Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Diferències en Diferències Robusta× | Diferències en Diferències amb Dades de Panell (Panel DiD / TWFE)× | |
|---|---|---|
| Camp | Inferència causal | Inferència causal |
| Família | Regression model | Regression model |
| Any d'origen≠ | 2021-2023 | 1985–2004 |
| Autor original≠ | Callaway & Sant'Anna; Sun & Abraham; Roth et al. (synthesised 2021-2023) | Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004) |
| Tipus | Causal inference / panel regression | Causal inference / panel regression |
| Font seminal≠ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Àlies | robust DiD, heterogeneity-robust DiD, staggered DiD, disaggregated ATT DiD | Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff |
| Relacionats≠ | 5 | 4 |
| Resum≠ | Robust Difference-in-Differences is a family of modern DiD estimators designed to remain valid when treatment timing is staggered across units and treatment effects are heterogeneous over time or across groups. Classical two-way fixed-effects (TWFE) DiD can be severely biased in such settings; robust variants estimate group-time average treatment effects (ATTs) separately and then aggregate them in a theoretically sound way. | 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. |
| ScholarGateConjunt de dades ↗ |
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