Arbeitspapier
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.
- Language
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Englisch
- Bibliographic citation
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Series: Volkswirtschaftliche Diskussionsreihe ; No. 322
- Classification
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Wirtschaft
Methodological Issues: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
- Subject
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Spatial econometrics
Paired bootstrap
Wild bootstrap
Parameter inference
- Event
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Geistige Schöpfung
- (who)
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Klarl, Torben
- Event
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Veröffentlichung
- (who)
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Universität Augsburg, Institut für Volkswirtschaftslehre
- (where)
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Augsburg
- (when)
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2013
- Handle
- Last update
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10.03.2025, 11:41 AM CET
Data provider
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Klarl, Torben
- Universität Augsburg, Institut für Volkswirtschaftslehre
Time of origin
- 2013
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Evaluating Neural Spatial Interaction. Modelling By Bootstrapping
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