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Lessons From Quantile Panel Estimation of the Environmental Kuznets Curve

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  • Carlos A. Flores
  • Alfonso Flores-Lagunes
  • Dimitrios Kapetanakis

Abstract

We employ quantile regression fixed effects models to estimate the income-pollution relationship on NO x (nitrogen oxide) and SO 2 (sulfur dioxide) using U.S. data. Conditional median results suggest that conditional mean methods provide too optimistic estimates about emissions reduction for NO x , while the opposite is found for SO 2 . Deleting outlier states reverses the absence of a turning point for SO 2 in the conditional mean model, while the conditional median model is robust to them. We also document the relationship's sensitivity to including additional covariates for NO x , and undertake simulations to shed light on some estimation issues of the methods employed.

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  • Carlos A. Flores & Alfonso Flores-Lagunes & Dimitrios Kapetanakis, 2014. "Lessons From Quantile Panel Estimation of the Environmental Kuznets Curve," Econometric Reviews, Taylor & Francis Journals, vol. 33(8), pages 815-853, November.
    • Handle: RePEc:taf:emetrv:v:33:y:2014:i:8:p:815-853
    DOI: 10.1080/07474938.2013.806148
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    10. Carolina Castagnetti, 2015. "The Analysis of the Gender Wage Gap in the Italian Public Sector: a Quantile Approach for Panel Data," DEM Working Papers Series 109, University of Pavia, Department of Economics and Management.
    11. Maralgua Och, 2017. "Empirical Investigation of the Environmental Kuznets Curve Hypothesis for Nitrous Oxide Emissions for Mongolia," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 117-128.
    12. Carolina Castagnetti & Luisa Rosti & Marina Töpfer, 2019. "The Public-Private Sector Wage Differential Across Gender in Italy: a New Quantile-Based Decomposition Approach," Economics Bulletin, AccessEcon, vol. 39(4), pages 2533-2539.
    13. Zhong, Sheng, 2016. "Structural decompositions of energy consumption, energy intensity, emissions and emission intensity - A sectoral perspective: empirical evidence from WIOD over 1995 to 2009," MERIT Working Papers 2016-015, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    14. Kim, Dong-Hyeon & Suen, Yu-Bo & Lin, Shu-Chin, 2019. "Carbon dioxide emissions and trade: Evidence from disaggregate trade data," Energy Economics, Elsevier, vol. 78(C), pages 13-28.
    15. Apergis, Nicholas & Christou, Christina & Gupta, Rangan, 2017. "Are there Environmental Kuznets Curves for US state-level CO2 emissions?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 551-558.
    16. Muhammad Tariq Majeed & Maria Mazhar & Isma Samreen & Aisha Tauqir, 2022. "Economic complexities and environmental degradation: evidence from OECD countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5846-5866, April.
    17. Zhu, Huiming & Duan, Lijun & Guo, Yawei & Yu, Keming, 2016. "The effects of FDI, economic growth and energy consumption on carbon emissions in ASEAN-5: Evidence from panel quantile regression," Economic Modelling, Elsevier, vol. 58(C), pages 237-248.
    18. Hübler, Michael, 2017. "The inequality-emissions nexus in the context of trade and development: A quantile regression approach," Ecological Economics, Elsevier, vol. 134(C), pages 174-185.
    19. Castagnetti, Carolina & Giorgetti, Maria Letizia, 2019. "Understanding the gender wage-gap differential between the public and private sectors in Italy: A quantile approach," Economic Modelling, Elsevier, vol. 78(C), pages 240-261.
    20. Apergis, Nicholas, 2016. "Environmental Kuznets curves: New evidence on both panel and country-level CO2 emissions," Energy Economics, Elsevier, vol. 54(C), pages 263-271.
    21. You, Wan-Hai & Zhu, Hui-Ming & Yu, Keming & Peng, Cheng, 2015. "Democracy, Financial Openness, and Global Carbon Dioxide Emissions: Heterogeneity Across Existing Emission Levels," World Development, Elsevier, vol. 66(C), pages 189-207.

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    JEL classification:

    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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