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

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journal contribution
posted on 30.03.2020, 14:29 by BH Baltagi, G Bresson, J-M Etienne
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.

History

Citation

Annals of Economics and Statistics, 2019 (134), pp. 43-77

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/School of Business

Version

AM (Accepted Manuscript)

Published in

Annals of Economics and Statistics

Volume

134

Pagination

43-47

eissn

1968-3863

Copyright date

2019

Available date

01/01/2019

Publisher version

https://www.jstor.org/stable/10.15609/annaeconstat2009.134.0043

Language

en