Linganisha mbinu

	Data Difference-in-Differences ya Panel (Panel DiD / TWFE)	Ulinganishaji wa Alama ya Mwelekeo
Nyanja	Uhitimisho wa Kisababishi	Takwimu za Utafiti
Familia	Regression model	Process / pipeline
Mwaka wa asili	1985–2004	1983
Mwanzilishi	Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004)	Paul Rosenbaum and Donald Rubin
Aina	Causal inference / panel regression	Method
Chanzo asilia	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355	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.
Majina mbadala	Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff	PSM, propensity score weighting, covariate balance
Zinazohusiana	4	3
Muhtasari	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.	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.