Nonlinear Dynamics and Wavelets for Business Cycle Analysis

Peter Martey Addo (pkaddo2000@yahoo.com), Monica Billio and Dominique Guegan (dominique.guegan@univ-paris1.fr)
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Peter Martey Addo: University of Ca’ Foscari [Venice, Italy], CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Dominique Guegan: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique

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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 Fourier and 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).

Keywords: business; cycle (search for similar items in EconPapers)
Date: 2014
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Published in Wavelet Applications in Economics and Finance, 2014, 978-3-319-07060-5. ⟨10.1007/978-3-319-07061-2_4⟩

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Related works:
Chapter: Nonlinear Dynamics and Wavelets for Business Cycle Analysis (2014)
Working Paper: Nonlinear Dynamics and Wavelets for Business Cycle Analysis (2014)
Working Paper: Nonlinear Dynamics and Wavelets for Business Cycle Analysis (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01310513

DOI: 10.1007/978-3-319-07061-2_4

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