Publication Type
Journal Article
Version
acceptedVersion
Publication Date
11-2016
Abstract
This paper first presents simple methods for conducting up to third-order bias and variance corrections for the quasi maximum likelihood (QML) estimators of the spatial parameter(s) in the fixed effects spatial panel data (FE-SPD) models. Then, it shows how the bias and variance corrections lead to refined t-ratios for spatial effects and for covariate effects. The implementation of these corrections depends on the proposed bootstrap methods of which validity is established. Monte Carlo results reveal that (i) the QML estimators of the spatial parameters can be quite biased, (ii) a second-order bias correction effectively removes the bias, and (iii) the proposed t-ratios are much more reliable than the usual t-ratios.
Keywords
Bias correction, Bootstrap, Fixed effects, Refined t-ratios, Spatial panels, Variance correction, Wild bootstrap
Discipline
Econometrics | Economics
Research Areas
Econometrics
Publication
Regional Science and Urban Economics D
Volume
61
First Page
52
Last Page
72
ISSN
0166-0462
Identifier
10.1016/j.regsciurbeco.2016.08.003
Publisher
Elsevier
Citation
YANG, Zhenlin; YU, Jihai; and LIU, Shew Fan.
Bias correction and refined inferences for fixed effects spatial panel data models. (2016). Regional Science and Urban Economics D. 61, 52-72.
Available at: https://ink.library.smu.edu.sg/soe_research/1919
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.
Additional URL
https://doi.org/10.1016/j.regsciurbeco.2016.08.003