Publication Type
Working Paper
Version
publishedVersion
Publication Date
10-2010
Abstract
The biasedness issue arising from the maximum likelihood estimation of the spatial autoregressive model (SAR) is further investigated under a broader set-up than that in Bao and Ullah (2007a). A major difficulty in analytically evaluating the expectations of ratios of quadratic forms is overcome by a simple bootstrap procedure. With that, the corrections on bias and variance of the spatial estimator can easily be made up to third-order, and once this is done, the estimators of other model parameters become nearly unbiased. Compared with the analytical approach, the new approach is much simpler, and can easily be extended to other models of a similar structure. Extensive Monte Carlo results show that the new approach performs excellently in general.
Keywords
Third-order bias, Third-order variance, Bootstrap, Concentrated estimating equation, Monte Carlo, Quasi-MLE, Spatial layout.
Discipline
Econometrics
Research Areas
Econometrics
First Page
1
Last Page
49
Publisher
SMU Economics and Statistics Working Paper Series, No. 12-2010
City or Country
Singapore
Citation
YANG, Zhenlin.
Bias-Corrected Estimation for Spatial Autocorrelation. (2010). 1-49.
Available at: https://ink.library.smu.edu.sg/soe_research/1251
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.