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

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  • Mynbaev, Kairat

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.

Suggested Citation

  • Mynbaev, Kairat, 2009. "OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model: Extended Version," MPRA Paper 15153, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:15153
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    File URL: https://mpra.ub.uni-muenchen.de/15153/1/MPRA_paper_15153.pdf
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    References listed on IDEAS

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    1. Paelinck, J., 1978. "Spatial econometrics," Economics Letters, Elsevier, vol. 1(1), pages 59-63.
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    Keywords

    $L_p$-approximability; mixed spatial model; OLS asymptotics;

    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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