Over the past few years the use of natural gas, which is a vital energy resource due to its usefulness as an essential input for productionhasincreased considerably in many economies around the world. According to EIA, [1] natural gasconsumptionas a percentage of total energy consumption hasincreased from 21 per cent in 1990 to 23 per cent in 2007: and it is expected to grow at 18per cent annually between 2007 and 2035. Currently, because of its efficiency in reducing carbon dioxide (CO₂) emissions and minimizing capital costs, natural gas isconsidered as an attractive alternative. This has made many countries to explore the option for increasing the use of natural gas as an alternative energy source that generates relatively less CO₂emissions compared to other fossil fuels [2-3].

The need to provide alternative and clean energy source to meet the needs of the Organization for Economic Cooperation and Development (OECD) countries and emerging economies is responsible for the growing interest in natural gas globally. Despite the issues security of crude oil supply brought about by the frequent change in international oil price for crude oil, the slow growth ofrenewable energy technology in Africa implies that the continuous dominanceof oil and gas resources in the region is still in sight [4]. As opined by Odumugbo, naturalgas is rapidly gaining more importance in the global energy market due to its inherent qualities as an efficient energy source. Several reasons have accounted for the ever increasing dependence on natural gas, including an abundant resource base which makes up the supply side of the economy: growing energy demand from an expanding world economy constituting the demand side: environmental pressures for the use of gas which is a relative clean fuel in comparison to oil or coal: improved technologies for the production, transportation and conversion of natural gas.

Federal ministry of power in 2017 admits that, of the total electricity generation in Nigeria, natural gas source account for about 74% and thispercentage is expected to increase by 7% in 2030. Therefore, improved naturalgas development and production is expected to improve electricity generationin Nigeria. Natural gas utilization reduces gas flaring, provides more jobopportunities, improves the welfare of the citizens, and enhances productivity in the energy sector of the economy [4]. What then is the impact of natural gas on Nigeria’s economic growth? This therefore underscore the importance of embarking on this study to unravel the importance of natural gas to the economic growth in Nigeria. Furthermore, the study aims to investigate if there are significant impact from shocks in natural gas supply on the Nigerian economy. More so, the check for the existence of a long run relationship between natural gas and economic growth in Nigeria will also be considered. 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.

Literature Review

Conceptual Issues

Natural Gas: Natural Gas has unique Qualities which makes it have variety of Applications as Premium Fuel as well as Feedstock in many Industrial and Domestic Settings World over. It is a Veritable Partner for Heating, Locomotion and Luminosity. Considering the importance of this Natural Resource, enough progress has not been made in its Development and Utilization in the Country. Nigeria has proven Reserves in excess of 187 Trillion Square Cubic Feet (SCF) according to the Department of Petroleum Resources (DPR) with a potential for New Discoveries in the neighborhood of 75 Trillion SCF. 56% of these Reserves exist in Association with Crude Oil, while 44% exist alone [5]. The Production of Gas entails very Complex Processes. As earlier mentioned Gas are exploited alone or in Association with Crude Oil. The Production Process are almost similar, just that in Gas Alone Exploitation and Production, additional Safety measures are required because of the behavior of some Wells, in some cases up to 4000 Pressure per Square inch (psi), which is highly volatile, requiring “Kill-Tools” to prevent Blow-out. Also, Gas Exploitation involves higher Throughput requiring larger diameter of Pipes and higher Schedule [6].

Economic Growth

A major goal of poor countries is economic development or economic growth. The two terms are not identical. Growth may be necessary but not sufficient for development. Economic growthrefers to increases in a country’s production or income per capita. Production is usually measured by gross national product(GNP) or gross national income(GNI), used interchangeably, an economy’s total output of goods and services. Economic developmentrefers to economic growth accompanied by changes in output distribution and economic structure. These changes may include an improvement in the material well-being of the poorer half of the population; a decline in agriculture’s share of GNP and a corresponding increase in the GNP share of industry and services; an increase in the education and skills of the labor force: and substantial technical advances originating within the country. As with children, growth involves a stress on quantitative measures (height or GNP), whereas development draws attention to changes in capacities (such as physical coordination and learning ability, or the economy’s ability to adapt to shifts in tastes and technology).

Gas Utilization

Gas utilization is the marketing and distribution of natural gas for the sole purpose of commercialization and activities surrounding this includes power plant, liquefied natural gas, gas to liquid plant, fertilizer plant, gas transmission and distribution pipelines. Gas utilization involves activities that revolve around marketing, and distribution of natural gas for commercial purposes. Natural gas utilizationas the activities that revolve around the refining, processing, marketing and distribution of natural gas for commercial purposes such as power plant, liquefied natural gas, Etc. Natural gas utilization is measured as the quantity of natural gas consumed annually in the country. This includes sales, re-injection/lift and fuel.

Empirical Review

Farhani et al. [7] examined the impact of natural gas consumption, real gross fixed capital formation and trade on the real GDP in case of Tunisia over the period 1980 to 2010using an ARDL bounds testing approach to test for cointegration between the variables. The Toda–Yamamoto approach was then used to test for causality. The findings of this paper also confirmed the presence of feedback effect between natural gas consumption and economic growth similar to Ishioro [8,2].

Shahbaz et al. [9] explored the relationship between natural gas consumption and economic growth in Pakistan for the quarterly data period of 1972q1–2011q4using the ARDL bound testing approach. Their findings showed that economic growth is a cause of natural gas consumption and, in turn, natural gas consumption is also a cause of economic growth in Granger sense.

Onolehemhen et al. suggests that domestic utilization of natural gas in Nigeria is slowed down due to poor investment in the sector in the past years which they attributed to poor electricity generation, in adequate infrastructure, poor commercial and regulatory framework in the Nigerian natural gas sector as compared with the crude oil sector. They studied the determinants of natural gas domestic utilization in Nigeria from 1990 to 2013, using econometric method by considering the impact of natural gas price, price of other energy source, foreign direct investment, electricity generation from natural gas, volume of gas flared and per capita real GDP. The result of their study showed that real GDP per capita, electricity generation from natural gas and changes in the flared volume hadpositive and significant effect on domestic utilization of natural gas.

Solarin and Shahbaz [10] reinvestigated the relationship between natural gas consumption and economic growth by including foreign direct investment, capital and trade openness in Malaysia for the period of 1971–2012 using an ARDL bounds testing method in the presence of structural breaks. Their results support the presence of feedback hypothesis between natural gas consumption and economic growth. In the sameline, Destek [11] explored the relationship between natural gas consumption and economic growth in 26 OECD countries within a multivariate production model, including capital and trade openness from 1991 to 2013. Their results showed that natural gas consumption positively affected GDP growth in the long run. Furthermore, the long-run VECM Granger causality test revealed bidirectional causality between natural gas consumption and economic growth, which confirms the feedback hypothesis.

Nwabueze et al. [4] investigates the relationship between natural gas consumption, natural gas price, crude oil price, foreign direct Investment and per capita GDP in Nigeria to ascertain their causal effects and dependencies by using time series data from 1990 to 2020 in an econometric platform using Vector Error Correction model (VECM). The result of VECM estimate, Granger causality test and Variance decomposition test all suggest the presence of a strong positive correlation between natural gas consumption and economic growth (represented by per capita GDP) in Nigeria, even though the price of natural gas is not consumption determined.

Hussain and Rehman, [12] examined the effect of CO2 emission on foreign investment, renewable energy utilization, and population growth in Pakistan. The ARDL bounds testing technique was applied on data from 1975 to 2019 to investigate the variables’interaction via short- and long-run analysis. Furthermore, pairwise Granger causality method was also utilized to check the causal relation amid the study variables. Outcomes expose that CO2 emission has an adverse interaction with renewable energy with probability value, while the variable foreign investment and population growth exposed a constructive association with carbon dioxide emission. Similarly, the results through long-run analysis expose that CO2 emission has an adverse influence to renewable energy. Moreover, the results also uncovered that foreign investment and population growth has positive interaction with CO2 emission. Solid steps are required from the Pakistani government regarding the demonization ofCO2 emission in order to upsurge the economic progress.

Hasan and Raza, investigated the nexus between natural gas consumption (NGC), economic growth (EG), urban population, unemployment, and services value-added in Bangladesh during 1990 to 2019. They used the ARDL bounds and vector error correction models to estimate the impacts of NGC on key economic factors to approximate the short and long-runcointegration bond. They found that economic growth, natural gas consumption, unemployment, urban population, and service value-added are all cointegrated in both short and long-term interactions, which mean that gas consumption causes economic growth. NGC and EG have a bidirectional link, according to the findings on causality break down. They therefore opined that to regulate both NGC and other factors could help Bangladesh’s prospects for achieving development goal under Vision-2041 over future.

Li et al. [13] researched on dynamic relationship between natural gas consumption and economic growth in China using panel data from 30 provinces from 2000 to 2014 estimated through panel quantile regression. The panel quantile results proved that the higher level of economy, the greater the marginal effect of natural gas is on economic growth; then considering the different economy scale of provinces, the panel data is divided into three groups, the results have drawn the same conclusion. Thus, measures to develop natural gas and reform gas market have been put forward, including deepening market-oriented reform of natural gas system, perfecting the construction and management of pipeline transportation and encouraging the consumption of natural gas.

Farhani and Rahman, [14] investigated the relationship between natural gas consumption and economic growth of France using data from 1990 to 2014 estimated with auto-regressive distributive lag bounds testing approach is applied to test the existence of the long-run relationship between the series. The vector error correction model Granger causality approach is implemented to detect the direction of causal relation between the variables. They found that variables are cointegrated for the long-run relationship. Also natural gas consumption, exports, capital and labor are the contributing factors to economic growth in France. The causality analysis indicates that feedback hypothesis is validated between gas consumption and economic growth.

Data and Model Specification

The ex-post facto design will be used in this study because it is descriptive and quantitative in nature. Historical data will be adopted for analyzing the model to be specified for the study. The data for the study will be collected from the Annual time series data from 1980 to 2021 have been obtained from the World Development Indicators (WDI) World Bank online database and NNPC Annual Statistical Bulletin, 2021. The study investigates the relationship between natural gas and economic growth in Nigeria by using the Cobb–Douglas production function akin to Ishioro [2]. The study follows the methodological framework of Shahbaz et al. [15], Ishioro [16-22,8], Alam et al. [23] and Farhani and Rahman [14] to construct the production function with some modifications. The general functional form of the model is given as:

GDP_t = f(NGU_t, NGF_t, GCF_t, FDI_t)

(1)

The econometric specification of the model is given as:

GDP_t = β₀+β₁NGU_t+β₂NGF_t+β₃GCF_t+β₄FDI_t+e_t                                                                   (2)

Where:

GDP is Gross Domestic Product at Current Basic Prices (₦' Billion), NGP is Natural gas utilization (Million Cubic Feet), NGF is Natural gas flared (Million Cubic Feet), GCF is Gross capital formation (constant 2015 US$) and FDI (% of GDP).

β₀is the constant term, β₁, β₂, β₃ and β₄ are the parameters to be estimated, e_t 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

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:

The descriptive statistics from Table1 above will be discussed briefly. The variables of the study are analysed to show their features. The LGDP which is the dependent variable has a mean value of 8.609688which represent an average of N8.609688 billion. Natural gas utilization (LNGU) has a mean of 12.34091which implies as an average of 12.34091mcf of gas is utilized in Nigeria. Natural gas flared (LNGF) have an average value of 14.44335mcf, Gross capital formation (GCF) have a mean of $6.09million while FDI have a mean value of 1.435467. The median value of LGDP was N8.852324billion, that of LNGU, LNGF, LGCF and FDI are 12.24702mcf, 14.67284mcf, $5.80million and1.093559 respectively. LGDP have a maximum and minimum value of N11.93377billion and N4.854270billion respectively. The maximum and minimum values of LNGU are 13.41128mcf and 10.54534mcf respectively which shows that the natural gas utilized rose to about 13.4mcf with the least been about 11mcf during the study period. The maximum and minimum values of the LNGF are 14.90469mcf and 13.73014mcf respectively, which is the least and the highest is level of gas flared for the study period. From the information on the maximum and minimum values above LGCF has the highest at $1.09million and the least value at $3.90thousand which clearly shows that the amount gross capital formation has been growing over the years. The maximum and minimum values of FDI are 5.790847 and -1.150856.

The standard deviation shows how the data used in the study spreads around the mean. For LGDP, it was N2.452759billion that of LNGU is 0.738397mcf, LNGF stood at 0.426809mcf signifying about 0.43million cubic feet of gas was flared deviations from the mean amount. LGCF with $1.43million signifies the spread in the gross capital formation, and FDI stood at 1.297427.

Table 1: Summary Statistics

Source: Author’s computation with Eviews

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

The Prob. values are given in parenthesis. The above Table 2 contains the correlation matrix, all the independent variables, LNGU, LNGF and LGCF have a statistically significant relationship with LGDP, FDI though is not significant. LNGU, LNGF and FDI displayed a very strong correlation with the dependent variable. LGCF have a weak correlation with the dependent variable. There exists a strong positive correlation between LNGF and LNGU. The correlation between LGCF and LNGU is positive, weak and insignificant, although LGCF has a positive and significant relationship with LNGF though their correlation is very weak. FDI have a weak negative correlation with LGCF.

Table 2: Correlation Matrix Results

Source: Author’s computation with EVIEWS

Model Estimation

In this section we proceed with the estimation of the model for the study. In doing this we conduct the unit root test, then we proceed with the cointegration test, thereafter we estimate the parameters

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;

The result of the Augmented Dickey Fuller test is presented in Table 3 above. From the result it can be observed that all the variables except foreign direct investment (FDI) are stationary at the first difference that is they are integrated at order one I 1. FDIis 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 [19]. The next step is to check for the existence of long run relationship among the variables using the ARDL Bounds test to cointegration technique.

Table 3: Adf Unit Root Test Result

Source: Author’s computation with EVIEWS

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 was 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:

• H₀: No long-run Relationship Exist

• H₁: Long-run Relationship Exist

The ARDL Long Run Form and Bounds Test is presented above in Table 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 6.844333 is greater than the upper bound at the 1% significance level 5.06. Thus we can infer that there exists a long run relationship among LGDP, LNGU, LNGF, LGCF and LFDI at the 1% 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.

Table 4: ARDL-Long Run Form and bound test

Source: Author’s computation with EVIEWS

Autoregressive Distributed Lag Model

The study used the Autoregressive Distributed Lag (ARDL)-Bound Test to cointegration proposed by Pesaran et al. [24] and applied by Ishioro [16-17,19], and the Error correction modelling approach to investigate the short run and long run impact of the independent variables on the dependent variable. The ARDL modelling approach has a number of advantages among which are that it can be applied to data series that are of mixed order of integration and it’s quite efficient for small and finite sample size.

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 (ᵧECT_t-1), which measures the speed of adjustment of economic growth to its equilibrium level.

We therefore proceed to estimate both the long run and short run model using the ARDL approach. The results are presented below.

The long run model estimation result is presented in Table 5 above. From the output of the OLS estimates, it can be observed that the constant term has a negative and insignificant relationship with the dependent variable (LGDP), it has an indirect impact on LGDP which implies that a when all the independent variables are held constant LGDPreduces by-4.748940. The lagged value of LGDP has a significant positive impact on the dependent variable (LGDP), there is also a direct impact on LGDP from it as a one-unit increase in it will cause LGDP to increase by 0.932254. There exists a positive insignificant relationship between LNGU and the dependent variable. LNGU have a direct impact on LGDP as a one percent increase in it will lead to increase LGDP by 0.099438. LNGF on the other hand has aninsignificant positive relationship with LGDP, the direct impact indicates that a one percent rise in LNGF increases LGDP by 0.147966. LGCF has positive and insignificant relationship with the dependent variable, it has a direct impact on LGDP which implies that a one percent increase in LGCF will increase LGDP by 0.225114, although its lagged value has an insignificant negative impact on LGDP. FDI on the other hand has a positive insignificant relationship with LGDP, although its lagged value has a significant positive impact on LGDP which means that a 1% increase in previous period FDI inflow will increase LGDP by 0.050643.

Table 5: Long run Model Result

From the Prob (F-statistic) value there exist a joint significance at the 1% level, there is no autocorrelation from the Durbin-Watson stat of approximately 2. 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 0.998799 suggests that about 99% of the systematic variations in Gross domestic product can be explained by natural gas utilization, natural gas flared, gross capital formation and foreign direct investment. The residual from the long run model (ect) is use to estimate the short run model.

The short run model estimation result is presented in Table 6 above. From the output of the OLS estimates, the error correction term (ECM) is negative and significant which is in line with econometric theory. This implies that last period deviation from equilibrium, is corrected by about 1.064129. It can be observed also that the constant term has a negative and insignificant relationship with the dependent variable (LGDP), it has an indirect impact on LGDP which implies that a when all the independent variables are held constant LGDP reduces by -0.012009. The lagged value of LGDP has a significant positive impact on the dependent variable (LGDP), there is also a direct impact on LGDP from it as a one-unit increase in it will cause LGDP to increase by 0.998822. There exists a positive significant relationship between LNGU and the dependent variable. LNGU have a direct impact on LGDP as a one percent increase in it will lead to increase LGDP by 0.118154. LNGF on the other hand has an insignificant positive relationship with LGDP, the direct impact indicates that a one percent rise in LNGF increases LGDP by 0.165007. LGCF has positive and significant relationship with the dependent variable, it has a direct impact on LGDP which implies that a one percent increase in LGCF will increase LGDP by 0.183678, although its lagged value has an insignificant negative impact on LGDP. FDI on the other hand has a positive insignificant relationship with LGDP, although its lagged value has a significant positive impact on LGDP which means that a 1% increase in previous period FDI inflow will increase LGDP by 0.038026.

From the Prob (F-statistic) value there exist a joint significance at the 1% level, there is no autocorrelation from the Durbin-Watson stat of approximately 2. 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 0.497877 suggests that about 50% of the systematic variations in Gross domestic product can be explained by natural gas utilization, natural gas flared, gross capital formation and foreign direct investment.

Table 6: Short Run Model Result

Source: Author’s computation with EVIEWS

Diagnostic Tests

The diagnostic test is used to evaluate the assumptions of the OLS of the classical ordinary least square. The serial correlation test is done to ascertain if the model has auto-correlation. The null hypothesis is that the series has no serial correlation. If the prob. Value is less 0.05 we reject the null hypothesis but is the prob. Value is greater than 0.05 we accept the null hypothesis. From Table 7, the prob. value of 0.9045 is greater than 0.05, there we accept the null hypothesis that the series has no serial correlation. The Breusch-Pagan-Godfrey heteroskedasticity test is presented in Table 8. From the result, we can observe that the prob. value of 0.5682 is clearly greater than 0.05 hence we accept the null hypothesis that there is no heteroskedasticity in the residual hence it is Homoskedastic. Also from the normality test presented in Figure 1 below, we can infer that the residual term is normally distributed based on the Jarque-Bera prob. value of 0.358137.

Figure 1: Normality Test

Source: Author’s computation with EVIEWS

Table 7: Breusch-Godfrey Serial Correlation Lm Test

Source: Author’s computation with EVIEWS

Table 8: Heteroskedasticity Test: Breusch-Pagan-Godfrey 

Source: Author’s computation with EVIEWS

This study examined the impact of natural gas and economic growth in Nigeria. The findings from the study reveal that both natural gas utilization and natural gas flared gross capital formation affects economic growth in Nigeria negatively. Foreign direct investment also has a significant and positive impact on economic growth in Nigeria. Therefore, the study sees the impact of natural gas as an important component in Nigeria’s economic growth, by ensuring that natural gas is efficiently utilized. Based on the findings, there is need for the government to initiate policies and reforms that can improve the petroleum sector in Nigeria. As well as encourage investment in the sector.

Based on the findings from the study, the following recommendations are made:

• The government should increase the investment in petroleum sector in order to ensure that the natural gas is utilized

• Gas flaring should be discouraged through policies aimed at mitigating it

• Government should create an enabling environmentfor businesses in order to attract foreign direct investment especially in the petroleum sector due to its capital intensive nature

1. EIA. International energy outlook 2010. Energy Information Administration, 2010, Washington, DC.

2. Ishioro B.O. “Energy consumption and economic growth in Nigeria: An augmented neoclassical growth model perspective.” Journal of Environmental Management and Tourism, vol. 10, no. 7, 2019, pp. 1637–1657.

3. Apergis N. and J.E. Payne. “Natural gas consumption and economic growth: A panel investigation of 67 countries.” Applied Energy, vol. 87, no. 8, 2010, pp. 2759–2763.

4. Nwabueze G. et al. “Analysis of Nigerian natural gas consumption (1990–2020): A vector error correction model approach.” International Journal of Engineering Technologies and Management Research, vol. 9, no. 1, 2022, pp. 7–19.

5. Eko-Raphaels M.U. et al. “Natural gas logistics, utilization and impact on Nigeria’s economic health: A simple empirics.” International Journal of Innovative Finance and Economics Research, vol. 10, no. 3, 2022, pp. 98–105.

6. Barnes J. et al. Introduction to natural gas and geopolitics from 1970 to 2040. Cambridge University Press, 2006.

7. Farhani S. et al. “The role of natural gas consumption and trade in Tunisia’s output.” Energy Policy, vol. 66, 2014, pp. 677–684.

8. Ishioro B.O. “Energy consumption and performance of sectoral outputs: Evidence from an energy-impoverished economy.” Journal of Environmental Management and Tourism, vol. 9, no. 7, 2018, pp. 1539–1558.

9. Shahbaz M. et al. “Short- and long-run relationships between natural gas consumption and economic growth: Evidence from Pakistan.” Economic Modelling, vol. 41, 2014, pp. 219–226.

10. Solarin S.A. and M. Shahbaz. “Natural gas consumption and economic growth: The role of foreign direct investment, capital formation and trade openness in Malaysia.” Renewable and Sustainable Energy Reviews, vol. 42, 2015, pp. 835–845.

11. Destek M.A. “Natural gas consumption and economic growth: Panel evidence from OECD countries.” Energy, vol. 114, 2016, pp. 1007–1015.

12. Hussain I. and A. Rehman. “Exploring the dynamic interaction of CO₂ emissions, population growth, foreign investment and renewable energy using ARDL bounds testing.” Environmental Science and Pollution Research, March 2021, pp. 1–12.

13. Li Z.G. et al. “Research on dynamic relationship between natural gas consumption and economic growth in China.” Structural Change and Economic Dynamics, 2018.

14. Farhani S. and M.M. Rahman. “Natural gas consumption and economic growth nexus: An investigation for France.” International Journal of Energy Sector Management, vol. 14, no. 2, 2020, pp. 261–284.

15. Shahbaz M. et al. “Natural gas consumption and economic growth in Pakistan.” Renewable and Sustainable Energy Reviews, vol. 18, 2013, pp. 87–94.

16. Ishioro B.O. “Intertemporal optimization of the consumption of petroleum stock: Empirical evidence from Nigeria.” Journal of Academic Research in Economics, vol. 7, no. 2, 2015, pp. 232–255.

17. Ishioro B.O. “The long-run relationship between foreign reserves inflows and domestic credit: Evidence from a small open economy.” Oeconomica, vol. 11, no. 2, 2015, pp. 18–41.

18. Ishioro B.O. “HIV/AIDS and macroeconomic performance: Empirical evidence from Kenya.” Scientific Papers of the University of Pardubice, Series D, vol. 23, no. 36, 2016, pp. 102–117.

19. Ishioro B.O. “Banking sector reforms and economic growth: Recent evidence from a reform-bound economy.” Binus Business Review, vol. 8, no. 1, 2017, pp. 46–60.

20. Ishioro B.O. “Crude oil and economic growth in Nigeria: A simplified pair-wise causality test.” Journal of Academic Research in Economics, vol. 12, no. 2, 2020, pp. 224–246.

21. Ishioro B.O. “Financial market inclusion, shadow economy and economic growth paradigm: A less developed country perspective.” Scientific Papers of the University of Pardubice, Series D, vol. 28, no. 1, 2020, pp. 67–78.

22. Ishioro B.O. “Dynamic effects of health expenditure shocks on HIV prevalence in Sub-Saharan Africa.” Journal of Academic Research in Economics, vol. 14, no. 3, November 2022.

23. Alam M.S. et al. “Natural gas, trade and sustainable growth: Empirical evidence from the top gas consumers of the developing world.” Applied Economics, vol. 49, no. 7, 2017, pp. 635–649.

24. Pesaran M.H. et al. “Bounds testing approaches to the analysis of level relationships.” Journal of Applied Econometrics, vol. 16, no. 3, 2001, pp. 289–326.