Asymptotic Properties of Estimators for the Linear Panel Regression Model with Individual Effects and Serially Correlated Errors: The Case of Stationary and Non-Stationary Regressors and Residuals

Badi Baltagi, Chihwa Kao and Long Liu

No 93, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: This paper studies the asymptotic properties of standard panel data estimators in a simple panel regression model with error component disturbances. Both the regressor and the remainder disturbance term are assumed to be autoregressive and possibly non-stationary. Asymptotic distributions are derived for the standard panel data estimators including ordinary least squares, fixed effects, first-difference, and generalized least squares (GLS) estimators when both T and n are large. We show that all the estimators have asymptotic normal distributions and have different convergence rates dependent on the non-stationarity of the regressors and the remainder disturbances. We show using Monte Carlo experiments that the loss in efficiency of the OLS, FE and FD estimators relative to true GLS can be substantial.

Keywords: Panel data; OLS; Fixed-effects; First-difference; GLS. (search for similar items in EconPapers)
JEL-codes: C33 (search for similar items in EconPapers)
Pages: 76 pages
Date: 2007-05
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://surface.syr.edu/cpr/72/ (application/pdf)

Related works:
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:93

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 ().