Alternative Methodology for Turning-Point Detection in Business Cycle: A Wavelet Approach
AbstractWe 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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Bibliographic InfoPaper provided by Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne in its series Documents de travail du Centre d'Economie de la Sorbonne with number 12023.
Length: 20 pages
Date of creation: Apr 2012
Date of revision:
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Nonlinearity analysis; surrogates; Delay Vector Variance (DVV) method; wavelets; business cycle; embedding parameters.;
Other versions of this item:
- Peter Martey Addo & Monica Billio & Dominique Guegan, 2012. "Alternative Methodology for Turning-Point Detection in Business Cycle : A Wavelet Approach," UniversitÃ© Paris1 PanthÃ©on-Sorbonne (Post-Print and Working Papers) halshs-00694420, HAL.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-05-02 (All new papers)
- NEP-BEC-2012-05-02 (Business Economics)
- NEP-ECM-2012-05-02 (Econometrics)
- NEP-ETS-2012-05-02 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
- Peter Martey Addo & Monica Billio & Dominique Guegan, 2013.
"Nonlinear Dynamics and Recurrence Plots for Detecting Financial Crisis,"
UniversitÃ© Paris1 PanthÃ©on-Sorbonne (Post-Print and Working Papers)
- 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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