Small Sample Properties and Pretest Estimation of A Spatial Hausman-Taylor Model
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
|Date of creation:||Aug 2012|
|Date of revision:|
|Contact details of provider:|| Postal: 426 Eggers Hall, Syracuse, New York USA 13244-1020|
Phone: (315) 443-3114
Fax: (315) 443-1081
Web page: http://www.maxwell.syr.edu/cpr.aspx
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:max:cprwps:141. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kelly Bogart)or (Katrina Wingle)
If references are entirely missing, you can add them using this form.