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Small Sample Properties and Pretest Estimation of A Spatial Hausman-Taylor Model

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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. Key Words: Hausman-Taylor estimator; Spatial random effects; Small sample properties JEL No. C23, 31

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  • Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2012. "Small Sample Properties and Pretest Estimation of A Spatial Hausman-Taylor Model," Center for Policy Research Working Papers 141, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:141
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    Keywords

    hausman-taylor estimator; spatial random effects; small sample properties jel no. c23; 31;
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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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