Small sample properties of maximum likelihood versus generalized method of moments based tests for spatially autocorrelated errors

This paper undertakes a Monte Carlo study to compare MLE-based and GMM-based tests regarding the spatial autocorrelation coefficient of the error term in a Cliff and Ord type model. The main finding is that a Wald-test based on GMM estimation as derived by Kelejian and Prucha (2005a) performs surprisingly well. Our Monte Carlo study indicates that the GMM Wald-test is correctly sized even in small samples and exhibits the same power as their MLE-based counterparts. Since GMM estimates are much easier to calculate, the GMM Wald-test is recommended for applied researches.

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Year of publication:	2005
Authors:	Egger, Peter ; Larch, Mario ; Pfaffermayr, Michael ; Walde, Janette F.
Publisher:	Munich : Center for Economic Studies and ifo Institute (CESifo)
Subject:	Maximum-Likelihood-Methode \| Momentenmethode \| Autokorrelation \| Statistischer Test \| Theorie \| spatial autocorrelation \| hypothesis tests \| Monte Carlo studies \| maximum likelihood estimation \| generalized method of moments

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Series:	CESifo Working Paper ; 1558
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	503677639 [GVK] hdl:10419/19022 [Handle]
Classification:	C12 - Hypothesis Testing ; R10 - General Regional Economics. General ; C21 - Cross-Sectional Models; Spatial Models
Source:	EconStor

Persistent link: https://www.econbiz.de/10010261344