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

## Author

Listed:
• 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
as

File URL: https://mpra.ub.uni-muenchen.de/15153/1/MPRA_paper_15153.pdf
File Function: original version

## References listed on IDEAS

as
1. Paelinck, J., 1978. "Spatial econometrics," Economics Letters, Elsevier, vol. 1(1), pages 59-63.
Full references (including those not matched with items on IDEAS)

### 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

### NEP fields

This paper has been announced in the following NEP Reports:

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