OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model: Extended Version
Kairat Mynbaev ()
MPRA Paper from University Library of Munich, Germany
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)
New Economics Papers: this item is included in nep-ecm and nep-geo
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