Re-examining the relationship between carbon emissions and economic development:An empirical analysis based on adaptive linear models

WANG Ce; XU Jiamin

Abstract：Conducting research on the internal laws and trends of carbon emissions is a basic work for formulating carbon emission reduction policies and achieving high-quality development.In view of the problem that current research mainly uses pre-set quadratic,cubic and other functional forms for empirical regression research,this paper establishes an adaptive linear model and uses panel data from 86 economies in the world from 1960 to 2019 to explore the relationship between per capita carbon dioxide emissions and economic growth.And robustness tests are conducted on issues such as segmentation methods and data sources.In addition,this paper uses the same data to compare and analyze several common different functional forms to verify the superiority of this empirical model.The research conclusions are as follows:First,the baseline regression results show that per capita carbon emissions and per capita GDP are in an inverted U-shaped relationship,and the turning point occurs when per capita GDP is US $ 19,590(PPP,2017).Second,the robustness test results of this paper show that the differences in segmentation methods and data sources do not affect the basic research conclusions of this paper.Third,the comparison of regression results of different functional forms shows that the adaptive linear model of this paper has better model advantages in exploring the relationship between per capita carbon emissions and economic development,and the empirical results of quadratic and cubic functions can verify the basic research conclusions of this paper from the side.