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

  • Egger, Peter
  • Larch, Mario
  • Pfaffermayr, Michael
  • Walde, Janette

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.

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Article provided by Elsevier in its journal Regional Science and Urban Economics.

Volume (Year): 39 (2009)
Issue (Month): 6 (November)
Pages: 670-678

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Handle: RePEc:eee:regeco:v:39:y:2009:i:6:p:670-678
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  1. Russell Davidson & James G. MacKinnon, 1994. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," Working Papers 903, Queen's University, Department of Economics.
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