Publication Type

Journal Article

Version

Postprint

Publication Date

5-2015

Abstract

Motivated by a recent study of Bao and Ullah (2007a) on finite sample properties of MLE in the pure SAR (spatial autoregressive) model, a general method for third-order bias and variance corrections on a nonlinear estimator is proposed based on stochastic expansion and bootstrap. Working with concentrated estimating equation simplifies greatly the high-order expansions for bias and variance; a simple bootstrap procedure overcomes a major difficulty in analytically evaluating expectations of various quantities in the expansions. The method is then studied in detail using a more general SAR model, with its effectiveness in correcting bias and improving inference fully demonstrated by extensive Monte Carlo experiments. Compared with the analytical approach, the proposed approach is much simpler and has a much wider applicability. The validity of the bootstrap procedure is formally established. The proposed method is then extended to the case of more than one nonlinear estimator.

Keywords

Third-order bias, Third-order variance, Bootstrap, Concentrated estimating equation, Monte Carlo, Spatial layout, Stochastic expansion

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of Econometrics

Volume

186

Issue

1

First Page

178

Last Page

200

ISSN

0304-4076

Identifier

10.1016/j.jeconom.2014.07.003

Publisher

Elsevier

Embargo Period

7-22-2014

Copyright Owner and License

Author

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1016/j.jeconom.2014.07.003

Included in

Econometrics Commons

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