Abstract
Given the dominant role of oil in terms of foreign exchange earnings in Nigeria, this study revisits the oil rents and output growth nexus, using the novel dynamic autoregressive distributive lag (DYNARDL) model and kernel-based regularized least squares (KRLS) approach over the period 1973–2020. The major finding from this study is that oil rents are less significant for output and also exhibit decreasing marginal effect on output growth in Nigeria. However, our robustness result shows that oil revenue is positive and significantly affects output growth, while corruption dampens output growth. Result from the oil revenue model with a minimum root square mean error, when compared with the oil rents model, corroborate the finding. We are thus of the opinion that oil revenue is more important for output growth in Nigeria than oil rents. Having established this fact, it is recommended that policymakers and the government should accord utmost attention to boosting oil revenue via transparency and accountability. They should also ensure a lasting solution to the nation’s high dependency on refined crude oil products importation for a sustainable economic growth and development. Also, more efforts should be directed at developing the seven identified strategic solid minerals to further enhance the revenue base of the government.
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Source: Authors’ compilation from data obtained from the World Bank
Source: Authors’ compilation from data obtained from the CBN (2019)
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As discussed in text.
Notes
− 6.10 and − 3.62 GDP growth rate in 2020Q2 and 2020Q3, respectively.
The choice of the timeframe was governed by data availability.
Detailed description of the model is provided in Sarkodie and Owusu (2020).
Utilizing several unit root tests such as Phillips and Perron (1988), augmented Dickey and Fuller (1979), and Kwiatkowski et al. (1992), we discover a mixture of level and first difference outcomes. However, the condition that the dependent variable must be strictly I(1) required by dynamic ARDL is satisfied. The results are available upon reasonable request.
Natural logarithms (LNRGDP) RGDP is the dependent variable, and is stationary at first-difference.
With over 100% convergence (obtained by multiplying 0.019 by 100).
We fail to reject the null hypothesis of no serial correlation based on 5% significance level, hence confirming that the residuals of the estimated ARDL (1,0,0,0) model are free from autocorrelation.
The null hypothesis of homoscedasticity cannot be rejected at 5% significance level, thus confirming that the residuals are homoscedastic.
The null hypothesis of normal distribution cannot be rejected at 5% significance level.
It shows that the estimated test statistic is within the 95% confidence band, hence confirming the stability of the estimated coefficients over time.
This means the unbeneficial impact of corruption in the economy.
This is based on the DYNARDL and KRLS.
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Abubakar, I.S., Akadiri, S.S. Revisiting oil rents-output growth nexus in Nigeria: evidence from dynamic autoregressive distributive lag model and kernel-based regularized least squares approach. Environ Sci Pollut Res 29, 45461–45473 (2022). https://doi.org/10.1007/s11356-022-19034-z
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DOI: https://doi.org/10.1007/s11356-022-19034-z