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Cycles de la production industrielle : une analyse historique dans le domaine des fréquences

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  • Pierre Villa
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    [fre] Cycles de la production industrielle : une analyse historique dans le domaine des fréquences par Pierre Villa Nous étudions les cycles par la méthode ARFIMA. Nous calculons des séries mensuelles de taux de chômage et de production industrielle, puis nous les filtrons par Holt et Winters puis par de Geweke et Porter-Husak pour retirer la tendance à mémoire longue correspondant à un processus d'intégration fractionnaire. Nous estimons les fluctuations mesurées par la différence entre la série corrigée des variations saisonnières et la tendance longue mesurée par la Fourier inverse du processus fractionnaire. Il n'y a pas de cycle régulier Selon la première interprétation, il y un effet de " cliquet ". Selon la deuxième, l'État a depuis la seconde guerre mondiale réduit les fluctuations de forte amplitude enregistrées auparavant par sa gestion de l'activité. Selon la troisième, les chocs aléatoires observés correspondent à une théorie des cycles réels. [eng] Industrial production cycles: a historical analysis of frequencies by Pierre Villa This paper uses the ARFIMA method to study industrial production cycles. We calculate monthly industrial production and unemployment rate data. We then filter them using "Holt and Winters" and then "Geweke and Porter-Husak" to find the long-run memory trend corresponding to a fractional degree of integration. We estimate the fluctuations, which are measured by the difference between the seasonally adjusted series and the long-run memory trend as measured by the inverse Fourier transform. No regular cycle is found. The first interpretation of this is that a "ratchet" effect is at work. The second interpretation is that the government has stabilised the economy using Keynesian policies since the Second World War. A third interpretation is that the observed random shocks are related to the real business cycle theory.

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    Article provided by Programme National Persée in its journal Économie & prévision.

    Volume (Year): 137 (1999)
    Issue (Month): 1 ()
    Pages: 95-108

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    Handle: RePEc:prs:ecoprv:ecop_0249-4744_1999_num_137_1_5949
    Note: DOI:10.3406/ecop.1999.5949
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    1. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-277, July.
    2. Diebold, Francis X. & Rudebusch, Glenn D., 1989. "Long memory and persistence in aggregate output," Journal of Monetary Economics, Elsevier, vol. 24(2), pages 189-209, September.
    3. Martin, Philippe & Ann Rogers, Carol, 2000. "Long-term growth and short-term economic instability," European Economic Review, Elsevier, vol. 44(2), pages 359-381, February.
    4. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
    5. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-328, April.
    6. Jacky Fayolle & Alexandre Mathis, 1993. "Tendances et cycles stylisés dans les pays du G7 - Une approche stochastique," Revue de l'OFCE, Programme National Persée, vol. 47(1), pages 201-233.
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