Block Bootstrap Theory for Multivariate Integrated and Cointegrated Processes

Jentsch, Carsten ; Paparoditis, Efstathios ; Politis, Dimitris N.

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URL:	https://ub-madoc.bib.uni-mannheim.de/36668
URN:	urn:nbn:de:bsz:180-madoc-366688
Document Type:	Working paper
Year of publication:	2014
The title of a journal, publication series:	Working Paper Series
Volume:	14-18
Place of publication:	Mannheim
Publication language:	English
Institution:	School of Law and Economics > Statistik (Mammen)
MADOC publication series:	Department of Economics > Working Paper Series
Subject:	330 Economics
Classification:	JEL: C15 , C32,
Keywords (English):	Block bootstrap , bootstrap consistency , spurious regression , functional limit theorem , continuous-path block bootstrap , model-based block bootstrap
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.