There have been a steady rise in Nigeria debt profile which has been greeted with dwindling export earnings due and an ever increasing debt servicing obligations it is based on this, the study examined the impact of public debt and export on the performance of the Nigerian economy from 1985 to 2020 by employing Autoregressive Distributed Lag as well as the Error Correction Model (ECM) techniques. The ARDL Bounds Test results confirmed that there is a long-run equilibrium relationship among the variables. The results of the Error Correction Mechanism (ECM) showed that domestic debt and export have a significant impact on economic performance in Nigeria through the existence of stable long-term equilibrium relationship among the variables employed in the model. Therefore, this study recommends that government fiscal policies should aim at funding critical infrastructural facilities and capital projects. This will ensure that the ratio of capital expenditure to fiscal deficit increases to sustainable level.
In recent times there has been an upward trajectory of the debt profile of Nigeria. This is as a result of an increasing deficit budgeting by the federal government of Nigeria. Deficit reflects the annual amount the government need to borrow, and it is primarily funded by selling government bonds (gilts) to the private sector. Nigeria’s debt profile stands at least N41.60 trillion, with a debt to GDP ratio projected at 39% by the end of 2022. According to information from the Debt Management Office (DMO), Nigeria’s total debt profile rose to its highest level in 2021, hitting a record high of N39.56 trillion ($95.78 billion) as of December 2021, representing an N6.64 trillion ($9.39 billion) increase compared to N32.92 trillion ($86.39 billion) recorded as of the same period of the previous year. Nigeria’s Federal government incurred a sum of N4.22 trillion on debt servicing in 2021, increasing by 29.3% compared to N3.27 trillion spent in the previous year. On the other hand, revenue for the period only increased marginally by 9.3% to N4.39 trillion. This means that Nigeria spent about 96% of its revenue on servicing debt obligations in the year under review. Compared to the previous year, Nigeria’s debt service-to-revenue ratio increased from 81.1% in 2020 to 96% in the year under review [1]
The increasing rise in Nigeria’s debt profile is as a result of a fall in the production and export of crude oil which is the main source of government. In fact Nigeria depends largely on crude oil earnings which contributes about 90 percent of export earnings [2] . Nigeria’s government revenue has been constrained in recent times by the underperformance of oil revenue due to the continuous decline in production capacity and volatility in the price of crude oil. According to data from the National Bureau of Statistics (NBS), Nigeria’s daily crude oil production dropped to 1.6mbpd in 2021 from 1.78mpbd recorded in the previous year. Notably according to recent data from the Organization of Petroleum Exporting Countries (OPEC), Nigeria’s crude oil production further declined to 1.238mbpd in March 2022 from 1.258mbpd average production recorded in February 2022.
Successive governments have been overspending their revenue. Currently, our budget deficit has exceeded the three percent bench mark by the Fiscal Responsibility Act. The International Monetary Fund (IMF) indicated that sustained budget deficit has been the chief driver for inflation, interest rate and macro-economic considerations in developing nations.
The debt and budget deficit discussed above does not take into consideration various state debts and budget deficits. Our recurrent expenditure is spiraling out of control and our capital expenditure is not efficiently allocative to critical infrastructure that will engineer growth and economic development. These are pointers to the current and future economic quagmire the country is likely to be bedeviled with. For Nigeria, it can be argued that the budget deficit experienced in the country is as a result of improperly anchored macro-economic policy; this is because both the Keynesian and neo classical school believes that fiscal deficit can spur economic growth if effectively harnessed, financed and such debt reduced; with a threshold.
[3] assert that trade, especially export are powerful tool in the movement of accelerating and boosting economic growth in present-day economies as a result of economic globalization. [4], further opined that trade has remained a vital driver of economic progression. The success and good organization of allocation of resources, and transmitting growth from one part of the world to another is influence by trade significantly. Generally, import and export of goods and services are important element in computation of balance of payment of any economy. Domestic investment, export and import are seen as the tools used to manipulating economic growth and development. Export of goods and services. Export of goods and services serves as a way in which an economy generates foreign exchange. Contrarily, import is a source of outflows of foreign exchange. The manipulation of both export and export affect domestic investment and also has implication on economic growth [5].Obviously, Nigeria has not gain from export relatively to it economic natural endowment, withabout 38 firm minerals types and a populace approximated to be over 180 million persons, one of themain gas and oil reserves in the sphere. Export, domestic investment and economic growth of thecountries are weak when linked to the incipient Asian nations such as Malaysia, Indian and Thailand.These nations have surpassed Nigeria in term of growth despite the humongous amount of debt Nigeria have incurred. In it on this note that we embark on this research to ascertain the debt as well as the export impact on the economic performance of Nigeria. The remaining parts of these study is therefore structured as follows; the literature review will be done in section two, in section three the methodology adopted for conducting the research is presented while the results and discussions as well as the conclusion and recommendations will be covered in section four and five.
2.1 Conceptual Issues
Debt: Public debt also referred to as government debt or external debt is conceptualized as the aggregate debts owed by a certain country to individuals, corporations and countries within the country or abroad. Public debts typify all forms of government borrowings at all levels of government [6]. Public debt forms part of the finance approach adopted by governments all over the world, although this approach is often resorted to when all measures have been exhausted, in fact the measure is considered favorable relative to other measures which includes the creation of money and the sale of national assets [7]. Notwithstanding, it has been observed that an increased level of external debt impacts negatively on the trade ability and economic prosperity of most nations. Also, debt overhangs influences economic improvement and the effectiveness of monetary policies, export growth and reduces the severity of trade policies thereby enhancing the friendliness of the market and by implication increasing trade openness. Despite this, debt if not adequately utilized reduces the level of economics development [8]. He further maintained that debt services ceases the resources required for socioeconomic development. The implementation of SAP in 1986 was as a result of the increased debt incurred by Nigeria this was needed to create a sustainable economic growth.
Export: Export is broadly categorized into oil and non-oil export. Non-oil sector comprises those groups of economic activities which are outside the petroleum and gas industry such as manufacturing, agriculture, telecommunication, service, finance, tourism, real estate, health sector and construction. Mostly, non-oil agricultural products such as groundnuts, palm kernel, palm oil, cocoa, rubber, cotton, coffee, beans, hides, skin and cattle surpassed Nigeria’s export trade in the 1960s. But it was the discovery of oil boom that shifted the attention of Nigeria from non-oil exports to oil export which have made Nigeria a mono-cultural economy since the 1970s. The increasing dependence of petroleum export has weakened non-oil exports in Nigeria. The international price of crude oil once again started declining that resulted in downward movement in export and government revenue in 2012. This negative shock is transmitted into the domestic economy through crude oil export proceeds, import and public expenditure.
Economic Growth: Economic growth is a rise in the productive capacity of a country on a per capita basis. It is the increase in the national output or GDP of the nation. Economic growth occurs whenever people take resources and rearrange them in ways that are more valuable. It refers only to the quantity of goods and services produced and say nothing about the way in which they are produced. It measures growth in monetary terms and looks at no other aspects of development. Although, it can be measured in nominal terms which includes inflation, or in real terms, which are adjusted for inflation. GDP like any other economic quantifier must be expressed in real terms, adjusting for the effects of inflations, as to provide a meaningful measure of growth overtime. Economic growth can be either positive or negative. Negative growth refers to shrinking economy. It is associated with economic recession and economic depression. Positive growth is the opposite.
2.2 Empirical Literature
[5] examined the relationship between imports, exports, domestic investment and economicgrowth in Nigeria. Their study make used of annual time series data which span from 1981 to 2016, which issourced from World Development Indicator (WDI) and Central Bank of Nigeria Statistical Bulletin. They employed ARDL Model and VEC Granger Causality Test to explore the relationship among thevariables. Their empirical results show that there is long run relationship among the variables. In the short run,empirical results show that only imports have negative effect on economic growth in Nigeria. The VECGranger Causality Test indicates that there is relationship among the variables. This negativity effect ofimports on economic growth in Nigeria requires stringent economic reforms.
[9] in their study Determinants of Non-oil Export and Economic Growthin Nigeria using data from 1970 to 2012 on non-oil export value, exchange rate, ConsumerPrice Index as proxy for inflation, Real Interest Rate and Real Gross Domestic Product (RGDP) as proxy for economic growth and employing the ARDL estimation technique. Their findings revealed that a significanteffect of non-oil export on economic growth in both the long and short run exist. They therefore recommended that policies aimed atboosting the level and significance of the nonoil export should be pursued.
[10], used the bounds test analysis - unrestricted errorcorrection model to analyze the long-run relationships between exports and economic growth for Nigeria over the period 1979-2005. Based on the model, exports, labour force and economic liberalization policies (since 1986) have stimulated economic growth, whereas, imports and exchange rate negatively impacted on economic growth. His findings showed that economic growth, exports, imports labour force and exchange rate are cointegrated. Further analysis showed economic growth uni-directionally Granger- causes exports during the period of study. He therefore concluded that his study does not provide evidence to support the export-led economic growth hypothesis in the Nigerian economy.
[11] using OLS method and annual data spanning the period 1980–2013 examinedthe impact of external debt on economic growth in Nigeria. The study modelled GDP as a function ofexternal debt stock, debt service payments and exchange rate. The empirical results indicated thatexternal debt stock and debt service payments impacted growth negatively while exchange rateshowed a positive impact. The study concentrated on external debt which is a fraction of total debtstock and used the OLS estimation technique that cannot separate the long- and short-run effect ofexternal debt on growth. [12] using the Vector Error Correction Model (VECM) andannual data from 1980 to 2015, analysed the relationship between public debt and economic growthin Nigeria. The variables used in the study included RGDP, foreign debt, domestic debt, and domesticprivate savings. The study findings revealed a significant negative impact of foreign and domesticdebt on economic growth in Nigeria. The study suffered from significant variable omission bias andadopted an inadequate estimation technique that cannot generate reliable coefficient estimatesabout the study variables.[13] in their study examined the resultant effect of government borrowings on economicdevelopment in Nigeria using data from 1990 to 2020 which were analyzed with multiple regression model, Johansen co-integration, and Error Correction Mechanism (ECM). The study employed external debt (EXD), domestic debt (DOD), interest rate (INTR), and inflation (INF) as independent variables whilst the human development index (HDI) was used as the dependent variable and was a proxy for development. The result revealed a positive statistically significant relationship between external debt and economic development the same as domestic debt and economic development in Nigeria, while interest rates have a negative statistically significant relationship with economic development in Nigeria. However, inflation was found to be negatively statically insignificant to economic development in Nigeria. They therefore recommended that the government should direct borrowed monies to sectors/areas of the economy that will spur growth, such as education, health, industry, and transportation. [14], investigated the impact of public debt on the economic growth in Nigeria with data from 1981to 2019. The Cointegration test result showed that the variables in the model were co-integrated meaning that the variables have a long run relationship. External debt was found to have a negative and insignificant impact on the economic growth in Nigeria while domestic debt has a positive and significant impact on the economic growth in Nigeria while credit to private sector has a negative and insignificant impact on the economic growth in Nigeria. In the long run external debt has a negative and insignificant impact on the economic growth in Nigeria while domestic debt has a positive and significant impact on the economic growth in Nigeria. They recommended based on these findingsthat government should reduce the rate at which it takes external loans to finance its activities. Moreover, domestic debts should be properly managed by channeling it towards those activities that will stimulate economic growth.
3.1 Data and Model Specification
This study employed annual secondary between 1981 and 2020. Thesedatasets were extracted from theWorld Development Indicators (WDI), Debt Management Office (DMO) and CentralBank of Nigeria (CBN) Statistical Bulletin.In order to investigate the impact of public debt on the economic growth of Nigeria, the model for this study follows the methodological framework of [9,13,14] with some modifications. The general functional form of the model is specified thus;
RGDPt = f( DODt, EXDt, TEXPt, INTt) (1) The econometric specification of the model is given as:
RGDPt = β0 + β1DODt +β2EXDt + β3TEXPt + β4INTt +et (2
Where;
RGDP is Real Gross Domestic Product at Current Basic Prices (₦' Billion), DOD is Domestic debt (₦' Billion), EXD is External debt (₦' Billion), TEXP is Total value of export (₦' Billion)and INT is Real interest rate (%).
β0 is the constant term, β1, β2, β3 and β4 are the parameters to be estimated, et is the residual term and f is the function denotation.
The a priori expectation is given as:
β1, >0, β2>0, β3 >0 and β4<0
The ARDL technique originated by Paseran et al. (2001) was used for theestimation. The ARDL bounds test that captures the cointegrating vectors is specified below.
The generalized ARDL (p, q) model is specified as:
![]()
A convention Error Correction Model (ECM) for cointegrated data is in the form:
![]()
The variables are as defined earlier,
is a difference operator. A crucial parameter in the estimation of the ARDL dynamic model is the coefficient of the error correction term (ᵧECTt-1),which measures the speed of adjustment of economic growth to its equilibrium level.We therefore proceed to estimate the data set for both the long run and short run model using the ARDL approach. The results are presented below.
4.1 Descriptive Statistics
The descriptive statistics is done to reveal the features of the data used in the study. The result of the descriptive statistics is presented below;
Table 4.1 Summary Statistics
| LRGDP | LDOD | LEXD | LTEXP | INT | |
| Mean | 10.45614 | 6.920967 | 6.858033 | 14.26273 | 2.541450 |
| Median | 10.37926 | 7.127016 | 6.555672 | 14.71207 | 4.946734 |
| Maximum | 11.18573 | 9.681836 | 9.449800 | 16.80676 | 18.18000 |
| Minimum | 9.750924 | 3.330385 | 2.850741 | 9.096118 | -31.45257 |
| Std. Dev. | 0.509173 | 1.941710 | 1.478062 | 2.309354 | 9.951241 |
| Observations | 36 | 36 | 36 | 36 | 36 |
Source: Author’s computation with EVIEWS
The descriptive statistics is presented in table 4.1 above generated from observations of 36 years, will be discussed briefly. The variables of the studyare analysed to show their characteristics. The RGDP which is the dependent variable has a mean value of 10.45614 which represent an average of N10.45614 billion. The domestic debt (DOD) has an average value of 6.920967 which implies an average of N6.9billion, external debt (EXD) have a mean of 6.858033, this means that on average Nigeria borrowed about N6.858033billionfrom foreign donors. The average level of total export in the countrywasN14.26273billion, while interest rate on average was put at 2.5percent. The interest rate highest value was 18.2percent with minimum value -31.5percent. The RGDP, DOD, EXD and TEXP have maximum and minimum values of N11billion and N9.7billion, N 9.68billion and 3.33billion, N9.44billion and N2.85billion, N16.8billion and N9.1billion respectively.
4.2 Correlation Matrix
The correlation matrix is done to show the degree of association among the variables of the study. The result of the correlation matrix is presented below; Table 4.2 Correlation Matrix Results
| Variable | LRGDP | LDOD | LEXD | LTEXP | INT |
| LRGDP | 1.000000 | ||||
| ----- | |||||
| LDOD | 0.951245 | 1.000000 | |||
| (0.0000) | ----- | ||||
| LEXD | 0.652562 | 0.794328 | 1.000000 | ||
| (0.0000) | (0.0000) | ----- | |||
| LTEXP | 0.899322 | 0.965227 | 0.767347 | 1.000000 | |
| (0.0000) | (0.0000) | (0.0000) | ----- | ||
| INT | 0.422101 | 0.354463 | 0.182556 | 0.333466 | 1.000000 |
| (0.0103) | (0.0339) | (0.2866) | (0.0469) | ----- |
Source: Author’s computation with EVIEWS; theprob. Values are given in parenthesis.
The above table 4.2 contains the correlation matrix, all the independent variables; LDOD, LEXD, LTEXP and INT have a statistically significant relationship with LRGDP.LNGU, LDOD and LTEXP displayed a very strong correlation with the dependent variable. LEXD have a strong correlation with the dependent variable while INT shows a weak correlation with LRGDP. Among the independent variables,there exist a strong positive correlation between LEXD and LDOD, LTEXP and LDOD, as well as between LTEXP and LEXD. The correlation between INT and the other independent variables although positive is weak.
4.3 Unit Root Test
It is important to conduct the test for stationarity for the variables especially given the fact that we are working with time series data. The use of non-stationary variables leads to spurious regression.
The Augmented Dickey Fuller technique was employed to test for unit root. The test result is presented below;
Table 4.3: ADF Unit Root Test Result
| Variables | ADF Test Stat Level | Critical Values @ 5% | ADF Test Stat first diff | Critical Values @ 5% | Order of Integration | Prob. Value |
| LRGDP | -0.753882 | -2.951125 | -3.636647 | -2.951125 | I(1) | 0.0101 |
| LDOD | -1.978185 | -2.948404 | -4.523226 | -2.951125 | I(1) | 0.0010 |
| LEXD | -1.732494 | -2.951125 | -4.057681 | -2.951125 | I(1) | 0.0034 |
| LTEXP | -2.464891 | -2.948404 | -4.436649 | -2.954021 | I(1) | 0.0013 |
| INT | -3.587875 | -2.948404 | - | - | I(0) | 0.0112 |
Source: Author’s computation with EVIEWS
The result of the Augmented Dickey Fuller test is presented in table 4.3 above. From the result it can be observed that all the variables except interest rate (INT) are stationary at the first difference that is they are integrated at order one I(1). INT is stationary at levels I(0). This is based on the absolute value of ADF test statistics been greater than absolute value of the critical values at the 5% level. The outcome from the unit root test makes the ARDL approach the best technique for analysis, this is so since there’s mixed order of integration. The next step is to check for the existence of long run relationship among the variables using the ARDL Bounds test to cointegration technique.
4.4 Cointegration
Based on the outcomes from the unit root test conducted it is necessary to check for the existence of cointegration. The ARDL-bound test approach to cointegration will be applied due to the mixed order of integration. The bound test approach makes it possible to test for the existence of long run relationship among the variables by conducting an F-test for the joint significance of the coefficients of the lagged levels of the variables. The outcome of the cointegration test is presented below.
Table 4.4: Result of the ARDL (Bounds) Test for Cointegration
| F-Bounds Test | Null Hypothesis: No levels relationship |
| Test StatisticValueK | |
| F-statistic 4.6144504 | |
| Critical Value Bound | |
| Significance I0 Bound I1Bound | |
| 10% 2.453.52 | |
| 5% 2.864.01 | |
| 2.5% 3.254.49 | |
| 1% 3.745.06 | |
Source: Author’s computation with EVIEWS
The ARDL Long Run Form and Bounds Test is presented above in table 4.4 above. From the result above, we reject the null hypothesis of no cointegration between the dependent and independent variables since the computed F statistic (4.614450) is greater than the upper bound at the 5% significance level (4.01). Thus we can infer that there exist a long run relationship among LRGDP, LDOD, LEXD, LTEXP and INT at the 5% level of significance. The series can then be combined in a linear fashion as shocks in the short run experienced by individual series can be corrected in the long run. That is, there will be convergence.
4.5 Model Estimation and Discussion of Findings
The estimates of the long run and short run models and the diagnostic test are presented below.
Table 4.5a: Long run Model Estimates
| Dependent Variable: LRGDP | ||||
| Method: Least Squares | ||||
| Variable | Coefficient | Std. Error | t-Statistic | Prob. |
| C | -0.315969 | 0.436251 | -0.724281 | 0.4747 |
| LRGDP(-1) | 1.013547 | 0.046115 | 21.97885 | 0.0000 |
| LDOD(-1) | -0.051672 | 0.020710 | -2.494991 | 0.0185 |
| LEXD(-1) | 0.006271 | 0.007741 | 0.810121 | 0.4245 |
| LTEXP(-1) | 0.036909 | 0.010150 | 3.636514 | 0.0011 |
| INT(-1) | 0.000755 | 0.000633 | 1.191366 | 0.2432 |
| F-statistics = 1541.600 | Prob.(F-statistics)= 0.000000 | |||
| R-squared= 0.99 | Adjusted R-squared= 0.99 | Durbin-Watson stat.= 1.7 | ||
Source: Author’s computation with EVIEWS
From the long run model presented in table 4.5a above, the OLS estimate output shows that only DOD has a negative relationship with the RGDP as the other independent variables displayed a positive relationship with RGDP. A 1% increase in the lagged value of the dependent variable will increase RGDP by 1.013547, while a 1% change in LEXD, LTEXP and INT will increase RGDP by 0.006271, 0.036909 and 0.000755 respectively. LDOD on the other hand when it is increased by 1% reduces RGDP by -0.051672. Only lagged dependent variable (LRGDP), LDOD and LTEXP are found to be statistically significant at the 1percent, 5percent and 1percent respectively. The F-statistic probability value of 0.00000 shows that there is joint significance among the variables of the study at the 1percent level. The Durbin-Watson stat of 1.7 shows that the model is free from serial correlation. The model has high explanatory and predictive power as evidenced by the R-squared and the adjusted R-squared values respectively. The Adjusted R-squared value of 0.995606suggests that about 99% of the systematic variations in Real Gross domestic product can be explained by domestic debt, external debt, total value of export and the real interest rate. The residual from the long run model (ecm) is use to estimate the short run mode
Table 4.5b: Error Correction Model
| Dependent Variable: D(LRGDP) | ||||
| Method: Least Squares | ||||
| Variable | Coefficient | Std. Error | t-Statistic | Prob. |
| C | 0.006375 | 0.016282 | 0.391569 | 0.6984 |
| D(LRGDP(-1)) | 1.093742 | 0.316145 | 3.459620 | 0.0018 |
| D(LDOD(-1)) | -0.117815 | 0.040237 | -2.928070 | 0.0068 |
| D(LEXD(-1)) | 0.017403 | 0.013722 | 1.268269 | 0.2155 |
| D(LTEXP(-1)) | 0.039673 | 0.015956 | 2.486403 | 0.0194 |
| D(INT(-1)) | 0.000192 | 0.000537 | 0.357276 | 0.7237 |
| ECM(-1) | -0.987055 | 0.392943 | -2.511952 | 0.0183 |
| F-statistics = 3.386162 | Prob.(F-statistics) = 0.012760 | |||
| R-squared= 0.429380 | Adjusted R-squared = 0.302576 | Durbin-Watson stat.= 1.8 | ||
Source: Author’s computation with EVIEWS
From the Error Correction Model output presented in table 4.5b, the domestic debt is negative and significant while the external debt is positive insignificant. The value of toatal value of export is positive and significant. The error correction term is negative and statistically significant at the 5% level which according to econometric literature implies that about 99% of any divergence from equilibrium in the short run can be corrected.
4.6 Diagnostics Test
Table 4.6: Diagnostics Test
| Test | F-Statistics | P-value |
| Heteroskedasticity | 0.447833 | 0.8401 |
| Serial correlation LM Test | 0.393594 | 0.5359 |
Source: Author’s computation with EVIEWS
From the table 4.6 above, it is evident that the model formulated and estimated for the study is robust and devoid of heteroskedasticity as well as serial correlation based on the probability values of 0.8401 and 0.5359 respectively which is clearly greater than the 5% level. The null hypothesis of the presence of heteroscedasticity is therefore rejected.
Figure1: Normality Test
The result for the test of normality with the use of Jarque-Bera Statistics is presented in figure1. It shows that the residuals are normally distributed. The observed Jarque-bera statistic is 5.333683with a p-value of 0.069471. Since the p-value is greater than the 5% level of significance, we cannot reject the null hypothesis, so this implies that the residuals are normally distributed.
Figure2: CUSUM
Figure3: CUSUM of Squares
The CUSUM and CUSUMQ test for stability shows that the model formulated for the study is stable as the 5% plot was not exceeded.
5.1 Conclusion
This study examined the impact of public debt and export on the performance of the Nigerian economy. The findings from the study reveals that both external debt and total affects economic growth in Nigeria positively, although external debt was not significant. Domestic debt have a negative and significant effect on the performance of the Nigerian economy.Interest rate have an insignificant positive impact on economic performance in Nigeria. Therefore the study sees the impact of domestic as an important component in Nigeria’s economic performance.Export also have an important implication on economic performance in Nigeria. Implications of these findings are thatgovernments at federal and state levels haveconsistently used borrowed funds to finance recurrent expenditures and have failed to linkborrowing to sustainable capital expenditure items which in the long run could have improved theoverall income profile of the country.
5.2 Recommendations
Based on the findings from the study, the following recommendations are made
Government fiscal policies should aim at funding critical infrastructural facilities and capital projects. This will ensure that the ratio of capital expenditure to fiscal deficit increases to sustainable level.
In the face of dwindling oil price and hence revenue, which is the source of fund for servicing debt, significant investment is urgently needed in agriculture, manufacturing, trade, logistics and tourism to diversify the economy of Nigeria. These sectors if properly explored will invariably create more jobs and increase economic activities that would generate revenue for the government and improve overall economic performance of Nigeria.
There should be commitment on the part of government to reduce costs of governance, cut down overheads and excessive wage bills of political office holders and increase funding for social safety nets programs and invest more on infrastructural development.
The authors declare that they have no conflict of interest
No funding sources
The study was approved by theDelta State University, Abraka, Nigeria.
Oyekanmi, S. October 7, 2022. ‘Nigeria spends 96% of its revenue on debt servicing in 2021, worst on record’. Nairametrics, www.nairametrics.com.
Aliyu, A. (2009). Exchange rate Volatility and Export Trade in Nigeria: An Empirical Investigation, MPRA 13490.
Ogbokor, C., A.& Meyer, D., A. (2016). An Econometric Time Series Analysis of the Dynamic Relationship between Foreign Trade and Economic Growth in a Developing Country: Evidence from Namibia. OEconomica, 12(4), 153-170.
Thirwall, A., P. (2000). Trade Agreements, Trade Liberalisation and Economic Growth: A Selective Survey. African Development Review, 12(2), 129-160.
Adekunle, O. A., Ebere, C., Kamaldeen, F., S.&Bolaji, Y., A. (2018). The relationship between import, export, domestic investment and economic growth in Nigeria. EuroEconomica, 3(7), 149-156.
Christabell, M. (2013). The relationship between public debt and economic growth in Kenya. International Journal of Social Science and Project Paining Management, 1(3), 2-34.
Edeminam, B., V. (2021). Impact of Public Debt on Economic Growth in Nigeria (1990 to 2019): Advances in Economics and Business,9(1), 1-10. DOI: 10.13189/aeb.2021.090101.
Ajayi, I., E. & Edewusi, D., G. (2020). Effect of Public Debt on Economic Growth of Nigeria: An empirical investigation: International Journal of Business and Management Review,8(1), 18-38.
Aladejare, S., A. & Saidi, A. (2014). Determinants of Non-oil Export and Economic Growthin Nigeria: An Application of the Bound Test Approach. Journal for the Advancement of Developing Economies, 3(1), 60-71.https://digitalcommons.unl.edu/jade/4
Omotor, D., G. (2008). The Role of Exports in the Economic Growth of Nigeria: The Bounds Test Analysis. International Journal of Economic Perspectives, 2(3), 222-235.
Udeh, S. N., Ugwu, J. I., & Onwuka, I. O. (2016). External Debt and Economic Growth: The Nigeria experience.European Journal of Accounting Auditing and FinanceResearch, 4(2), 33–48.
Elom-Obed, F. O., Odo, S. I., Elom-Obed, O., & Anoke, C., I.(2017). Public Debt and Economic Growth in Nigeria.Asian Research Journal of Arts & Social Sciences, 4(3),1–16. https://doi.org/10.9734/ARJASS/2017/36095.
Ezenwobi, N., F. & Anisiobi, C., A. (2020). Effect of Government Public Debt on Economic Development in Nigeria. Social Science Research, 2021 7(2), 75-99.
Nwamuo, C. & Agu, S. (2021). Public Debt and Economic Growth: The Nigerian Experience.International Journal of Research and Scientific Innovation (IJRSI), 8(5), 133-141.