Publication Type
Working Paper
Version
publishedVersion
Publication Date
1-2013
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 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
First Page
1
Last Page
56
Citation
SU, Liangjun and YANG, Zhenlin.
QML Estimation of Dynamic Panel Data Models with Spatial Errors. (2013). 1-56.
Available at: https://ink.library.smu.edu.sg/soe_research/1490
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.
Comments
Published in Journal of Econometrics https://doi.org/10.1016/j.jeconom.2014.11.002