ScholarGate
Assistant

Comparer des méthodes

Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.

Appariement Exact Coarsened sur Données de Panel×Modèle à effets fixes pour données de panel×
DomaineInférence causaleÉconométrie
FamilleRegression modelRegression model
Année d'origine2012 (CEM); 2021 (panel extension)2014
Auteur d'origineIacus, King & Porro (CEM, 2012); panel extension via Imai, Kim & Wang (2021)Hsiao (textbook treatment); within transformation of panel data
TypeMatching / quasi-experimentalPanel data regression
Source fondatriceIacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
AliasPanel CEM, CEM for panel data, coarsened exact matching with panel datafixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Apparentées65
RésuméPanel Data Coarsened Exact Matching applies the Coarsened Exact Matching (CEM) algorithm to repeated-measures panel data, matching treated and control units within the same coarsened covariate strata across multiple time periods. It balances pre-treatment characteristics before estimating a causal treatment effect, combining the transparency of exact matching with the richer identification available in longitudinal datasets.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).
ScholarGateJeu de données
  1. v1
  2. 2 Sources
  3. PUBLISHED
  1. v1
  2. 2 Sources
  3. PUBLISHED

Aller à la recherche Télécharger les diapositives

ScholarGateComparer des méthodes: Panel Data Coarsened Exact Matching · Panel Fixed Effects. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare