Hidalgo, Javier (2003) A bootstrap causality test for covariance stationary processes. EM, 462. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, 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)|
|Additional Information:||© 2003 Javier Hidalgo|
|Uncontrolled Keywords:||Causality tests, long range, bootstrap tests.|
|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:||Collections > Economists Online
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Departments > Economics
|Date Deposited:||09 Jul 2008 14:46|
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