EconPapers    
Economics at your fingertips  
 

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

Kairat Mynbaev ()

MPRA Paper from University Library of Munich, Germany

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.

Keywords: $L_p$-approximability; mixed spatial model; OLS asymptotics (search for similar items in EconPapers)
JEL-codes: C02 C31 C01 (search for similar items in EconPapers)
Date: 2009-05-10
New Economics Papers: this item is included in nep-ecm and nep-geo
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/15153/1/MPRA_paper_15153.pdf original version (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:pra:mprapa:15153

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

 
Page updated 2020-10-23
Handle: RePEc:pra:mprapa:15153