EFFECT OF CAPITAL FLIGHT ON ECONOMIC GROWTH IN NIGERIA

Agbo, Innocent Sunny¹ & Gina Oghogho Olufemi ²

Department of Accounting

Igbinedion University, Okada

Mail: blessedsamsun@gmail.com; atugina18@gmail.com

Abstract

The study examined the effect of capital flight on economic growth in Nigeria and the study proxies capital flight using net foreign investment and gross domestic product. These methodologies are superior to the OLS for many reasons. The study employed a descriptive and time series research design, which is a very important in determining the relationship between time-series variables. The population of the study consist of all data on capital flight and economic growth from Central Bank of Nigeria Statistical Bulletin. For the purpose of the research, a sample size from 1981 to 2019 is selected from the CBN Statistical Bulletin in order to determine the relationship between the variables. The Descriptive Statistics, Correlation Matrix and Fully Modified Least Squares regression technique were adopted to analyse the relationship between the variables. The results reveal that the effect of NFI on RGDP is negative and across all the estimations and significant in DOLs at 5% and FMOLS at 10%. Based on the findings of the study, the recommendation is to keep an eye on net foreign investments, make sure that more investments are brought into Nigeria, and make sure that these channels for foreign investment are not used to transfer capital to other countries.

Keywords: Capital flight, Net foreign investment and economic growth

INTRODUCTION

Through Direct Portfolio Investment (DPI) or Foreign Direct Investment (FDI), successive Nigerian governments have continued to advocate for capital influxes as a means of boosting economic growth. This is based on the requirement of obtaining sufficient funding to supplement the limited current financial position with financial growth. According to Murphy (2004), capital flight is the movement of money and investments outside of a country to a location where individuals believe the assets will be safe for their use, with the intention of concealing the capital from authorities. It is viewed as the massive transfer of currency from one nation to another, which represents the outflow of financial resources.

According to England, Oputa, Ogunleye, & Omotosho (2007), capital flight includes all illegal flows that are designed to disappear from records in the country of origin as well as earnings on the stock of illegal capital movement outside of a country that typically do not return to the country of origin as in the case of Nigeria. When economic fundamentals are deemed unsuitable for investment within the domestic economy, economic agents divert their capital away from domestic economies in order to avoid extremely high losses on their domestic assets. According to research, investors will move their capital away from nations with high sovereign risk and uncertainty in order to avoid investing in economic climates that are uncertain.

According to Onwioduokit (2007), capital flight, whether normal or abnormal, has a negative impact on the economy of the source or domestic nation. Domestic investment is significantly and negatively impacted by capital flight. According to World Bank (1985), the implication is that the movement of capital abroad leaves little or no resources for financing domestic investment. It is generally acknowledged that the African continent faces a significant challenge due to a lack of funds to finance economic development. Hence uplifting consistent activity and inflow of unfamiliar capital by the method of unfamiliar speculation can’t be over stressed to connect the current asset hole in the underdeveloped nations. If it were possible, the economic burden of capital flight would be lifted, leaving more resources available for poverty alleviation. According to Orji, Ogbuabor, Kama, and Anthony-Orji (2020), capital flight has a negative impact on economic growth. Wujung and Mbella (2016) likewise tracked down a negative huge connection between capital flight and economy development; Lawal, Kazi, Adeoti, Osuma, Akinmulegun, and Ilo (2017), who discovered a negative impact between the variables, also supported this. Makwe and Oboro (2019) discovered a strong connection; Bredino, Fiderikumo, and Adesuji (2018) discovered a negative effect. According to Adedayo and Ayodele (2016), the variables have a significant positive effect. This suggests that the Nigerian economy benefits from an increase in the exchange rate as a result of the increase in capital flight into the economy. This study aims to determine the effects of capital flight—foreign direct investment, interest rates, and foreign reserves—on economic expansion as a result of the preceding. The research critically examines the effect of capital flight on economic growth in Nigerian, using net foreign investments and Gross Domestic Product in Nigeria.

LITERATURE REVIEW

Capital Flight

Capital flight does not generally have a defined definition; However, its activities can be traced all the way back to the 17th century. Because there are many different definitions of capital flight, calculating it will produce different results. Because the term has been used interchangeably between developed and developing nations, the lack of a widely accepted definition of capital flight has resulted in a controversy. As a result, some schools of thought classify capital outflows from developed nations as foreign direct investment, whereas residents of emerging nations classify the same activity as capital flight (Ajayi, 2003). However, it is important to emphasize that the purpose for which an inflow or outflow has been used is what makes the difference. The assertion that foreign investors from advanced nations are swayed by better opportunities elsewhere and that investors from emerging nations are presumed to be evading the perceived high risk associated with investments, which is a characteristic of some emerging nations, is the foundation of the aforementioned dichotomy. It is a common belief that all investors, regardless of whether they are from a developed or developing nation, are rational and will base their decisions on the relative returns and risks associated with investing.

According to Schneider (2013), capital flight is the portion of resident capital outflow that is driven by political and economic uncertainty. Mahon (1996) argues in his own contribution that capital flight is a means of safeguarding savings from the depredations of corrupt politicians. According to Otene (2010), capital flight is the movement of large sums of money between nations in order to escape political or economic turmoil or seek higher returns. Helleiner (2005) defines capital flight as “an outflow of capital that is not part of normal commercial transactions” from a nation with a relatively low capital stockpile. According to Chipalkatti and Rishi (2001), capital flight is defined as any private capital outflows that result in the acquisition of foreign assets by a nation’s citizens. The motivations of capital holders form the basis of this definition. It assumes that an individual does not have complete control over capital, but rather that it is subject to intricate and adaptable social control. The behavior of a risk-averse individual who diversifies their wealth to maximize returns is directly linked to capital flight. As part of portfolio diversification, this informs the decision to hold assets overseas (Lensink, Hermes, & Murinde, 1998).

This decision is influenced by the amount of wealth, risk and uncertainty, differences in return rates between domestic and foreign asset holdings, and other factors. Macroeconomic instability, political instability, capital stock, and real interest rate differentials, which occur when aggregate domestic demand exceeds aggregate domestic supply structurally, influence individual portfolio diversification decisions. Capital flight, as defined by Ramachanran (2006), refers to the exodus of a nation’s wealth, savings, and financial and capital assets. A country’s macroeconomic instability can manifest itself in a variety of ways, including the following: Current account deficits and budget deficits rise, exchange rate overvaluation occurs, and inflation rises. Expectations of tax-like distortions like exchange rate devaluation rise as a result of macroeconomic instability.

Nigeria Economy

The overall economic activity in Nigeria has experienced crises that have had devastating effects on global commodity prices as a result of the global economic recession. These crises have presented the economy of Nigeria with a number of obstacles. This subsequently created structural imbalances occasioned by the collapse of oil prices which adversely affected the Nation’s revenue (Obansa, Okoroafor, Aluko, & Eze, 2010).

Every attempt by Nigerian policymakers to contain these waves of external shocks has been accompanied by the implementation of one economic reform or another. The Structural Adjustment Program (SAP) was launched by the Nigerian government by the middle of 1986.The SAP’s goal was to resolve the crises and get the economy moving in the right direction. There were a number of different kinds of corrective actions taken, including financial sector reform policies. The National Economic Empowerment and Development Strategy (NEEDS), which was launched in 2004, is another policy response that has been used in the last ten years with a similar goal (Obansa, Okoroafor, Aluko, & Eze, 2010). This all-encompassing policy aims to reduce unemployment, particularly among young people, and the economy’s ever-increasing cost of living. Currently, the slogan for the economic development blueprint is “vision 20:20” (Eze; 2013). Policymakers and development partners have focused primarily on macroeconomic policy and economic growth in relation to interest rates, exchange rates, and inflation rates. Despite the significant progress made during the 1980s’ economic reforms, particularly in the financial system, there were still numerous unresolved economic issues; In particular, the interest rate has remained extremely high, which has had devastating effects on borrowing costs and investment costs in Nigeria. This has discouraged foreign investment (Hakkio, 2000; Jelilov, 2016).

Foreign Direct Investment and Economy Growth

According to Farrell (2008), a company’s use of technology, capital, management, and entrepreneurial skills to operate and provide goods and services in a foreign market is referred to as “foreign direct investment.” Nigeria is the third economy in Africa to welcome FDI, following Ethiopia and Egypt. The United States, the United Kingdom, China, the Netherlands, and France are among the nations that invest in Nigeria (UNCTAD (2018). Nigeria’s FDI flows in 2017 decreased by 21% to reach 3.5 billion USD. This could be due to political instability, widespread corruption, a lack of transparency, or poor infrastructure. Foreign direct investments have a negative impact on growth in the primary sector, a positive impact in manufacturing, and an ambiguous impact in the service sector. Using the Error Correction Model, Akinlo (2004) investigated how foreign direct investment affected Nigeria’s economic growth between 1970 and 2001. According to the findings, financial development had a significant negative effect on growth, possibly as a result of the high level of capital flight it generates. Private capital and foreign capital had little effect on economic growth and were not statistically significant.

Using multiple regression models, Onu (2012) investigated the effect of FDI on Nigeria’s economic growth between 1986 and 2007. Even though its contribution to GDP was very low during the time period under review, the analysis revealed that FDI has the potential to benefit the economy. Abbes, Guelli, Seghir, and Zakarya (2014) examined the FDI-economic growth causal interactions: a panel co-integration and Granger causality test case study of 65 nations. The panel co-integration revealed a disparity result during the study period, while the results demonstrate a unidirectional causality between foreign direct investment and gross domestic product. Using the ordinary least squares regression method, Adeleke, Olowe, and Fasesin (2014) investigated the impact of foreign direct investment on Nigeria’s economic growth from 1999 to 2013.The findings showed that Nigeria’s economic growth is positively impacted by inflows of foreign direct investment, which is statistically significant. John (2016) also used a multiple regression approach to examine the impact of foreign direct investment on Nigeria’s economic growth from 1981 to 2015. According to the study, foreign direct investment has a positive and significant impact on economic growth as measured by gross domestic product in Nigeria. Additionally, it was discovered that the exchange rate has a positive but not significant impact on GDP.

Empirical Review

Orji, Ogbuabor, Kama, and Anthony-Orji (2020) looked into how capital flight affected Nigeria’s economic growth. Data from the CBN statistical bulletin covering the years 1981 to 2017 were used in the analysis. The study used the Autoregressive Distributed Lag (ARDL) bounds test method. According to the study, both short-term and long-term economic growth are significantly hampered by capital flight. Money supply, credit to the private sector, and domestic investment are additional variables that have been found to have a significant impact on economic growth. The goal of the study by Anetor (2019) was to look at the macroeconomic factors that caused capital flight from Sub-Saharan African (SSA) countries between 1981 and 2015.The autoregressive distributed lag (ARDL) model was used in conjunction with secondary data from the World Bank Development Indicators (WDI) to identify the macroeconomic factors that influence capital flight from the SSA region. Economic expansion was found to have a significant negative relationship with capital flight in both the long run and the short run, according to the study’s findings. Between 1990 and 2017, Makwe and Oboro (2019) looked at how capital flight affected Nigeria’s economic growth. Cointegration analysis was used to analyze the data for both the short run and the long run, and ADF tests were used to test for the time series’ stationarity. Time series data covering these study periods were used. The ordinary least square (OLS) econometrics approach was utilized by the researchers for the purpose of data analysis. The results of the T-test showed that the proxies of capital flight and the gross domestic product, which is a proxy for economic growth, had a strong relationship. The work by Adedayo and Ayodele (2016) provides an empirical analysis of the impact that capital flight has on the economy of Nigeria. Secondary data from the National Bureau of Statistics and the Central Bank of Nigeria’s Statistical Bulletin of various issues were used in the study. The sample period from 1980 to 2014 is the subject of the empirical measurement. A Standard Least Square (OLS), Increased Dickey-Fuller unit root test and Co-mix test were embraced to do a broad examination of the embraced factors which incorporate GDP, Capital Flight and Swapping scale. The findings demonstrated that the variables have a significant positive influence. This suggests that, during the time period under consideration, the Nigerian economy will benefit from an increase in the exchange rate as a result of an increase in capital flight into the economy. Bredino, Fiderikumo, and Adesuji (2018) investigated how capital flight affected Nigeria’s economic expansion. Predicting the impact of capital flight on economic expansion has not been very successful using traditional methods. The model assessed to cover the period 1980 – 2012 was dissected utilizing joined worldwide strategy, Fake Brain Organization (ANN) as a prescient procedure and old style methods like Standard Least Square (OLS) and co-incorporation/mistake rectification techniques. According to the findings of the study, capital flight has a negative effect on GDP, while exchange rate has a positive effect on GDP, which is in line with expectations. The study by Obidike, Uma, Odionye, and Ogwuru (2015) looked at how capital flight affected Nigeria’s economic growth. It was decided to use the Autoregressive Distributed Lagged model (ARDL). Capital flight has a negative and significant impact on economic growth, as the Auto Regressive Distributed Lagged (ARDL) model revealed. The model’s parameters were found to be stable over time in the CUSUM and CUSUMSQ tests. Between 1980 and 2012, Nwakoby, Ajike, and Ezejiofor (2017) looked at how Nigerian government financial incentives affected small and medium-sized businesses (SMEs) and economic expansion between 1999 and 2015.The significant impact of SMEs’ output on the country’s economic growth was determined using straightforward regression analysis. Gross Domestic Product and loans to small and medium-sized businesses were the two variables used. According to the study, the output of SMEs in Nigeria and the expansion of the economy are significantly influenced by government spending, loans, and other credit options. Olawale and Ifedayo (2015) investigate the effects of capital flight on Nigeria’s economic expansion. Co-integration, Ordinary Least Square (OLS), and Error Correction Mechanism (ECM) were the primary estimation methods utilized in the study. During the study year, findings showed that capital flight, foreign reserve, external debt, foreign direct investment, and current account balance all cointegrate with GDP in Nigeria. Additionally, it was discovered that the economy was adversely affected by capital flight.

METHODOLOGY

The study employed a descriptive and time series research design, which is a very important in determining the relationship between time-series variables.

The population of the study consist of all data on capital flight and economic growth from inception to the 2019 period in the Central Bank of Nigeria Statistical Bulletin. For the purpose of the research, a sample size from 1981 to 2019 is selected from the CBN Statistical Bulletin in order to determine the relationship between the variables. Data are quarterly data from 1981 to 2019 from Central Bank of Nigeria Statistical Bulletin (various issues).

The data were selected from the CBN Statistical Bulletin 2019 and the National Bureau of Statistics 2019.

Method of Data Analysis

The Descriptive Statistics, Correlation Matrix and Fully Modified Least Squares regression technique were adopted to analyse the relationship between the variables. Preliminary tests to know the normality and stationarity of the data are conducted through Jarque- Bera, Skewness, Kurtosis tests, and the unit root test. The test for the Jarque-Bera, Skewness and Kurtosis tests is to find out whether that the data are normal. This is because it includes macroeconomic variables that determine the economic growth in Nigeria.

Model Specification

In order to achieve the broad objective of this study, the model of John (2016) was adapted.

In his study of the effect of foreign direct investment on economic growth in Nigeria, the model was specified as:

NEG = CF …………………………………………………….….. i

Where

NEG = Nigeria Economy Growth

CF = Capital Flight

NEG is measured by RGDP and CF is measured by NFI,

Further, equation i is expanded below to capture the objectives of the study;

GDP = f (NFI, EDS, ER, CAB) …………………………….. ii

The econometric form of the functional model is specified as:

GDP = μ₀ + μ₁NFI + εt

Where

GDP = Gross Domestic Product

NFI = Net foreign investments

μ₁   = Shift Parameters ε = error term

t = time series

ANALYSIS OF RESULT

Table 1. Descriptive Statistics

	GDP	NFI
Mean	34690.67	-8918.853
Maximum	71387.83	19793.32
Minimum	13779.26	-99332.80
Std. Dev.	20237.78	23028.95
Skewness	0.673787	-2.231932
Kurtosis	1.880848	8.520117
Jarque-Bera	4.986242	81.89638
Probability	0.082652	0.000000
Observations	39	39

Source: Researcher’s compilation (2021). (GDP = Gross Domestic Product; NFI = Net foreign investments; EDS = External debt servicing; ER = External reserves; CAB = Current account balance)

The mean for GDP stood a 34690.67bn with a standard deviation of 20237.78 and maximum and minimum values of 71387.83bn and 13779.26bn. The standard deviation is large which suggest huge year on year fluctuations in GDP and the variable appears to be positively skewed (0.673). The p-value for the Jacque-bera statistics stood at 0.083 which indicates that the series is normally distributed and the presence outliers is unlikely. The mean for NFI stood at -8918.853bn with a standard deviation of 23028.95. The maximum and minimum values stood at 19793.32 and -99332.8 respectively and negatively skewed (-2.23). The p-value for the Jacque-bera statistics stood at0.065 which indicates that the series is normally distributed and the presence outliers is unlikely.

Table 2: Pearson Correlation

Probability	GDP	NFI
RGDP	1
Prob.	(0.6332)
NFI	-0.10467	1
Prob.	(0.5260)

Source: Researchers compilation (2021).

The Pearson correlation results show the relationship between the dependent and independent variables as can be seen from the results, shows that RGDP is negatively correlated with NFI (r=-0.10467) though not significant at 5% (p=0.5260). The inter-correlations between the explanatory variables are quite low and hence there are no multicollinearity threats which may bias the results.

Test of Hypotheses

H₀₁: There is no significant relationship between net foreign investments and the growth of the Nigerian economy

Table 3: Co-integrating Regression

Variable	Canonical Cointegration regression (CCR)	Dynamic Least Squares (DOLS)	Fully-Modified OLS (FMOLS)
C	5537.481 (3084.7) {0.0821}		5164.172 (3066.93) {0.10955}	5756.477 (3194.69) {0.0810}
NFI	-0.1311 (0.07852) {0.1046}		-0.2413 (0.0940) {0.0194}	-0.12791 (0.0641) {0.0547}
@Trend	1099.194 (288.086) {0.0006}		1102.772 (357.003) {0.0063}	1060.65 (305.398) {0.0015}
R2	-2.815		0.977	0.922
R2 Adjusted	-15.394		0.956	0.910

Source: Researchers compilation (2021).

The Cointegrating equation is estimated using recently developed econometric methodologies, namely: fully modified ordinary least squares (FMOLS) of Phillips and Hansen (1990), dynamic ordinary least squares (DOLS) technique of Stock and Watson (1993) and Conical Cointegration Regression (CCR) of Park (1992). These methodologies provide a check for the robustness of results and have the ability to produce reliable estimates in small sample sizes. CCR, DOLS and FMOLS are superior to the OLS for many reasons so let me give you the key ones: (1) OLS estimates are super- consistent, but the t-statistic gotten without stationary 0r I(0) terms are only approximately normal. Even though, OLS is super-consistent, in the presence of “a large finite sample bias” convergence of OLS can be low in finite samples (2) OLS estimates may suffer from serial correlation, heteroskedasticity since the omitted dynamics are captured by the residual so that inference using the normal tables will not be valid -even asymptotically. Therefore, “t” statistics for the estimates OLS estimates are useless (3) DOLS & FMOLS take care endogeneity by adding the leads & lags (DOLS). In addition, white heteroskedastic standard errors are used. FMOLS does the same using a nonparametric approach.

The effect of NFI on RGDP is negative and across all the estimations and significant in DOLs at 5% and FMOLS at 10%. Hence; CCR (-0.1311, p=0.1046), DOLS (-0.2413, p=0.0194) and FMOLS (-0.1279, p=0.0547). This implies that increases in NFI have a significant negative impact on growth. The effect of EDS on RGDP is positive and across all the estimations and significant at 5%; CCR (0.569, p=0.0019), DOLS (0.745, p=0.0016) and FMOLS (0.59122, p=0.00177). This implies increases in external reserves as a positive and significant impact on growth. The finding is in line with theoretical expectations as reserves constitute an economic savings that can be used when necessary to stimulate the economy. Reserves are also an indication of the ability of the control to estimate its debt cover and hence can determine the riskiness of debt growth to economic stability.

The effect of NFI on RGDP is negative and across all the estimations and significant in DOLs at 5% and FMOLS at 10%. Hence; CCR (-0.1311, p=0.1046), DOLS (-0.2413, p=0.0194) and FMOLS (-0.1279, p=0.0547). This implies that increases in NFI have a significant negative impact on growth. Hence the null hypothesis that there is no significant relationship between net foreign investments and the growth of the Nigerian economy is rejected at 5%.

CONCLUSION AND RECOMMENDATION

The study examined the impact of capital flight on economic growth in Nigeria and the study proxies capital flight using net foreign investment. The Cointegrating equation is estimated using recently developed econometric methodologies, namely: fully modified ordinary least squares (FMOLS) of Phillips and Hansen (1990), dynamic ordinary least squares (DOLS) technique of Stock and Watson (1993) and Conical Cointegration Regression (CCR) of Park (1992). These methodologies are superior to the OLS for many reasons. The results reveal that the effect of NFI on RGDP is negative and across all the estimations and significant in DOLs at 5% and FMOLS at 10%. Hence; CCR (-0.1311, p=0.1046), DOLS (-0.2413, p=0.0194) and FMOLS (-0.1279, p=0.0547).

This implies that increases in NFI have a significant negative impact on growth. Based on the findings of the study, the recommendation is to keep an eye on net foreign investments, make sure that more investments are brought into Nigeria, and make sure that these channels for foreign investment are not used to transfer capital to other countries.

 

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