Hidalgo, Javier (2000) Nonparametric test for causality with long-range dependence. EM (387). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.
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Abstract
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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| Official URL: | http://sticerd.lse.ac.uk |
| Additional Information: | © 2000 Javier Hidalgo |
| Divisions: | Economics STICERD |
| Subjects: | H Social Sciences > HB Economic Theory |
| JEL classification: | C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C32 - Time-Series Models C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C12 - Hypothesis Testing |
| Date Deposited: | 09 Jul 2008 16:25 |
| Last Modified: | 10 Apr 2024 01:18 |
| URI: | http://eprints.lse.ac.uk/id/eprint/6866 |
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