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Consistent Estimation of Panel Data Models with a Multifactor Error Structure when the Cross Section Dimension is Large

Bin Peng () and Giovanni Forchini
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Bin Peng: Economics Discipline Group, University of Technology, Sydney

No 20, Working Paper Series from Economics Discipline Group, UTS Business School, University of Technology, Sydney

Abstract: The paper studies a panel data models with a multifactor structure in both the errors and the regressors in a microeconometric setting in which the time dimension is fixed and possibly very small. An estimator is proposed that is consistent for fixed T as N tends to infinity and that does not impose restrictive conditions on the number of factors or the number of regressors or the time series properties of the panel. A small Monte Carlo simulation shows that this estimator is very accurate for very small values of T. Two empirical cases are provided to demonstrate performances of our estimator in practice.

Keywords: Panel data model; cross-sectional dependence; asymptotic theory (search for similar items in EconPapers)
JEL-codes: C10 C13 C23 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2014-03-01
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