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La causalité entre la monnaie et le revenu : une analyse fondée sur un modèle VARMA-échelon

Listed author(s):
  • Dufour, Jean-Marie

    (Département de sciences économiques, Université de Montréal)

  • Tessier, David

    (Département des Relations Internationales, Banque du Canada)

Causality analysis in the sense of Wiener-Granger are usually based on a vector autoregressive (VAR) specification of the data-generating process. This is the case in particular for the numerous studies of causality between money and income in macro-economics. Since a VAR specification is typically only approximate and, most importantly, is not robust to disaggregation into subvectors, we study here causality between money and income using the more general and logically coherent framework of vector ARMA models (VARMA). To solve the identification problems associated with such models, we consider a VARMA model in echelon form, which is automatically identified. To specify the orders of the model, we use the new methodology proposed by Nsiri and Roy (1992, 1996) which is based on estimating the Kronecker indices of the model. This approach is applied to a five-variable model of the U.S. economy, containing: real income, the price level, a short-term interest rate, the monetary base and the M1 multiplier. Contrary to earlier studies, we find that monetary variables (base and multiplier) cause income (in the sense of Granger), causality being unidirectional causality in the case of the base, while the interest rate does not cause income directly but may have an indirect effect through monetary variables. The price level appears to be a passive variable with no influence on the other variables of the system. Les analyses de causalité, au sens de Wiener-Granger, sont habituellement fondées sur une spécification autorégressive (VAR) du processus générateur des données. C’est le cas, en particulier, pour les nombreuses études de causalité entre la monnaie et le revenu au niveau macroéconomique. Comme la spécification VAR ne constitue qu’une approximation et surtout n’est pas robuste à la désagrégation en sous-vecteurs, nous étudions ici la causalité entre monnaie et revenu à partir du cadre plus général et logiquement cohérent des modèles ARMA multivariés (VARMA). Pour résoudre les problèmes d’identification associés à ces modèles, nous considérons un modèle VARMA sous la forme échelon, lequel fournit automatiquement un modèle identifié. Nous utilisons, pour spécifier les ordres du modèle, la nouvelle méthodologie proposée par Nsiri et Roy (1992, 1996) et fondée sur une estimation des indices de Kronecker du modèle. Cette approche est appliquée à un modèle de l’économie américaine comprenant cinq variables : le revenu réel, le niveau des prix, un taux d’intérêt à court terme, la base monétaire et le multiplicateur de M1. Contrairement à certaines études antérieures, nous trouvons que les variables monétaires (base et multiplicateur) causent le revenu (au sens de Granger), la relation étant unidirectionnelle dans le cas de la base, tandis que le taux d’intérêt ne cause pas directement le revenu, mais a possiblement un effet indirect passant par les variables monétaires. Le niveau des prix apparaît comme une variable passive sans influence sur les autres variables du système.

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Article provided by Société Canadienne de Science Economique in its journal L'Actualité économique.

Volume (Year): 73 (1997)
Issue (Month): 1 (mars-juin-septembre)
Pages: 351-366

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Handle: RePEc:ris:actuec:v:73:y:1997:i:1:p:351-366
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  1. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-442, October.
  2. Runkle, David E, 1987. "Vector Autoregressions and Reality: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 454-454, October.
  3. Nsiri, Saïd & Roy, Roch, 1996. "Identification of Refined ARMA Echelon Form Models for Multivariate Time Series," Journal of Multivariate Analysis, Elsevier, vol. 56(2), pages 207-231, February.
  4. David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
  5. Lütkepohl, Helmut & POSKITT, D.S., 1996. "Testing for Causation Using Infinite Order Vector Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 12(01), pages 61-87, March.
  6. Eberts, R W & Steece, B M, 1984. "A Test for Granger-Causality in a Multivariate ARMA Model," Empirical Economics, Springer, vol. 9(1), pages 51-58.
  7. Sims, Christopher A, 1980. "Comparison of Interwar and Postwar Business Cycles: Monetarism Reconsidered," American Economic Review, American Economic Association, vol. 70(2), pages 250-257, May.
  8. Guilkey, David K & Salemi, Michael K, 1982. "Small Sample Properties of Three Tests for Granger-Causal Ordering in a Bivariate Stochastic System," The Review of Economics and Statistics, MIT Press, vol. 64(4), pages 668-680, November.
  9. Boudjellaba, Hafida & Dufour, Jean-Marie & Roy, Roch, 1994. "Simplified conditions for noncausality between vectors in multivariate ARMA models," Journal of Econometrics, Elsevier, vol. 63(1), pages 271-287, July.
  10. Feige, Edgar L & Pearce, Douglas K, 1979. "The Casual Causal Relationship between Money and Income: Some Caveats for Time Series Analysis," The Review of Economics and Statistics, MIT Press, vol. 61(4), pages 521-533, November.
  11. Boudjellaba, B. & Dufour, J.-M. & Roy, R., 1991. "Testing Causality Between Two Vextors in Multivariate Arma Models," Cahiers de recherche 9119, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  12. Christiano, Lawrence J. & Ljungqvist, Lars, 1988. "Money does Granger-cause output in the bivariate money-output relation," Journal of Monetary Economics, Elsevier, vol. 22(2), pages 217-235, September.
  13. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  14. Stock, James H. & Watson, Mark W., 1989. "Interpreting the evidence on money-income causality," Journal of Econometrics, Elsevier, vol. 40(1), pages 161-181, January.
  15. 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.
  16. Geweke, John & Meese, Richard & Dent, Warren, 1983. "Comparing alternative tests of causality in temporal systems : Analytic results and experimental evidence," Journal of Econometrics, Elsevier, vol. 21(2), pages 161-194, February.
  17. Lutkepohl, Helmut & Poskitt, D S, 1996. "Specification of Echelon-Form VARMA Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 69-79, January.
  18. Dufour, Jean-Marie & Tessier, David, 1993. "On the relationship between impulse response analysis, innovation accounting and Granger causality," Economics Letters, Elsevier, vol. 42(4), pages 327-333.
  19. Thoma, Mark A., 1994. "Subsample instability and asymmetries in money-income causality," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 279-306.
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