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An Empirical Study of Some Driving Factors of CO2 Emissions: Evidence from Quantile Regression

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  • Yaya KEHO

Abstract

A growing body of research has examined the determinants of CO2 emissions. This literature has used mean-based regression methods in which only the mean effects of covariates are estimated. In this paper, we use the quantile regression methodology for a panel of 45 countries to investigate whether or not the factors that drive pollution do so in the same way for high and low pollution countries. The Environmental Kuznets Curve is confirmed and the positive effect of economic development is larger in low pollution countries. Energy consumption and financial development increase CO2 emissions and their effects are larger in countries with lower levels of pollution. Industrialization increases pollution especially in countries with higher level of pollution. Openness to trade and urbanization are negatively related to emissions in low pollution countries. All these findings suggest that pollution control policies should be tailored differently across low and high pollution countries.

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  • Yaya KEHO, 2020. "An Empirical Study of Some Driving Factors of CO2 Emissions: Evidence from Quantile Regression," Bulletin of Applied Economics, Risk Market Journals, vol. 7(2), pages 87-95.
    • Handle: RePEc:rmk:rmkbae:v:7:y:2020:i:2:p:87-95
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    More about this item

    Keywords

    CO2 emissions; Energy consumption; GDP; trade openness; financial development; quantile regression.;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F18 - International Economics - - Trade - - - Trade and Environment
    • O50 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - General
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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