The Nexus between Industrial Production and CO2 Emissions in Oil-Exporting Countries and the Role of Variations in Oil Revenue in the Volatility of the Emissions: Evidence from Nigeria

Abstract

Oil-exporting countries, such as Nigeria, are striving to diversify their economies, hence they engage in several industrial activities that lead to some dimension of CO₂ emissions. However, while several studies have examined CO₂ emissions in such countries, surprisingly, the volatility of the emissions has been overlooked. The volatility of CO₂ emissions points to the fluctuations of the emissions, which generates uncertainty and makes controlling the emissions to be difficult. Oil-revenue variations are a potential channel of the volatility of CO₂ emissions in oil-exporting countries. Therefore, the objective of this paper is to contribute to filling the observed gap in the literature by examining the impact of industrial production on CO₂ emissions in oil-exporting countries, by evaluating the volatility of the emissions, and by investigating the role of oil-revenue variations in the volatility, drawing inferences from Nigeria. Based on data spanning 1990 to 2021, the paper employs the multiplicative heteroscedastic linear regression (MHLR) model for the analysis. The main findings are: (i) Relative to the production of other sectors, such as the agricultural sector, industrial production is the main source of CO₂ emissions in Nigeria. (ii) The emissions demonstrate a statistically significant level of volatility. (iii) The volatility is driven largely by the variations in the country’s oil revenue. (iv) Oil stabilization fund reduces the volatility largely through the channel of oil revenue. These findings imply that fiscal policy instruments that are designed to control oil revenue variations in oil-exporting countries, such as oil stabilization funds and oil-price-based fiscal rules, can also be employed to control CO₂ emissions in the countries by using the instruments to restrain the emissions from fluctuating beyond desired levels.