Publication Type
Journal Article
Version
submittedVersion
Publication Date
3-2015
Abstract
We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the cross-sectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models, and prove consistency and derive the limiting distributions of the QML estimators under different assumptions on the initial observations. We propose a residual-based bootstrap method for estimating the standard errors of the QML estimators. Monte Carlo simulation shows that both the QML estimators and the bootstrap standard errors perform well in finite samples under a correct assumption on initial observations, but may perform poorly when this assumption is not met.
Keywords
Bootstrap Standard Errors, Dynamic Panel, Fixed Effects, Random Effects, Spatial Error Dependence, Quasi Maximum Likelihood, Initial Observations.
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
185
Issue
1
First Page
230
Last Page
258
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2014.11.002
Citation
SU, Liangjun and YANG, Zhenlin.
QML estimation of dynamic panel data models with spatial errors. (2015). Journal of Econometrics. 185, (1), 230-258.
Available at: https://ink.library.smu.edu.sg/soe_research/1485
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.jeconom.2014.11.002