Porovnat metody

	IPAT Decomposition	Tapio Decoupling Analysis
Obor	Environmental Sociology	Environmental Sociology
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	1971	2005
Tvůrce	Paul R. Ehrlich & John P. Holdren (IPAT); Yoichi Kaya (Kaya identity)	Petri Tapio (building on OECD decoupling indicators)
Typ	Multiplicative accounting identity and decomposition of environmental impact	Elasticity-based classification of growth-versus-pressure trajectories
Původní zdroj	Ehrlich, P. R., & Holdren, J. P. (1971). Impact of Population Growth. Science, 171(3977), 1212-1217.	Tapio, P. (2005). Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001. Transport Policy, 12(2), 137-151.
Další názvy	IPAT Identity, Ehrlich-Holdren Identity, Kaya Identity Decomposition, Impact Equation	Decoupling Elasticity Analysis, Tapio Decoupling Index, OECD Decoupling Indicator, Growth-Pressure Decoupling
Příbuzné	4	3
Shrnutí	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.	Decoupling analysis measures whether economic growth can proceed without a proportional increase in environmental pressure such as emissions, energy use, or resource consumption. The elasticity-based formulation introduced by Petri Tapio in 2005, refining the earlier OECD decoupling indicator, expresses the relationship as the ratio of the percentage change in environmental pressure to the percentage change in an economic driving force, typically GDP. This single decoupling elasticity is then sorted into a logical scheme of states — strong and weak decoupling, expansive and recessive coupling, and strong and weak negative decoupling — that distinguishes the desirable case where pressure falls while the economy grows from the undesirable case where pressure grows faster than the economy. Tapio's scheme has become a standard diagnostic for tracking progress toward green growth and sustainability.