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.

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Year of publication:	2013
Authors:	Klarl, Torben
Publisher:	Augsburg : Universität Augsburg, Institut für Volkswirtschaftslehre
Subject:	Spatial econometrics \| Paired bootstrap \| Wild bootstrap \| Parameter inference

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Series:	Volkswirtschaftliche Diskussionsreihe ; 322
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	778122751 [GVK] hdl:10419/92958 [Handle] RePEc:aug:augsbe:0322 [RePEc]
Classification:	c18 ; C21 - Cross-Sectional Models; Spatial Models ; R11 - Regional Economic Activity: Growth, Development, and Changes
Source:	EconStor

Persistent link: https://www.econbiz.de/10010332645