Empirical Economics

, Volume 48, Issue 2, pp 517–535 | Cite as

Panel data dynamics with mis-measured variables: modeling and GMM estimation

Article
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Abstract

Generalized Method of Moments (GMM) estimation is discussed under the joint occurrence of fixed effects and random measurement errors in an autoregressive panel data model. Finite memory of measurement errors is allowed for. Two GMM specializations are considered: (i) using instruments (IVs) in levels for a differenced version of the equation and (ii) using IVs in differences for the level version. Index sets for lags and leads are convenient in examining how the potential IV-set is affected by changes in the memory pattern. While measurement errors with long memory may give an IV-set too small for identification, problems of “IV proliferation” and “weak IVs” may arise unless the panel is short. An application based on data for (log-transformed) capital stock and output from Norwegian manufacturing firms, supplemented with Monte Carlo simulations, to illustrate finite sample biases, is considered. Overall, with respect to bias and IV strength, GMM specialization (ii) seems superior to inference using GMM specialization (i).

Keywords

Panel data Measurement error Dynamic modeling  GMM Monte Carlo simulation 

JEL Classification

C21 C23 C31 C33 C51 E21 
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Notes

Acknowledgments

Versions of this paper have been presented at: Conference on Factor Structures for Panel and Multivariate Time Series Data, Maastricht, September 2008, the North American Summer Meeting of the Econometric Society, Boston, June 2009, the 15th International Conference on Panel Data, Bonn, July 2009 and the 64th Econometric Society European Meeting, Barcelona, August 2009, as well as seminars at the University of Oslo and Statistics Norway. I thank Xuehui Han for excellent assistance in the programming and testing of the numerical procedures, and Terje Skjerpen, two referees, and conference participants for comments.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of EconomicsUniversity of OsloBlindernNorway

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