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Feedback, causality and distance between arma models

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  • Triacca, Umberto

Abstract

The purpose of this paper is to analyze in bivariate vector autoregression the relationship between feedback in stochastic systems, Granger causality and a measure of dissimilarity between ARMA models. In particular, we consider a bivariate vector autoregressive processes of order p (a bivariate VAR(p) process) and we prove if the distance between the univariate ARMA models implied by the VAR representation is greater than a certain number that is a function of p, then Granger causality must exist in at least one direction in the variables.

Suggested Citation

  • Triacca, Umberto, 2004. "Feedback, causality and distance between arma models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(6), pages 679-685.
    • Handle: RePEc:eee:matcom:v:64:y:2004:i:6:p:679-685
    DOI: 10.1016/j.matcom.2003.11.019
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    References listed on IDEAS

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    1. Domenico Piccolo, 1990. "A Distance Measure For Classifying Arima Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(2), pages 153-164, March.
    2. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    3. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
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    Cited by:

    1. Cook, Steven, 2008. "Further analysis of spurious causality," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 647-651.

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