विधियों की तुलना करें

	Environmental Kuznets Curve Estimation	IPAT Decomposition
क्षेत्र	Environmental Sociology	Environmental Sociology
परिवार	Regression model	Process / pipeline
उद्भव वर्ष	1995	1971
प्रवर्तक	Gene M. Grossman & Alan B. Krueger	Paul R. Ehrlich & John P. Holdren (IPAT); Yoichi Kaya (Kaya identity)
प्रकार	Reduced-form polynomial panel regression of pollution on income	Multiplicative accounting identity and decomposition of environmental impact
मौलिक स्रोत	Grossman, G. M., & Krueger, A. B. (1995). Economic Growth and the Environment. The Quarterly Journal of Economics, 110(2), 353-377.	Ehrlich, P. R., & Holdren, J. P. (1971). Impact of Population Growth. Science, 171(3977), 1212-1217.
उपनाम	EKC Estimation, Environmental Kuznets Curve, Income-Pollution Inverted-U Model, Grossman-Krueger Curve	IPAT Identity, Ehrlich-Holdren Identity, Kaya Identity Decomposition, Impact Equation
संबंधित	4	4
सारांश	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.	IPAT decomposition expresses environmental impact as the product of three factors, population, affluence, and technology, providing a simple accounting framework for attributing degradation to its proximate human drivers. The identity was crystallized in the debate between Paul Ehrlich, John Holdren, and Barry Commoner around 1971, with Ehrlich and Holdren's Science article on the impact of population growth a foundational statement. In the equation, affluence is output per person and technology is impact per unit of output, so the three factors multiply back exactly to total impact, making IPAT a definitional identity rather than an empirical claim. Its best-known specialization, the Kaya identity, decomposes carbon emissions into population, GDP per capita, energy intensity of output, and carbon intensity of energy, and underpins much emissions-scenario work. By taking growth rates, IPAT also yields a clean additive decomposition that apportions the change in impact among its drivers. Because the identity assumes each factor contributes proportionally, it was the stimulus for the stochastic STIRPAT model, in which Dietz and Rosa relaxed that assumption to test the drivers statistically.