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Environmental Kuznets curve for CO2 emissions: a literature survey

Muhammad Shahbaz (Department of Energy and Sustainable Development, Montpellier Business School, Montpellier, France)
Avik Sinha (School of Management and Entrepreneurship, Atria Institute of Technology, Bangalore, India)

Journal of Economic Studies

ISSN: 0144-3585

Article publication date: 7 January 2019




The purpose of this paper is to provide a survey of the empirical literature on environmental Kuznets curve (EKC) estimation of carbon dioxide (CO2) emissions over the period of 1991–2017.


This survey categorizes the studies on the basis of power of income in empirical models of EKC. It has been hypothesized that the EKC shows an inverted U-shaped association between economic growth and CO2 emissions.


For all the contexts, the results of EKC estimation for CO2 emissions are inconclusive in nature. The reasons behind this discrepancy can be attributed to the choice of contexts, time period, explanatory variables, and methodological adaptation.

Research limitations/implications

The future studies in this context should not only consider new set of variables (e.g. corruption index, social indicators, political scenario, energy research and development expenditures, foreign capital inflows, happiness, population education structure, public investment toward alternate energy exploration, etc.), but also the data set should be refined, so that the EKC estimation issues raised by Stern (2004) can be addressed.


By far, no study in the literature of ecological economics has focused on the empirical estimation of EKC for CO2 emissions. This particular context has been used for this study, as CO2 is one of the highest studied pollutants in the ecological economics, and especially within the EKC hypothesis framework.



The authors of this paper have not made their research data set openly available. Any enquiries regarding the data set can be directed to the corresponding author.


Shahbaz, M. and Sinha, A. (2019), "Environmental Kuznets curve for CO2 emissions: a literature survey", Journal of Economic Studies, Vol. 46 No. 1, pp. 106-168.



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