Asymptotic Distribution of the OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model

Kairat Mynbaev ()

Abstract: We find the asymptotics of the OLS estimator of the parameters $\beta$ and $\rho$ in the spatial autoregressive model with exogenous regressors $Y_n = X_n\beta+\rho W_nY_n+V_n$. Only low-level conditions are imposed. Exogenous regressors may be bounded or growing, like polynomial trends. The assumption on the spatial matrix $W_n$ is appropriate for the situation when each economic agent is influenced by many others. The asymptotics contains both linear and quadratic forms in standard normal variables. The conditions and the format of the result are chosen in a way compatible with known results for the model without lags by Anderson (1971) and for the spatial model without exogenous regressors due to Mynbaev and Ullah (2006).

Keywords: mixed regressive spatial autoregressive model; OLS estimator; asymptotic distribution (search for similar items in EconPapers)
JEL-codes: C21 C31 (search for similar items in EconPapers)
Date: 2006-08-01
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

https://mpra.ub.uni-muenchen.de/4411/1/MPRA_paper_4411.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