JSM 2005 - Toronto

Abstract #304305

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 231
Type: Contributed
Date/Time: Tuesday, August 9, 2005 : 8:30 AM to 10:20 AM
Sponsor: Business and Economics Statistics Section
Abstract - #304305
Title: Short- and Long-run Causality Measures
Author(s): Abderrahim Taamouti*+ and Jean-Marie Dufour
Companies: University of Montreal and University of Montreal
Address: Département de sciences économiques,, Montréal, PQ, C.P. 6128, Canada
Keywords: Indirect effect ; short-run causality measure ; long-run causality measure ; predictability ; estimation by simulation ; valid bootstrap confidence intervals
Abstract:

The concept of causality introduced by Wiener (1956) and Granger (1969) is defined in terms of predictability one period ahead. Recently, Dufour and Renault (1998) generalized this concept by considering causality at a given (arbitrary) horizon h and causality up to any given horizon h, where h is a positive integer and can be infinite. This generalization is motivated by the fact that, in the presence of an auxiliary variable Z, it is possible to have the situation where the variable Y does not cause variable X at horizon 1, but causes it at horizon h>1. In this case, this is an indirect causality transmitted by the auxiliary variable Z. Another related problem consists in measuring the importance of causality between two variables. Existing causality measures have been established only for the horizon 1 and fail to capture indirect causal effects. This paper proposes nonparametric and parametric measures for feedback and instantaneous effects at any horizon h. Parametric measures are defined in terms of impulse response coefficients of VMA representation.

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Revised March 2005