KLASMOE & School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China.
Department of Social Sciences, Education University of Hong Kong, Hong Kong 999077, China.
Int J Environ Res Public Health. 2019 Oct 29;16(21):4176. doi: 10.3390/ijerph16214176.
Most authors apply the Granger causality-VECM (vector error correction model), and Toda-Yamamoto procedures to investigate the relationships among fossil fuel consumption, CO emissions, and economic growth, though they ignore the group joint effects and nonlinear behaviour among the variables. In order to circumvent the limitations and bridge the gap in the literature, this paper combines cointegration and linear and nonlinear Granger causality in multivariate settings to investigate the long-run equilibrium, short-run impact, and dynamic causality relationships among economic growth, CO emissions, and fossil fuel consumption in China from 1965-2016. Using the combination of the newly developed econometric techniques, we obtain many novel empirical findings that are useful for policy makers. For example, cointegration and causality analysis imply that increasing CO emissions not only leads to immediate economic growth, but also future economic growth, both linearly and nonlinearly. In addition, the findings from cointegration and causality analysis in multivariate settings do not support the argument that reducing CO emissions and/or fossil fuel consumption does not lead to a slowdown in economic growth in China. The novel empirical findings are useful for policy makers in relation to fossil fuel consumption, CO emissions, and economic growth. Using the novel findings, governments can make better decisions regarding energy conservation and emission reductions policies without undermining the pace of economic growth in the long run.
大多数作者应用格兰杰因果关系-VECM（向量误差修正模型）和 Toda-Yamamoto 程序来研究化石燃料消耗、CO2 排放和经济增长之间的关系，尽管他们忽略了变量之间的群体联合效应和非线性行为。为了规避这些限制并弥补文献中的差距，本文结合协整和多元环境下的线性和非线性格兰杰因果关系，研究了 1965-2016 年中国经济增长、CO2 排放和化石燃料消耗之间的长期均衡、短期影响和动态因果关系。利用新发展的计量经济学技术的组合，我们得出了许多新的经验发现，这些发现对政策制定者很有用。例如，协整和因果关系分析表明，CO2 排放的增加不仅会导致当前的经济增长，而且还会导致未来的经济增长，无论是线性的还是非线性的。此外，多元环境下的协整和因果关系分析的结果不支持这样一种观点，即减少 CO2 排放和/或化石燃料消耗不会导致中国经济增长放缓。这些新的经验发现对政策制定者在化石燃料消耗、CO2 排放和经济增长方面很有用。利用这些新发现，政府可以在不破坏长期经济增长速度的情况下，就能源节约和减排政策做出更好的决策。
