Impact of foreign aid on Nigerian economy

Abstract

The study critically assessed the impact of foreign aid on the Nigerian economy with a specific interest in official development assistance from 1980 to 2019. It employed the ARDL bounds testing approach to cointegration and finds a long-run relationship among the variables employed. Furthermore, the estimated results suggest that official development assistance as a form of foreign aid and credit extensions does not contribute to the progress of the Nigerian economy, it rather retards it. Also, the study concludes both the short and long run that the labor force contributes to economic progress in Nigeria, whereas gross capital formation just like foreign aid retards growth. The Granger causality test reveals no sign of either unidirectional or bidirectional causal relationship between official development assistance and economic growth in Nigeria. The study recommends that adequate support through credit extensions to SMEs should be fostered to strengthen domestic capital formation. The originality of this work lies in its rigorous analysis of the long-term impact of official development assistance on the Nigerian economy, employing the ARDL bounds testing approach. The findings challenge conventional wisdom and offer valuable insights into the dynamics of foreign aid and economic growth in Nigeria. However, this study has certain limitation. The study temporal scope spans from 1980 to 2019 due to limited data.

Keywords:

• ODA
• foreign aid
• ARDL
• Nigerian economy
• labor force
• granger causality

Reviewing Editor:

• Prakash Matura
• Taylor & Francis
• New Delhi
• India

Subjects:

• Economics
• Economics and Development
• Regional Development
• Politics & Development

1. Introduction

According to Adekunle and Alokpa (2018), economic growth can be characterized as the expansion of the production possibility frontier (PPF) due to an augmentation in the supply of resources and advancements in technology. Inflation-adjusted increases in the market value of a country’s output over time constitute economic growth. According to the International Monetary Fund (2012), real Gross Domestic Product (GDP) growth rates are the standard by which statisticians evaluate economic growth. Additionally, the advantages of economic expansion encompass a rise in production output, as denoted by the real Gross Domestic Product (GDP). A higher GDP signifies that the economy is generating a greater quantity of goods and services, thereby enabling consumers to access a wider range of goods and services. If there exists a correlation between human well-being and consumption, then societal advancement will be facilitated by growth. According to Pettinger (2016), an increase in consumption levels can potentially alleviate instances of absolute poverty, which refers to the inability of individuals to fulfill their basic survival needs.

Furthermore, it is noteworthy that Nigeria’s gross domestic product (GDP) reached a total of 443 billion U.S. dollars in the year 2020, thereby attaining the highest GDP among all African countries (Varrella, 2021). This information is based on a report on the GDP of African countries in 2020, categorized by country. The National Bureau of Statistics has released data indicating that the Gross Domestic Product (GDP) of Nigeria experienced a mean growth rate of 6.48% during the third quarter of 2012, in comparison to the previous quarter as shown in Figure 1. The historical Gross Domestic Product (GDP) rate of Nigeria exhibited an average of 6.8%, with a peak of 8.6% in December 2010 and a low of 4.5% in March 2009.

Figure 1. Nigeria’s GDP at current US $. Source: World Bank (2019).

The Nigerian government came up with numerous programs in order to boost it is national output and to achieve positive sustainable economic growth for a long period such as SAP, NEEDS I AND II, and OFN including ERGP and ESP which were recently initiated like ERGP during the current administration (i.e. 2018 and 2020).

Notwithstanding the implementation of various policies, the Nigerian economy has failed to attain sustainability in its pursuit of desired outcomes. Paradoxically, the government’s efforts to achieve progress through initiated policies and programs have resulted in retrogression = rather than improvement. Many developing nations, including Nigeria, exhibit unfavorable macroeconomic indicators, such as low-income levels, high unemployment rates, low industrial capacity utilization, and elevated poverty levels. These economic challenges are commonly encountered by these countries. The utilization of foreign aid has been proposed as a viable solution for supplementing the limited domestic resources in addressing these issues. The term ‘foreign aid’ is used to describe the provision of money, products, or services from one nation or international organization (such as UNICEF, USAID, WHO, or UNCTAD) to another nation for the benefit of its population. Foreign aid encompasses various forms of assistance, including economic, social, educational, military, and emergency humanitarian aid. As an illustration, the assistance provided in the aftermath of natural calamities has been documented by the World Bank (2019).

Concessional foreign aid is frequently directed toward developing nations, such as Nigeria, either through direct or indirect means via multilateral institutions or private voluntary organizations. The objective of such aid is to provide support for social and economic development. Foreign aid plays a pivotal role in fostering economic development through two distinct mechanisms. Foreign aid has the potential to expedite the achievement of a stable and sustainable growth rate for countries with limited domestic capital, such as Nigeria. Secondly, foreign aid has the potential to enhance a nation’s long-term economic growth rate by facilitating the transfer of technology and technical expertise from more developed countries. According to McKinnon (1964), this fosters positive governance and ethical conduct.

According to the Development Assistance Committee (DAC) of the Organization for Economic Co-operation and Development, Official Development Assistance (ODA) refers to monetary resources that are specifically targeted toward developing countries and multilateral institutions. The aforementioned streams are furnished by authorized entities, such as state and municipal administrations, or their corresponding executive departments. In order to be classified as Official Development Assistance (ODA), a transaction must satisfy two conditions. The first condition requires that the transaction be executed with the primary aim of advancing the economic development and well-being of developing nations. Furthermore, it is imperative that the loan exhibits a concessional nature and possesses a grant element that meets or exceeds 25%, which is determined by applying a discount rate of 10% as per the OECD guidelines (OECD, 2020).

Small and medium enterprises (SMEs) have significantly contributed to the Nigerian economy in the real sector for an extended period. However, they encounter several challenges, including insufficient capital, inadequate infrastructural development, an enabling environment, poor technology and technical know-how, and unfavorable government policies. Iyoha (2004) posits that the utilization of Official Development Assistance (ODA) in the form of foreign aid has a noteworthy impact on augmenting the capacity of businesses in Nigeria, thereby presenting the potential for economic growth and development. The graph presented in Figure 1 depicts the reaction of the Nigerian economy to official development assistance received as foreign aid.

Figure 2 illustrates that periods characterized by higher levels of foreign aid have experienced a noteworthy increase in comparison to those with lower levels of aid. Based on the observed patterns of economic growth in relation to foreign aid, it can be inferred that Official Development Assistance (ODA) has the potential to stimulate economic growth in Nigeria. The current research aims to investigate the reaction of the Nigerian economy to consecutive foreign aid, with a particular focus on Official Development Assistance (ODA), against the aforementioned context.

Figure 2. Net Official Development Assistance (ODA). Source: World Bank (2019).

The motivation for this study derives from the poor facilitation and financing of key sectors of the Nigerian economy leading to poor macroeconomic indicators and poor economic outlook, hence, the study considers ODA as a form of foreign aid toward tackling such problems. Objectively, this study attempts to make a noteworthy addition to the extant body of literature by distinctively investigating the effect of foreign aid, domestic businesses, and the labor force on the Nigerian economy. It also made a huge effort to review the methodologies of estimations in studies on Nigeria regarding the statistical relationship between foreign aid, domestic businesses, and economic growth. The current study discovered a significant literature gap (also known as a research gap) in terms of modeling and estimation techniques in past conducted studies after a critical review. It is on this premise that, this study employed the Auto Regressive Distributed Lag (ARDL) method of data analysis which to the best of our knowledge has not been adopted by existing studies conducted in Nigeria.

The remaining parts of this study are structured as follows: Literature review and methodology are presented in Sections 2 and 3, respectively. Section 4 provides results and discussions, and Section 5 advances the conclusion and recommendations.

2. Literature Review

2.1. Theoretical framework for the study

Theoretically, this study is structured upon the Harrod–Domar growth theory hypothesized in 1939. The fundamental objective of the Harrod–Domar growth theory is to provide a comprehensive understanding of the mechanisms behind economic growth by focusing on the concepts of savings and investment. The Keynesian model provides valuable insights into the interplay between savings, investment, and economic growth. The Harrod–Domar model relies on two crucial factors: the rate of savings and the capital-output ratio. The savings rate denotes the ratio of income that people or corporations set aside for saving instead of spending. The capital-output ratio represents the quantity of capital required to generate one more unit of output. Theoretically, the model is specified thus, (1) $$Y_t=S+I\mathrm{ }$$(1)

Where,

Y = total production, output, income, and economic growth at a given period of time

S = total savings on the part of either individuals or the government

I = investment of all types

While the Harrod–Domar growth theory primarily focuses on the relationship between domestic savings, investment, and growth, the Harrod–Domar model’s consideration of foreign aid revolves around the idea that aid inflows can supplement domestic savings, contributing to increased investment and, thus, economic growth. Additionally, within the framework of the Harrod–Domar model, the introduction of foreign aid can be regarded as an exogenous kind of investment. Foreign aid, when allocated to sectors like infrastructure, education, or healthcare, can bolster a country’s capital base, hence fostering higher productivity and economic expansion. Furthermore, foreign assistance can alleviate the limitations imposed by insufficient local savings. When a country encounters challenges in amassing adequate savings for essential investments, the arrival of help can bridge the gap and stimulate economic progress. This viewpoint is consistent with the Harrod–Domar model’s focus on the crucial significance of investment in stimulating economic growth. The rationale for optioning the Harrod–Domar theory for this study among others are as follows; first, it is an economic growth model. The determinants of growth included in the model (i.e. savings/investments and capital-output ratio) align with the determinants of growth in the current study (i.e. foreign aid, domestic businesses, labor force, and capital formation) (Harrod & Domar 1939). These variables are similar in terms of the effects they may have on the economic prospects of a given nation.

For the purpose of this study, the highlighted model above (i.e. Harrod–Domar) is adopted, slightly modified, and incorporated as an additional potential determinant of economic growth. Thus, the functional form of the model is specified in Equation (4)(4) $$\Delta {{\rm X}}_t=\alpha +{\beta }_t+\beta {{\rm X}}_{t-1}+{\displaystyle \sum _{i=1}^k\gamma }i\Delta {{\rm X}}_{t-i}+{\epsilon }_t$$(4) as follows: (2) $${\mathit{\text{GDP}}}_t=\left({\mathit{\text{NODAP}}}_t,{\mathit{\text{LF}}}_t,\mathit{\text{GCFt}},\right)$$(2)

Where: GDP represents the Nigerian economy, NODA, represents net official development assistance (i.e. assistance in the form of loans and grants to selected economic sectors), LF represents labor force and GCF stands for gross capital formation.

2.2. Empirical Literature review

Throughout history, the initial manifestation of foreign aid can be traced back to the military support provided to belligerent factions deemed to be of strategic significance. The modern-era’s significance of this phenomenon can be traced back to the 18th century, during which Prussia provided financial support to certain allied nations. In a comparable vein, during the 19th and 20th centuries, European nations allocated substantial funds to their colonies, primarily to enhance infrastructure with the ultimate objective of augmenting the economic productivity of the colony.

The contemporary configuration and extent of foreign aid can be attributed to two significant advancements that occurred after the conclusion of World War II. Initially, the implementation of the Marshal Plan was a U.S.-sponsored initiative aimed at rehabilitating the economies of seventeen Western and Southern European states. Furthermore, noteworthy global institutions such as the International Monetary Fund (IMF), United Nations (U.N), and World Bank were established. International organizations have had a notable impact on the distribution of global funds, the establishment of eligibility criteria for aid recipients, and the evaluation of the effects of foreign aid.

Numerous scholarly investigations have been carried out to explore the interconnection among foreign aid, domestic enterprises, and economic advancement. There is a considerable body of theoretical research that supports the idea that foreign aid is effective in encouraging economic growth and development in developing and impoverished countries, suggesting that it promotes enhanced capital accumulation. This study aims to examine the extent to which foreign aid contributes to the growth of domestic businesses in Nigeria, which is considered one of the developing economies. The study undertook a thorough evaluation of empirical research on Nigeria and other developing countries in order to achieve this objective.

Furthermore, Adamu and Patricia (2013) looked at how the Economic Community of West African States (ECOWAS) members’ economies have grown in response to foreign aid. The study used three simultaneous equations models to analyze time series panel data that covered the years 1990 to 2009. The findings of the study point to a strong and positive relationship between foreign aid and economic growth in the ECOWAS nations under investigation. The current interest rate, the amount of foreign direct investment, and the size of overseas reserves are further important elements that help the economy progress. The findings derived from the equation pertaining to foreign aid have revealed a positive correlation between foreign aid and domestic investment, exports, as well as international reserves. The equation elucidating investment reveals a positive correlation between investment and both domestic savings and exchange rates.

Also, Fashina et al. (2018) conducted a study to examine the relationship between foreign aid and human capital in fostering the economic development of Nigeria. The research employed two distinct models. The initial model was utilized to assess the credibility of the medical model in Nigeria. Meanwhile, the extended model was employed to examine the impact of foreign aid and human capital shocks on growth through the application of Engle-Granger and Vector Error Correction Model (VECM) estimation techniques, respectively. The results obtained from the initial model indicate that a continual rise in foreign aid disbursements beyond a specific threshold (the optimal threshold) could potentially have a negative impact on economic growth, thereby corroborating the assertion put forth by the Medicine Model. The study’s expanded model reveals that the economic growth of Nigeria is significantly impacted by human capital shock through education, while the effect of aid shock is negligible over a prolonged period. The impact of aid on economies is subject to various heterogeneous factors, with the recipient governments’ role being a significant consideration that is often overlooked. This study differentiated itself from Adamu and Patricia (2013) in the following ways; it was conducted more recently (i.e. 2018), it employed the Granger test to assess multidirectional causality among its variables and the VECM model measures the speed of adjustment resulting from short term distortions on the dependent variables toward stability in the long run. However, in terms of variable selection, the study appeared to be similar to most of the studies reviewed (see Adamu & Patricia, 2013; Appiah-Konadu et al., 2016; Mitra, 2013).

Furthermore, Mitra (2013) conducted an analysis wherein a structural Vector Error Correction Model (VECM) was estimated for the time frame spanning from 1971 to 2009. The study aimed to investigate the enduring association between economic growth and foreign aid in Cambodia, an Asian economy that is reliant on aid. The study utilized the Johansen cointegration test as a means of analysis, which revealed a statistically significant positive impact of foreign aid on Cambodia’s economic growth for the study. This study is similar to Fashina et al. in terms of methodology (i.e. VECM), but it differs in the unit of analysis (i.e. Cambodia), scope, and sampling (i.e. 1971–2009) and the use of Johansen cointegration technique for determining the long run relationship among the selected variables.

In addition, Appiah-Konadu et al. (2016) undertook a research project utilizing time series data that encompassed the years 1972 to 2012 in Ghana. The research aimed to investigate the proposition that foreign aid has the potential to foster economic growth in developing countries. The research employed the ARDL approach for cointegration, commonly referred to as the bounds test, to examine long-term and short-term associations between aid and economic growth. The results of the bounds test have revealed that there is a cointegrating relationship between economic growth and foreign aid in the Ghanaian setting. The aforementioned assertion was supported by the error correction factor, which displayed a significant level of statistical significance and was signed appropriately. The examination of the error correction component suggests that the pace of approaching the steady-state equilibrium is moderate. The results suggest that in Ghana, factors such as labor, capital, and government expenditure have a positive impact on economic growth in both the short and long run. On the other hand, it has been observed that growth is negatively affected by foreign aid and the payment of interest on external debt.

Furthermore, Fatima (2014) investigated the influence of foreign aid on the economic growth of Pakistan. The study incorporated previous research conducted on the same subject matter in various developing nations. The findings indicate that the effective allocation of aid to areas requiring development can yield positive outcomes. However, aid provided to certain countries is often accompanied by predetermined objectives and designated areas for utilization. If these countries were granted autonomy in the allocation of aid, they could direct it toward their specific needs, resulting in more suitable and favorable development outcomes. Moreover, in nations of this nature, the possibility of corruption arises. However, if corruption is effectively eradicated from the foundation of the economy, it will inevitably yield superior developmental outcomes for the economy.

Also, Mkinde and Isiaka (2020) conducted a study to investigate the impact of foreign aid on the economic growth of Nigeria. The study employed yearly time series data spanning from 1990 to 2017, sourced from the CBN statistical bulletin and the World Bank data indicators. The study employed the Augmented Dickey-Fuller test and Error Correction Model for analysis. The research employed Granger causality and cointegration tests to analyze the data. The findings of the study suggest that all variables used demonstrate stationarity upon the first difference and integration at the same order level, which is specifically I (1). The results of the cointegration test indicate the presence of a prolonged association among the variables under consideration. The results of the analysis suggest that the provision of foreign aid has an adverse effect on the economic growth of Nigeria. This study conducted in Nigeria is more recent (i.e. 2020) as compared to Agunbiade & Salam, 2018; Fashina et al., 2018; Saibu & Obioesio, 2018). More so, the scope covered a more recent period in terms of sample selection.

In another development, Agunbiade and Salam (2018) conducted an empirical investigation to evaluate the impact of foreign aid on the economic development of Nigeria. The study employed diverse statistical methodologies such as the vector error correction mechanism, the Johansen cointegration test, and the unit root test. The research findings indicate a positive correlation between foreign aid and gross domestic product (GDP) in Nigeria. Nevertheless, the establishment of statistical significance of the aforementioned findings was not established.

The study conducted by Siddique et al. (2017) investigated the effects of foreign aid on the economic growth and development of a group of South and East Asian countries over a span of 18 years, from 1995 to 2013. The employed analytical approach involved the utilization of the dynamic panel estimation technique. The empirical findings of the study suggest that foreign aid plays a significant role in these countries’ growth prospects.

The study conducted by Saibu and Obioesio (2018) aimed to examine the impact of foreign aid on sustainable growth and development in Nigeria. The study employed the extended Barro methodology to investigate the correlation between government spending, which was supplemented by foreign aid, and the growth of the economy. The study employs the instrumental variable two-stage least squares (IV-2SLS) approach to conduct empirical analysis. The results of the study suggest that foreign aid plays a significant role in Nigeria’s growth prospects. In addition, Maruta et al. (2020) conducted a study to analyze the effects of foreign aid on the agriculture, education, and health sectors in 74 developing nations across Africa, Asia, and South America. The study included the time period from 1980 to 2016. The study employed a panel Two-Stage Least Squares (2SLS) methodology to examine the geographical disparities in the impact of foreign aid and emphasized the importance of different levels of institutional quality.

Moreover, Ugwuegbe et al. (2016) conducted a study to investigate the impact of external borrowing and foreign financial aid on the economic growth of Nigeria from 1980 to 2013. The CBN statistical bulletin was utilized to obtain the yearly time series data. The Johansen cointegration test and the augmented Dickey-Fuller tests were utilized to estimate the variables under investigation. The findings indicate that external debt exerts a positive and noteworthy impact on economic growth, while foreign aid is positively associated with economic growth, albeit lacking statistical significance. Contemporary foreign aid is characterized not only by its humanitarian nature, which is sometimes devoid of self-interest on the part of the donor country but also by its substantial magnitude, which has amounted to trillions of dollars since the conclusion of World War II. Additionally, it is distinguished by the significant number of governments that provide it and the transparent manner in which the transfers are conducted.

Hence, the study seeks to add to the existing body of literature by evaluating the relationship between foreign aid, indigenous firms, and economic advancement in Nigeria using an alternative analytical approach (ARDL). The essence of ADRL analysis is the inclusion of the first lag of the dependent variable among the regressors. This is essential as it signifies the essence of past behavior of the dependent variable amongst its current determinants. Also, Bahmani-Oskooee and Ghodsi (2018) suggest that the ARDL approach applies to any time series with different order of integration as long as it is not integrated at a second difference. In other words, it can be applied to both level variables and first difference variables or even a combination of both, respectively. Moreover, another advantage of the ARDL method as discussed in Ghatak and Siddiki (2001) is that it is a regression technique that can be used to simultaneously estimate short-term and long-term relationships irrespective of the order of integration of variables employed. Additionally, the ARDL method is applicable in case some of the regressors are endogenous or in series with a smaller sample size as compared to other estimation techniques (Odhiambo, 2009).

The current study endeavors to contribute to the extant body of literature by utilizing an alternative analytical method (ARDL) to evaluate the correlation between foreign aid, domestic enterprises, and economic advancement in Nigeria and extend its scope in terms of years of coverage to the period of 2019.

3. Methodology and hypotheses

This section contains model specification, method of analysis, nature of variables, and sources of the data. This study intends to reexamine the effects of foreign aid on the Nigerian economy with the possibility of employing other relevant determinants of growth in comparison to previous studies. NODA was employed as the independent variable of interest because it directly affects the MSMEs, which is one of Nigeria’s vibrant sectors of the economy. On the other hand, Nigeria is endowed with abundant human resources, for this reason, the labor force is included as one of the determinants of economic growth. This, of course, is an advancement to previous studies. Lastly, capital formation is a growth determinant which is a part of the growth theory employed (i.e. Harrod–Domar). It is well-known that capital formation boosts the economy as a whole.

3.1. Source of data and modelling

The empirical analysis in this study employed annual time series data spanning from 1980 to 2019 for Nigeria. The data utilized in the study is sourced from the World Development Indicators (WDI) database (http://www.worldbank.org).

The general economic growth model including variable of interest (ODA) and other important determinants of economic growth such as; LF and GCF, is specified below; (3) $${\mathit{\text{GDP}}}_t={\partial }_0+{\partial }_1{\mathit{\text{ODA}}}_t+{\partial }_2{\mathit{\text{LF}}}_t+{\partial }_3{\mathit{\text{GCF}}}_t+{\epsilon }_t$$(3)

Where

GDP is the Nigerian Economy

ODA is official development assistance as % of GNI

LF is the labor force

GCF is gross capital formation

3.2. Stationarity test

The pre-estimation testing involved the utilization of an annual time series unit root test, which is conducted on time series data for a single nation (i.e. Nigeria). The Augmented Dickey-Fuller (ADF) and the Philip-Perron (PP) tests. Prior to model estimation with the ARDL-ECM approach, a unit root test is conducted utilizing the t-statistic on the regression specified by Kwiatkowski et al. (1992). (4) $$\Delta {{\rm X}}_t=\alpha +{\beta }_t+\beta {{\rm X}}_{t-1}+{\displaystyle \sum _{i=1}^k\gamma }i\Delta {{\rm X}}_{t-i}+{\epsilon }_t$$(4)

The unit root test is conducted by testing the null hypothesis (H0) against the alternative hypothesis (H1) using the following equations:

• H0: β = 1 (Presence of unit root)

• H1: -1 < β < 0 (Stationary series)

The test statistic is expected to be negative and statistically significant at either 1%, 5%, or 10% level of significance, it can then be concluded that variables are stationary hence the null hypothesis (H0) is rejected and vice versa.

3.3. ARDL bounds test to cointegration

To capture the short and long-run effect of official development assistance (ODA) on some vibrant sectors of the Nigerian economy (GDP) that require funding in the form of foreign loans and grants, the ARDL and ECM models as suggested by Pesaran et al. (2001) are specified in Equations (5)(5) $$\begin{array}{l}\Delta \mathit{\text{ln}}{\left(\mathit{\text{GDP}}\right)}_t={\partial }_0+{\partial }_1\hspace{0.17em}L{\left(\mathit{\text{GDP}}\right)}_{t-1}+{\partial }_2\hspace{0.17em}L\left(\mathit{\text{ODA}}\right)+{\partial }_3\hspace{0.17em}L{\left(\mathit{\text{LF}}\right)}_{t-1}+{\partial }_{4}L{\left(\mathit{\text{GCF}}\right)}_{t-1}+{{\displaystyle \sum }}_{i=1}^n{\beta }_i\Delta L{\left(\mathit{\text{GDP}}\right)}_{t-i}\\ +{{\displaystyle \sum }}_{i=0}^h{\beta }_2\Delta L{\left(\mathit{\text{ODA}}\right)}_{t-i}+{{\displaystyle \sum }}_{i=0}^j{\beta }_3\Delta L{\left(\mathit{\text{LF}}\right)}_{t-i}+{{\displaystyle \sum }}_{i=0}^c\hspace{0.17em}{\beta }_4\Delta L{\left(\mathit{\text{GCF}}\right)}_{t-i}+e_t\end{array}$$(5) and (6)(6) $${L\left(\mathit{\text{GDP}}\right)}_t={\partial }_0+{\sum }_{i=0}^b\mathrm{ }{\beta }_{2}L{\left(\mathit{\text{ODA}}\right)}_{t-i}+{\sum }_{i=0}^k\mathrm{ }{\beta }_3{L\left(\mathit{\text{LF}}\right)}_{t-i}+{\sum }_{i=0}^v\mathrm{ }{\beta }_{4}L{\left(\mathit{\text{GCF}}\right)}_{t-i}{+e}_t$$(6) as follows: (5) $$\begin{array}{l}\Delta \mathit{\text{ln}}{\left(\mathit{\text{GDP}}\right)}_t={\partial }_0+{\partial }_1\hspace{0.17em}L{\left(\mathit{\text{GDP}}\right)}_{t-1}+{\partial }_2\hspace{0.17em}L\left(\mathit{\text{ODA}}\right)+{\partial }_3\hspace{0.17em}L{\left(\mathit{\text{LF}}\right)}_{t-1}+{\partial }_{4}L{\left(\mathit{\text{GCF}}\right)}_{t-1}+{{\displaystyle \sum }}_{i=1}^n{\beta }_i\Delta L{\left(\mathit{\text{GDP}}\right)}_{t-i}\\ +{{\displaystyle \sum }}_{i=0}^h{\beta }_2\Delta L{\left(\mathit{\text{ODA}}\right)}_{t-i}+{{\displaystyle \sum }}_{i=0}^j{\beta }_3\Delta L{\left(\mathit{\text{LF}}\right)}_{t-i}+{{\displaystyle \sum }}_{i=0}^c\hspace{0.17em}{\beta }_4\Delta L{\left(\mathit{\text{GCF}}\right)}_{t-i}+e_t\end{array}$$(5)

The ARDL bounds testing approach tests long-run relationships (cointegration) among variables of study using the following set of hypotheses specified as follows;

• Ho ${\partial }_0$=${\partial }_1={\partial }_2={\partial }_3={\partial }_4=$ 0

• H₁:${\partial }_0$≠${\partial }_1$≠${\partial }_2$≠${\partial }_3$≠${\partial }_4\ne$0

Narayan and Narayan (2004) has presented two discrete sets of critical values. The upper bound critical values are associated with the I(1) series, while the lower bound critical values are associated with the I(0) series. At a specified level of significance, a conclusive inference can be made irrespective of the order of integration of the explanatory variables, provided that the F-statistic surpasses the critical threshold. If the F-statistic exceeds the critical value, the null hypothesis that assumes the non-existence of cointegration is rejected. When the F-statistic is situated within the upper and lower bounds, it is not feasible to arrive at a conclusive inference. Before performing bounds testing, it is essential to have an understanding of the integration order of the explanatory variables. Following the establishment of a long-term relationship among the variables under investigation, a long-term model is computed in accordance with Equation (6)(6) $${L\left(\mathit{\text{GDP}}\right)}_t={\partial }_0+{\sum }_{i=0}^b\mathrm{ }{\beta }_{2}L{\left(\mathit{\text{ODA}}\right)}_{t-i}+{\sum }_{i=0}^k\mathrm{ }{\beta }_3{L\left(\mathit{\text{LF}}\right)}_{t-i}+{\sum }_{i=0}^v\mathrm{ }{\beta }_{4}L{\left(\mathit{\text{GCF}}\right)}_{t-i}{+e}_t$$(6) : (6) $${L\left(\mathit{\text{GDP}}\right)}_t={\partial }_0+{\sum }_{i=0}^b\mathrm{ }{\beta }_{2}L{\left(\mathit{\text{ODA}}\right)}_{t-i}+{\sum }_{i=0}^k\mathrm{ }{\beta }_3{L\left(\mathit{\text{LF}}\right)}_{t-i}+{\sum }_{i=0}^v\mathrm{ }{\beta }_{4}L{\left(\mathit{\text{GCF}}\right)}_{t-i}{+e}_t$$(6)

However, the ARDL methodology is limited to the analysis with a small sample size. For instance (1992–2021), this sample is not above 30 as compared to other estimation techniques (Johansen) that analyze larger sample sizes which are above thirty.

3.4. Error correction model (ECM)

Moreover, to obtain the short-run estimates of the ARDL model, an error correction model (ECM) is estimated as specified in (7); (7) $$\Delta {L\left(\mathit{\text{GDP}}\right)}_t={\partial }_0+{\sum }_{i=1}^n\mathrm{ }{\beta }_{1\mathrm{ }}{\Delta L\left(\mathit{\text{GDP}}\right)}_{t-1}{\sum }_{i=0}^m\mathrm{ }{\beta }_2\Delta L{\left(\mathit{\text{ODA}}\right)}_{t-i}+{\sum }_{i=0}^h\mathrm{ }{\beta }_3\Delta {L\left(\mathit{\text{LF}}\right)}_{t-i}+{\sum }_{i=0}^j\mathrm{ }{\beta }_4\Delta L{\left(\mathit{\text{GCF}}\right)}_{t-i}{+{\gamma }_i\mathrm{ }{\mathit{\text{ECM}}}_{t-1}\mu }_t$$(7)

3.5. Diagnostic tests

In order to ensure that the ARDL-ECM models used in cointegration analysis are robust and well-specified, the current study employs several diagnostic tests. The Breusch-Godfrey test is used to determine serial correlation. Other diagnostic tests conducted include; Descriptive Statistics, Normality Test, correlation analysis, and Heteroskedasticity test. Stability tests include; the Ramsey reset test, CUSUM & CUSUM of square tests.

4. Results and discussions

The subsequent section presents empirical results and associated discussions for the study. The present study offers an analysis and interpretation of the findings related to official development assistance (ODA), gross domestic product (GDP) as an indicator of economic growth, labor force (LF), and gross capital formation (GCF) in Nigeria from 1980 to 2019.

4.1. Summary of descriptive statistics

Descriptive statistics depicts the behavioral level of the chosen variables in this study. Moreover, Table 1 presents a summary of the descriptive statistics which includes the mean values of economic growth (GDP), official development assistance (ODA), Labor force (LF), and gross capital formation (GCF) as follows i.e. 0.539752, 8.540179, 1.025871, 10.61762, respectively. Furthermore, the standard deviations of the variables labor force (LF) and gross capital formation (GFC) show fewer dispersions from average indicating that the variables are quite close around their respective means i.e. 0.011806, and 0.288948 respectively. Also, the standard deviations of official development assistance (ODA) and gross domestic product (GDP) (i.e. 14.43239, 5.257504 respectively) showed wider variations which indicates that the variables are quite dispersed around their respective means. In essence, the statistical behaviors of our selected variables exhibit distinct behaviors, yet, they fit the established model with an average result. Statistically, the labor force stands as the variable that fits the model best due to its low dispersions from its expected value (mean). Also, the observed means of the variables appeared to be sufficient for empirical analysis with that of GDP as the least. Based on the statistical results, it can be concluded that the selected variables are fit for the model, hence they can be used for empirical analysis.

Table 1. Descriptive statistics test results.

	Mean	Std. dev	Min	Max	Obs.
GDP	0.539752	5.257504	15.45036	12.45747	40
ODA	8.540179	14.43239	0.379475	80.20272	40
LLF	1.025871	0.011806	1.003958	1.047950	40
LGCF	10.61762	0.288948	10.09155	11.16735	40

Source: Authors’ computation (2023).

4.2. Results of unit root test

According to the findings presented in Table 2, the unit root test revealed that the labor force (LF) and gross capital formation (GCF) variables exhibit unit roots at their respective levels. However, subsequent to the first difference, both variables achieved stationarity at the 1% significance level. Consequently, they exhibit co-integration of the first order [1(1)]. The variables of economic growth (GDP) and official development assistance (ODA) exhibit no unit root at their respective levels and fall within the range of 1% and 10% level of significance. This indicates that they are stationary at level and possess an integration order of zero [1(0)]. Based on the test results, the stochastic trends of the selected variables show they have no unit root and the mixed order of integration of the variables provides a strong justification for the adoption of the ARDL method of analysis for the study. Note, that steady stochastic trends justify the stability of a variable over a longer period of time, therefore the researcher should be assured of spurious-free results.

Table 2. Results of unit root test.

	ADF
Variables	Level	First difference	Stationarity status
GDP	−0.8544*	−3.632900***	I(0)
ODA	−2.938987**	−3.621023***	I(0)
LLF	−2.621007	−2.941145**	I(1)
LGCF	−2.621007	−2.941145**	I(1)

Notes: Lag lengths are selected based on the Akaike Information Criterion (AIC). The test statistics are compared with critical values from MacKinnon (1996); ***, ** and * denote significance at 1%, 5% and 10%, respectively.

4.3. Results of bounds testing to cointegration

The ARDL bounds testing approach is utilized to conduct the cointegration test, given the stationary status of the employed variables. The results for the bounds test as presented in Table 3 show the calculated value of F-statistic (i.e. 10.44613) is greater than the upper critical bounds at 1%, 2.5%, 5%, and 10% significant levels, respectively. This means that a long-run relationship (cointegration) exists between official development assistance (ODA), economic growth (GDP), labor force (LLF), and gross capital formation (LGCF). The presence of cointegration signifies that the bounds testing conducted is effective due to the coherence of the selected variables. Being a joint test of significance, the ARDL bounds test suggests that besides, the individual effect each variable might have on the regress and, they also possessed a joint effect on it. This result is consistent with the findings of Appiah-Konadu et al. (2016) who conducted the study in Ghana in the different time frames of 1972–2012 and also the Harrod–Domar growth theory perspective for comprehending the dynamics of economic growth, highlighting the crucial significance of investment in stimulating favorable economic results. Having established that a long-run relationship exists among the variables, the next step is to estimate the long-run and short-run ARDL Models for the study.

Table 3. Results of bounds test.

Dependent variables	Function	F statistics
LGDP	f (GDP/ODA, LLF, LGCF)	10.44613***
Critical value bounds
10%	5% 2.5%	1%
I(0) I(1)	I(0) I(1) I(1) I(0)	I(1) I(0)
2.37 3.2	2.79 3.67 4.08 3.15	4.66 3.65

Source: Authors’ computation (2023).

***Denotes statistical significance at 1% level.

4.4. Results of selected short run model

The result of the short-run model is presented in Table 4 with an optimal lag length as suggested by the Akaike Information Criterion (AIC) as (1, 0, 0, 1). The results reveal that there is a short-run negative and significant relationship between gross capital formation (GCF) and economic growth (GDP) at the 1% level of significance. A 1% increase in gross capital formation (LGCF) will lead to about 0.079% decrease in economic growth in the short run. This result implies that capital formation in Nigeria is not sufficient for businesses, it retards economic growth. The negative effect it had on growth could be connected to poor funding of the medium-small enterprises sector by the Nigerian government and poor infrastructural development that supports businesses.

Table 4. Results of short run model.

Panel A: short-run coefficients – dependent variable is GDP
Regressor	Coefficient	Standard error	T-statistics	Prob
$\Delta$ (LGCF)	−793.3589	104.0013	−7.628356	0.0000
CointEq(−1)*	−0.812403	0.106161	−7.652558	0.0000

Source: Authors’ computation (2023). Δ is the first difference operator.

*Denotes lagged variable in the previous time period.

Moreover, the coefficient of the error correction term lagged by one period (ECT-1) shows a negative sign and is statistically significant at the 1% level. This implies that about 81% distortion of the equilibrium in the short run will be corrected within a year toward the long run. In essence, the error term coefficient measures the speed of adjustments from short-run distortions of economic growth toward its proper adjustment in the long run. The result indicates 81% speed, this is considered a higher speed of adjustment. The implication for this is that it will not take much time for the economy to be revamped.

4.5. Results of selected long run model

The long-run estimated results are reported in Table 5. The result illustrates that official development assistance ODA has a negative value (i.e. −0.012946) and an insignificant effect on economic growth GDP. The implication of this result is ineffective disbursement and poor utilization of foreign aid by the Nigerian authorities. Moreover, the labor force (LLF) has a positive (i.e. 2.438618) impact on economic growth at 1% level of significance. The implication for this result is that A 1% increase in the labor force (LF) will lead to about 2.44% increase in economic growth GDP this indicates that Nigerians are endowed with adequate human resources for economic prosperity. Furthermore, gross capital formation (LGCF) has a negative (i.e. −1.003467) and significant effect on economic growth at 1% significance level. A 1% increase in gross capital formation (LGCF) leads to a decrease in the economic growth rate (GDP) by 1.00%. The long-run results uncovered in this study are in line with the findings of extant literature (see Appiah-Konadu, et al. 2016; Makinde & Isiaka, 2020). However, Appiah-Konadu et al. (2016) conducted their study in Ghana using a different time frame but the same method of analysis. On the other hand, Makinde and Isiaka, share the same unit of analysis with the current study (Nigeria). More so, their study employed the causality test and pre-estimation tests (ADF) similar to that of the current study, however, the time frame differs as they employed the (1970–2020) period.

Table 5. Results of long run model.

Panel B: long-run coefficients – dependent variable is GDP
Regressor	Coefficient	Standard error	T-ratio	Prob
NODAP	−0.012946	0.058873	−0.219892	0.8273
LLF	2.438618	5647.371	4.318148	0.0001
LGCF	−1.003467	231.0325	−4.343401	0.0001
C	−1.436226	3340.672	−4.299214	0.0001

Source: Authors’ computation (2023).

4.6. Results of diagnostic tests for the ARDL model

Diagnostic tests were conducted to check for the presence of serial correlation, heteroskedasticity, functional form misspecification, and normality of the error terms. The results of the diagnostic test are presented in Table 6. The Jacque-Bera statistic with a Probability value of 0.740673 show the residuals are normally distributed. Also, the test statistic for heteroskedasticity is 1.408025 with a probability value of (i.e. 0.2470) this shows that the error terms are homoscedastic.

Table 6. Results of diagnostic tests.

Test statistic	Results
Serial correlation: CHSQ(2,31)	0.781792 [0.4664]
Functional form: reset F-stat (1,32)	0.007471[0.9317]
Normality: Jarque-Bera	0.600391[0.740673]
Heteroscedasticity: CHSQ(5,33)	1.408025[0.2470]

Source: Authors’ computation (2023).

Furthermore, the Ramsey RESET shows a probability value of 0.9317 and this illustrates that there is no problem of misspecification in the estimated model (i.e. the model is well specified in a linear form). The probability value (i.e. 0.4664) for serial correlation LM test result demonstrates that the variables employed are free from serial correlation problems.

4.7. Results of the stability test

The study employed the cumulative sum (CUSUM) and cumulative sum of squares (CUSUMSQ) methods to assess the stability of the long-term parameters. Figures 3 and 4 depict the plots of the aforementioned tests. The plots of CUSUM and CUSUMSQ fall within the critical bounds. This suggests that the estimated parameters and model exhibit stability over an extended period of time, thereby enabling their utilization in the development of policies.

Figure 3. Plot of the cumulative sum of recursive residuals.

Figure 4. Plots of the cumulative sum of recursive residuals.

4.8. Results of the Granger causality test for the ARDL model

The Granger causality statistic was utilized to conduct the causality test. Granger (1969) posited that variable A can be considered a ‘Granger cause’ of variable B only if the past values of A provide better predictions of B than when the past values of B are used alone, regardless of whether past values of A are used. Stated differently, the concept of Granger causality posits that if scalar A is capable of serving as a predictor for another scalar B, then A is said to exert Granger causality over B. Table 7 presents the outcomes of the Granger causality examination. This study establishes that the presence of a Granger causality relationship can be inferred if the probability values fall below the 10% significance level. Based on our analysis, it can be concluded that there is no evidence of either unidirectional or bidirectional causal relationships between official development assistance (ODA) and economic growth as measured by gross domestic product (GDP). In essence, the two-way directional test, suggests no directional effect on any of the affected variables.

Table 7. Results of Granger causality.

Null hypothesis	lags	Chi sq	Prob	Conclusion
NODAP does not cause GDP	1	0.39379	0.5343	Accept null hypothesis
GDP does not cause NODAP	1	1.22975	0.2748	Accept null hypothesis

Source: Authors’ computation (2023).

5. Conclusions and recommendations

5.1. Conclusions

This study critically examines the effect of foreign aid on Nigeria’s economic growth. Moreover, the study employed additional variables that determine economic growth for the robustness of the results. This study is significant in the current period where foreign aid and extended credits are rampantly disbursed to developing nations including Nigeria. However, most findings from past scholars indicate that these aids make lesser or non-contribution to GDP. This necessitates the re-examination of such phenomenon to find possible ways of utilizing foreign aid effectively for businesses to thrive. Based on the study’s findings, the following conclusions can be drawn. First, official development assistance as a form of foreign aid and credit extensions does not contribute to the progress of the Nigerian economy, it rather retards it. This suggests that these loans are not channeled to the right sectors of the economy and are misappropriated by relevant authorities receiving such assistance, and it manifests the presence of ineffective economic policies. Second, the study concludes that the labor force contributes to economic progress in Nigeria, whereas gross capital formation just like foreign aid retards growth. Moreover, this study is limited by constraints in its conduct. First, the high cost of obtaining various statistical and econometric software for robust analysis and results and also the high cost of sourcing information and data from various visual libraries, international journals, and internet archives serve as bottlenecks to this study. Second, this study left out other potential determinants of economic growth such as trade openness, government expenditure, inflation, and corruption due to the limited number of observations obtained, covering only the 1980–2019 period. Lastly, this study is limited to only one estimation approach, which is the ARDL method of analysis.

5.2. Recommendations and limitations

Based on the study’s findings and conclusions, a few recommendations were outlined. According to the estimated results, official development assistance is statistically insignificant to economic growth, this study recommends an independent commission of the Nigerian government responsible for overseeing the receipt and utilization of financial foreign aid to Nigeria and ensuring it’s channeled appropriately to relevant sectors for economic prosperity. The study also recommends sufficient capital disbursements to small and medium enterprises (SMEs) which according to the results declines economic growth due to poor contributions. It is recommended that stakeholders and policymakers in the Nigerian government implement a robust and consistent macroeconomic policy to encourage domestic savings and optimize the utilization of foreign aid, specifically official development assistance. It is anticipated that the disparity between savings and investments will be resolved through the utilization of domestic savings to fund both private and public investments over an extended period. The government should take measures to ensure the proper implementation of said policies.

It is recommended that the Central Bank of Nigeria (CBN) devise a monetary policy strategy that fosters private investment and mitigates investment barriers by facilitating access to credit facilities for private enterprises, particularly small and medium-sized enterprises (SMEs). It is recommended that the government offer incentives to private investors and establish a conducive environment to facilitate the growth and success of private enterprises. This study has certain limitations. First, important variables that can affect economic growth such as inflation, exchange rate, and savings were left out of this study. Second, the scope of this study is 1980–2019. Therefore, future researchers can consider the variables that were left out and extend the scope to the most recent periods. The Nigerian government should endeavor to disbursed foreign aid in the form of official development assistance ODA to the most deserving business sector of the economy which is the MSME’s sector.

Authors’ contributions

The collaborative efforts of the authors, Stanislav Rojík, Mansoor Maitah, Karel Malec, and Kamal Tasiu Abdullahi, in the development of this paper were marked by their substantial contributions at various stages. The inception and design of the project benefited from the insightful input of all authors, highlighting their collective commitment to shaping the conceptual framework. In the subsequent phases of the paper, Stanislav Rojík and Mansoor Maitah actively participated in the acquisition, analysis, and interpretation of data, demonstrating their integral roles in the research process. The meticulous drafting of the paper was spearheaded by Stanislav Rojík, who, in collaboration with Mansoor Maitah, Karel Malec, and Kamal Tasiu Abdullahi, engaged in critical reviews, ensuring the incorporation of important intellectual content. A collaborative consensus among all authors, including Stanislav Rojík, Mansoor Maitah, Karel Malec, and Kamal Tasiu Abdullahi, culminated in the final approval of the version intended for publication. This collective approval underscores their joint responsibility for the accuracy and integrity of the entire body of work.

Data availability statement

Authors commit to providing access to the data supporting the findings and analyses presented in the paper upon receiving a reasonable request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This paper was supported by the Internal Grant Agency (IGA) of the Faculty of Economics and Management, Czech University of Life Sciences Prague, grant no. 2022B0008 Economic Governance as a Key Determinant of Macroeconomic Development in Africa.

Notes on contributors

Stanislav Rojík

Dr. Stanislav Rojík is an Assistant Professor at Czech University of Life Sciences in Prage and College of Polytechnics in Jihlava in the Czech republic. He is also regularly teaching as guest lecturer at University of Applied Sciences Kaiserslautern in Germany. Research interest and main research areas are focused on Economics, Management and Marketing in main fields i. e. sustainable agriculture and food production; organic food and agricultural products; foods labels of origin and quality; healthy foods; environmental values; agriculture markets and trade; food policy and food security and.food consumer behavior.

Mansoor Maitah

Mansoor Maitah is a full Professor in Applied Economics, Department of Economics, Faculty of Economics and Management, Czech University of Life Sciences in Prague. He lectures the following courses in the English taught programmes: Trade Theory and Foreign Trade, Macroeconomics, International Economics and Quantitative Methods in Macroeconomics. His main research interests are in Foreign Trade, International Economics, Quantitative Methods in Macroeconomics. He is a member of of the editorial boards of “International Journal of Trade and Global Markets”, ”Journal of Trade and Global Markets”, “African Journal of Economic and Management Studies” and “PSU Research Review: An International Journal” (The Netherlands), the European Association of Agricultural Economists, the International Association of Agricultural Economists and Czech Agricultural Sciences.

Karel Malec

Karel Malec is a highly skilled academic researcher and independent consultant with expertise in agricultural economics, commodity markets, sustainability, and climate change. He has a deep understanding of the economic and sectoral consequences of climate policies, with the ability to analyze complex documents and identify key trends and implications. Karel has always had a passion for exploring the world and experiencing new cultures, especially in Asia and Africa. Throughout his career, he has been involved in numerous projects as a principal researcher, co-researcher, and consultant. This experience is reflected in his publication output, as he has published more than fifty scientific and conference papers, with an H-index of 6.

Kamal Tasiu Abdullahi

Kamal Tasiu Abdullahi is a distinguished researcher whose scholarly pursuits span the domains of economics, finance, international relations, and social policy. As a member of esteemed research associations such as the Social Science & Humanities Research Association (SSHRA), OCEANS Network, International Adam Smith Society (IASS), and International Association for Research in Income and Wealth (IARIW), Abdullahi has made significant contributions to advancing knowledge in his field. Some of his extensive publication record includes peer-reviewed journal papers addressing critical issues such as economic growth, governance structures, and environmental sustainability.