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Spatial correlation robust inference with errors in location or distance
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DOI：10.1016/j.jeconom.2006.09.003.png)
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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. (C) 2006 Elsevier B.V. All rights reserved.
Keyword:
spatial models
HAC estimation
measurement error
specification test
parametric bootstrap
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被引数:
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