Driving effect of CO₂ emissions on economic growth—application of empirical likelihood for generalized method of moments

Abstract

In this paper, the panel data of 19 out of 21 APEC members from 1993 to 2018 is selected as a research sample. Firstly, based on the extended Cobb-Douglas production function, the relationship between CO₂ emissions and economic growth is explored via the panel data methods, which fully consider the endogeneity between variables and the unobserved individual heterogeneity. Secondly, to examine the driving effect of CO₂ emissions on economic growth, the Empirical Likelihood for Generalized method of moments with nonparametric estimation characteristics is utilized to calculate the returns on economic scale and the corresponding confidence interval. The results show that CO₂ emissions have a significant positive impact on economic growth. Moreover, the confidence interval of returns to economic scale is very small, indicating current levels of CO₂ emissions have reached the limit to drive economic growth when the technical level, labor employment, capital, urbanization, trade, and other factors tend to stabilize. Finally, some recommendations were presented to achieve sustainable development goals.

Highlights

1. In combination with the extended Cobb-Douglas production function theory, employs 2SLS and GMM method that takes unobserved the heterogeneity between regions and endogeneity between variables in consideration to explore the relationship between CO₂ emissions for economic growth.

2. The extended model of the GMM-Empirical Likelihood for Generalized Moment Method (GMEL) is used to investigate whether the Driving effect of CO₂ emissions on Economic Growth reaching its limit or not?

3. Selected the panel data of APEC countries or regions as the research samples, which has never been studied by scholars.

4. The GMEL is a non-parametric statistical inference method that has higher estimation accuracy than the traditional parametric estimation method.

5. The confidence interval constructed by the GMEL method has the advantages of domain retention, transformation invariance.

Keywords:

• CO₂ emissions
• Economic scale
• Empirical likelihood confidence interval
• Generalized method of moments
• Nonparametric estimation

2010 MR SUBJECT CLASSIFICATION:

• 62F25
• 62J05
• 62P20

Acknowledgments

The authors are deeply thankful to the editor and reviewers for their valuable suggestions to improve the quality of this manuscript.

Additional information

Funding

This study was supported by the National Social Science Foundation of China (16BGL033); National Natural Science Foundation of China (11201088).