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Panel Data Entropy Balancing×Panel Data Difference-in-Differences (Panel DiD / TWFE)×
PodručjeUzročno zaključivanjeUzročno zaključivanje
ObiteljRegression modelRegression model
Godina nastanka2012 (cross-section); panel adaptation mid-2010s onward1985–2004
TvoracHainmueller (2012); extended to panel settings by subsequent applied econometric workAshenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004)
VrstaCovariate balancing / reweighting estimatorCausal inference / panel regression
Temeljni izvorHainmueller, J. (2012). Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies. Political Analysis, 20(1), 25-46. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Drugi naziviEB-panel, panel entropy balancing, entropy reweighting in panel data, panel-EBTwo-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff
Srodne54
SažetakPanel data entropy balancing extends Hainmueller's (2012) entropy balancing method to longitudinal settings. It computes unit-level weights for control observations so that their covariate moments exactly match those of the treatment group across panel periods, then plugs these weights into a weighted panel regression to estimate causal treatment effects without requiring a correctly specified propensity score model.Panel Data Difference-in-Differences extends the classic two-period DiD design to settings with multiple units observed across many time periods. By absorbing unit-level fixed effects and time fixed effects simultaneously, it isolates the causal effect of a treatment or policy change while controlling for both time-invariant unit heterogeneity and common time shocks affecting all units.
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ScholarGateUsporedite metode: Panel Data Entropy Balancing · Panel Data Difference-in-Differences. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare