QML estimation of dynamic panel data models with spatial errors

Liangjun Su () and Zhenlin Yang

Journal of Econometrics, 2015, vol. 185, issue 1, 230-258

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; Initial observations; Quasi maximum likelihood; Random effects; Spatial error dependence (search for similar items in EconPapers)
JEL-codes: C10 C13 C15 C21 C23 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (61)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407614002668
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:185:y:2015:i:1:p:230-258

DOI: 10.1016/j.jeconom.2014.11.002

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().