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

Mynbaev, Kairat (2009): OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model: Extended Version.

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.

• Item Type: MPRA Paper
• Commentary on: Mynbaev, Kairat (2006): Asymptotic Distribution of the OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model.
• Language: English
• Keywords: $L_p$-approximability; mixed spatial model; OLS asymptotics
• Subjects: C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C31 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions ; Social Interaction Models; C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics

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