OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model: Extended Version

Author Info

• Mynbaev, Kairat

Abstract

We find the asymptotic distribution of the OLS estimator of the parameters $% \beta$ and $\rho$ in the mixed spatial model with exogenous regressors $% Y_n=X_n\beta+\rho W_nY_n+V_n$. The exogenous regressors may be bounded or growing, like polynomial trends. The assumption about the spatial matrix $W_n$ is appropriate for the situation when each economic agent is influenced by many others. The error term is a short-memory linear process. The key finding is that in general the asymptotic distribution contains both linear and quadratic forms in standard normal variables and is not normal.

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File URL: http://mpra.ub.uni-muenchen.de/15153/1/MPRA_paper_15153.pdf
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 15153.

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 Length: Date of creation: 10 May 2009 Date of revision: Handle: RePEc:pra:mprapa:15153 Contact details of provider: Postal: Schackstr. 4, D-80539 Munich, GermanyPhone: +49-(0)89-2180-2219Fax: +49-(0)89-2180-3900Web page: http://mpra.ub.uni-muenchen.deMore information through EDIRC

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