The Impact of Corruption on Financial Development in Africa

Saied EA

Published on: 2020-12-24

Abstract

This study examines the impact of corruption on financial development in 50 African countries during the period 2000 – 2014. The study uses dynamic system GMM estimator because it take care the endogeneity and country-specific-effect problems that may arise in panel data estimation. The results show that control of corruption, bank branches, human capital are highly determine financial development in Africa. The results provide empirical evidence for African policy-makers to introduce polices that aim to lower and to control corruption and to cover large areas by commercial bank branches in addition to invest more in the education of human capital.

Keywords

Corruption; Financial development; Africa; GMM

Introduction

It's now widely accepted that financial development has an important role to play in economic growth of countries. In fact, financial sector contributes in a positive significant manner to economic development as a source of fund to private sector that accelerates growth and facilitates trade. Not only this but also financial development conditioning the impact of FDI on economic growth as FDI starts enhancing economic growth only after financial development exceeds a threshold level [1]. It's also worth to mention that financial development attracts FDI flows into the host countries which has positive spillover effects on host economies such as –but not limited to- technology transfer, job creation, reducing poverty [2-3]. Also, financial development by itself enhances economic growth in most countries, reduces poverty rate of the poorer people, and decreases income inequality among population [4]. Since African economy depends mostly on trade of goods and services, then one have to consider the importance of financial sector to provide credits to private sectors and to finance African traders. However, on the other hand, corruption remains a serious problem that currently facing the region since most African countries are extremely suffering to control corruption. In this regard, corruption in Africa is one of the main deflators that harm economic growth of the continent. For instance, corruption significantly reduces economic growth and harms the financial market in countries where corruption levels are high Ali. Furthermore, corrupted countries tend to receive a less foreign capital flow which reduces the development of domestic financial markets [5]. From this end, this paper aims to examine the impact of corruption on financial development in Africa due to the importance of financial development in the performance of the economies. (Figure 1) shows the degree of association between control of corruption to proxy corruption- and financial development in Africa for the period of interest. The Figure shows that the two variables are highly associated which confirms the need to examine the impact of corruption on financial development in Africa. The rest of the paper organized as follows: section 2 is literature review, section 3 is methodology and data, section 4 is empirical results, and section 5 is conclusion.

Figure 1: Control of Corruption and Financial Development.

Literature Review

There is a huge gap in examining the relationship between corruption and financial development especially in Africa. In fact, a few studies have highlighted this issue, however, the impact of corruption on economic growth and economic development is a well-investigated issue. For instance, corruption affect healthcare services negatively as it seems to reduce the efficiency of the services provided throughout the healthcare system, this will affect the economic development of countries since it has been proven that health have positive significant impact on growth [6]. It's also worth to mention that the level of corruption in a country negatively affects the foreign financial inflows, as a results, highly corrupted countries tends to receive less FDI as well as foreign aid [7]. Also, corruption reduces the effective performance in many sectors and public programs as countries with higher corruption experience low performance compared to countries with low corruption- in many sectors [8]. That corruption is responsible for negative effects on different sectors in economies and omits the role of law and weakens the institutional foundation that economic growth depends on [9]. Theoretical and empirical literatures have identified five categories that determine the financial development level in a country. First, the legal tradition such as, but not limited to, contract enforcement, proper treatment of creditors, and property rights protection have been proved to be important in explaining the differences between countries in term of financial development [10]. Second, institution' quality play an important role in developing financial system in countries as institution quality can play important role in determining how financial development may affect economic growth [11]. Third, government intervention which harms financial development by allowing governments to controls banks and the allocations of credits, however, freeing financial system is critical to financial development. Fourth, trade-openness also critical in promoting financial development as countries with higher level of openness experience high level of financial development [12]. Fifth, political economy factors are very important in determining financial development as unconstrained political power undermines financial accumulation. However, political stability has important role in developing the financial sector as it's very important for local financial corporations to work under a stable system in order to provide credits co private investors and public companies as well [12]. Foreign direct investment (FDI) have a significant role to play in African country to develop the financial services in two ways, first, FDI provides the source of fund for many companies and domestic financial corporations, second, FDI has positive spillover over such as technology transfer that improve financial services in the host countries [13-14]. The impact of corruption on financial development is a less-investigated issue since most of the studies focus on other determinants of financial development that raises the need to conduct this study.

Methodology Empirical Model and Data

Methodology

To estimate the impact of corruption on financial development in Africa, this study uses the GMM estimator that introduced by [15]. The estimator is extended by Arellano and Bond, then by Arellano and Bover in addition to further extension by Blundell and Bond [16-17]. The study uses this estimator as it take care of the endogeneity problem that may arise in panel data estimations which means, at-least, one of the independent variables and the dependent variable are causing each other in the estimated Model. Also, GMM controls for country-specific effects which cannot be handled by using country-specific dummies because the dynamic behavior of the estimated Model. To overcome the possible endogeneity problem, suggested to use the lagged level of regressors as instruments if the error term not serially correlated, and if the lag of the explanatory variables are weakly exogenous. Also, to overcome the country-specific effects, suggested transforming the estimated model into first-difference to eliminate country-specific effects [18]. The moment conditions increase with the time in GMM estimations, therefore, the Sargan test will be performed to test the over-identification restrictions, Sargan test is to check the validity of the instruments used in the estimation. There is convincing evidence that too many moment conditions introduce bias while increasing efficiency. Therefore, it suggested that a subset of these moment conditions be used to take advantage of the trade-off between the reduction in bias and the loss in efficiency [19]. Besides, to test for the serial correlation in the error term, Arellano and Bond auto-correlation test will be performed to test the hypothesis of no second-order serial correlation (AR2). To provide support for the estimated models, the null hypothesis in the both tests should not be rejected.

Empirical Model

The study uses the following specification to estimate the impact of corruption and other controlling variables on financial development in Africa:

Where  is financial development,  is control of corruption index,  is other controlling variables that may affect financial development in African countries. , ,  and are the slope parameters to be estimated, and is the error term. Equation (1) shows that financial development is determined by control of corruption and other controlling variables, beside all time-invariant country specific factors, including geography, climate, ethno-linguistic characteristics, as well as all unchanging political economy factors. ,  and  are expected to be positive. To eliminate country-specific effects, the estimated Model (Equation 1) will be transformed to first difference as suggested by Arellano and Bond:

 (2)

To take care of the possible endogeneity between  and , the study uses the lagged levels of independent variables as instruments as suggested by (Arellano and Bond, 1991) as follows:

Blundell and Bond argue that the lagged level of explanatory variables are weak instruments when they are highly persistent, as a results, they will produce biased estimates in small sample as in our case. To solve this problem, a system estimator has been introduced by that combines both level and difference Equations (Eq. 1 and 2) which produce less biased estimates than the difference estimator dose Blundell and Bond. Therefore, the study set additional moment conditions for the independent variables in level:

Empirical Results

We conducted four estimations, namely, difference GMM one-step, difference GMM two-step, system GMM one-step, and system GMM two-step, however, we rely on the results obtained from system GMM two-step. The descriptive statistics of the variables, and the correlation matrix. the results of difference GMM one-step, the results of difference GMM two-step, presents the results of system GMM one-step, and the results obtained from system GMM two-step' estimation

Note: LFD is financial development, LCCR is control of corruption, LGDP is economic growth LFDI is foreign direct investment, LSCH is human capital, LINF is inflation, and LCBB is commercial bank branches

Note: LFD is financial development, LCCR is control of corruption, LGDP is economic growth LFDI is foreign direct investment, LSCH is human capital, LINF is inflation, and LCBB is commercial bank branches

that control of corruption, commercial bank branches, and human capital have positive significant impact on financial development in Model one, two, three, and four. FDI have positive insignificant impact on financial development in all estimated Models, while inflation has negative insignificant impact on financial development in all Models. However, economic growth appeared to have negative significant impact on financial development in Africa. Importantly, estimated Models one and two have failed to pass the Sargan test since the p-value of the test is less than 0.05, this reveals the invalidity of the instruments used in the estimation. the results of system GMM two-step' estimation which is the main results of this study since it has been proven that system GMM estimator performs better than difference GMM estimator Blundell and Bond, It's also worth to mention that system GMM estimator produce less-biased estimates than what difference GMM estimator does [20-23]. The results of system GMM for the first Model that examined the impact of control of corruption, commercial bank branches, and inflation on financial development in Africa show that controls of corruption and bank branches have positive significant impact on financial development, however, inflation has negative significant impact on financial development. The second Model that included FDI provides similar results to the first Model; in addition, FDI inflows appeared to have positive significant impact on financial development in the region. Economic growth seems to not be important in developing the financial sector since it has insignificant impact on financial development in Model three and four. However, the results indicate that education has positive significant impact on financial development in Africa. Importantly, all estimated Models have passed the Sargan test and auto-correlation test since all (p-value)s of the tests are greater than 0.05 which reveals that all instruments used in the estimations are valid and the Models are not suffer from the auto-correlation problem. The results show that the higher control of corruption the higher financial development in the region. This reflects the importance of controlling the corruption in developing the financial system that enhances economic growth of African countries, however, more hard work is needed to control corruption by African governments. It's worth to mention that African policy-makers should have introduced policies that aim to control corruption in order to have developed a financial market that facilitates trade and doing business in the region's countries. It's also important to cover large areas by bank branches to make it easier for firms to get credits which will returns more economic growth for all African countries [24-25].

Conclusions

This study examined the impact of corruption on financial development in 50 African countries during the period 2000 – 2014. The study used dynamic system GMM estimator because it take care the endogeneity and country-specific-effect problems that may arise in panel data estimation. The results show that control of corruption, bank branches, human capital are highly determine financial development in Africa. The results provide empirical evidence for African policy-makers to introduce polices that aim to lower and control corruption and to cover large areas by commercial bank branches in addition to invest more in education of human capital.

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