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A bootstrap causality test for covariance stationary processes

Hidalgo, Javier (2005) A bootstrap causality test for covariance stationary processes. Journal of Econometrics, 126 (1). pp. 115-143. ISSN 0304-4076

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Abstract

This paper examines a nonparametric test for Granger-causality for a vector covariance stationary linear process under, possibly, the presence of long-range dependence. We show that the test converges to a nondistribution free multivariate Gaussian process, say indexed by μ[0,1]. Because, contrary to the scalar situation, it is not possible, except in very specific cases, to find a time transformation g(μ) such that is a vector with independent Brownian motion components, it implies that inferences based on will be difficult to implement. To circumvent this problem, we propose to bootstrapping the test by two alternative, although similar, algorithms showing their validity and consistency.

Item Type: Article
Official URL: http://www.elsevier.com/locate/jeconom
Additional Information: © 2005 Elsevier
Library of Congress subject classification: H Social Sciences > HB Economic Theory
Journal of Economic Literature Classification System: C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models
Sets: Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Collections > Economists Online
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Date Deposited: 01 Sep 2008 11:52
URL: http://eprints.lse.ac.uk/16147/

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