ScholarGate
Βοηθός

Σύγκριση μεθόδων

Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.

Διαφορές-σε-Διαφορές Πολλαπλών Περιόδων (Σταδιακή DiD)×Μοντέλο Σταθερών Επιπτώσεων Δεδομένων Πάνελ×
ΠεδίοΑιτιακή ΣυμπερασματολογίαΟικονομετρία
ΟικογένειαRegression modelRegression model
Έτος προέλευσης20212014
ΔημιουργόςCallaway & Sant'Anna; Goodman-BaconHsiao (textbook treatment); within transformation of panel data
ΤύποςCausal inference / panel regressionPanel data regression
Θεμελιώδης πηγήCallaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
Εναλλακτικές ονομασίεςstaggered DiD, multi-period DiD, staggered difference-in-differences, heterogeneous timing DiDfixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Συναφείς55
ΣύνοψηMulti-period Difference-in-Differences extends the classic two-period DiD framework to settings where units adopt treatment at different points in time. Formalised by Callaway and Sant'Anna (2021) and Goodman-Bacon (2021), it decomposes the overall treatment effect into group-time average treatment effects and addresses the bias that arises when conventional two-way fixed-effects regressions are applied to staggered adoption designs.The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).
ScholarGateΣύνολο δεδομένων
  1. v1
  2. 2 Πηγές
  3. PUBLISHED
  1. v1
  2. 2 Πηγές
  3. PUBLISHED

Μετάβαση στην αναζήτηση Λήψη διαφανειών

ScholarGateΣύγκριση μεθόδων: Multi-period Difference-in-differences · Panel Fixed Effects. Ανακτήθηκε στις 2026-06-15 από https://scholargate.app/el/compare