Abstract

Conventional panel models that overlook nonlinearity, nonstationarity, heterogeneity and cross-sectional dependency when analysing the energy-growth nexus might produce misleading conclusions. In addressing these issues, this study extends the examination of the nexus by applying nonstationary panel models with common correlated effects (CCE). They involve two estimators, namely CCE mean group (CCEMG) and augmented mean group (AMG) estimators. The main objective is to examine the effects of total and renewable energy consumption on the gross domestic product (GDP) by comparing the top oil-importing and top oil-exporting countries. The datasets are in annual frequency, ranging from 1992 to 2015. The results are compared to ordinary least squares (OLS)-type models that serve as benchmarks. This study innovates the models by incorporating the asymmetric effects of energy consumption into the estimations. The findings reveal a positive correlation between total energy consumption and GDP for both panel groups, and capital input is one of the determinants in all cases. The results disclose evidence of the asymmetric effects of total and renewable energy consumption. The positive impact of total/renewable energy consumption decreases for the top oil-exporting group is more apparent than its increases, signifying the importance of energy conservation. For top oil-importing nations, increased renewable energy consumption impedes the GDP, but the increase in total energy consumption accelerates it. Energy efficiency policies should be implemented in oil-importing countries since the positive impact of total energy consumption is smaller than in the other group.

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