Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/129571
Authors: 
Jentsch, Carsten
Paparoditis, Efstathios
Politis, Dimitris N.
Year of Publication: 
2014
Series/Report no.: 
Working Paper Series, Department of Economics, University of Mannheim 14-18
Abstract: 
We develop some asymptotic theory for applications of block bootstrap resampling schemes to multivariate integrated and cointegrated time series. It is proved that a multivariate, continuous-path block bootstrap scheme applied to a full rank integrated process, succeeds in estimating consistently the distribution of the least squares estimators in both, the regression and the spurious regression case. Furthermore, it is shown that the same block resampling scheme does not succeed in estimating the distribution of the parameter estimators in the case of cointegrated time series. For this situation, a modified block resampling scheme, the so-called residual based block bootstrap, is investigated and its validity for approximating the distribution of the regression parameters is established. The performance of the proposed block bootstrap procedures is illustrated in a short simulation study.
Subjects: 
Block bootstrap
bootstrap consistency
spurious regression
functional limit theorem
continuous-path block bootstrap
model-based block bootstrap
JEL: 
C15
C32
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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