방법 비교

	정책 평가 역확률 가중치 (Policy Evaluation Inverse Probability Weighting)	성향 점수 가중치 (PSW / IPW)
분야	인과추론	인과추론
계열	Regression model	Regression model
기원 연도	1952 (IPW origin); 2000s (policy evaluation application)	1983 (propensity score); 2003 (efficient IPW estimator)
창시자	Horvitz & Thompson (1952); extended to causal policy settings by Robins, Hernan & Brumback (2000) and Imbens & Wooldridge (2009)	Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
유형	Reweighting estimator for causal policy analysis	Causal inference / reweighting
원전	Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, 47(1), 5-86.	Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55.
별칭	IPW policy evaluation, propensity-weighted policy analysis, inverse probability of treatment weighting	PSW, inverse probability weighting, IPW, propensity-based weighting
관련	6	6
요약	Policy evaluation inverse probability weighting (IPW) uses estimated propensity scores to reweight observed units so that the weighted sample mimics a randomised experiment. Each unit is weighted by the inverse of its probability of receiving the policy, creating a pseudo-population in which treatment assignment is independent of observed covariates and the average treatment effect (ATE) can be read off directly.	Propensity score weighting is a causal-inference method that reweights observations so that the covariate distributions of treated and untreated units look exchangeable, enabling unbiased estimation of average treatment effects from observational data. Each unit receives a weight that is the inverse of its probability of receiving the treatment it actually received — a strategy formalised by Rosenbaum and Rubin (1983) and given its efficient semiparametric form by Hirano, Imbens and Ridder (2003).