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Finite Sample Properties of Alternative GMM Estimators for Random Effects Models with Spatially Correlated Errors

Title data

Larch, Mario ; Walde, Janette:
Finite Sample Properties of Alternative GMM Estimators for Random Effects Models with Spatially Correlated Errors.
In: The Annals of Regional Science. Vol. 43 (2009) Issue 2 . - pp. 473-490.
ISSN 1432-0592
DOI: https://doi.org/10.1007/s00168-008-0222-2

Abstract in another language

For panel data models with error components that are spatially correlated, the finite sample properties of alternative generalized method of moments (GMM) estimators are determined. We suggest using a continuously updated GMM estimator which is invariant to curvature altering transformations and which should improve small sample efficiency. A Monte Carlo study using a wide range of settings compares the small sample efficiency of various GMM approaches and the maximum likelihood estimator (MLE). The GMM estimators turn out to perform comparably to the MLE approach and even outperform the latter for complex weighting matrices and non-normally distributed errors.

Further data

Item Type: Article in a journal
Refereed: Yes
Subject classification: C21; C23; H77; R15
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Economics > Lehrstuhl Volkswirtschaftslehre VI: Empirische Wirtschaftsforschung
Faculties > Faculty of Law, Business and Economics > Department of Economics > Lehrstuhl Volkswirtschaftslehre VI: Empirische Wirtschaftsforschung > Lehrstuhl für Volkswirtschaftslehre VI: Empirische Wirtschaftsforschung - Univ.-Prof. Dr. Mario Larch
Faculties
Faculties > Faculty of Law, Business and Economics
Faculties > Faculty of Law, Business and Economics > Department of Economics
Result of work at the UBT: No
DDC Subjects: 300 Social sciences > 330 Economics
Date Deposited: 15 Oct 2015 11:03
Last Modified: 15 Oct 2015 11:03
URI: https://eref.uni-bayreuth.de/id/eprint/16667