Carbon Dioxide Emissions and Economic Activities: A Mean Field Variational Bayes Semiparametric Panel Data Model with Random Coefficients

Badi Baltagi, Georges Bresson and Jean-Michel Etienne

Annals of Economics and Statistics, 2019, issue 134, 43-77

Abstract: This paper proposes semiparametric estimation of the relationship between CO2 emissions and economic activities for a panel of 81 countries observed over the period 1991-2015. The observed differentiated behaviors by country reveal strong heterogeneity as well as different trends across countries and years. This is the motivation behind using a mixed fixed- and random-coefficients panel data model to estimate this relationship. Following Lee and Wand (2016a), we apply a mean field variational Bayes approximation to estimate a log model with structural breaks between CO2 emissions per capita and GDP per capita including control covariates such as energy intensity and use, energy consumption, population density, urbanization and trade. Results reveal a strong "CO2 emissions - GDP elasticity", close to one, confirming the increasing but complex link between these two variables. The use of this methodology enriches the estimates of climate change models underlining a large diversity of responses across variables and countries.

Keywords: Carbon Dioxide Emissions; Energy Intensity; Environmental Kuznets Curve; GDP; Greenhouse Gas Emissions; Mean Field Variational Bayes Approximation; Panel Data; Random Coefficients; Semiparametric Model (search for similar items in EconPapers)
JEL-codes: C11 C14 C23 Q53 Q54 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (3)

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Working Paper: Carbon Dioxide Emissions and Economic Activities: A Mean Field Variational Bayes Semiparametric Panel Data Model with Random Coefficients (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:adr:anecst:y:2019:i:134:p:43-77

DOI: 10.15609/annaeconstat2009.134.0043

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