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Lessons from Quantile Panel Estimation of the Environmental Kuznets Curve

Author

Listed:
  • Carlos A. Flores

    (Department of Economics, University of Miami)

  • Alfonso Flores-Lagunes

    (Food and Resource Economics Department, University of Florida and IZA, Bonn, Germany)

  • Dimitrios Kapetanakis

    (Food and Resource Economics Department, University of Florida)

Abstract

The environmental Kuznets curve (EKC) hypothesizes that the income-pollution relationship has an inverted U shape: pollution increases with income up to a turning point beyond which it decreases. The empirical literature has concentrated on estimation of this relationship at the mean employing longitudinal data, with the typical ?nding supporting the inverted U shape. Conditional mean estimation, however, can mask heterogeneities present at higher and/or lower quantiles of the emissions?distribution, in addition to being more sensitive to the presence of outliers. We apply methods for conditional-quantile panel ?xed e¤ects models to the estimation of the income-pollution relationship on U.S. state-level data on NOx (nitrogen oxide) and SO2 (sulfur dioxide) pollutants over the period 1929- 1994. Our results indicate that conditional mean methods provide too optimistic estimates about emissions reduction of NOx, as conditional-quantile methods suggest that the turning point of the relationship occurs at higher values of income; while the opposite is found for SO2. Another important lesson drawn is that the income-pollution relationship is sensitive to the presence of outliers in the data.

Suggested Citation

  • Carlos A. Flores & Alfonso Flores-Lagunes & Dimitrios Kapetanakis, 2009. "Lessons from Quantile Panel Estimation of the Environmental Kuznets Curve," Working Papers 2010-4, University of Miami, Department of Economics.
  • Handle: RePEc:mia:wpaper:2010-4
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    3. Pei-Ing Wu & Je-Liang Liou & Hung-Yi Chang, 2015. "Alternative exploration of EKC for $$\hbox {CO}_{2}$$ CO 2 emissions: inclusion of meta-technical ratio in quantile regression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 57-73, January.
    4. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    5. Elheddad, Mohamed & Benjasak, Chonlakan & Deljavan, Rana & Alharthi, Majed & Almabrok, Jaballa M., 2021. "The effect of the Fourth Industrial Revolution on the environment: The relationship between electronic finance and pollution in OECD countries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
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    7. Al-Mulali, Usama & Ozturk, Ilhan, 2016. "The investigation of environmental Kuznets curve hypothesis in the advanced economies: The role of energy prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1622-1631.
    8. Chien, Fengsheng & Anwar, Ahsan & Hsu, Ching-Chi & Sharif, Arshian & Razzaq, Asif & Sinha, Avik, 2021. "The role of information and communication technology in encountering environmental degradation: Proposing an SDG framework for the BRICS countries," Technology in Society, Elsevier, vol. 65(C).
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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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    More about this item

    Keywords

    Environmental Kuznets Curve; Panel Quantile Estimation; Income and the Environment;
    All these keywords.

    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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