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

Author(s)/Creator(s)

Badi Baltagi, Syracuse UniversityFollow
Peter H. Egger, ETH Zurich
Michaela Kesina, ETH Zurich

Description/Abstract

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.

Document Type

Working Paper

Date

8-2012

Keywords

Hausman-Taylor estimator; Spatial random effects; Small sample properties

Series

Working Papers Series

Disciplines

Economics | Public Affairs, Public Policy and Public Administration

Additional Information

Working paper no. 141

Recommended Citation

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.
https://surface.syr.edu/cpr/189

Source

local input

Creative Commons License

This work is licensed under a Creative Commons Attribution 3.0 License.