TY - JOUR T1 - Testing for time-invariant unobserved heterogeneity in generalized linear models for panel data JF - Journal of Econometrics Y1 - 2015 A1 - Francesco Bartolucci A1 - Belotti, F. A1 - Peracchi, F. KW - Health Conditions and Status KW - Methodology AB - Recent literature on panel data emphasizes the importance of accounting for time-varying unobservable individual effects, which may stem from either omitted individual characteristics or macro-level shocks that affect each individual unit differently. In this paper, we propose a simple specification test of the null hypothesis that the individual effects are time-invariant against the alternative that they are time-varying. Our test is an application of Hausman (1978) testing procedure and can be used for any generalized linear model for panel data that admits a sufficient statistic for the individual effect. This is a wide class of models which includes the Gaussian linear model and a variety of nonlinear models typically employed for discrete or categorical outcomes. The basic idea of the test is to compare two alternative estimators of the model parameters based on two different formulations of the conditional maximum likelihood method. Our approach does not require assumptions on the distribution of unobserved heterogeneity, nor it requires the latter to be independent of the regressors in the model. We investigate the finite sample properties of the test through a set of Monte Carlo experiments. Our results show that the test performs well, with small size distortions and good power properties. We use a health economics example based on data from the Health and Retirement Study to illustrate the proposed test. PB - 184 VL - 184 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-84913536688andpartnerID=40andmd5=72f27b89df012501a4fbcd9a41c40830 IS - 1 N1 - Export Date: 20 January 2015 U4 - Fixed-effects/Generalized linear models/Generalized linear models/Hausman-type tests/Longitudinal data/Self-reported health ER -