Comparing the environmental impacts of nuclear and renewable energy in top 10 nuclear-generating countries: evidence from STIRPAT model.

Abstract

The purpose of this study is to assess the impact of nuclear energy and renewable energy on CO2 emissions in major top 10 nuclear-generating countries based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model from 1993 to 2018. For comparison, the impact of renewable energy on emissions is also examined. For robust checking, four models would be used. The cross-sectional dependence (CD) test reveals the existence of CD in the panel data. Stationary tests indicate the selected variables have no unit root in 1st difference, and cointegration tests confirm the time series data in four multivariable models are long-run cointegrating relationship in each model. Fully modified ordinary least squares (FMOLS) and augmented mean group (AMG) are employed to estimate the long-run coefficients of independent variables, which reveals the positive impacts of variables on emissions. One percent increase in population, economic growth, carbon intensity, and nuclear or renewable energy consumption can lead to 0.984 ~ 1.060%, 1.001 ~ 1.012%, 1.000 ~ 1.011%, 0.009 ~ 0.011%, or 0.003 ~ 0.005% increase in emissions, respectively. Dumitrescu-Hurlin (DH) panel Granger causality test reveals that the causalities between the variables are mixed. Finally, some implications are proposed, such as limiting population quantity and improving the population quality, implementing a green economy, and developing safe nuclear and renewable energy.