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dc.contributor.authorEgger, Peteren_US
dc.contributor.authorLarch, Marioen_US
dc.contributor.authorPfaffermayr, Michaelen_US
dc.contributor.authorWalde, Janette F.en_US
dc.date.accessioned2009-01-28T15:54:31Z-
dc.date.available2009-01-28T15:54:31Z-
dc.date.issued2005en_US
dc.identifier.urihttp://hdl.handle.net/10419/19022-
dc.description.abstractThis 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.en_US
dc.language.isoengen_US
dc.publisheren_US
dc.relation.ispartofseriesCESifo working papers 1558en_US
dc.subject.jelC12en_US
dc.subject.jelR10en_US
dc.subject.jelC21en_US
dc.subject.ddc330en_US
dc.subject.keywordspatial autocorrelationen_US
dc.subject.keywordhypothesis testsen_US
dc.subject.keywordMonte Carlo studiesen_US
dc.subject.keywordmaximum likelihood estimationen_US
dc.subject.keywordgeneralized method of momentsen_US
dc.subject.stwMaximum-Likelihood-Methodeen_US
dc.subject.stwMomentenmethodeen_US
dc.subject.stwAutokorrelationen_US
dc.subject.stwStatistischer Testen_US
dc.subject.stwTheorieen_US
dc.titleSmall sample properties of maximum likelihood versus generalized method of moments based tests for spatially autocorrelated errorsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn503677639en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
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