Estimation of Spatial Regression Models with Autoregressive Errors by Two Stage Least Squares Procedures: A Serious Problem

Harry H. Kelejian () and Ingmar Prucha
Additional contact information
Harry H. Kelejian: Department of Economics, University of Maryland, http://econweb.umd.edu/~kelejian/

Electronic Working Papers from University of Maryland, Department of Economics

Abstract: Various two stage least squares procedures have been suggested for the estimation of the autoregressive parameter in the spatial autoregressive model of order one. These procedures are computationally convenient and so their use is "tempting". In this paper we show that these procedures are, in general, not consistent and therefore should not be used.

Keywords: Spatial Models; Autocorrelation; Two Stage Least Squares (search for similar items in EconPapers)
JEL-codes: C13 C21 (search for similar items in EconPapers)
Date: 1997-04
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (41)

Downloads: (external link)
http://www.econweb.umd.edu/papers/Kelepruc.pdf Full text (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found

Related works:
Journal Article: Estimation of Spatial Regression Models with Autoregressive Errors by Two-Stage Least Squares Procedures: A Serious Problem (1997)
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:umd:umdeco:97-001

Ordering information: This working paper can be ordered from
Department of Economics, University of Maryland, Tydings Hall, College Park, MD 20742

Access Statistics for this paper

More papers in Electronic Working Papers from University of Maryland, Department of Economics Department of Economics, University of Maryland, Tydings Hall, College Park, MD 20742.
Bibliographic data for series maintained by Peter Murrell ().