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Environmental Kuznets Curve Estimation

Environmental Kuznets curve (EKC) estimation tests the hypothesis that environmental degradation first rises and then falls as a country grows richer, tracing an inverted-U relationship between per-capita income and pollution. The empirical pattern was popularized by Gene Grossman and Alan Krueger's 1995 study of how air and water quality vary with income across countries, which found that several pollutants worsen at low income but improve beyond a turning point. Methodologically, the EKC is estimated as a reduced-form regression of an environmental indicator on a polynomial, usually quadratic, in income, with the signs of the linear and squared terms determining whether the inverted-U holds and the coefficients pinning down the income level at which degradation peaks. The framework is named by analogy to Simon Kuznets's hypothesized inverted-U between income and inequality. David Stern's 2004 critical review documented how fragile many early EKC results were once proper panel econometrics, unit roots, and specification issues were taken seriously. EKC estimation remains a central, much-contested tool in environmental economics and sociology for studying the growth-environment relationship.

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출처

  1. Grossman, G. M., & Krueger, A. B. (1995). Economic Growth and the Environment. The Quarterly Journal of Economics, 110(2), 353-377. DOI: 10.2307/2118443
  2. Stern, D. I. (2004). The Rise and Fall of the Environmental Kuznets Curve. World Development, 32(8), 1419-1439. DOI: 10.1016/j.worlddev.2004.03.004

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ScholarGate. (2026, June 23). Environmental Kuznets Curve Estimation (Income-Pollution Inverted-U Regression). ScholarGate. https://scholargate.app/ko/environmental-sociology/environmental-kuznets-curve

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ScholarGateEnvironmental Kuznets Curve Estimation (Environmental Kuznets Curve Estimation (Income-Pollution Inverted-U Regression)). 2026-06-24에 다음에서 검색함: https://scholargate.app/ko/environmental-sociology/environmental-kuznets-curve · 데이터셋: https://doi.org/10.5281/zenodo.20539026