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Small Sample Properties of Maximum Likelihood versus Generalized Method of Moments based Tests for Spatially Autocorrelated Errors

Title data

Egger, Peter ; Larch, Mario ; Pfaffermayr, Michael ; Walde, Janette:
Small Sample Properties of Maximum Likelihood versus Generalized Method of Moments based Tests for Spatially Autocorrelated Errors.
In: Regional Science and Urban Economics. Vol. 39 (2009) Issue 6 . - pp. 670-678.
ISSN 0166-0462
DOI: https://doi.org/10.1016/j.regsciurbeco.2008.09.003

Abstract in another language

Many applied researchers have to deal with spatially autocorrelated residuals (SAR). Available tests that identify spatial spillovers as captured by a significant SAR parameter, are either based on maximum likelihood (MLE) or generalized method of moments (GMM) estimates. This paper illustrates the properties of various tests for the null hypothesis of a zero SAR parameter in a comprehensive Monte Carlo study. The main finding is that Wald tests generally perform well regarding both size and power even in small samples. The GMM-based Wald test is correctly sized even for non-normally distributed disturbances and small samples, and it exhibits a similar power as its MLE-based counterpart. Hence, for the applied researcher the GMM Wald test can be recommended, because it is easy to implement.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Spatial autocorrelation; Hypothesis tests; Monte Carlo studies; Maximum likelihood estimation; Generalized method of moments
Subject classification: C12; C21; R10
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Economics > Chair Economics VI: Empirical Economic Research
Faculties > Faculty of Law, Business and Economics > Department of Economics > Chair Economics VI: Empirical Economic Research > Chair Economics VI: Empirical Economic Research - 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: 14 Oct 2015 13:38
Last Modified: 20 Jan 2022 13:01
URI: https://eref.uni-bayreuth.de/id/eprint/16644