Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/71445
Title: Analysis of the Determinants of CO<inf>2</inf> Emissions: A Bayesian LASSO Approach
Authors: Heng Wang
Jianxu Liu
Songsak Sriboonchitta
Authors: Heng Wang
Jianxu Liu
Songsak Sriboonchitta
Keywords: Computer Science;Mathematics
Issue Date: 1-Jan-2020
Abstract: © 2020, Springer Nature Switzerland AG. CO2 emissions are recognized as the main driving factor to climate change. This study applies Bayesian LASSO approach to investigate the main determinants of CO2 emissions in 56 countries from 1995 to 2014. In a multivariate framework, this study examines two hypotheses, including Environmental Kuznets curve (EKC) hypothesis and Pollution haven hypothesis (PHH). The sample is divided into two subperiods to compare the different determinants of CO2 emissions before and after Kyoto Protocol came into effect in 2005. The results show that CO2 emissions are mainly affected by energy consumption while using renewable energy and public transportation can reduce CO2 emissions. Although economic development and urbanization are two factors opposite to the demand of emission reduction, technology and international trade, as well as international political cooperation, can mitigate CO2 emissions. Education has a positive impact before 2005 and become negative on CO2 emissions after 2005, which supports the EKC hypothesis, but no strong evidence for the PHH.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85096626029&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/71445
ISSN: 16113349
03029743
Appears in Collections:CMUL: Journal Articles

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