Hausman-Taylor estimator; Spatial random effects; Small sample properties
Economics | Public Affairs, Public Policy and Public Administration
This paper considers a Hausman and Taylor (1981) panel data model that exhibits a Cliff and Ord (1973) spatial error structure. We analyze the small sample properties of a generalized moments estimation approach for that model. This spatial Hausman-Taylor estimator allows for endogeneity of the time-varying and time-invariant variables with the individual effects. For this model, the spatial effects estimator is known to be consistent, but its disadvantage is that it wipes out the effects of time-invariant variables, which are important for most empirical studies. Monte Carlo results show that the spatial Hausman-Taylor estimator performs well in small samples.
Baltagi, Badi; Egger, Peter H.; and Kesina, Michaela, "Small Sample Properties and Pretest Estimation of a Spatial Hausman-Taylor Model" (2012). Center for Policy Research. 189.
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