Small Sample Properties of Maximum Likelihood Versus Generalized Method of Moments Based Tests for Spatially Autocorrelated Errors

Peter Egger, Mario Larch, Michael Pfaffermayr and Janette Walde

No 1558, CESifo Working Paper Series from CESifo

Abstract: 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.

Keywords: spatial autocorrelation; hypothesis tests; Monte Carlo studies; maximum likelihood estimation; generalized method of moments (search for similar items in EconPapers)
Date: 2005
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Small sample properties of maximum likelihood versus generalized method of moments based tests for spatially autocorrelated errors (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_1558

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