Unobservable individual effects in panel data models are employed to control for heterogeneity. These can be thought of as random variables that are uncorrelated with the regressors, thus generating a random effects model. Alternatively, these random individual effects are allowed to be completely correlated with the regressors, thus generating a fixed effects model. The choice between these two alternatives is usually settled using a Hausman (Econometrica 46:1251–1271, 1978) test. This article argues that one should interpret a rejection by the Hausman test as a rejection of the random effects model, not necessarily an endorsement of the fixed effects model.
Attrition Autocorrelation Cross-section data Fixed effects Haavelmo, T Heteroskedasticity Instrumental variable estimators Least squares dummy variables (LSDV) model Multicollinearity Over-identification Panel data Random effects Sample selection
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Angrist, J.D., and W.K. Newey. 1991. Over-identification tests in earnings functions with fixed effects. Journal of Business and Economic Statistics 9: 317–323.Google Scholar
Arellano, M. 1987. Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics 49: 431–434.CrossRefGoogle Scholar
Arellano, M. 1993. On the testing of correlated effects with panel data. Journal of Econometrics 59: 87–97.CrossRefGoogle Scholar
Balestra, P., and M. Nerlove. 1966. Pooling cross-section and time-series data in the estimation of a dynamic model: The demand for natural gas. Econometrica 34: 585–612.CrossRefGoogle Scholar
Lancaster, T. 2000. The incidental parameter problem since 1948. Journal of Econometrics 95: 391–413.CrossRefGoogle Scholar
Mundlak, Y. 1961. Empirical production function free of management bias. Journal of Farm Economics 43: 44–56.CrossRefGoogle Scholar
Mundlak, Y. 1978. On the pooling of time series and cross-section data. Econometrica 46: 69–85.CrossRefGoogle Scholar
Nerlove, M., and P. Balestra. 1992. Formulation and estimation of econometric models for panel data. In The econometrics of panel data: Handbook of theory and applications, ed. L. Matyas and P. Sevestre. Dordrecht: Kluwer.Google Scholar
Neyman, J., and E.L. Scott. 1948. Consistent estimation from partially consistent observations. Econometrica 16: 1–32.CrossRefGoogle Scholar
Swamy, P.A.V.B., and S.S. Arora. 1972. The exact finite sample properties of the estimators of coefficients in the error components regression models. Econometrica 40: 261–275.CrossRefGoogle Scholar
Wallace, T.D., and A. Hussain. 1969. The use of error components models in combining cross-section and time-series data. Econometrica 37: 55–72.CrossRefGoogle Scholar