Salīdzināt metodes

	Paneļdatu entropijas balansēšana	Panel Data Difference-in-Differences (Panel DiD / TWFE)
Nozare	Cēloņsakarību secināšana	Cēloņsakarību secināšana
Saime	Regression model	Regression model
Izcelsmes gads	2012 (cross-section); panel adaptation mid-2010s onward	1985–2004
Autors	Hainmueller (2012); extended to panel settings by subsequent applied econometric work	Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004)
Tips	Covariate balancing / reweighting estimator	Causal inference / panel regression
Pirmavots	Hainmueller, J. (2012). Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies. Political Analysis, 20(1), 25-46.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Citi nosaukumi	EB-panel, panel entropy balancing, entropy reweighting in panel data, panel-EB	Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff
Saistītās	5	4
Kopsavilkums	Panel 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.