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A NEW PANEL DATA TREATMENT FORHETEROGENEITY IN TIME TRENDS

Published online by Cambridge University Press:  01 May 2012

Alois Kneip,
Robin C. Sickles and
Wonho Song
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Abstract

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This paper introduces a new estimation method forarbitrary temporal heterogeneity in panel datamodels. The paper provides a semiparametric methodfor estimating general patterns of cross-sectionalspecific time trends. The methods proposed in thepaper are related to principal component analysisand estimate the time-varying trend effects using asmall number of common functions calculated from thedata. An important application for the new estimatoris in the estimation of time-varying technicalefficiency considered in the stochastic frontierliterature. Finite sample performance of theestimators is examined via Monte Carlo simulations.We apply our methods to the analysis of productivitytrends in the U.S. banking industry.

Information

Type
Research Article
Information
Econometric Theory , Volume 28 , Issue 3 , June 2012, pp. 590 - 628
Copyright
Copyright © Cambridge University Press 2011

Footnotes

Earlier versions of this paper under the title“On Estimating the Mixed Effects Model” werepresented at North American Productivity Workshop,Toronto, June 2004; COMPSTAT 2004, Prague, August2004; and the European Workshop of Efficiency andProductivity IX, Brussels, July 2005. The paperwas also given at the 2005 Econometric SocietyWorld Congress, University College, London, andMichigan State, Rice University, and SyracuseUniversity econometrics workshops. The authorsthank participants at those conferences andworkshops, particularly Peter Schmidt, MahmoudEl-Gamal, Yoosoon Chang, Joon Park, and LeopoldSimar, for constructive criticisms and insights.We also thank three anonymous referees and editorGuido Kuersteiner for their insightful commentsand criticisms that substantially strengthened thepaper, and Levent Kutlu for his very crucialresearch assistance. The usual caveat applies.Song gratefully acknowledges financial supportfrom Chung-Ang University through research grantsin 2011.

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