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A bootstrap causality test for covariance stationary processes

Hidalgo, Javier (2003) A bootstrap causality test for covariance stationary processes. EM (462). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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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 non-distribution free multivariate Gaussian process, say vec (B(μ)) indexed by μ Є [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 vec (B(g(μ))) is a vector with independent Brownian motion components, it implies that inferences based on vec (B(μ)) will be difficult to implement. To circumvent this problem, we propose bootstrapping the test by two alternative, although similar, algorithms showing their validity and consistency.

Item Type: Monograph (Discussion Paper)
Official URL:
Additional Information: © 2003 Javier Hidalgo
Divisions: STICERD
Subjects: H Social Sciences > HB Economic Theory
JEL classification: C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models
Date Deposited: 09 Jul 2008 14:46
Last Modified: 21 Jan 2021 00:44

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