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Is Spatial Bootstrapping A Panacea For Valid Inference?

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  • Torben Klarl

Abstract

type="main"> Bootstrapping methods have so far been rarely used to evaluate spatial datasets. 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 ([Davidson, Russell, 2008]) based on restricted residuals clearly outperforms asymptotic as well as competing bootstrap tests, like the pairs bootstrap.

Suggested Citation

  • Torben Klarl, 2014. "Is Spatial Bootstrapping A Panacea For Valid Inference?," Journal of Regional Science, Wiley Blackwell, vol. 54(2), pages 304-312, March.
    • Handle: RePEc:bla:jregsc:v:54:y:2014:i:2:p:304-312
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    File URL: http://hdl.handle.net/10.1111/jors.12075
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    More about this item

    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

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