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

Badi Baltagi, Peter Egger and Michaela Kesina
Additional contact information
Michaela Kesina: ETH Zurich

No 141, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

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

Pages: 22 pages
Date: 2012-08
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ure
References: Add references at CitEc
Citations:

Downloads: (external link)
https://surface.syr.edu/cpr/189/ (application/pdf)

Related works:
Chapter: Small Sample Properties and Pretest Estimation of a Spatial Hausman–Taylor Model (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:max:cprwps:141

Access Statistics for this paper

More papers in Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University 426 Eggers Hall, Syracuse, New York USA 13244-1020. Contact information at EDIRC.
Bibliographic data for series maintained by Katrina Fiacchi ().