Torben Klarl

Is Spatial Bootstrapping a Panacea for Valid Inference?


Bootstrapping 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.

JEL: C18, C21, R11


Paper available as pdf-file. Beitrag Nr. 322, Volkswirtschaftliche Diskussionsreihe, Institut für Volkswirtschaftslehre der Universität Augsburg


Torben Klarl, University of Augsburg, Department of Economics, D-86135 Augsburg, Germany, phone +49-821-598-4189, fax +49-821-598-4231

Bo., 27.05.2013