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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"The wild bootstrap, tamed at last,"
LSE Research Online Documents on Economics
6560, London School of Economics and Political Science, LSE Library.
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- Daniel C. Monchuk & Dermot J. Hayes & John Miranowski, 2008.
"Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States,"
Center for Agricultural and Rural Development (CARD) Publications
08-wp471, Center for Agricultural and Rural Development (CARD) at Iowa State University.
- Daniel C. Monchuk & Dermot J. Hayes & John A. Miranowski & Dayton M. Lambert, 2011. "Inference Based On Alternative Bootstrapping Methods In Spatial Models With An Application To County Income Growth In The United States," Journal of Regional Science, Wiley Blackwell, vol. 51(5), pages 880-896, December.
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- Daniel C. Monchuk & Dermot J. Hayes & John Miranowski & Dayton M. Lambert, 2010. "Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States," Center for Agricultural and Rural Development (CARD) Publications 10-wp507, Center for Agricultural and Rural Development (CARD) at Iowa State University.
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Elsevier, vol. 133(2), pages 421-441, August.
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