Linganisha mbinu

	Mtihani wa Mahali pa Data ya Paneli	Data Difference-in-Differences ya Panel (Panel DiD / TWFE)
Nyanja	Uhitimisho wa Kisababishi	Uhitimisho wa Kisababishi
Familia	Regression model	Regression model
Mwaka wa asili	2004-2010	1985–2004
Mwanzilishi	Bertrand, Duflo & Mullainathan; Abadie, Diamond & Hainmueller	Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004)
Aina	Falsification / validation test	Causal inference / panel regression
Chanzo asilia	Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How Much Should We Trust Differences-in-Differences Estimates? Quarterly Journal of Economics, 119(1), 249-275.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Majina mbadala	placebo regression test, falsification test, pseudo-treatment test, in-time placebo	Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff
Zinazohusiana	4	4
Muhtasari	A panel data placebo test is a falsification procedure used to assess the credibility of causal estimates in quasi-experimental panel designs. By applying the same estimation strategy to a period, group, or outcome where no true effect should exist, researchers verify that the observed treatment effect is not merely an artifact of model specification, coincidental trends, or data patterns unrelated to the intervention.	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.