Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/129571 
Erscheinungsjahr: 
2014
Schriftenreihe/Nr.: 
Working Paper Series No. 14-18
Verlag: 
University of Mannheim, Department of Economics, Mannheim
Zusammenfassung: 
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.
Schlagwörter: 
Block bootstrap
bootstrap consistency
spurious regression
functional limit theorem
continuous-path block bootstrap
model-based block bootstrap
JEL: 
C15
C32
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
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