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Functional sensitivity of testing the environmental Kuznets curve hypothesis


  • Wang, Yi-Chia


Conventional tests for the environmental Kuznets curve (EKC) hypothesis mostly apply a quadratic equation in modeling the non-linear relationship between environmental indices (such as air pollutants) and welfare measures (such as income per capita). If their inverted-U shaped pattern is empirically accepted with two significant regressors, the income per capita and its square transformation, the EKC hypothesis is supported. Using an OECD sample, this paper shows that the validity of testing the EKC hypothesis is sensitive to how we transform income non-linearly in sulfur and carbon EKC regressions. This paper carries out experiments on different powers of γ for transforming income non-linearly and concludes that only when 0<γ<1 and 1<γ<2 will the EKC regression demonstrate a testable non-linear cointegration relationship between the two air pollutants and income per capita. In the generalized EKC regressions estimated in this paper, although we find sulfur and carbon EKC patterns in the OECD sample, none of the EKC regressions using different γ is a cointegrating equation. This finding implies an inside critique to the EKC literature that failure of cointegration of the conventional EKC regression is not because of using the quadratic functional form, but because of the fundamentally spurious relationship between the trends of pollutants and income levels.

Suggested Citation

  • Wang, Yi-Chia, 2013. "Functional sensitivity of testing the environmental Kuznets curve hypothesis," Resource and Energy Economics, Elsevier, vol. 35(4), pages 451-466.
  • Handle: RePEc:eee:resene:v:35:y:2013:i:4:p:451-466
    DOI: 10.1016/j.reseneeco.2013.01.003

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    References listed on IDEAS

    1. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    2. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    3. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, Oxford University Press, vol. 110(2), pages 353-377.
    4. Galeotti, Marzio & Lanza, Alessandro & Pauli, Francesco, 2006. "Reassessing the environmental Kuznets curve for CO2 emissions: A robustness exercise," Ecological Economics, Elsevier, vol. 57(1), pages 152-163, April.
    5. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    6. Pedroni, Peter, 1999. " Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 653-670, Special I.
    7. Panayotou, Theodore, 1997. "Demystifying the environmental Kuznets curve: turning a black box into a policy tool," Environment and Development Economics, Cambridge University Press, vol. 2(04), pages 465-484, November.
    8. Torras, Mariano & Boyce, James K., 1998. "Income, inequality, and pollution: a reassessment of the environmental Kuznets Curve," Ecological Economics, Elsevier, vol. 25(2), pages 147-160, May.
    9. Roger Perman & David I. Stern, 2003. "Evidence from panel unit root and cointegration tests that the Environmental Kuznets Curve does not exist," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 47(3), pages 325-347, September.
    10. Shafik, Nemat & Bandyopadhyay, Sushenjit, 1992. "Economic growth and environmental quality : time series and cross-country evidence," Policy Research Working Paper Series 904, The World Bank.
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    Cited by:

    1. Liddle, Brantley & Messinis, George, 2015. "Revisiting sulfur Kuznets curves with endogenous breaks modeling: Substantial evidence of inverted-Us/Vs for individual OECD countries," Economic Modelling, Elsevier, vol. 49(C), pages 278-285.
    2. Brantley Liddle & George Messinis, 2018. "Revisiting carbon Kuznets curves with endogenous breaks modeling: evidence of decoupling and saturation (but few inverted-Us) for individual OECD countries," Empirical Economics, Springer, vol. 54(2), pages 783-798, March.
    3. Weber, Shlomo & Wiesmet, Hans, 2016. "Environmental awareness: The case of climate change," CEPR Discussion Papers 11525, C.E.P.R. Discussion Papers.
    4. Yang, Haisheng & He, Jie & Chen, Shaoling, 2015. "The fragility of the Environmental Kuznets Curve: Revisiting the hypothesis with Chinese data via an “Extreme Bound Analysis”," Ecological Economics, Elsevier, vol. 109(C), pages 41-58.
    5. Özbuğday, Fatih Cemil & Erbas, Bahar Celikkol, 2015. "How effective are energy efficiency and renewable energy in curbing CO2 emissions in the long run? A heterogeneous panel data analysis," Energy, Elsevier, vol. 82(C), pages 734-745.
    6. Fujii, Hidemichi & Managi, Shunsuke, 2015. "Economic development and multiple air pollutant emissions from the industrial sector," MPRA Paper 67027, University Library of Munich, Germany.
    7. Wiesmeth, Hans & Weber, Shlomo, 2015. "Awareness of Climate Change in a Diverse World," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113024, Verein für Socialpolitik / German Economic Association.
    8. Marie-Sophie Hervieux & Pierre-Alexandre Mahieu, 2014. "A detailed systematic review of the recent literature on environmental Kuznets curve dealing with CO2," Working Papers hal-01010243, HAL.

    More about this item


    Environmental Kuznets curve; EKC; Non-linear regression;

    JEL classification:

    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - 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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