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Alternative Methodology for Turning-Point Detection in Business Cycle : A Wavelet Approach

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  • Peter Martey Addo

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, Università Ca' Foscari of Venice - Department of Economics)

  • Monica Billio

    ()
    (Università Ca' Foscari of Venice - Department of Economics)

  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

Abstract

We provide a signal modality analysis to characterize and detect nonlinearity schemes in the US Industrial Production Index time series. The analysis is achieved by using the recently proposed 'delay vector variance ' (DVV) method, which examines local predictability of a signal in the phase space to detect the presence of determinism and nonlinearity in a time series. Optimal embedding parameters used in the DVV analysis are obtained via a differential entropy based method using wavelet-based surrogates. A complex Morlet wavelet is employed to detect and characterize the US business cycle. A comprehensive analysis of the feasibility of this approach is provided. Our results coincide with the business cycles peaks and troughs dates published by the National Bureau of Economic Research (NBER).

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Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00694420.

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Date of creation: Apr 2012
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Handle: RePEc:hal:cesptp:halshs-00694420

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Keywords: Nonparametric methods; STAR models; business cycles.;

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  1. Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
  2. Gallegati Marco & Gallegati Mauro, 2007. "Wavelet Variance Analysis of Output in G-7 Countries," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(3), pages 1-25, September.
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Cited by:
  1. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Turning point chronology for the Euro-Zone: A Distance Plot Approach," Documents de travail du Centre d'Economie de la Sorbonne 13025r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Oct 2013.
  2. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Nonlinear Dynamics and Recurrence Plots for Detecting Financial Crisis," Documents de travail du Centre d'Economie de la Sorbonne 13024, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

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