Can We Trust Cluster-Corrected Standard Errors? An Application of Spatial Autocorrelation with Exact Locations Known
AbstractStandard error corrections for clustered samples impose untested restrictions on spatial correlations. Our example shows these are too conservative, compared with a spatial error model that exploits information on exact locations of observations, causing inference errors when cluster corrections are used.
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Bibliographic InfoPaper provided by University of Waikato, Department of Economics in its series Working Papers in Economics with number 10/07.
Length: 9 pages
Date of creation: 18 Aug 2010
Date of revision:
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clustered samples; GPS; spatial correlation;
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-11-27 (All new papers)
- NEP-ECM-2010-11-27 (Econometrics)
- NEP-ETS-2010-11-27 (Econometric Time Series)
- NEP-URE-2010-11-27 (Urban & Real Estate Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Thomas Barrios & Rebecca Diamond & Guido W. Imbens & Michal Kolesar, 2010.
"Clustering, Spatial Correlations and Randomization Inference,"
NBER Working Papers
15760, National Bureau of Economic Research, Inc.
- Thomas Barrios & Rebecca Diamond & Guido W. Imbens & Michal Koles�r, 2012. "Clustering, Spatial Correlations, and Randomization Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 578-591, June.
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