Sectoral Decomposition of CO2 World Emissions: A Joint Quantile Regression Approach

Luca Merlo, Lea Petrella and Valentina Raponi

International Review of Environmental and Resource Economics, 2020, vol. 14, issue 2-3, 197-239

Abstract: Different economic sectors interact with each other and contribute in increasing CO2 emissions in different ways and with different intensities. A modeling framework describing CO 2 cross-sectoral dependencies could be fruitful to authorities providing guidance to policies on emissions regulations and environment preservation. After surveying the existing literature that investigates on the relationship between urbanization and CO 2 emissions, we focus on the role of quantile regression in environmental modeling to provide a more complete view of the the nexus between socio-demographic factors and CO 2 emissions coming from different sources of economic activities, that can be missed by other regression methods. In particular, using a new joint quantile regression approach, in this paper we consider a sectoral disaggregation of total CO 2 emissions of 154 world countries and hypothesize a heterogeneous effect of population, urbanization, industrialization and economic growth in different sectors and at different quantile levels of the multivariate CO distribution.

Keywords: CO2 emissions; joint quantile regression; sectoral disaggregation; multivariate CO2 distribution; multivariate STIRPAT model (search for similar items in EconPapers)
JEL-codes: C31 C54 Q51 Q53 Q56 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:now:jirere:101.00000116

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