Inference on time-invariant variables using panel data: a pretest estimator
Résumé
This paper proposes a new pretest estimator of panel data models including time-invariant variables based on the Mundlak-Krishnakumar estimator and an "unrestricted" Hausman-Taylor estimator. Furthermore, the paper evaluates the biases of currently used estimators: repeated between, ordinary least squares, two-stage restricted between, Oaxaca-Geisler estimator, fixed effect vector decomposition, and generalized least squares. Some of these may lead to erroneous conclusions regarding the statistical significance of the estimated parameter values of time-invariant variables, especially when time-invariant variables are correlated with the individual effects.
Origine | Fichiers produits par l'(les) auteur(s) |
---|
Loading...