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Nonparametric test for causality with long-range dependence

Hidalgo, Javier (2000) Nonparametric test for causality with long-range dependence. EM, 387. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, London, UK.

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Identification Number: 387


This paper introduces a nonparametric Granger-causality test for covariance stationary linear processes under, possibly, the presence of long-range dependence. We show that the test is consistent and has power against contiguous alternatives converging to the parametric rate T-½. Since the test is based on estimates of the parameters of the representation of a VAR model as a, possibly, two-sided infinite distributed lag model, we first show that a modification of Hannan's (1963, 1967) estimator is root-T consistent and asymptotically normal for the coefficients of such a representation. When the data is long-range dependent this method of estimation becomes more attractive than Least Squares, since the latter can be neither root-T consistent nor asymptotically normal as is the case with short-range dependent data.

Item Type: Monograph (Discussion Paper)
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Additional Information: © 2000 Javier Hidalgo
Subjects: H Social Sciences > HB Economic Theory
Sets: Collections > Economists Online
Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Date Deposited: 09 Jul 2008 16:25
Last Modified: 01 Oct 2010 08:58

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