; Hassan et al., 2011; Afawubo and Fromentin, 2013;

Uddin et al., 2013; Puryan, 2017). Conversely, many other studies reported that financial development

undermines economic growth (e.g., Narayan and Narayan, 2013; Herwartz and Walle, 2014;

Samargandi et al., 2015; Iheanacho, 2016; Seven and Yetkiner, 2016).

In terms of causality, a number of studies found evidence of financial development causing

growth (Levine and Zervos, 1998; Agbetsiaga, 2004; Christopoulos and Tsionas, 2004; Ghirmay,

2004) while others support the reverse causality that economic growth leads to financial sector

development (Al-Yousif, 2002; Chakraborty, 2008; Odhiambo, 2008; Hassan et al., 2011; Godfrey,

2013). In contrast to these studies, there is empirical evidence in support of bi-directional causality

between financial development and economic growth (e.g., Demetriades and Hussein, 1996; Ahmed


and Ansari, 1998; Akinboade, 1998; Kul and Khan, 1999; Luintel and Khan, 1999; Craigwell and

Downes, 2001; Shan and Morris, 2002; Odhiambo, 2005; Apergis et al., 2007; Acaravci et al., 2009;

Wolde-Rufael, 2009; Akinlo and Egbetunde, 2010; Fowowe, 2011; Jun, 2012; Godfrey, 2013; Pradhan

et al., 2014; Adeyeye et al., 2015; Lebe, 2016). Still others do not find evidence of any causal

relationship between financial development and economic growth (e.g., Ram, 1999; Majid, 2008;

Arestis et al., 2001; Eng and Habibullah, 2011; Nain and Kamaiah, 2014; Akbas, 2015; Hasan and

Barua, 2015).

Among the reasons of these mixed results are country-characteristics, data, variables

measurement, and econometric techniques employed in the empirical analysis. For example, Esso

(2009) examines the relationship between financial development and economic growth in ECOWAS

countries, using data from 1960 to 2005. He employs the autoregressive distributed lag analysis and the

Ganger causality test proposed by Toda and Yamamoto (1995). He finds a positive long-run

relationship between financial development proxies by the ratio of M2 to GDP and economic growth in

four countries, namely, Cote d'Ivoire, Guinea, Niger and Togo, and a negative one in Cape Verde and

Sierra Leone. The results of the causality test show that finance causes economic growth only in Cote

d'Ivoire and Guinea. The author concluded that the relationship between financial development and

economic growth cannot be generalized across countries because these results are country specific. In

another work, Esso (2010a) re-examines the relationship between financial development and economic

growth in the ECOWAS countries over the period 1960 - 2005. He employs the autoregressive

distributed lag analysis and the Ganger causality test proposed by Toda and Yamamoto (1995).

Financial development is measured by the credit to private sector as a percentage of GDP. He finds that

there is a positive long - run relationship between financial development and economic growth in five

countries, namely, Cape Verde, Cote d'Ivoire, Ghana, Guinea and Liberia. In addition, financial

development leads economic growth in Ghana, Liberia and Mali; growth causes financial development

in Cote d'Ivoire, and a bidirectional causality exists in Cape Verde and Sierra Leone. Esso (2010b) re-

visits the evidence from ECOWAS over the period 1960-2005, using cointegration tests that account

for structural change. The study shows that financial development leads economic growth in Ghana

and Mali, while growth causes finance in Burkina Faso, Cote d'Ivoire and Sierra Leone, and finance

and growth cause each other in Cape Verde and Liberia. Aka (2010) also examines the link between

financial development and economic growth for the eight member countries of the West Africa

Economic and Monetary Union (WAEMU) over the period 1961-2005. He builds a synthetic financial

development indicator using the principal component analysis. He finds unidirectional causality

running from finance to economic growth in 3 countries, and bidirectional causality in 5 countries.

Even though the studies by Esso (2009, 2010a,b) and Aka (2010) considered the ECOWAS or

WAEMU region, they analyze each country individually, instead of collectively as a panel, which

would have improved the efficiency of the parameter estimates and reveal cross sectional dependencies

if any. Ncanywa and Mabusela (2019) employ panel autoregressive and distributive lag model to

depict the relationship between financial development and economic growth in five selected sub-

Saharan African countries (Botswana, Ghana, Kenya, Nigeria, South Africa) for the period 1980–2014.

In the long run, bank credit to the private sector and liquid liabilities have a positive influence on

economic growth.

With respect to the relationship between trade openness and economic growth, the empirical

evidence is also quite varied and inconclusive. There is accumulated evidence supporting the positive

influence of trade openness on economic growth (e.g., Frankel and Romer, 1999; Deme, 2002;

Yanikkaya, 2003; Wang et al., 2004; Das and Paul, 2011; Shahbaz, 2012; Hye et al., 2016; Kim et al.,

2016; Zarra-Nezhad et al., 2016). On the other hand, a number of studies reported a negative impact of

trade openness on economic growth (e.g., Vlastou, 2010; Hye and Lau, 2015), while others fail to find

significant relationship between trade openness and economic growth (Vamvakidis, 2002; Tekin, 2012;

Fenira, 2015; Ulaşan, 2015). Dufrenot et al. (2010) apply the quantile regression approach to explore

the trade-growth nexus for 75 developing countries. Their results indicate that the effect of openness on

economic growth is higher in low-growth countries relative to high-growth countries. The low-growth


economies include countries from all the continents, but a majority is in Africa (Benin, Cote d’Ivoire,

Madagascar, and Zambia) and Latin America. For a sample of 34 African countries, Vlastou (2010)

finds that openness to trade has a negative impact on economic growth. He also reports a causal

relationship running from openness to growth. Kim et al. (2011) use instrumental variable threshold

regressions to examine whether the trade-income relationship varies with the level of economic

development. Their results show that trade openness stimulates economic development in high-income

countries. In low-income countries, however, the effect is negative. Asfaw (2014) investigates the

impact of trade liberalization on economic growth in 47 Sub-Saharan African countries. He shows that

openness to trade stimulates both economic growth and investment. Brueckner and Lederman (2015)

employ the instrumental variable approach to a panel of 41 Sub-Saharan African countries. They find

that trade openness increases economic growth both in the short and long run. Were (2015) finds that

trade exerts a positive and significant effect on economic growth rate in developed and developing

countries, but its effect is not significant for least developed countries which largely include African

countries. Keho (2017) examines the impact of trade openness on economic growth for Cote d’Ivoire

over the period 1965–2014 in a multivariate framework including capital stock, labor and trade

openness. Using the Autoregressive Distributed Lag bounds test to cointegration and the Toda and

Yamamoto (1995) Granger causality tests, he shows that trade openness has positive effects on

economic growth both in the short and long run. In addition, the results from Granger causality tests

reveal unidirectional causality from capital, labor, and trade openness to economic growth.

Furthermore, a positive and strong complementary relationship exists between trade openness and

capital formation in promoting economic growth in Cote d’Ivoire. Khobai et al. (2017) study the

relationship between trade openness and economic growth in Ghana and Nigeria for the period from

1980 to 2016. The results from the application of the ARDL bounds test show that trade openness has a

positive and significant impact on economic growth in Ghana while in Nigeria trade openness has a

negative but insignificant effect on economic growth. In the short-run trade has a positive and

significant impact on economic growth in both countries. Alam and Sumon (2020) examine the causal

relationship between economic growth and trade openness for 15 Asian countries over the period 1990-

2017. They apply panel cointegration and causality approaches and find that trade openness has a

positive impact on economic growth. Furthermore, the Granger causality analysis reveals a

bidirectional causality between economic growth and trade openness.

Most of the above studies have been conducted in a bivariate framework or do not consider the

joint effect of trade openness and financial development on economic growth. Recently, an extensive

empirical literature has attempted to investigate the relationship between financial development, trade

openness and economic growth, simultaneously thereby creating multivariate analytical frameworks.

Using various time spans, different econometric methodologies and different measures for trade,

financial development and economic growth, this literature produced mixed and even conflicting

results. For instance, Udegbunam (2002) examines the relationship between trade openness, economic

growth and financial development in Nigeria for the period from 1970 to 1997. The study reveals that a

combination of financial development and trade openness had a strong positive and significant effect

on economic growth in Nigeria. Beck and Levine (2004) analyze the impact of stock market and bank

development on economic growth in a panel of 40 countries over the period 1976-1998. Using the

Generalized Method of Moments (GMM) estimators, the results show that both variables positively

influence economic growth. The effect of trade openness is insignificant in most of the models. Gries

et al. (2009) investigate financial development, economic development and trade openness

interrelationships in the Sub-Saharan African (SSA) countries and record that financial development

and trade openness have negligibly influenced economic growth. They also provide evidence that

economic growth causes trade openness in Ethiopia, Gabon, Kenya, Mauritius, Senegal, Sierra Leone,

and Togo, whereas a feedback causal relationship exists for Cameroon, Cote d’Ivoire, Nigeria and

Rwanda. On the contrary, no causal relationship between trade and growth was found for Burundi,

Ghana, Madagascar, South Africa, and Gambia. Furthermore, they find bi-directional causality


between financial development and trade openness. Ogbonna (2010) examines the case of Botswana

and finds that trade openness and economic growth were responsible for sustainable financial

development. Gries et al. (2011) investigate the causal link between finance, growth and trade

openness for 13 Latin American and Caribbean countries. Their empirical results do not reveal any

direct or indirect link between the three variables. Kim (2011) shows that openness to trade exerts

positive effects on economic growth and real income in developed countries but negative effects in

developing countries. Furthermore, the growth effect of trade openness also depends on the level of

financial development and inflation. Openness to trade has negative effect on growth in countries with

low financial development, but has insignificant impact in countries with high financial development.

In addition, trade openness is conducive to economic growth in low-inflation countries but has

insignificant impact on economic growth in high-inflation countries. Kim et al. (2012) provide

evidence that trade promotes economic growth in high-income, low-inflation, and non-agricultural

countries but has a negative impact in countries with the opposite attributes. Adu et al. (2013)

investigate the effects of financial development on economic growth in Ghana over the period 1961-

2010. They use the ARDL bounds approach to cointegration and find that credit to private sector and

domestic credit are conducive to growth, whereas money supply is growth-retarding. They also report

some evidence of trade openness impeding growth. Adusei (2013) also examines the case of Ghana

using annual data for the period from 1971 to 2010. He finds that whereas domestic credit as well as

broad money supply hamper economic growth both in the short and long run, credit to private sector

has a positive but statistically insignificant relationship with economic growth. The author concludes

that financial development undermines economic growth in Ghana. The effect of trade openness on

growth is positive but statistically insignificant. Investigating the case a panel of 46 countries, Huang

and Chang (2014) find that the effect of trade on growth depends on the extent of stock market

development. Trade enhances economic growth only when the country reaches a threshold level of

stock market development. Menyah et al. (2014) study the causal nexus among financial development,

trade openness, and economic growth for 21 Sub-Saharan African countries. The empirical results

suggest that financial development and trade openness do not Granger-cause economic growth in Sub-

Saharan Africa. Further, trade openness was found to cause economic growth in Benin, Sierra Leone,

and South Africa. Abubakar et al. (2015) examine the relationship among financial development,

human capital accumulation and growth in the ECOWAS region over the period from 1980 to 2011.

They employ panel cointegration approaches as well as the Fully Modified OLS (FMOLS) and

Dynamic OLS estimators. The results reveal that bank private credit and domestic private credit

contribute significantly to economic growth in the ECOWAS, both directly and through their influence

on human capital accumulation. The results also show that openness to trade has positive effect on

growth while FDI has either negative or insignificant influence on growth. Kaushal and Pathak (2015)

investigate the causal relationship among financial development, economic growth and trade openness

in India over the period 1991-2013. Their findings suggest that economic growth and financial

development have a positive effect on trade openness. Ngongang (2015) tests the link between

financial development and economic growth in the context of 21 Sub-Saharan African countries during

the period 2000-2014. Financial development is measured by stock market capitalization and bank

credit to private sector as ratios to GDP. Using the dynamic panel method of GMM, stock market

capitalization appears to be positively but insignificantly correlated to the growth rate of real GDP per

capita. On the contrary, bank credit to private sector negatively and significantly impacts on economic

growth. Furthermore, trade openness has a positive but insignificant impact on economic growth. Polat

et al. (2015) report that financial development stimulates economic growth in South Africa, while trade

openness impedes growth. They also find bidirectional causality between financial development and

trade openness both in the short and long run. Iheanacho (2016) applies the ARDL approach to Nigeria

over the period 1981–2011 and finds that the relationship between financial intermediary development

and economic growth in Nigeria is insignificantly negative in the long-run and significantly negative in

the short-run. The effect of trade openness is found to be insignificant in the long run and negative and

significant in the short run. For the Author, her findings confirm what has been observed generally in


oil-dependent economies where economic activities are driven by oil price determined in the

international oil market and not by domestic economic activities; creating economic conditions that

adversely affect the ability of financial intermediaries to allocate resources efficiently. Lawal et al.

(2016) apply the ARDL methodology to Nigeria and find a negative long-run impact of trade openness

on economic growth but a positive effect in the short run. Further, a two-way causality was found

between the two variables. Sehrawat and Giri (2016) investigate the finance-growth nexus for South-

Asian Association for Regional Cooperation (SAARC) countries over the period 1994-2013. Using

FMOLS and DOLS methods, they find that financial development and trade openness contribute to

economic growth in SAARC region. Diallo and Mendy (2017) examine the growth effect of financial

development in the West African Monetary Zone (WAMZ). They apply the Group Mean method and

Dynamic OLS (DOLS) technique to annual data covering the period 1990-2015. The results indicate

that financial development has a positive long run impact on economic growth when measured by

liquid liabilities whilst domestic credit to private sector exerts no impact on economic growth in the

long run. The results further show a significant and negative effect for trade openness suggesting that

trade undermines economic growth in WAMZ. At country level, the results reveal that financial

development contributes to economic growth in four countries (The Gambia, Ghana, Nigeria and

Sierra Leone), while it undermines economic growth in Liberia and has not significant effect in

Guinea. Ofori-Abebrese et al. (2017) apply the ARDL approach and Granger causality test to examine

the finance and growth relationship in Ghana over the period 1970-2013. They report that domestic

credit to private sector has a positive and significant impact on economic growth while trade openness

impedes economic growth. Bist (2018) investigates the issue for a panel of 16 selected low-income

countries for the period from 1995 to 2014. The author finds that trade openness and financial

development proxied by credit to private sector, have long-run positive and significant impact on

economic growth. The estimates of individual countries showed that 9 countries out of 16 have a

significant positive relationship between financial development and economic growth. The short run

causality analysis shows that economic growth causes financial development and there is no causal link

between economic growth and trade openness. Ogbebor and Ohiomu (2018) investigate the impact of

FDI, and trade openness on economic growth in the ECOWAS area by including financial

development and other control variables. They apply fixed and random effects models along with the

system generalized method of moments to data covering the period 2000-2016. The results show that

FDI, trade openness and domestic credit to private sector exert significant and positive influence on per

capita income in ECOWAS. Rani and Kumar (2018) examine the case of BRICS countries using panel

data from 1993 to 2015. They find that trade openness and money supply have positive effects on

economic growth while foreign direct investment inflows have a negative impact. The results from

Granger causality confirm bidirectional causality between FDI and economic growth, and between

domestic credit and growth. Furthermore, money supply is caused by economic growth. Guru and

Yadav (2019) investigate the relationship between financial development and economic growth for a

panel of five major emerging countries of BRICS (Brazil, Russia, India, China and South Africa)

during the period from 1993 to 2014. The results from System Generalized Method of Moment

estimation show that financial development and exports are positively and significantly determining

the economic growth of the selected countries. Guei and Le Roux (2019) examine the impact of trade

on GDP per capita in 15 ECOWAS member countries over the period 1990–2016. Using the PMG

estimation method in a multivariate framework, the results show that trade openness and GDP per

capita have a negative relationship in the long run. The impact of trade openness on economic growth

is negative and significant in eight countries (Cape Verde, Cote d’Ivoire, Gambia, Guinea-Bissau,

Mali, Niger, Nigeria, Senegal). Finally, Ogbebor et al. (2020) investigate the case of Nigeria for the

period 1986-2016, using vector error correction model and causality tests. They find that stock market

development, foreign direct investment and trade openness promote economic growth. Furthermore,

the Granger causality results confirm the existence of bidirectional causality between economic growth

and FDI, trade openness, stock market development and banking sector development.


All in all, the literature reviewed above clearly shows that the relationship between financial

development, trade openness and economic growth is subject to diverse and conflicting findings. This

suggests that not all countries take equal advantage from financial development and trade openness.

Notwithstanding this, the conventional wisdom remains that openness to international trade and

development of the financial sector are beneficial to economic development, especially for developing

countries. It is mainly in view of this belief, that international organizations routinely recommend trade

and financial liberalization policies to developing countries in the hope of opening up and integrating

them into the global market. These recommendations are fueled by findings from empirical studies

showing that more outward-oriented and financially-developed economies record higher economic

growth rates.

The major factors responsible for controversial results in the empirical literature include, inter

alia, the time periods, the data measurement and the methodologies used. At the methodological level,

most of previous studies did not address the problem of endogeneity which is a serious problem in time

series studies. When this issue is addressed, the choice of instrumental variables is questionable. For

instance, in their study on 74 developing countries, Beck et al.(2000) control for the endogeneity of

financial development by using the legal origin of the law (Anglo-saxon, French, Germanic and

Scandinavian). With regard to studies that have employed Generalized Method of Moments,

endogeneity is controlled for by using lagged levels or differences of the explanatory variables as

instrumental variables. The use of those internal instruments may not be efficient under certain

conditions. Furthermore, previous studies did not adequately dealt with the issues of cross-section

dependency and heterogeneity; they relied on the assumptions of independence and homogeneity

concerning the countries studied. Differences in economic structure, financial sector reform and trade

policies as well as in their implementation may explain why the relationship among financial

development, trade openness and economic growth is country-specific (Badun, 2009). Consequently,

the results from these studies may be questionable if data exhibit cross-country dependency and

heterogeneity.

The mixed evidence in the empirical literature implies a literature gap that calls for further

examination of the connections between financial development, trade openness and economic growth

where few studies have been conducted. Specifically, not many studies have been attempted to depict

the causal relationship among financial development, trade openness and economic growth in the

context of West African countries. Therefore, this paper contributes to the ongoing debate on the

growth effects of trade openness and financial development by using relevant estimation methods that

accounts for some shortcomings in previous studies.

3. Model Specification and Methodology This section presents the empirical model and outlines the econometric methodology of the study.

3.1. Model Specification

To examine the long run relationship between financial development, trade openness and economic

growth, the following econometric model is specified:

Yit=β0i+ β1iFDit+ β2iTOit +β3i Xit +µ it (1)

where Yit stands for economic growth defined as the logarithm of real gross domestic product per

capita, FDit is financial development indicator, TOit represents trade openness, Xit denotes a set of

control variables, and µ it is an error term assumed to be a white-noise process. The coefficient β0i is the

country-specific fixed effect, while β1i and β2i are the country parameters related to financial

development and trade openness, respectively. The model assumes heterogeneity amongst the


countries, allowing individual intercepts and slope coefficients to vary across countries. The set of

control variables considered in this study includes gross fixed capital formation and population as

proxy for labor force. In terms of a priori expectations, financial development and trade openness are

predicted to be positively correlated with real GDP per capita. Gross fixed capital formation

contributes to capital accumulation and is expected to be positively correlated with GDP per capita.

3.2. Econometric Methodology

The estimation procedure used in this study draws on recent developments in heterogeneous panel

regressions. The methodology of the study follows five steps. First, the question of whether a cross-

country dependency exists was tested. It has been shown that if the variables as well as the error term

of Eq.(1) suffer from cross-sectional dependence, the estimates will be biased and inconsistent

(Driscoll and Kraay, 1998; Pesaran, 2006; Sarafidis and Wansbeek, 2012). To test for cross-sectional

independence (i.e. cov(µ it , µ jt )=0), we employ the tests suggested by Breusch and Pagan (1980) and

Pesaran (2004). The second step examines the heterogeneity between countries, which arises as a result

of different country intercepts and varying regression coefficients of the relationship among the

variables. More especially, we test the null hypothesis H0: βki=βk for all i and k=0,1,2,3, against the

alternative of heterogeneity H1: βki≠βk. To achieve this end, we use the delta tilde and adjusted delta

tilde homogeneity tests developed by Pesaran and Yamagata (2008) along with the test proposed by

Swamy (1970). In a third step, to avoid the problem of spurious regression related to non-stationary

variables, we determine the integration order of the variables. This is achieved through the use of the

Cross-sectionally Augmented Dickey-Fuller (CADF) unit root test proposed by Pesaran (2007), which

takes into account cross-sectional dependency and heterogeneity. Fourth, we estimate Eq.(1) using the

Common Correlated Effects Mean Group (CCEMG) estimator designed by Pesaran (2006). This

estimator deals with the issue of cross-section dependence by augmenting the regression equation with

the cross-sectional averages of the dependent variable as well as the regressors, as follows:

ittitititiitiitiitiiit eXdTOdFDdYdXTOFDY ++++++++= 43213210 ββββ (2)

where X=(lnK, lnPOP). This equation is estimated by OLS for each cross-section. The consistent mean

group estimator is derived as the simple average of the group-specific estimates. The CCEMG

estimator was found to be robust to cross-country dependence, heterogeneity, omitted variables,

endogeneity of regressors and structural breaks (Pesaran, 2006; Kapetanios et al., 2011; Pesaran and

Tosetti, 2011).

To test whether there is a long-run relationship between the variables, we perform the residual-

based panel cointegration test. We apply the Cross-sectionally Augmented Dickey-Fuller (CADF) unit

root test to the residuals obtained from the CCEMG estimation of Eq.(1). In presence of cointegration

among the variables, we estimate the short run relationship through a panel error correction model

given by:

∆Yit=γ0i+ γ1i∆FDit+ γ2i∆TOit + γ3i ∆Xit +λiECTit-1+µ it (3)

where Δ denotes the first difference operator and ECTit-1 is the lagged error correction term which is

derived from the long-run relationship among the variables. Eq.(3) is estimated using the CCEMG

estimator.

Finally, after estimating the long and short run dynamics of the variables, the study carries out

panel Granger causality tests to establish the direction of causality among the variables. The Granger

causality tests are based on the following panel vector error correction model:


ititjit

p

j

jjit

p

j

jjit

p

j

jjit

p

j

jit eECTXTOFDYY 111

1

1

1

1

1

1

1

11 ++∆+∆+∆+∆+=∆ −−

=

−

=

−

=

−

=

λθφγβα (4)

ititjit

p

j

jjit

p

j

jjit

p

j

jjit

p

j

jit eECTXTOFDYFD 212

1

2

1

2

1

2

1

22 ++∆+∆+∆+∆+=∆ −−

=

−

=

−

=

−

=

λθφγβα (5)

ititjit

p

j

jjit

p

j

jjit

p

j

jjit

p

j

jit eECTXTOFDYTO 313

1

3

1

3

1

3

1

33 ++∆+∆+∆+∆+=∆ −−

=

−

=

−

=

−

=

λθφγβα (6)

The optimal lag p is determined by Akaike Information Criterion (AIC). The Granger causality

approach explains that a variable Z1 causes another variable Z2 when the past values of Z1 help to

predict current changes in Z2. In addition to providing indication on the direction of causality, the error

correction model also allows us to identify both long and short run Granger causality. The long run

causality is identified by testing the significance of the coefficients on the error correction term (ECT).

The short run causality is determined by testing the significance of the coefficients of the lagged

difference terms by mean of Wald tests. For instance, in terms of short run causality, financial

development (FD) does not cause economic growth (Y) if the null hypothesis γ1j =0 (for all j) is not

rejected. Similarly, economic growth (Y) does not cause financial development (FD) if the null

hypothesis β2j = 0 (for all j) is not rejected. With regard to long run causality, financial development

does not cause economic growth (Y) if the null hypothesis λ1=0 is not rejected. The above system of

equations is estimated using the CCEMG estimator and SURE.

4. Data Description The study uses annual data for 11 West African countries, covering the period from 1985 to 2018. The

countries covered are: Benin, Burkina Faso, Cote d’Ivoire, Gambia, Ghana, Mali, Niger, Nigeria,

Senegal, Sierra Leone and Togo. The selection of countries and time periods is limited by data

availability.

The ultimate findings from an empirical study are sensitive to the choice of measurement for

variables. Several indicators of financial depth and trade openness have been used in the empirical

literature. These measures are considered as ratios of GDP. Thus, financial development is commonly

measured by credit to the private sector as a percentage of GDP or broad money as a share of GDP (De

Gregorio and Guidotti, 1995; Demetriades and Hussein, 1996; Beck et al., 2000; Levine et al., 2000;

Quartey and Prah, 2008; Uddin et al., 2013; Adeniyi et al., 2015). Trade openness is commonly

measured by the ratio of the sum of exports and imports over GDP (Yanikkaya, 2003; Kim, 2011; Adu

et al., 2013; Menyah et al., 2014; Bist, 2018). It is obvious that using such ratios may lead to

unexpected empirical results. Indeed, if GDP and an indicator X are positively correlated, and that

GDP grows faster than X, then GDP and X/GDP will be negatively correlated. A negative coefficient

on log of X/GDP does not necessarily imply that X impedes growth but that the elasticity of GDP with

respect to X is lower than one. Many studies have reached different conclusions depending on the

indicators used to proxy for financial development and trade openness (e.g., Quartey and Prah, 2008;

Ndako, 2010; Adu et al., 2013).

In this study, the variables are measured as follows. Following the literature (e.g., King and

Levine, 1993a; De Gregorio and Guidotti, 1995; Acaravci et al., 2009; Akinlo and Egbetunde, 2010;

Odhiambo, 2010), we use real per capita GDP as a measure for economic growth (Y). With respect to

financial development, we argue that focusing only on credit extended to the private sector is

insufficient to capture the essence of the financial sector which is that of intermediation, especially in

African countries where governments are compelled to borrow from the financial markets to provide

the needed infrastructure for economic growth and social development. Hence, in this study we use

total domestic credit provided by the financial sector (FD) instead of credit to the private sector


because we want to capture the full degree of financial intermediation in African economies. This

indicator is also preferred to broad money measure which reflects the use of currency rather than the

real level of financial intermediation. In most African countries, the large portion of broad money is

currency held outside the banking system. Total domestic credit by the financial sector accurately

mirrors the role of financial intermediation in transmitting funds to the whole economy.

With regards to trade openness, it is measured by the sum of real exports per capita and real

imports per capita (TO). We also include into the analysis per capita gross fixed capital formation (K)

and total population as control variables. The data are in 2010 constant US dollar and were gathered

from the World Development Indicators of the World Bank. All data enter the model in logarithm

form.

Table 1: Descriptive Statistics and Correlation Matrix

Y FD TO K POP

Panel A: Summary Statistics

Mean 6.603 4.894 6.000 4.818 16.176

Median 6.591 4.980 6.020 4.861 16.146

Maximum 7.849 6.619 7.270 6.690 19.092

Minimum 5.609 -4.151 4.442 -0.159 13.535

Std. Dev. 0.531 0.965 0.667 0.829 1.091

Panel B: Correlation Matrix

Y 1.000

FD 0.653* 1.000

TO 0.846* 0.614* 1.000

K 0.787* 0.452* 0.661* 1.000

POP 0.511* 0.357* 0.243* 0.607* 1.000

Note: Y: log of real GDP per capita, FD: log of per capita domestic credit provided by financial sector, TO: trade openness

as the log of the sum of real per capita exports and real per capita imports, K: log of per capita gross fixed capital formation,

POP: log of total population. * denotes significance at the 5% level

Table 1 outlays the summary statistics for the variables. This Table reveals a disparity among

the countries. The log of real per capita GDP averages 6.603 and varies from 5.609 to 7.849. The

financial development indicator also varies from -4.151 to 6.619. The maximum and minimum values

of the variables suggest that there is a wide gap among the countries in terms of per capita income,

capital accumulation, trade openness, financial development and population in the sub-region. The

features of the data clearly show that the use of heterogeneous panel data analysis procedure for the

estimation of the empirical model is appropriate. A look at the correlation matrix shows that real per

capita GDP correlates positively with all explanatory variables. Furthermore, all correlation

coefficients are lower than 0.8, implying that there is no problem of multicollinearity among the

explanatory variables.

5. Empirical Results and Discussion Our empirical analysis begins with tests of cross-sectional dependence and homogeneity. The results of

these tests are portrayed in Table 2. The results strongly indicate that the null hypothesis of no cross-

sectional dependence is rejected at the 5 percent level of significance. The cross-sectional dependence

tests thereby support evidence of high integration among the selected countries, implying that any

shock that occurs in one country can quickly be transmitted to other countries. The results also support

cross-country heterogeneity, implying that the relationship among real GDP per capita, financial

development, and trade openness differs across countries.


Table 2: Results for Cross-Sectional Dependence and Homogeneity Tests

Tests Statistic p-value

Cross-sectional dependence test

Breusch-Pagan LM 369.081 0.000*

Pesaran CD 12.174 0.000*

Pesaran scaled LM 29.946 0.000*

Homogeneity test

Delta 297.074 0.000*

Delta adjusted 316.063 0.000*

Swamy test 7406.80 0.000*

Note: * indicates significance at the 5% level

Given these results, the study uses panel unit root tests to depict the order of integration of the

variables. We first apply the well-known IPS test developed by Im et al. (2003), which is less

restrictive and more powerful compared to other first generation panel unit root tests. The IPS test

allows heterogeneity in the autoregressive coefficients, but assumes cross-section independence across

countries. We further employ the Cross-sectional Augmented Dickey-Fuller (CADF) test proposed by

Pesaran (2007), which deals with both heterogeneity and cross-sectional dependency. The results of

these tests are reported in Table 3. The IPS test indicates that the null hypothesis of unit root cannot be

rejected for real GDP and financial development while trade openness, capital and population are

stationary. On the contrary, the CADF test shows that all variables have unit root in level. However,

when applied to the first differences, the null hypothesis of unit root is rejected for all variables. Thus,

we can regard all variables as being integrated of order one, which suggests that there might be a long-

run relationship among them.

Table 3: Results of Panel Unit Root Tests

Variables Level First difference

IPS test CADF test IPS test CADF test

Y 1.052 [0.853] 2.669 [0.996] -9.612* [0.000] -3.518* [0.000] FD -0.093 [0.462] 3.033 [0.999] -15.918* [0.000] -2.566* [0.005] TO -3.201* [0.000] 0.375 [0.646] -17.002* [0.000] -4.506* [0.000] K -1.677* [0.046] 0.002 [0.501] -17.069* [0.000] -2.903* [0.002] POP -2.230* [0.012] 1.867 [0.969] -5.241* [0.000] -6.935* [0.000]

Notes: Y: log of real GDP per capita, FD is the log of per capita domestic credit provided by financial sector, TO is trade openness as the

log of the sum of real per capita exports and real per capita imports, K is the log of per capita gross fixed capital formation, POP is the log

of total population. The IPS test provides W-t-bar statistic, whereas the CADF test provides z-t-bar statistic of Pesaran (2007) test. p-

values are given in brackets. Optimal lag length was determined using AIC with a maximum of 5. * denotes rejection of the null

hypothesis of unit root at the 5% significant level.

After checking the variables for unit root, we estimate the long run relationship among the

variables. For comparison purposes, we first run the Mean Group (MG) estimator proposed by Pesaran

and Smith (1995), the Fully Modified OLS (FMOLS) developed by Pedroni (2000) and the Dynamic

OLS estimator suggested by Kao and Chiang (2000). Results are reported in Table 4. As expected,

financial development and trade openness are significantly positively related to economic growth in

two out of the three regressions. With regard to control variables, we can see that the effect of gross

fixed capital formation on real per capita GDP is positive and significant only in the mean group

regression. On the contrary, population has a positive and significant effect on real per capita GDP in

all the three alternative regressions. The magnitude of coefficients varies across regression methods.

The long run growth effects of financial development are 0.067, 0.014 and 0.084 for FMOLS, DOLS,

and MG regressions, respectively. Those of trade openness are 0.307, 0.261 and 0.041 for FMOLS,

DOLS and MG, and regressions, respectively. From these results, we can conclude that financial

development and trade openness are growth enhancing in the selected countries. Among the control

variables, the labor force proved to be a robust determinant of long-run economic growth.


Table 4: Long Run Estimates from FMOLS, DOLS and MG

Dependent Variable: lnYit

Variables FMOLS DOLS MG

FD 0.067* (4.823) 0.014 (0.663) 0.084* (4.930)

TO 0.307* (8.706) 0.261* (6.300) 0.041 (1.000)

K 0.009 (0.401) 0.039 (1.361) 0.093* (4.770)

POP 0.110* (2.527) 0.089** (1.865) 0.281* (2.02)

IPS -1.874* [0.030] -9.483* [0.000] -5.063* [0.000]

CADF 1.844 [0.967] -0.846 [0.199] -2.380* [0.009]

CD test 5.098* [0.000] 3.873* [0.000] 4.126* [0.000] Note: Y: log of real GDP per capita, FD is the log of per capita domestic credit provided by financial sector, TO is trade openness as the

log of the sum of real per capita exports and real per capita imports, K is the log of per capita gross fixed capital formation, POP is the log

of total population. Figures in parentheses are t-statistics. Unit root tests are conducted under the model with intercept and p-values are

given in brackets. Optimal lag length was determined using AIC with a maximum of 5. * (**) indicates significance at the 5% (10%) level

The three estimators allow for coefficient heterogeneity but do not deal with cross-sectional

dependence. As can be seen from the bottom rows of Table 4, they exhibit cross-section dependence in

the residuals. In addition, the CADF test results suggest rejection of the null hypothesis of unit root in

the residuals only in the MG regression. The residuals from both FMOLS and DOLS regressions have

unit root, rejecting the existence of a long run relationship among the variables. As mentioned above,

the existence of cross-sectional dependence may lead to misleading results. Therefore, estimator that

can accommodate both slope heterogeneity and cross-section dependence is required so as to provide

more reliable estimates.

We employ the CCEMG method to estimate both the long and short run relationships among

the variables. The results for the whole panel are reported in Table 5. For each model we test the

residuals for unit root using heterogeneous panel unit root tests. The point estimate on the error

correction term (ECT) is negative and statistically significant. This provides evidence in support of the

existence of a long-run relationship between the variables. Furthermore, the IPS and CADF test results

suggest rejection of the null hypothesis of unit root in the residuals. Therefore, we can conclude that

there is a long run relationship among financial development, trade openness and economic growth in

selected countries over the period from 1985 to 2018.

Table 5: CCEMG Long and Short Run Estimates

Variables Long run coefficients Short run coefficients

Coef. t-stat. Prob. Coef. t-stat. Prob.

FD 0.037** 1.750 0.081 0.032** 1.67 0.094

TO 0.052* 2.390 0.017 0.044** 1.72 0.085

K 0.057* 2.740 0.006 0.039* 2.93 0.003

POP -1.011 -0.580 0.561 0.325 0.53 0.599

ECT -0.696* -13.86 0.000

Obs. 374 363

IPS -9.568* [0.000] -11.519* [0.000]

CADF -5.404* [0.000] -4.267* [0.000] Note: The dependent variable is the log of real GDP per capita. FD is the log of per capita domestic credit provided by financial sector,

TO is trade openness as the log of the sum of real per capita exports and real per capita imports, K is the log of per capita gross fixed

capital formation, POP is the log of total population, ECT denotes the error correction term. IPS unit root test provides W-t-bar statistic,

whereas the CADF test provides z-t-bar statistic. Optimal lag length was determined using AIC with a maximum of 5. IPS and CADF

tests are conducted in the case of an intercept only. The p-values are indicated in brackets. The asterisks * and ** indicate significance at

the 5% and 10% levels, respectively.

Looking at the long run estimates, we note that financial development exerts a significant

positive effect on real per capita GDP. Other things remain the same, a one percent increase in per

capita domestic credit causes the real per capita GDP to increase by 0.037 percent in the long run.

Similarly, trade openness has a positive impact on economic growth. The results show that keeping


other things constant, a one percent rise in trade openness increases real per capita GDP by 0.052

percent. Thus, financial intermediation and trade are playing a significant role in enhancing economic

growth in ECOWAS countries. These results suggest that ECOWAS countries can accelerate their

economic growth by improving their financial systems and opening up their economies. Another

important determinant of economic growth is gross fixed capital formation. The results indicate that

gross fixed capital formation is positively related to real per capita GDP. If all other things remain the

same, one percentage increase in gross fixed capital formation is associated with 0.057 percent increase

in real per capita GDP.

With regard to the short run estimates, domestic credit and trade openness exert positive impact

on economic growth. The results also show that gross fixed capital formation impacts positively on

economic growth. Conversely, population shows a positive but non-significant effect on economic

growth. The results confirm that financial intermediation, trade openness and capital formation are

major factors influencing economic growth of West African countries both in the long and short run.

Overall, the results of this study show that financial development has significant enhancing

impact on economic growth both in the long and short run. This finding is consistent with those of a

number of studies (e.g., King and Levine, 1993a; Beck et al., 2000; Beck and Levine, 2004;

Christopoulos and Tsionas, 2004), but contradicts with others (Demetriades and James, 2011;

Ngongang, 2015). Similarly, international trade plays a significant role in the economic growth of

West African countries, validating the trade-led growth hypothesis both in the short and long run. This

finding accords with those of Asfaw (2014), Zarra-Nejad et al. (2014), and Brueckner and Lederman

(2015), but contradicts with Vlastou (2010), Beck and Levine (2004), Ngongang (2015), Polat et al.

(2015), Ulaşan (2015), and Were (2015) who reported a negative or insignificant impact of trade

openness on economic growth. The findings of this study are also in accordance with those of

Abubakar et al. (2015), Bist (2018) and Ogbebor and Ohiomu (2018) who reported that domestic credit

to private sector and trade openness have positive and significant effect on economic growth. However,

they are not consistent with those of Gries et al. (2009) who found that financial development and trade

openness have negligible influence on economic growth in Sub-Saharan Africa.

Once the long-run panel coefficients are estimated for the whole panel, we further estimate the

long-run relationship for each individual country. This is important to understand the impact of

financial development and trade openness on real per capita GDP across the sample countries. Table 6

displays the country-level results for the long run relationship between the variables. The long-run

coefficients are estimated using the CCEMG estimator. For comparison purposes, we also report the

results from estimation using the Seemingly Unrelated Regression Estimator (SURE). Our empirical

analysis will combine the results from these two estimation methods. As expected, the results show

considerable heterogeneity in the relationship between financial development, trade openness and

economic growth. It is worth emphasizing that out of the 11 countries, financial development exerts a

positive and significant impact on economic growth in eight countries (Benin, Burkina Faso, Cote

d’Ivoire, Ghana, Niger, Nigeria, Senegal and Togo). This means that development in the financial

sectors will positively affect economic growth. Thus, these countries have much to gain by developing

their financial sectors. Likewise, for 3 countries (Gambia, Mali, Sierra Leone), there is no significant

impact of financial development on real per capita GDP.

The absence of significant effect of financial development on economic growth in Gambia,

Mali and Sierra Leone could be attributed to the relatively less developed financial sectors in these

countries. Weak financial institutions provide rooms for misallocation of resources which leads to poor

economic growth. As a policy recommendation, policies must be put in place to support development

of growth-enhancing financial sector. For financial development to have a positive effect on economic

growth in these three countries, it is necessary that the expansion of the financial system be

accompanied by an increase in the domestic credit towards productive uses. Our finding for Sierra

Leone is not in line with Kargbo and Adamu (2009) who reported that financial development has a

positive and significant effect on economic growth.


The results also reveal a significant positive long run effect of trade openness on real per capita

GDP for six countries (Benin, Cote d’Ivoire, Mali, Senegal, Sierra Leone and Togo). Thus, the strategy

of opening up these countries is a better development policy with the aim of accelerating economic

growth. Likewise, the effect of trade openness on real per capita GDP is insignificant for 4 countries

(Burkina Faso, Gambia, Niger and Nigeria). However, in the case of Ghana, trade openness has a

negative impact on real per capita GDP. The results for Cote d’Ivoire confirm those of Keho (2017)

who found that trade openness has a positive effect on economic growth both in the long and short run.

Our findings for Burkina Faso, Nigeria, Senegal, Sierra Leone and Togo support those of Sakyi et al.

(2014) while the results for Benin, Cote d’Ivoire, Gambia, Ghana, Mali and Niger contradict with it.

The results of this study also contradict Osabuohien (2007) who found that trade openness impacts

positively economic growth in Ghana and Nigeria. On the other hand, our results are not in line with

Iheanacho (2016) who finds that financial development has insignificant long run effect on economic

growth and negative effect in the short run in Nigeria. In the case of Ghana, a justification of the

negative long run relationship between trade and growth is that trade liberalization might have exposed

domestic industrial sector to foreign competition thereby adversely impacting on long run real GDP.

Our results further show that gross capital formation has a positive impact on economic growth in the

majority of the countries.

Table 6: Individual Country Results of Long-Run Estimates

CCEMG SURE

Country FD TO K POP FD TO K POP

Benin -0.011

[-0.77]

0.027

[1.06]

0.014

[0.47]

3.007*

[3.91]

0.018*

[3.571]

0.109*

[6.100]

0.023

[1.269]

0.276*

[9.572]

Burkina Faso 0.053

[1.54]

-0.030

[-0.50]

0.023

[0.45]

2.621

[0.90]

0.065*

[5.421]

0.008

[0.392]

0.053*

[1.977]

0.634*

[15.911]

Cote d’Ivoire 0.182*

[3.80]

0.167*

[2.00]

0.041

[1.10]

3.831*

[5.53]

0.142*

[7.175]

0.054

[1.430]

0.171*

[9.957]

-0.132*

[-4.391]

Gambia -0.002

[-0.28]

0.034

[0.74]

0.058*

[2.82]

-1.115

[-1.14]

0.001

[0.536]

-0.004

[-0.201)

0.018*

[1.959]

-0.088*

[-3.229]

Ghana 0.094**

[1.79]

-.012

[-0.24]

0.034

[1.54]

0.481

[0.22]

0.217*

[4.637]

-0.219*

[-5.230]

-0.035

[-1.194]

1.212*

[13.217]

Mali 0.098*

[2.97]

0.121

[1.60]

0.126*

[1.97]

0.073

[0.10]

0.023

[1.387]

0.101*

[2.067]

0.111*

[3.079]

0.396*

[7.462]

Niger 0.009

[0.29]

-0.035

[-0.53]

-0.027

[-0.60]

-1.231

[-0.79]

0.126*

[8.693]

-0.066

[-1.422]

0.101*

[3.824]

-0.140*

[-4.179]

Nigeria 0.069*

[4.16]

-0.011

[-0.31]

0.027

[0.36]

-17.500*

[-6.30]

0.074*

[3.671]

0.020

[0.702]

0.181*

[2.002]

0.916*

[8.531]

Senegal 0.061

[1.35]

0.083

[1.15]

0.070

[1.12]

-1.988*

[-3.38]

0.144*

[12.071)

0.097*

[2.168]

0.047

[1.030]

0.220*

[6.402]

Sierra Leone 0.020

[0.72]

0.143*

[3.80]

0.031

[1.30]

0.754

[1.41]

0.018

[0.746]

0.278*

[7.577]

0.028*

[1.855]

-0.002

[-0.027]

Togo 0.020

[0.38]

0.084

[1.41]

0.235*

[4.59]

-0.055

[-0.03]

0.065*

[2.293]

0.083*

[2.490]

0.159*

[5.131]

-0.024

[-0.786]

Table 7 reports the country-level results of short run dynamics. As can be seen, financial

development enhances economic growth in 6 countries (Burkina Faso, Cote d’Ivoire, Mali, Nigeria,

Senegal, and Sierra Leone). Trade openness growth is associated with an increase in economic growth

in five countries (Benin, Cote d’Ivoire, Mali, Sierra Leone, and Togo). The point estimate on the

lagged error correction terms is negative and statistically significant in all countries. This provides

additional evidence in support of the existence of a long run relationship between financial

development, trade openness and economic growth.


Table 7: Individual Country Results of Short-Run Estimates

Country CCEMG SURE

∆FD ∆TO ∆K ∆POP ECT ∆FD ∆TO ∆K ∆POP ECT

Benin 0.006

[0.550]

0.068*

[2.590]

0.003

[0.150]

2.314*

[1.070]

-0.764*

[-3.390]

0.003

[0.413]

0.113*

[5.814]

-0.001

[-0.049]

-0.597

[-0.514]

-0.497*

[-3.253]

Burkina Faso 0.038**

[1.840]

-0.023

[-0.580]

0.023

[0.720]

3.216

[0.740]

-0.654*

[-2.110]

0.043*

[3.175]

-0.044**

[-1.778]

0.047*

[1.982]

3.144

[1.175]

-0.393*

[-3.057]

Cote d’Ivoire 0.195*

[5.920]

0.156*

[3.200]

0.027

[1.160]

2.420*

[3.280]

-0.450*

[-3.230]

0.162*

[4.370]

0.089*

[1.986]

0.085*

[3.861]

-0.123

[-0.197]

-0.339*

[-2.514]

Gambia -0.011

[-1.480]

0.009

[0.240]

0.044*

[3.030]

-0.775

[-0.550]

-0.909*

[-3.910]

0.001

[0.298]

0.004

[0.165]

0.038*

[4.187]

-0.895

[-1.409]

-0.912*

[-6.767]

Ghana -0.025

[-0.790]

0.005

[0.190]

0.037**

[1.910]

-0.528

[-0.200]

-0.392**

[-1.870]

0.001

[0.015]

0.023

[1.044]

0.035*

[2.527]

-4.786*

[-3.162]

-0.213**

[-1.803]

Mali 0.090*

[2.780]

0.135*

[2.780]

0.046

[1.000]

0.637

[0.610]

-0.745*

[-3.630]

0.077*

[3.240]

0.123*

[3.131]

0.067*

[1.924]

-0.597

[-0.768]

-0.469*

[-3.312]

Niger -0.003

[-0.130]

-0.099**

[-1.710]

0.042

[1.160]

-2.415

[-1.200]

-0.691*

[-3.580]

-0.001

[-0.069]

-0.064

[-1.365]

0.058*

[2.000]

1.909

[1.335]

-0.494*

[-2.886]

Nigeria 0.028**

[1.900]

-0.021

[-1.160]

-0.018

[-0.430]

0.639

[0.090]

-0.875*

[-5.330]

0.036*

[3.753]

-0.006

[-0.510)

0.024

[0.771]

13.121*

[2.527]

-1.005*

[-8.389]

Senegal 0.053

[1.150]

0.012

[0.280]

0.045

[1.170]

-2.964*

[-1.940]

-0.737*

[-3.820]

0.093*

[3.169]

0.012

[0.407]

0.041

[1.524]

-3.263*

[-2.970]

-0.620*

[-4.540]

Sierra Leone 0.031**

[1.780]

0.180*

[5.460]

0.021

[0.990]

-1.070

[-0.660]

-0.585*

[-3.240]

0.023

[1.308]

0.178*

[6.187]

-0.018**

[-1.756]

1.220**

[1.789]

-0.730*

[-3.752]

Togo -0.048

[-0.920]

0.067

[1.530]

0.160*

[3.000]

2.110

[0.850]

-0.854*

[-4.050]

-0.009

[-0.207]

0.091*

[2.518]

0.122*

[3.644]

2.991

[1.469]

-0.676*

[-3.503]

Notes: CCEMG and SURE denote the Common Correlated Effects Mean Group estimator and the Seemingly Unrelated

Regression Estimator, respectively. The dependent variable is the growth rate of real GDP per capita, FD is the log

of per capita domestic credit provided by financial sector, TO is trade openness as the log of the sum of real per

capita exports and real per capita imports, K is the log of per capita gross fixed capital formation, POP is the log of

total population, ECT denotes lagged error correction term. Figures in brackets are t-statistics. The asterisks * and ** indicate significance at the 5% and 10% levels, respectively

Based on these results, the next step is to test for the existence and the direction of causal

relationships among the variables. The outcomes of Granger causality test are depicted in Table 8. It is

evident from the results that both financial development and trade openness cause real per capita GDP

in the long run. On the other hand, economic growth and trade also cause financial development.

Furthermore, economic growth and financial development cause trade openness. Thus, in the long run,

financial development, trade openness and economic growth are mutually causal. This finding suggests

that financial development and trade openness are both a cause and a consequence of economic

growth. The bidirectional causal relationship between financial development and economic growth is

consistent with the view of Robinson (1952) that financial development promotes economic growth

and this, in turn, generates higher demand for financial services and resources which induces further

financial development. This result is consistent with the findings of Fowowe (2011) for 17

Sub‐Saharan Africa countries. We conclude that policies aimed at improving financial sectors will

have a significant effect on economic growth and vice versa. The bidirectional causal relationship

between trade openness and economic growth is also consistent with Sakyi et al. (2014). Our findings

contradict those of Menyah et al. (2014) who found limited support for trade and finance causing

economic growth in a panel of 21 Sub-Saharan African countries. As mentioned in the literature

review, previous studies based on panel data may be plagued with the problems of cross-sectional

dependence and heterogeneity.


Table 8: Results of the Granger Causality Tests

Dependent

variable

Direction of Granger Causality

Short Run Long Run

Y FD TO K ECTt-1

Y - 6.860 [0.143] 9.580* [0.048] 10.740* [0.029] 10.840* [0.001]

FD 3.670 [0.452] - 9.710* [0.045] 44.770* [0.000] 2.640** [0.09]

TO 6.430 [0.169] 4.490 [0.344] - 5.350 [0.253] 4.100* [0.042]

K 2.430 [0.656] 10.640* [0.030] 13.600* [0.008] - 0.270 [0.600]

Note: Y: log of real GDP per capita, FD: per capita domestic credit provided by financial sector, TO: trade openness as the

sum of real per capita exports and real per capita imports, K: per capita gross fixed capital formation, ECT: error

correction term. The lag order was set to 4 based on AIC. χ2 statistics for Wald tests are reported here and the p-

values are indicated in brackets. Significance at 5% and 10% levels are denoted with * and ** , respectively

A look at the short run causality shows strong evidence of unidirectional causality running from

trade openness and gross fixed capital formation to economic growth and financial development. On

the other hand, both financial development and trade openness cause gross fixed capital formation.

Thus, we can say that in the short run, financial development causes economic growth indirectly

through capital formation while trade openness causes economic growth directly and indirectly through

capital accumulation. Therefore, investment is an important channel through which financial

development and trade openness feed economic growth. Financial development as proxy by domestic

credit increases supply of funds to productive sectors which influences overall economic growth

through increased investment in the economy. These findings are not consistent with those of Bist

(2018) who found that economic growth causes financial development and that there is no causal link

between economic growth and trade openness.

6. Conclusion The relationship between financial development, trade openness and economic growth has received a

great deal of attention among economists over the last three decades. Despite voluminous research on

this topic, the empirical evidence is inconclusive. This is particularly true for studies that have

examined the experience of African countries. These studies end up with mixed results due to several

reasons including the use of various estimation techniques and proxies of financial development and

trade openness measures. With regards to estimation technique, most existing studies have used

standard panel estimation methods assuming cross-country independence and slope homogeneity. This

study empirically contributes to the ongoing debate on the relationship between financial development,

trade openness and economic growth for a panel of 11 selected West African countries which are

working towards achieving a convergence macroeconomic framework. As proxy for financial

development, the study used per capita domestic credit provided by financial sector which measures

how much intermediation is performed by the financial system, including credit to the public and

private sectors. The study also used per capita foreign trade as proxy for trade openness, and real per

capita GDP as measure of economic growth. Further, per capita gross fixed capital formation and

population were included as control variables. The study utilizes panel unit root, cointegration and

Ganger causality tests and data covering the period from 1985 to 2018. The first tests showed that there

exists a cross-sectional dependence across the countries. Therefore, contrary to previous studies, we

applied the Common Correlated Effects Mean Group (CCEMG) estimator and the Seemingly

Unrelated Regression Estimator (SURE) that cope with both cross-sectional dependency and

heterogeneity. The empirical results of the study showed that financial development and trade openness

have, on average, positive effect on real per capita GDP both in the long and short run. The results also

confirmed the positive and significant role of capital formation in economic growth.

The country-level results revealed, however, considerable heterogeneity across countries. The

long-run effect of financial development was positive in the majority of the countries. The estimates


revealed that out of 11 countries, 8 countries (Benin, Burkina Faso, Cote d’Ivoire, Ghana, Niger,

Nigeria, Senegal and Togo) have a positive and significant impact of domestic credit on real per capita

GDP. Conversely for 3 countries (Gambia, Mali, Sierra Leone), there is no significant impact of

financial development on real per capita GDP. Further, the results showed that trade openness is

positively related to economic growth in 6 countries (Benin, Cote d’Ivoire, Mali, Senegal, Sierra Leone

and Togo). Likewise, for 4 countries (Burkina Faso, Gambia, Niger, Nigeria) there is no significant

impact of trade openness on economic growth. However, trade openness has a negative impact upon

real per capita GDP in Ghana. Granger causality tests are conducted in order to find the direction of

causality between the variables. The results indicate that real GDP, financial development and trade

openness are complementary to each other in the long run. Trade and financial openness affect

economic growth positively and it in turn paves the way for financial development. In the short run,

there is unidirectional causality running from trade openness to economic growth and financial

development. The results also suggest that investment is an important conduit through which both

financial development and trade openness affect economic growth.

In the view of these findings it is recommended that countries in the sub-region should adopt

policies aimed at enhancing the development of the financial sector to accelerate their economic

growth. One of the reasons that have been slowing African growth is the small financial systems that

allocate capital inefficiently. One particular policy recommendation is to improve the accessibility to

affordable credits and financial services by a broader set of people and economic sectors. Access to

financial services may be improved by promoting the use of modern information and communication

technologies via electronic money and mobile banking, and sustaining the growth of microfinance

institutions particularly in rural areas. This would increase liquidity in the economy and also access to

funding by small and medium-scale enterprises. Additionally, policies should improve financial

markets so as to make the efficient and effective allocation of resources among the productive sectors

which in turn will enhance long run economic growth. The findings of this study also imply that a

portion of the economic growth of West African countries is external. Therefore, further efforts should

be made to allow more trade openness of the countries in order to achieve high and sustainable

economic growth. They should reduce trade barriers and simplify procedures and controls. However,

the heavily dependence on international trade may be detrimental to fiscal sustainability and economic

growth under the Prebisch–Singer law of decline in the terms of trade. Most African countries export

mainly primary products, which prices are unstable and determined on the international market. For

outward-oriented strategy to have much larger impact on economic growth, West African countries

should modify the composition of their exports by switching from exports of raw materials and semi-

manufactured goods to high valued-added goods. Furthermore, trade policy should promote

investments in capital intensive sectors and develop human capital that can absorb technologies

coming from advanced countries. The results also show that gross capital formation has a positive

impact on economic growth. This suggests that the public and private investment in the productive

sector are essential for the economic growth.

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International Research Journal of Finance and Economics ......International Research Journal of Finance and Economics - Issue 179 (2020) 17 is in view of these expected gains from