The Effects of Foreign Aid and Foreign Direct Investment on Human Capital Development in Nigeria: Evidence from 1990 to 2018

Oluwaseun Ibukun¹, Joshua Alahira², Bankole Kumolu-Johnson³, Babatunde Oloyede²

¹Department of Geography and Planning, University of Toledo, Toledo Ohio, USA.
²School of Computer Science and Information Study, University of the Cumberlands, Williamsburg, KY, USA.
³School of Counseling, Higher Education, Leadership and Foundations, Bowling Green State University, Bowling Green, OH, USA.

DOI: 10.4236/jhrss.2024.122014                

Abstract

Economic growth and human development have been one of the top goals of every forward-looking country; hence there is a constant need to analyze the important factors driving its growth or decline. This study explores the impact of foreign aid and foreign direct investment (FDI) on the human capital development mirrored by human development index (HDI) in Nigeria from 1990-2018 using World Bank indicators. Johansen cointegration test results show a long-term relationship between foreign aid, FDI and human development index. Regression results show a positive relationship between foreign aid and HDI but a negative relationship between FDI and HDI.

Keywords

Human Development Index, Foreign aid, Foreign Direct Investment, Johansen Cointegration Test, World Bank, Nigeria

1. Introduction

The contribution of foreign aid to the economy has been debated extensively over the years. This debate covers both the developed and developing economies but with much emphasis on the impact of foreign private investment and foreign aid on the economies of developing countries of which Nigeria is one. Series of studies have been done in the areas of the relationship between education and human development capital in Nigeria and several articles have found a positive relationship between both variables (Sulimana, Elian, & Ali, 2018; Sulimana & Ali, 2012; Aigheyisi, 2017) . However much has not been done in holistically looking at the impact foreign aid has on human development capital, mirrored by human development index (HDI). In the developed world, it is agreed that foreign private investment generally plays a positive role in the economy, although it varies from country to country and depends on the country’s characteristics, policy environment and sectors. Blomström & Kokko (1997) reviewed the empirical evidence on host country effects of foreign direct investment. One of the main arguments in support of FDI is its positive influence on economic growth. That being said, while a large fraction of researchers find evidence for FDI-led growth hypotheses—meaning that FDI contributes immensely to the growth rate of the host country (Osinubi & Amaghionyeodiwe, 2010; Ayanwale, 2007; Ayanwale & Bamire, 2004; Omorogbe & Ubeagbu, 2007) —there are also some controversial discoveries claiming that FDI is detrimental to economic growth (Olaniyi, 1995; Al-sadig, 2013; Asiedu, 2002; Adelegan, 2000) . These contradictory results indicate that the relationship between FDI and economic growth is prone to be affected by mitigating factors, such as low level of secondary school education (Aigheyisi, 2017) , encouragement of pro-consumption and pro-import (Adelegan, 2000) , as well as corruption and political instability (Asiedu, 2002) . When these factors are considered, the effect of FDI on economic growth becomes a controversial issue (Omri, Nguyen, & Rault, 2014) . Recently, Sulimana, Elian, & Ali (2018) examined FDI and economic growth in terms of a “bi-directional relationship between FDI and economic growth” for ESCWA countries from 1980-2011 and found that FDI positively and significantly impact growth, and growth rate positively affects FDI inflow as well as development levels of human capital; however, FDI impact on growth is conditional to levels of human capital. The objective of this study is to take a closer look at FDI and foreign aids with pre-Covid data from 1990 to 2018 and see if there is a clear-cut impact on human capital development in Nigeria as well as to see how efficient these variables are in forecasting the direction of HDI.

2. Literature Review

FDI is the capital invested in another country to achieve long-run economic profit from that investment. In today’s’ globalized world, FDI reflects both positive and negative consequences. Moosa (2002) observed that even at times when world commerce slowed down because of restrictions and barriers for free trade, FDI was still increasing because companies usually found ways to avoid restrictions. Contradicting arguments are taking place regarding consequences of FDI, especially for the host country. From one side, FDI is considered as a factor that contributes to developing country’s economy success during recessions. Sulimana & Ali (2012) found a relationship between FDI and GDP growth while Osinubi & Amaghionyeodiwe (2010) , in their study, examined the issue of Foreign Private Investment and its impact on the Nigerian Economy and found that Foreign Private Investment was non-stationary and Foreign Private Investment, Domestic Investment growth and Net Export growth were positively related to GDP growth rate. Ayanwale (2007) explored the relationship between FDI and GDP growth in Nigeria and to ascertain the long-run sustainability of the FDI-induced growth process and found that FDI induces the nation’s economic growth and concluded that while the overall effect of FDI on the whole economy may not be significant, FDI needs to be encouraged. A key indication of improvement in human capital is the reduction in poverty level. Studies have shown a negative relationship between FDI and poverty reduction in Nigeria (Omorogbe & Ubeagbu, 2007; Osemwengie & Sede, 2013) .

Whilst Foreign aid has been shown to improve poverty and GDP growth, Ayanwale & Bamire (2004) reported a positive and significant effect of FDI on firm’s productivity of both domestic and foreign firms in the Nigerian agro-allied sector. Al-Sadig (2013) investigated the effect of FDI outflows on domestic investment using a panel of 121 developing and transition economies covering 1990 to 2010 using cross sectional regression and concluded that FDI outflow had significant negative effect on domestic investment because 1% increase in the outflow of FDI was associated with 0.97% decrease in domestic investment. This result is also in sync with the findings of Ndikumana & Verick (2007) in their studies in sub-Saharan Africa.

Aigheyisi (2017) investigated the effect of FDI on domestic investment in Nigeria. The effects of interactions between FDI and financial system development and FDI and secondary school enrolment (proxy for human capital) were also investigated with results indicating that the long-run effect of FDI on domestic investment is positive, but not statistically significant while the relationship between FDI and secondary school enrolment is negatively related which is indicative of low quality of secondary education in the country and hence human capital has not been able to absorb the benefits of FDI to translate it into positive effect on domestic investment. Asiedu (2002) examined the factors that affect FDI in developing countries, and aimed at discovering if the factors affect countries in Sub-Saharan Africa (SSA) differently with results indicating positive impact of FDI on SSA countries, however not significant.

Different factors affect the inflow of FDI into countries and Asiedu (2006) in his investigation found that developed local markets, natural endowment, improved infrastructure, low inflation, efficient legal system, and enhanced investment framework promotes FDI whereas, corruption, political instability had opposite effects. It is also inferred from the study that increase in FDI does not invariably mean economic growth rather, policies that promote FDI have direct impact and long-term effect on economic growth. Akinlo (2004) observed that export, labor, and human capital are positively related to Nigeria’s economic growth. He also discovered that foreign capital has a small and statistically insignificant effect on economic growth in Nigeria. Balasubramanyam, Salisu, & Sapsford (1996) used cross-section data and OLS regressions to analyze how FDI affects economic growth in developing economies and finds that FDI has a positive effect on economic growth in host countries using an export promoting strategy but not in countries using an import substitution strategy.

Okodua (2009) examined the sustainability of the FDI-growth relationship in Nigeria. Utilizing the Johansen cointegration framework and a multivariate VAR within a vector error correction model, found evidence of a long-run equilibrium relationship between economic growth and FDI inflows. The study also revealed a unidirectional causality from FDI to economic growth. In his own work, Herzer (2010) obtained a slight difference from this result, looking at a cross-country study, Herzer used a bivariate VAR modeling technique and found evidence of a positive FDI-led growth for Nigeria, Sri Lanka, Tunisia, and Egypt; and based on weak exogeneity tests, a long-run causality between FDI and economic growth running in both directions was found for the same set of countries. Adelegan (2000) investigated the impact of FDI on economic growth in Nigeria and found out that FDI is pro-consumption and pro-import and negatively related to gross domestic investment.

Human Development Index (HDI) is a statistical tool used to measure a country’s overall achievement in terms of social and economic dimensions. The social and economic dimensions of a country are based on people’s health, their level of educational attainment, and their standard of living. Calculation of the index combines four significant indicators: life expectancy for health, expected years of schooling, mean of years of schooling for Education, and Gross National Income per capita for the standard of living. Nigeria as a nation is largely blessed with a large deposit of diverse natural resources and ranked as the largest crude oil producer in the sub-Saharan African region but still crawls in terms of development. Oyefusi (2007) investigated the issues of educational objectives, causes of poverty, and their effect on development in Nigeria; and stated that the identified causes of poverty include political instability, human resources, wastage, illiteracy, poor leadership, mental slavery. Possible solutions that could positively resolve the relationship between poverty education developments were documented as, well-formulated workforce policy, an in-service program for workers, and provision of necessities by government, reassessment of our economic, social, cultural, and political needs. According to Kumolu-Johnson (2024) organizations often use policy as a tool in coordinating workforce behavior in both the private and public sector. Policies are an integral part of a business and help to drive consistency of action across an organization’s culture. Of the factors identified as causes of poverty, the issues of workforce and illiteracy (and poverty itself) are some of the core issues that economic development is addressed. Education is only one factor when development is being measured.

According to the statistics released by UNDP, in 1990, the life expectancy of the citizens in Nigeria was 45.9 years which plays a significant role in the Human development index for that year. Also, the expected year in school was 6.7. In 2005, the life expectancy increased to 48.3 years due to improved health system the country witness which came up due to change of power, leading to reduced death date. The expected year in school astronomical increase to 9 year due to flaws witnessed in the academic sector, during this period, the government defaulted in its responsibilities for providing funds to cater for the smooth running of the schools from primary school to the tertiary institution causing lingering strikes which elongate the supposed program duration of students. In the preceding year specifically 2011, UNDP stated that the life expectancy has increased to 50.9 years due to improved health system, within this periods the government focused more on the health sector than Education which leads to a reduction in the death rate witnessed in the Country, while an increment is witnessed in the expected year in school due to government’s attitude to the sector, with a GNI per capita of $4793 more than that of 2005. As a result, huge fund realized from the oil market and the mean year of schooling was 5.2 years giving an HDI of 0.484.despite the massive sale of crude oil at the foreign market the standard of living and the access of citizens to basic amenities keeps reducing. In 2015, there is a positive change in the life expectancy which was 53.1 years coupled with a reduced expected year in the school of 8.1 due to stable health system access to medical facilities and improved educational sector respectively, during this period the governed turned a new leave by channeling many funds to Education. An increased GNI per capital was recorded moving up to $5540 which was tagged the highest till date; this year witnessed an increased HDI of 0.527 which attest to the fact that people’s standard of living reduced and tended to alleviate poverty slightly. A year after, the HDI was 0.582 with a life expectancy of 53.5 years and increased expected year in the school of 9.5 years coupled with a GNI per capita of 0.528. A slight improvement has surfaced in 2017 and 2018 with HDI of 0.533 and 0.534 respectively but with a reduced Gross national income per capita of $5086 and $5203 respectively lower than the ones obtained in 2015 and 2016 due to effect of corruption witnessed and the status of the Nigerian dollar in the foreign market.

In summary, Nigeria’s HDI value for 2018 is 0.534, which put the country in the low human development category, positioning it at 158 out of 189 countries and territories. Between 2005 and 2018, Nigeria’s HDI value increased from 0.467 to 0.534, increasing by 14.4 percent. Nigeria’s economy depends mainly on oil and non-oil resources obtained from the Country yet, poverty and unemployment still at peak Oyefusi (2007) . The UNDP data shows that the probability of not living past the age of 40 is 39%, adult literacy for ages 15 and above is 30.9%, 52% of the population have no access to clean drinking water and the Human Poverty Index was estimated at 37.3 points. There is evidence that economic growth has led to development in other parts of the world; Nigeria’s evidence is mixed. From 2001 to 2003, Nigeria’s HDI dropped from 0.463 to 0.45 (UNDP, 2009) . For the same period, GDP growth rate moved from 4.6% to 10.2% (CBN, 2004) . It shows that, while the nation recorded growth in the economy, it did not lead to development. While official figures are being published daily to show that the Nigerian economy is growing, the average quality of life for Nigerians is still low as captured by the Human Development Index.

3. Data and Methodology

The data used for this study is an annual time series data that spans from 1990 to 2018 on foreign aids, foreign direct investment, total population growth rate, trade openness and human development index. These data sets were gotten from World Bank indicators.

3.1. The Model Specification

Gökmenoğlu et al. (2018) in their article gave an insight into the relationship between foreign aids and economic development. They argued that foreign aid influences economic development via increased investment in human capital among others and that the relationship that exists between them can be mathematically summarized as below.

${\text{HDI}}_t=f\left({\text{AID}}_t,C_t\right)$ (1)

where ${\text{AID}}_t$ is foreign aid, ${\text{HDI}}_t$ means human development index and $C_t$ denotes control variables. The reason for the introduction of some control variables is because there are other factors (variables) that contributes to that for introducing a set of control variables is explained by the fact that there are other variables that affect ${\text{HDI}}_t$ , which might not be explained by foreign aid alone. For this study, C_t is defined below;

$C_t=f\left({\text{FDI}}_t,{\text{PoP}}_t,{\text{Trade}}_t\right)$ (2)

where ${\text{FDI}}_t$ represents Foreign Direct Investment, ${\text{PoP}}_t$ stands for Total Population, and ${\text{Trade}}_t$ represents international trade. Hence the explicit model is as below.

${\text{HDI}}_t=f\left({\text{AID}}_t,{\text{FDI}}_t,{\text{PoP}}_t,{\text{Trade}}_t\right)$ (3)

The log-log econometric model adopted for this study is stated below.

$\ln {\text{HDI}}_t={\alpha }_0+{\alpha }_1\ln {\text{AID}}_t+{\alpha }_2\ln {\text{FDI}}_t+{\alpha }_3\ln {\text{PoP}}_t+{\alpha }_4\ln {\text{Trade}}_t+{\epsilon }_t$ (4)

All the previous definition of variables remains the same, ${\epsilon }_t$ is the error term and the natural log of the variables are taken as it helps reduce if not eliminate problems related to heteroscedasticity.

3.2. Model Estimation

3.2.1. Unit Root Test

The standard Augmented Dickey-Fuller (ADF) test propounded by Dickey and Fuller in 1981 was used to determine the order of integration (stationarity) of the variables in the model.

3.2.2. Linear Regression Model

For this study, a log-log multiple regression was carried out with human development index (HDI) as the dependent variable; foreign aid, foreign direct investment, population, and international trade are the explanatory variables. This logarithm model helps to measure the elasticity of the variables because it makes it easier for comparison.

3.2.3. Granger Causality Test

The granger causality test is used to determine if the past value of independent variables determines the value or outcome of the dependent variable. An independent variable causes a dependent variable only if its past value gives additional information to forecast the dependent variable. This analysis is important to determine the independence of the variables to know whether past values of one variable can be used to forecast future values of another.

This study models the Granger causality test at lag of two as depicted below.

$Y_t={\alpha }_0+{\alpha }_1{X}_{t-1}+{\alpha }_2{X}_{t-2}+{\beta }_1{Z}_{t-1}+{\beta }_2{Z}_{t-2}+{\psi }_1{Y}_{t-1}+{\psi }_2{Y}_{t-2}+{\upsilon }_t$ (5)

where $Y_t$ indicates Human development index, $X_{t-1}$ indicates lag values of foreign aid, $Z_{t-1}$ represents lag values of Foreign direct investment and $Y_{t-1}$ indicates the lag values of Human development index. For i = 1, 2. Variable X does not cause variable Y if all parameters are equal to zero.

$H_0:{\alpha }_1={\alpha }_2=0$

3.2.4. Cointegration Test

Pesaran hypothesize that Autoregressive Distributed Lag (ARDL) model is a good way to determine if variables are cointegrated and this model has the advantages in that it assumes all variables are endogenous and it is also possible for the different variables to have different number of lags and as it relates to this study, this model can be applied to small sample. To have a feel of the relationship between these variables in the long run, a bound test based on the joint F-statistics is done to observe the joint significance of the lagged level variables. To achieve this, the null hypothesis of no cointegration is stated as:

$H_0={\alpha }_1={\alpha }_2={\alpha }_3={\alpha }_4={\alpha }_5={\alpha }_6={\alpha }_7={\alpha }_8=0$ (6)

Against the alternative hypothesis,

$H_1\ne {\alpha }_1\ne {\alpha }_2\ne {\alpha }_3\ne {\alpha }_4\ne {\alpha }_5\ne {\alpha }_6\ne {\alpha }_7\ne {\alpha }_8\ne 0$ (7)

If the computed F-statistics exceeds the upper critical bound, I(1) the alternative hypothesis is accepted which means the variables are cointegrated in the long run. There is no cointegration when the estimated F-statistics is less than the lower critical value, I(0). When the estimated F-statistics lies between the upper and the lower critical bound, the result is inconclusive.

4. Results and Discussion

The study explores the relationship between foreign aids and foreign direct investment on human capital development by first checking the stationarity of the variables as shown below. From the result as shown in Table 1, it can be inferred that only LnPOP is stationary at all levels while the remaining variables are stationary at first difference. It can also be concluded that only LnPOP had no unit root simply because it is level stationary. Contrary to this, the other variables in the model have unit root since they are only stationary at first difference. As a result of this, the variables are integrated in order one since all the variables were

Table 1. Result of unit root test.

stationary at first difference. Since this result showed that all the variables are stationary at first differencing, they can be used in regression analysis because of their temporary shock effect.

The result of the regression shown in Table 2 indicated a positive relationship between foreign aid and human development in Nigeria, which is expected apriori and this is also statistically significant because Nigeria has several countries that they obtain foreign aids from. This result is in sync with the findings of Mohamed & Mzee (2017) in their study “foreign aid and human development: a quantile regression approach”, where foreign aid had a positive impact on human capital development at 10, 25, 50, 75 and 90 percentiles and it was statistically significant at all percentiles except at 90 percentiles. However, looking at this result, it is evident that the contribution of this foreign aid is not greatly felt as the government always project it. This could be largely attributed to political instability, poor disbursing, and management of funds. Contrary to the popular idea that as population growth increases, there should be an increase in human capital development, a study carried out by Oketch (2006) suggested that this is not necessarily true, especially in Africa. Education, access to social amenities and standard of living are the main drivers of HDI and Nigeria is majorly an agrarian country with a large proportion of her labor force still highly uneducated and without access to basic amenities, a surge in the population would have a negative impact on HDI.

Since the unit root test in Table 1 shows that most of the variables are stationary at first differencing, meaning they are mostly integrated at first order, there is a need to perform a cointegration test to establish a long run relationship. The result of Johansen cointegration test in Table 3 indicate that, there are indeed at most four cointegrating equations in the model, as we should expect if the variables included in the model would be useful for long run forecasting. We can therefore conclude that the independent variables included in the model have a massive role to play in forecasting the values of human development index in the long run.

Finally, granger causality test was done to affirm the causal relationship between foreign aid and human capital development. From the result obtained as

Table 2. Regression result of the predictors of HDI.

Table 3. Result of Johansen Cointegration test.

Trace test indicates 2 cointegrating eqn(s) at the 0.05 level; *denotes rejection of the hypothesis at the 0.05 level; **MacKinnon-Haug-Michelis (1999) p-values.

displayed in Table 4, there is no causal relationship between foreign aid and HDI and the decision is to fail to reject the null hypothesis put forward that there is no causal relationship between them. The implication of this is that the relationship between foreign aid and HDI is merely correlation, not causality.

The probability value of no causality running from lnAID to lnHDI is 0.09067, hence we fail to reject the null hypothesis of no causality running from lnAID to lnHDI. Also, the probability value of no causality running from lnHDI to lnAID

Table 4. Pairwise Granger Causality Test result.

is 3.32207 which is quite greater than 0.05 and hence we also fail to reject the null hypothesis at 5% significance level. From this analysis, we can safely draw the conclusion that there is no direction of causality between foreign aid and human capital development, mirrored by HDI in Nigeria.

5. Conclusion

The main goal of this study was to examine the effect of foreign aid and foreign direct investment on human capital development mirrored by human development index HDI in Nigeria. Annual pre-Covid time series data from 1990 to 2018 on specific variables were used to model this relationship. The results showed that foreign aid has a positive impact on HDI in the short run as well as in the long run, but the impact could have been overstated and inflated by the Nigerian government. On the other hand, it shows that foreign direct investment has negatively impacted the economy, and this is in line with the findings of some authors. One policy implication that can be drawn from this study is the need for Nigerian government to invest greatly in education; a key component of HDI to raise its human capital development. Again, prompt, and transparent audit should be done from time to time to ensure these foreign aids are utilized judiciously. A future recommendation to advance the understanding of this topic is the inclusion of post Covid-19 data.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

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