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Spatial Correlation Robust Inference with Errors in Location or Distance Author info | Abstract | Publisher info | Download info | Related research | Statistics Conley, Timothy G. (U of Chicago)
Molinari, Francesca (Cornell U)
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This paper presents results from a Monte Carlo study concerning inference with spatially dependent data. We investigate the impact of location/distance measurement errors upon the accuracy of parametric and nonparametric estimators of asymptotic variances. Nonparametric estimators are quite robust to such errors, method of moments estimators perform surprisingly well, and MLE estimators are very poor. We also present and evaluate a specification test based on a parametric bootstrap that has good power properties for the types of measurement error we consider.
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Paper provided by Cornell University, Center for Analytic Economics in its series Working Papers with number
05-12.
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Date of creation: Feb 2005Date of revision:
Handle: RePEc:ecl:corcae:05-12Contact details of provider: Postal: 402 Uris Hall, Ithaca, NY 14853 Phone: (607) 255-9901 Fax: (607) 255-2818 Web page: http://www.arts.cornell.edu/econ/CAE/workingpapers.html More information through EDIRC
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"On the asymptotic distribution of the Moran I test statistic with applications ,"
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Pede, Valerien O. & Florax, Raymond J.G.M. & Holt, Matthew T., 2008.
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6518, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
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