Is Spatial Bootstrapping a Panacea for Valid Inference?
AbstractBootstrapping methods have so far been rarely used to evaluate spatial data sets. Based on an extensive Monte Carlo study we find that also for spatial, cross-sectional data, the wild bootstrap test proposed by Davidson and Flachaire (2008) based on restricted residuals clearly outperforms asymptotic as well as competing bootstrap tests, like the pairs bootstrap.
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Bibliographic InfoPaper provided by Universitaet Augsburg, Institute for Economics in its series Discussion Paper Series with number 322.
Date of creation: May 2013
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Spatial econometrics; Paired bootstrap; Wild bootstrap; Parameter inference;
Find related papers by JEL classification:
- C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-04 (All new papers)
- NEP-ECM-2013-06-04 (Econometrics)
- NEP-URE-2013-06-04 (Urban & Real Estate Economics)
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