Correlated random effects models with unbalanced panels

By Jeffrey M. Wooldridge. Journal of Econometrics, 2019

496 citations recorded by the source corpus.

Abstract I propose some strategies for allowing unobserved heterogeneity to be correlated withobserved covariates and sample selection for unbalanced panels. The methods are extensions of the Chamberlain–Mundlak approach for balanced panels when explanatory variables are strictly exogenous conditional on unobserved effects. A byproduct is fully robust Hausman tests for unbalanced panels. Even for nonlinear models, in many cases the estimators can be implemented using standard software. The framework suggests straightforward tests for sample selection that is correlated with unobserved shocks while allowing selection to be correlated with the observed covariates and unobserved heterogeneity.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/1f44eb1f5de3d07ee7dcb0783b64518e3179cdfa

Citations in the corpus

• Selection into Identification in Fixed Effects Models, with Application to Head Start (2019, unknown): “We surveyed publications from January 2000 to May 2017 in 11 leading journals that publish applied microeconomics articles.”
• The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry (2017, unknown): “This model, known as the correlated random trends, or random growths, model (Wooldridge, 2005; Murtazashvili and Wooldridge, 2008; Wooldridge, 2009), allows for correlation between the hotel-speci(cid:28)c trend component and time-varying observables.”