Effects of Energy Consumption, Agricultural Trade, and Productivity on Carbon Emissions in Nigeria: A Quantile Regression Approach
The focus of this investigation was to examine the effects of energy consumption, agricultural commerce, and productivity on CO<sub>2</sub> emissions in Nigeria using quantile regression. Time series data from 1960 to 2021 were used. The findings revealed that the impact of agricultural...
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MDPI AG
2024-12-01
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| author | Prosper E. Edoja Goodness C. Aye Rangan Gupta |
| author_facet | Prosper E. Edoja Goodness C. Aye Rangan Gupta |
| author_sort | Prosper E. Edoja |
| collection | DOAJ |
| description | The focus of this investigation was to examine the effects of energy consumption, agricultural commerce, and productivity on CO<sub>2</sub> emissions in Nigeria using quantile regression. Time series data from 1960 to 2021 were used. The findings revealed that the impact of agricultural raw materials imports (AGRIMs) and exports on carbon footprints is positive. There is a prevalence of a set of notable percentile differences in the conditional distribution of the variables on CO<sub>2</sub> emissions. Initially, the coefficient of energy consumption (EnCons) was high, but constantly nosedived from the 25th quantile until it reached the 90th quantile when it picked up again, and the same was true in the case of AGRIM. Thus, a 1% increase in agricultural imports will bring about 0.0047—a significant unit increase in CO<sub>2</sub> emissions in Nigeria from the 0.382946 coefficient in the 10th quantile to the 0.264392 coefficient in the 50th quantile, and thereafter, the effects become insignificant. Profound significant variance across disparate percentiles in the conditional spread of AGRIM, food production index (FPI), CPI, and FDI was found. It further showed that the effects of the regressors on carbon emissions differ over the quantiles. Overall, AGRIM and EnCons have positive and significant effects on carbon emission. However, the agricultural raw material export has significant negative effects on CO<sub>2</sub> emissions as the movement (transportation) of goods within a country prior to export involves a huge level of carbon release. This study provides recommendations and policy implications. |
| format | Article |
| id | doaj-art-a105da893119416fb0b51149a161a120 |
| institution | Kabale University |
| issn | 2813-2432 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Commodities |
| spelling | doaj-art-a105da893119416fb0b51149a161a1202024-12-27T14:18:52ZengMDPI AGCommodities2813-24322024-12-013449451110.3390/commodities3040028Effects of Energy Consumption, Agricultural Trade, and Productivity on Carbon Emissions in Nigeria: A Quantile Regression ApproachProsper E. Edoja0Goodness C. Aye1Rangan Gupta2Department of Agricultural Economics, Faculty of Agriculture, Delta State University, Abraka 330105, NigeriaDepartment of Agricultural Economics, Joseph Sarwarn Tarka University, Makurdi 970001, NigeriaDepartment of Economics, University of Pretoria, Hatfield 0028, South AfricaThe focus of this investigation was to examine the effects of energy consumption, agricultural commerce, and productivity on CO<sub>2</sub> emissions in Nigeria using quantile regression. Time series data from 1960 to 2021 were used. The findings revealed that the impact of agricultural raw materials imports (AGRIMs) and exports on carbon footprints is positive. There is a prevalence of a set of notable percentile differences in the conditional distribution of the variables on CO<sub>2</sub> emissions. Initially, the coefficient of energy consumption (EnCons) was high, but constantly nosedived from the 25th quantile until it reached the 90th quantile when it picked up again, and the same was true in the case of AGRIM. Thus, a 1% increase in agricultural imports will bring about 0.0047—a significant unit increase in CO<sub>2</sub> emissions in Nigeria from the 0.382946 coefficient in the 10th quantile to the 0.264392 coefficient in the 50th quantile, and thereafter, the effects become insignificant. Profound significant variance across disparate percentiles in the conditional spread of AGRIM, food production index (FPI), CPI, and FDI was found. It further showed that the effects of the regressors on carbon emissions differ over the quantiles. Overall, AGRIM and EnCons have positive and significant effects on carbon emission. However, the agricultural raw material export has significant negative effects on CO<sub>2</sub> emissions as the movement (transportation) of goods within a country prior to export involves a huge level of carbon release. This study provides recommendations and policy implications.https://www.mdpi.com/2813-2432/3/4/28agricultural commodity tradeCO<sub>2</sub> emissionenergy consumptionquantile regression |
| spellingShingle | Prosper E. Edoja Goodness C. Aye Rangan Gupta Effects of Energy Consumption, Agricultural Trade, and Productivity on Carbon Emissions in Nigeria: A Quantile Regression Approach Commodities agricultural commodity trade CO<sub>2</sub> emission energy consumption quantile regression |
| title | Effects of Energy Consumption, Agricultural Trade, and Productivity on Carbon Emissions in Nigeria: A Quantile Regression Approach |
| title_full | Effects of Energy Consumption, Agricultural Trade, and Productivity on Carbon Emissions in Nigeria: A Quantile Regression Approach |
| title_fullStr | Effects of Energy Consumption, Agricultural Trade, and Productivity on Carbon Emissions in Nigeria: A Quantile Regression Approach |
| title_full_unstemmed | Effects of Energy Consumption, Agricultural Trade, and Productivity on Carbon Emissions in Nigeria: A Quantile Regression Approach |
| title_short | Effects of Energy Consumption, Agricultural Trade, and Productivity on Carbon Emissions in Nigeria: A Quantile Regression Approach |
| title_sort | effects of energy consumption agricultural trade and productivity on carbon emissions in nigeria a quantile regression approach |
| topic | agricultural commodity trade CO<sub>2</sub> emission energy consumption quantile regression |
| url | https://www.mdpi.com/2813-2432/3/4/28 |
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