Political Elites’ Corruption, Political Stability and

Economic Growth in Nigeria: Bound Testing Approach

Richard Kyarem¹, Ibrahim Abubakar Sani², Feyisayo Oyolola³, Olasunkanmi Lawal⁴

Abstract: This paper investigated the impact of political elites’ corruption and political stability on economic growth in Nigeria using ARDL bound test approach. The study adopts annual time series data for the period of 1996-2017. The stationarity properties of the variables were tested using Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) tests. Result from the bound test reveals that corruption exact a negative and significant impact on economic growth both in the short and long run, while political stability exact a positive and significant impact on economic growth in the short run and an insignificant impact in the long run. This finding reveals that political stability which includes stability in government, absence of internal, external and ethnic conflict/tension promote economic growth in Nigeria in the short run while corruption contributes to the Nigeria’s economic growth by reducing cumbersome bureaucratic control.

Keywords: Corruption; Political Stability; Economic growth; ARDL

JEL Classification: D73

1. Introduction

There exist several opinions on the effect of corruption and political stability on economic growth process. Prominently, two schools of thought the non-beneficial sand hypothesis and the beneficial grease hypothesis explained the role of corruption and political stability in an economy. The non-beneficial sand hypothesis argues that corruption and political instability tends to harm the economy by raising the level of poverty and directly or indirectly exerting negative influence on output and foreign private investment. On the other hand, the beneficial grease hypothesis asserts that corruption contributes to the growth of the economy through the reduction in bureaucratic inefficiencies which constitute barriers to investment and economic activities (Abu, 2018; Kamaldeen, Umar, & Faliat, 2013).

Overtime, corruption and political instability have continue to remain pervasive in Nigeria. This is apparent from the various corruption cases and political tumult in the country. Some of the notable corruption cases include; the unaccountable $16 billion appropriated for power project under Obasanjo administration, Diezani’s corruption case involving billions of naira which led the Federal High Court to order the forfeiture of her assets worth ₦7.6 billion in 2017 and the case of recovered $9.2 million and E74 thousand cash from former group managing director of the Nigerian National Petroleum Corporation (NNPC). Others include; the charges of armed money scandal amounting to ₦28.3 billion by former security adviser to President Jonathan, Col. Sambo Dasuki and the corruption charges against former secretary to the government of the federation (SGF)⁵. Additionally, desperation of power by politicians, election violence, rigging and many more are manifestations of political instability in the country [Council of Foreign Relations (CFR) Report, 2019].

Similarly, statistics have further revealed the co-existence of high corruption, political instability and unimpressive economic growth in Nigeria. Nigeria’s corruption index and political stability and absence of violence index have remained less than 0.40 on the average out of the maximum of 1.0 between the periods of 1996 and 2017 periods. A lower value indicates high degree of corruption and high political instability and prevalence of violence while a higher value indicates low degree of corruption, high political stability and absence of violence. In the same vein, Nigeria’s rate of growth measured by the gross domestic product (GDP) growth rate shows an unimpressive performance in recent years especially in year 2015, 2016 and 2017 in which the growth rates were negative (these periods coincide with the periods of economic recession in Nigeria). The high degree of corruption, political instability and poor growth rates reveals the existence of an interaction amongst these variables and the effect of corruption and political instability on Nigeria’s economic growth.

Furthermore, past literatures have established that corruption especially among political elites and political instability is a major obstacle militating against the rapid growth and development of the Nigerian economy. The debilitating effect of corruption and political instability manifest in the form of increased level of social vices, insecurity and poverty across the country. However, in spite of the fact that corruption and political instability slows growth, there still exist dearth of literature and an inconclusive debate on the resultant impact of corruption on an economy. Studies such as Nwaobi (2004), Ekundayo, Barnabes, Adedoyin & Olorunkanmi, (2013), Umeh, Kyarem & Martins (2013) and Tarek (2014) maintained that corruption increases expenditure on education and capital expenditure, erodes the social economic value of a nation, creates inefficiency and injustice in an economic system and increases inefficiencies in government expenditure which in turn reduces investment and human capital and eventually reduces output. Conversely, studies such as Abu, Zaini & Izraf (2014) argued that even though inefficient institutions (or bureaucracies) are bad for economic growth, corruption can help reduce the damaging impact of such institutions on the economy.

In consequence, given the controversy on the impact of corruption on economic growth in Nigeria and the nonexistence of any study on the interaction between political elites, corruption, political stability and economic growth in Nigeria, except the study of Abu et al., (2014) who carried out a study on corruption, political instability and economic devel­opment in the ECOWAS⁶ region, this gap in the literature ignites and motivate the conduct of this study.

Against the above background, this study is conducted to investigate the interaction of corruption, political stability and economic growth in Nigeria from 1996-2017. Beside this introduction, this paper is divided into four sections. Section two of this paper discusses the literature review on corruption, political stability and economic growth, while part three presents the methodology. The fourth section discusses result and section five concludes and presents policy recommendations and direction for future work.

2. Literature Review

In this section categorized into two subsections, namely; conceptual clarification and empirical review subsections.

2.1. Conceptual Clarification

The concept of corruption is complex, which follows the contention of Marquette & Peiffer (2014) that, corruption is dynamic and the conceptual interpretation of corruption depends on the ability to identify the contexts in which the diverse perspectives will be analytically useful when exploring the issue of corruption. Generally defined, corruption is “the misuse of public funds for private gains” (Rose-Ackerman, 2008). According to Amundsen (2006), political corruption can defined with reference to both the persons at the peak of political systems and purpose of corrupt behavior which in this case is the desire to hold on to power. The “elites” refers to the wealthy, well-read and politically influential groups who have capacity to dictate public policies through their influence (Okeke & Idike, 2016). Therefore, within this purview, political elites corruption can be describe as political elites at the peak of influential levels in the political system who manifest corrupt behaviors for the purpose of sustaining power or status and amassing wealth. Political elite corruption is when elite politicians and state representatives who are responsible for making and enforcing laws on behalf of the people are themselves corrupt in that they use political power to ensure that they hold on to power.

The nonexistence of political stability is the existence of political instability. Dowding and Kimber (1993) defined political stability to imply a form of stability that refers to specific aspect of the society which form both the political system and all its components. On the other hand, Williams (2014), described political instability to mean giving an insight on stability and the propensity of a government to collapse either as a result of conflict or rampant competition between various political parties. Notably, the study observed a deep interconnection between economic growth and political stability. It was found that a number of uncertainty is associated with an unstable political environment which reduces investment and the pace of economic growth. Economic growth is the increase in the volume of production in a country. In economic theory, an increase in a country’s material production usually expressed in values implies economic growth.

2.2. Empirical Review of Literature

There exist a number of studies on the issue of corruption, political stability and economic growth. In the foreign scene, the study of Subarwa (2011) revealed that economic performance responds positively to less corruption and dominant religion, especially Islam. Likewise, Abu et al., (2014) found a positive unidirectional granger causal­ity resulting from political instability to economic development in the short term and a positive unidirectional granger causality from political instability and economic development to corruption in the long term within ECOWAS countries. Frunzik (2002) studied the effects of corruption on economic and political development of Armenia. From the study, high scale corruption had very harmful effects on economic and political development in Armenia. Shera, Dosti and Grabova (2014) also analyzed the impact of corruption on economic growth and found a statistically significant negative relationship between corruption and economic growth. The findings of Tarek (2014) suggests that corruption increases inefficiencies in government expenditure and reduces investment and human capital, leading to a negative impact on output. The study however noted that, human capital, openness and political instability are the most important channel variables, through which corruption is likely to reduce growth.

In the Nigerian context, Kamaladden et al., (2013) investigated the impact of corruption on economic development. The findings show that corruption has a significant negative effect on economic growth and development. Also, Egunjobi (2013) found that corruption per worker directly exert a negative influence on output per worker and indirectly exert a negative influence on foreign private investment, expenditure on education and capital expenditure per worker. Abu (2018) tested the ‘Grease’ Versus ‘Sand’ Hypothesis by investigating how corruption affects economic growth. The results show that higher corruption positively and significantly affect economic growth both in the short-run and the long-run. The finding supports the ‘Grease’ hypothesis, and suggests that corruption contributes to the growth of the economy by reducing bureaucratic inefficiencies which constitute barriers to investment and economic activities. However, Nwakwo (2014) observed a negative relationship between corruption and economic growth. Ekundayo et al., (2013) maintained that corruption impairs and impacts economic growth while, Shuib, Ekeria and Ogedengbe (2016) found that corruption is inversely related to economic growth. Also, the study of Ayoola & Lateef (2014) revealed that corruption granger causes foreign direct investment inflow, government expenditure, gross capital formation, openness and globalization of the economy.

Following the review previous literatures above, it can be concluded that studies on corruption and economic growth have yielded mixed result. For instance, Nwakwo (2014), Kamaldeen et al., (2013) and Egunjobi (2013) all found that corruption negatively affect economic growth while, Ayoola and Lateef (2014) found no significant relationship between corruption and economic growth. Furthermore, a cursory look at previous studies show that the interaction between corruption, political stability and economic growth in Nigeria were ignored and no specific distinction between political elite corruption and political corruption was found.

Thus, having identified gaps in previous studies, this study will fills these gaps in so many ways. First, the study will use a different data source on corruption and political stability and absence of violence from political risk service (PRS) of the international country risk guide (ICRG). The international country risk guide includes a political risk index, which consists of 12 components measuring various dimensions of the political and business environment of a country. Second, the study will extend the study period to cover 2017 from 1996 as against the scope of previous studies. Thirdly, the study will use a different methodology i.e. Autoregressive Distributive Lag Model (ARDL) and also conduct important post evaluation diagnostic tests including normality and stability test which were missing in previous studies.

3. Methodology

3.1. Theoretical Framework

The origin of the institutional theory seems controversial as Lessig (2013) believes Dennis Thompson first developed the Institutional corruption theory in 1995. There is however, evidence that Klitgaard had a treatise on institutional corruption in 1988 (Klitgaard, 1990). The Dennis Thompson version first appeared in the context of legislative ethics. Institutional corruption in the context of legislative ethics refers to states of affairs in which political benefits such as campaign contributions, endorsements, organizational support, or media exposure are made available to lawmakers under conditions that tend to promote private interests at the expense of the legislature’s public purpose.

Many variants of institutional corruption have emerged in literature. Lawrence Lessig viewed institutional corruption as an economy of influence that weakens the effectiveness of an institution, especially by weakening public trust of that institution. In this light, he presented his own conception of institutional corruption applicable to Congress in the context of a call for campaign finance reform (Lessig, 2013). While Thompson’s theory focuses on systemic influences inside of Congress, Lessig’s account focuses on the systemic effect that Congress’ dependency on campaign donations has on its legislative activities. Whatever is the variant institutional corruption theory, the attention is on corruption in corporate organization and institutions, as opposed to individual corruption.

The variant of institutional corruption that interest us is the one propounded by Klitgaard (1990), and further developed by the United Nations Development Programme (UNDP). This school of thought believes corruption exists because of the failure of state institutions to effectively discharge their responsibilities. When the social, political, judicial and economic institutions fail to enforce checks and balances that ensure general equilibrium, then the outcome is corruption. The theory proposes that Corruption (C) is a function of Monopoly (M), Discretion (D) and Accountability. The model is:

C = M +D –A

Corruption thrives where there is monopolistic power with an agent on what to produce, how much to produce and for whom to produce. When the discretional powers reside sorely in one or few agents on when the recipient should have the product and how much of it, then fertile grounds for corruption exist. If however, the system insists on accountability, then this will be a check on corruption.

Further developing the Klitgaardian model, the UNDP (2004) added Integrity (I) and Transparency (T) i.e. Corruption (C) = Monopoly (M) + Discretion (D) – Accountability + Integrity + Transparency; thus making the model:

C = (M + D) – (A+I+T)

When accountability, integrity and transparency are sacrificed in the discharge of public offices, corruption spreads fast and can easily become endemic.

This theory seems apt for Nigeria, both in explaining the scope of corruption prevailing in institutions like the Nigeria Police Force, and in postulating possible solutions. Virtues like accountability and corruption were ignored and institutions like the military governments held absolute monopolistic powers on what project to do, when to it, and how much it was to cost Nigeria. Later, other institutions like political parties demonstrated discretional powers on who occupied which elective position, disregarding the outcomes of many elections.

3.2. Sources and Description of Data

This study adopts annual time series data for the period of 1996-2017. The data on corruption (COR) and political stability and absence of violence (PSV) were sourced from Political Risk Service (PRS) International Country Risk Guide (ICRG) and data Gross Domestic Growth rate (GDP) a proxy for economic growth was sourced from World Bank Data Indicator (WDI).

3.3. Model Specification

Against the issues raised above in the theoretical framework, a simple model in which economic growth (GDP) is dependent on the level of corruption (COR) and political stability (PSV) is specified bellow:

(1)

3.4. Descriptive Statistics of the Variables

Descriptive statistics was employed to describe the data by exploring the mean of the series, standard deviation, minimum, maximum, kurtosis and skewness. The analysis was done using E-views 9.0 after this.

3.5. Unit Root Test

In order to determine whether the variables are stationary or non-stationary, we used Augmented Dickey Fuller (ADF) and Phillips and Perron (PP) tests for stationary. Unit root equation is specified in the following forms.

Y_t= ₁ + _2l + Y_t-1 +a_{i t-1}+ U_t (2)

Where Δ denotes the first difference, is the time series being tested, t is the time trend variable, and n is the number of lags which are added to the model to ensure that the residuals, are white noise.

A generalized Philips Perron unit root test is also presented in equation 3 below.

(3)

The null hypothesis to be tested is Ho: p = 1 indicating the presence of a unit root.

3.6. ARDL Bounds Testing for Cointegration

The Co-integration test is based on Autoregressive Distributed Lag (ARDL) by Pesaran and Shin (1996); Pesaran and Pesaran (1997); Pesaran and Smith (1998) and Pesaran et al., (2001). This technique has a number of advantages over and above the Johansen cointegration technique. First, the ARDL model is the more statistically significant approach to determining the co-integration relationship in small samples (Ghalak and Siddiki, 2001).While the Johansen cointegration technique requires large data samples for validity. Second, the Johansen approach of Co-integration requires all regressors to be integrated of the same order, while the ARDL approach can be applied whether the regressors are 1(1) and 1(0). This means that the ARDL approach avoids the pre-testing problems associated with standard co-integration, which requires that the variables be already classified into 1(1) or 1(0) (Pesaran et al, 2001).

The condition for determining the presence of co-integration relationship or otherwise requires that if F-stat of the bound test is less than the lower bounds, null hypothesis which state that there is no co-integrating relationship is accepted and if the F-stat is greater than the upper bounds, then the null hypothesis is rejected. However, if the computed F-stat fall between the lower and the upper bounds values, the results is inconclusive.

The ARDL model to be estimated is specified as follows:

(4)

The error correction model is expressed as follows:

(5)

4. Analysis and Discussion of Result

4.1. Descriptive Analysis of the Variables

From the descriptive statistics in table 1 below, it is affirmed that all the variables under investigation are normally and identically distributed based on the Jarque-Bera probability.

Table 1. Descriptive Statistics of the Variables

GDP COR PSV

Source: Researcher’s computation using E-views v.9.0

4.2. Unit Root Tests

Consequently, the result of the ADF and PP unit root tests in table 2 show that all the variables have unit roots after differencing except political stability (PSV) which is stationary at level; hence the null hypothesis could not be rejected, thereby concluding that the variables (GDP and COR) are not stationary at levels. However, the ADF and PP tests revealed that the unit roots in the variables disappear after taking first difference of the variables, therefore, the variables become stationary, which implies that they are integrated of order one 1(I).

Table 2. Results of ADF and PP Unit Root Tests

ADF PP

Variables Level 1^st difference Level 1^st difference stationary status

GDP -2.297 -6.084*** -2.237 -6.084** I(I)

COR -2.658 -4.285*** -2.695 -4.285*** I(I)

PSV -3.922*** -4.487*** -2.885** -5.060*** I(0)

Source: Researchers’ Computations using E-views 9.0

Note: Schwarz Information criterion (SIC) is used to select optimal lag length in the ADF test *** and ** indicates statistical significant at 1%, 5% and 10%

4.3. ARDL Bound Test

The bounds testing results reported in Table 3 revealed that the computed F-statistic (3.352) is lower than the upper bound I(1) at 1% level, however, at 5% the computed F-statistic fall between the lower and the upper bounds values. This implies that there is no cointegrating or long run relationship between the variables at 1% level of significance. But at 5% the result is inconclusive. It is necessary therefore to seek further evidence of co-integration from ECM Wald (F-test). This result is in conflict with the finding of Abu (2018) who found a long run relationship at 1% level of significant. Meanwhile, the result is supported by the finding of Kyarem and Usman (2017) and Kyarem and Samuel (2017). The absence of long run relationship likely means that corruption and political stability passes through variables to impact economic growth, hence the long run relationship is not immediately noticeable.

Table 3. Results of Bounds Test

Source: Researchers’ Computations using E-views 9.0. (***), (**) and (*) indicates statistical significant at 1%, 5% and 10%

4.4. Short Run Dynamic ECM Wald (F-test) and Long Run Dynamic

In estimating the ARDL model, the Akaike Information Criterion (AIC) demonstrates that the optimal lag-length for the variables is (4,0,4). The results of the long-run and short-run for the selected models are reported in Table 4 below. The results illustrate that reducing corruption has a significant impact on economic growth in Nigeria in the long run at 5%, moreover in the short-run reducing corruption also has a significant impact on economic growth in Nigeria at 5%, and vice versa. A 1 unit increase in the control of corruption index (decrease in corruption) reduces economic growth by 47.705% in the long-run and a 1 unit increase in the control of corruption index (decrease in corruption) reduces economic growth in Nigeria by 41.57% (significant) in the short-run. This means that in the short run, control of corruption grease the wheels of corruption in Nigeria. This finding is inconsistent with the grease the wheel hypothesis. This suggest that tackling or lowering corruption is associated with lower economic growth in Nigeria in the short and long run. This finding tallies with the findings of Abu (2018).

Meanwhile, the results further revealed that higher political stability and absence of violence (reducing political instability) has a positive and significant effect on economic growth in the short-run at 5%. But in the long run higher political stability and absence of violence (reducing political instability) does not affect economic growth in Nigeria. Therefore, a unit increase in the political stability and absence of violence index (improvement in the political environment) raises economic growth by 17.69%. The positive sign of the coefficient of political stability is consistent with the view that, in a politically stable environment, the uncertainty and risk associated with savings and investment is less which encourages economic growth.

The coefficient of the error correction term lagged by one period (ECT_t-1) is negative and significant at 1%, and therefore satisfies a priori expectation. This result demonstrates that 13.8% of any deviations from the equilibrium will be corrected within one year.

The result of the coefficient of determination (R²) show that the model is well fit and the probability of the F-statistic show that the overall model well fitted and explained by the variables used in the model. Moreover, by approximation the D.W statistic is 2, this means the model does not suffer from autocorrelation.

Table 4. Results of ARDL model

Source: Researchers’ Computations using E-views 9.0

4.5. Results of Residual Diagnostic Tests

Diagnostics test is a post estimation test conducted to validate the established result. Thus, residual diagnostic tests reported in Table 5 below show that the ARDL model passes all tests including serial correlation, functional form, normality and Heteroscedasticity.

Table 5. ARDL-ECM Model Diagnostic Tests

Source: Researchers’ Computations using E-views 9.0

The stability property of the estimated parameters was checked using cumulative sum of recursive residuals (CUSUM) and cumulative sum of squares of recursive residuals (CUSUMQ). The CUSUM and CUSUMQ results show the constancy of estimated parameters in the study period because the plots of both CUSUM and CUSUMQ are within the boundaries (see Figures below).

5. Recommendations and Direction for Future Work

It was generally acknowledged that Nigeria has been suffering from high corruption and the political aura is unstable overtime. The study found that corruption exact significant impact on economic growth both in the long and short run. Corruption was found to be negatively related with economic growth in Nigeria, such that increase in control of corruption (reducing corruption) reduces economic growth by 47.7% and 41.5% at 5% level of significance in the long and short run respectively. Moreover, in the short run, political stability and absence of violence was found to exact positive significant impact on economic growth in Nigeria, while in the long run the impact is not significant. This suggests that increase in political stability and absence of violence index (improvement in the political environment) raises economic growth by 17.69%. The positive sign of the coefficient of political stability is consistent with the view that, in a politically stable environment, the uncertainty and risk associated with savings and investment is less, and thus encourages economic growth. Thus, based on the finding of the study, the study recommends the following measures:

1. Government should strengthen the anti-corruption agencies and ensure immediate punishment of any individual found with corruption cases;

2. The political elites’ should be caution for desperation of power and common/public interest of the society should supersede individual interest.

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