skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?

American journal of political science, 2019-04, Vol.63 (2), p.467-490 [Peer Reviewed Journal]

2019 Midwest Political Science Association ;2019, Midwest Political Science Association ;2019 by the Midwest Political Science Association ;ISSN: 0092-5853 ;EISSN: 1540-5907 ;DOI: 10.1111/ajps.12417

Digital Resources/Online E-Resources

  • Title:
    When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?
  • Author: Imai, Kosuke ; Kim, In Song
  • Subjects: AJPS WORKSHOP ; Data analysis ; Economic models ; Estimation ; GATT ; Inference ; Membership ; Regression analysis
  • Is Part Of: American journal of political science, 2019-04, Vol.63 (2), p.467-490
  • Description: Many researchers use unit fixed effects regression models as their default methods for causal inference with longitudinal data. We show that the ability of these models to adjust for unobserved time-invariant confounders comes at the expense of dynamic causal relationships, which are permitted under an alternative selection-on-observables approach. Using the nonparametric directed acyclic graph, we highlight two key causal identification assumptions of unit fixed effects models: Past treatments do not directly influence current outcome, and past outcomes do not affect current treatment. Furthermore, we introduce a new nonparametric matching framework that elucidates how various unit fixed effects models implicitly compare treated and control observations to draw causal inference. By establishing the equivalence between matching and weighted unit fixed effects estimators, this framework enables a diverse set of identification strategies to adjust for unobservables in the absence of dynamic causal relationships between treatment and outcome variables. We illustrate the proposed methodology through its application to the estimation of GATT membership effects on dyadic trade volume.
  • Publisher: Oxford: Wiley Subscription Services, Inc
  • Language: English
  • Identifier: ISSN: 0092-5853
    EISSN: 1540-5907
    DOI: 10.1111/ajps.12417
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait