Vertaile menetelmiä

	Paneelitapahtumatutkimus	Propensity Score Matching
Tieteenala	Kausaalipäättely	Tutkimuksen tilastomenetelmät
Menetelmäperhe	Regression model	Process / pipeline
Syntyvuosi	2021	1983
Kehittäjä	Callaway & Sant'Anna (2021); Borusyak, Jaravel & Spiess (2024); Sun & Abraham (2021)	Paul Rosenbaum and Donald Rubin
Tyyppi	Causal inference / quasi-experimental panel design	Method
Alkuperäislähde	Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230.	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.
Rinnakkaisnimet	panel event study, event-study DiD, staggered event study, difference-in-differences event study	PSM, propensity score weighting, covariate balance
Liittyvät	6	3
Tiivistelmä	A panel event study is a quasi-experimental design that traces how an outcome evolves in periods before and after a policy event, using unit and time fixed effects to identify the causal effect. Widely used in economics and policy research, it tests for anticipation effects, verifies parallel pre-trends, and estimates dynamic treatment effects across post-treatment horizons — making it the standard toolkit for rigorous policy evaluation with observational panel data.	Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.