Different economic sectors interact with each other and contribute in increasing CO2 emissions in different ways and with different intensities. A modeling framework describing CO2 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 CO2 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 CO2 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 CO2 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 CO2 distribution.
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20 October 2020
Research Article|
October 20 2020
Sectoral Decomposition of CO2 World Emissions: A Joint Quantile Regression Approach
Luca Merlo;
Luca Merlo
Department of Statistics,
Sapienza University of Rome
, RomeItaly
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Lea Petrella;
Lea Petrella
Memotef Department,
Sapienza University Of Rome
, RomeItaly
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Valentina Raponi
Valentina Raponi
IESE Business School,
University of Navarra
, Barcelona, Spain
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Online ISSN: 1932-1473
Print ISSN: 1932-1465
© 2020 L. Merlo and L. Petrella and V. Raponi
2020
L. Merlo and L. Petrella and V. Raponi
Licensed re-use rights only
International Review of Environmental and Resource Economics (2020) 14 (2-3): 197–239.
Citation
Merlo L, Petrella L, Raponi V (2020), "Sectoral Decomposition of CO2 World Emissions: A Joint Quantile Regression Approach". International Review of Environmental and Resource Economics, Vol. 14 No. 2-3 pp. 197–239, doi: https://doi.org/10.1561/101.00000116
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