Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/129554
Authors: 
Doukhan, Paul
Lang, Gabriel
Leucht, Anne
Neumann, Michael H.
Year of Publication: 
2014
Series/Report no.: 
Working Paper Series, Department of Economics, University of Mannheim 14-01
Abstract: 
In this paper, we propose a model-free bootstrap method for the empirical process under absolute regularity. More precisely, consistency of an adapted version of the so-called dependent wild bootstrap, that was introduced by Shao (2010) and is very easy to implement, is proved under minimal conditions on the tuning parameter of the procedure. We apply our results to construct confidence intervals for unknown parameters and to approximate critical values for statistical tests. A simulation study shows that our method is competitive to standard block bootstrap methods in finite samples.
Subjects: 
Absolute regularity
bootstrap
empirical process
time series
V -statistics
quantiles
Kolmogorov-Smirnov test
JEL: 
C14
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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