Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study
Carolina Castagnetti and
Eduardo Rossi
MPRA Paper from University Library of Munich, Germany
Abstract:
Recently some new techniques have been proposed for the estimation of the slope coefficients in presence of unobserved components. Though, the presence of common observed and unobserved factors is neither considered or the estimation of their impacts is not taken into account. In this work a range of estimators is surveyed and their finite-sample properties are examined by means of Monte Carlo experiments. We consider both the properties of estimators for the individual specific components and for the observed common effects.
Keywords: factor error structure; principal component; common regressors; cross-section dependence; large panels, Monte Carlo simulations. (search for similar items in EconPapers)
JEL-codes: C23 C33 (search for similar items in EconPapers)
Date: 2008-12
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/26196/1/MPRA_paper_26196.pdf original version (application/pdf)
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:pra:mprapa:26196
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().