Small Sample Properties of Maximum Likelihood Versus Generalized Method of Moments Based Tests for Spatially Autocorrelated Errors
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.
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Bibliographic InfoPaper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 1558.
Date of creation: 2005
Date of revision:
spatial autocorrelation; hypothesis tests; Monte Carlo studies; maximum likelihood estimation; generalized method of moments;
Other versions of this item:
- Egger, Peter & Larch, Mario & Pfaffermayr, Michael & Walde, Janette, 2009. "Small sample properties of maximum likelihood versus generalized method of moments based tests for spatially autocorrelated errors," Regional Science and Urban Economics, Elsevier, Elsevier, vol. 39(6), pages 670-678, November.
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