International Review of Environmental and Resource Economics > Vol 14 > Issue 2-3

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

Luca Merlo, Department of Statistics, Sapienza University of Rome, Italy, , Lea Petrella, MEMOTEF Department, Sapienza University of Rome, Italy, , Valentina Raponi, IESE Business School, University of Navarra, Spain,
Suggested Citation
Luca Merlo, Lea Petrella and Valentina Raponi (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.

Publication Date: 20 Oct 2020
© 2020 L. Merlo and L. Petrella and V. Raponi
Robust estimation,  Semiparametric and nonparametric estimation,  Environmental Economics
JEL Codes: C31C54Q51Q53Q56
CO2 emissionsjoint quantile regressionsectoral disaggregationmultivariate CO2 distributionmultivariate STIRPAT model


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In this article:
1. Introduction 
2. Literature Review 
3. Quantile Regression and Environmental Modeling 
4. The Case Study 
5. Conclusion 


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.