Abstract
This paper analyzes the time-varying impacts of Chinaʼs economic growth, energy efficiency, and industrial development on carbon dioxide (CO2) emissions from 1970 to 2019. First, we examined and found that there are two significant structural changes in the CO2 sequence over the years, and there was a significant nonlinear relationship among the four. The first nonlinear structural model constructed is the TVP regression model. According to the Bayesian model comparison criterion, TVP-SV-VAR was selected as the second constructed model from four types of VAR models containing nonlinear structures. The results show that the conduction intensity value of energy use efficiency to CO2 emissions has increased year by year, from 0.45 in 1971 to 0.97 in 2019. The short-term transmission mechanism of energy use efficiency to carbon emissions is the most significant. The conduction intensity of Chinaʼs economic growth on CO2 emissions increases year by year. Chinaʼs economic growth plays a major role in long-term CO2 emission reduction. The impact of industrial development on CO2 emissions reached a peak of 0.34 in 1977, and the intensity of the impact has basically stabilized at 0.26.
Highlights
Global warming caused by the growth of carbon emissions has become a major challenge to human beings
Since the United Nations Framework Convention on Climate Change (UNFCCC) in 1992, the international community has started to cooperate on carbon emission control ( e United Nations Framework Convention on Climate Change (UNFCCC) was adopted by the United Nations General Assembly on May 9, 1992, and entered into force on March 21, 1994). e legally binding Kyoto Protocol and the Paris Agreement entered into force in 2005 and 2016, respectively (the Kyoto Protocol was formulated by the United Nations Framework Convention on Climate Change (UNFCCC) at the third meeting in December 1997 and came into force on February 16, 2005; the Paris Agreement was adopted at the Paris Climate Change Conference on December 12, 2015)
If a conventional linear framework is used for analysis, significant deviations may occur in the test results, leading to biased conclusions about the factors affecting carbon emission. erefore, we use the model with nonlinear structure to deeply explore the inducing effect of Chinas economic growth, energy efficiency, and industrial development in carbon emission. rough dynamic mechanism analysis method, we discuss the emission reduction potential of the three factors, respectively, so as to provide a more reasonable basis for precise policies to achieve the carbon reduction target
Summary
Global warming caused by the growth of carbon emissions has become a major challenge to human beings. (2) We performed BDS and RESET nonlinear tests on the data structure and found that there is a significant nonlinear relationship between Chinas carbon emissions and economic growth, energy efficiency, and industrial development. According to the Bayesian model comparison criterion, we selected TVP-SV-VAR from the four types of VAR models containing nonlinear structures as the second nonlinear structure model and used the three-dimensional time-varying parameter impulse response function to analyze in detail the conduction process of Chinas economic growth, energy efficiency, and industrial development on carbon emissions, including conduction direction, conduction intensity, etc. We construct a timevarying parameter (TVP) regression model, and the dynamic trend of time-varying coefficients shows that Chinas economic growth, energy efficiency, and industrial development have obvious time-varying characteristics.
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