Model Selection in Panel Data Models: A Generalization of the Vuong Test
Abstract
This paper generalizes the classical Vuong (1989) test to panel data models by employing modified profile likelihoods and the Kullback-Leibler information criterion. Unlike the standard likelihood function, the profile likelihood lacks certain regular properties, making modification necessary. We adopt a generalized panel data framework that incorporates group fixed effects for time and individual pairs, rather than traditional individual fixed effects. Applications of our approach include linear models with non-nested specifications of individual-time effects.
Fields of Study & Subjects
Spatial and Panel Data Analysis
Statistical Methods and Inference
Statistical Methods and Bayesian Inference
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 29 January 2026
- Document type
- Preprint