OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model: Extended Version
AbstractWe 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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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 15153.
Date of creation: 10 May 2009
Date of revision:
$L_p$-approximability; mixed spatial model; OLS asymptotics;
Find related papers by JEL classification:
- C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
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- NEP-ALL-2009-05-16 (All new papers)
- NEP-ECM-2009-05-16 (Econometrics)
- NEP-GEO-2009-05-16 (Economic Geography)
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