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Accuracy and Efficiency of Various GMM Inference Techniques in Dynamic Micro Panel Data Models

Jan Kiviet (), Milan Pleus () and Rutger Poldermans ()
Additional contact information
Milan Pleus: IKZ, Newtonlaan 1-41, 3584 BX Utrecht, The Netherlands
Rutger Poldermans: Amsterdam School of Economics, University of Amsterdam, P.O. Box 15867, 1001 NJ Amsterdam,The Netherlands

Econometrics, 2017, vol. 5, issue 1, 1-54

Abstract: Studies employing Arellano-Bond and Blundell-Bond generalized method of moments (GMM) estimation for linear dynamic panel data models are growing exponentially in number. However, for researchers it is hard to make a reasoned choice between many different possible implementations of these estimators and associated tests. By simulation, the effects are examined in terms of many options regarding: (i) reducing, extending or modifying the set of instruments; (ii) specifying the weighting matrix in relation to the type of heteroskedasticity; (iii) using (robustified) 1-step or (corrected) 2-step variance estimators; (iv) employing 1-step or 2-step residuals in Sargan-Hansen overall or incremental overidentification restrictions tests. This is all done for models in which some regressors may be either strictly exogenous, predetermined or endogenous. Surprisingly, particular asymptotically optimal and relatively robust weighting matrices are found to be superior in finite samples to ostensibly more appropriate versions. Most of the variants of tests for overidentification and coefficient restrictions show serious deficiencies. The variance of the individual effects is shown to be a major determinant of the poor quality of most asymptotic approximations; therefore, the accurate estimation of this nuisance parameter is investigated. A modification of GMM is found to have some potential when the cross-sectional heteroskedasticity is pronounced and the time-series dimension of the sample is not too small. Finally, all techniques are employed to actual data and lead to insights which differ considerably from those published earlier.

Keywords: cross-sectional heteroskedasticity; model specification strategy; Sargan-Hansen (incremental) tests; variants of t-tests; weighting matrices; Windmeijer-correction (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2017
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Related works:
Working Paper: Accuracy and Efficiency of Various GMM Inference Techniques in Dynamic Micro Panel Data Models (2015) Downloads
Working Paper: Accuracy and efficiency of various GMM inference techniques in dynamic micro panel data models (2014) Downloads
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