The wild bootstrap, tamed at last
The wild bootstrap is studied in the context of regression models with heteroskedastic disturbances. We show that, in one very specific case, perfect bootstrap inference is possible, and a substantial reduction in the error in the rejection probability of a bootstrap test is available much more generally. However, the version of the wild bootstrap with this desirable property is without the skewness correction afforded by the currently most popular version of the wild bootstrap. Simulation experiments show that this does not prevent the preferred version from having the smallest error in rejection probability in small and medium-sized samples.
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|Date of creation:||Sep 2008|
|Publication status:||Published in Journal of Econometrics, Elsevier, 2008, 146 (1), pp.162-169. 〈10.1016/j.jeconom.2008.08.003〉|
|Note:||View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00649250|
|Contact details of provider:|| Web page: https://hal.archives-ouvertes.fr/|
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"The Size Distortion Of Bootstrap Tests,"
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- MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.Full references (including those not matched with items on IDEAS)
- James G. MacKinnon & Halbert White, 1983. "Some Heteroskedasticity Consistent Covariance Matrix Estimators with Improved Finite Sample Properties," Working Papers 537, Queen's University, Department of Economics.
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