IDEAS home Printed from https://ideas.repec.org/p/mse/cesdoc/12023r.html
   My bibliography  Save this paper

Studies in Nonlinear Dynamics and Wavelets for Business Cycle Analysis

Author

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)

Suggested Citation

  • Peter Martey Addo & Monica Billio & Dominique Guegan, 2012. "Studies in Nonlinear Dynamics and Wavelets for Business Cycle Analysis," Documents de travail du Centre d'Economie de la Sorbonne 12023r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Nov 2013.
    • Handle: RePEc:mse:cesdoc:12023r
    as

    Download full text from publisher

    File URL: https://mse.univ-paris1.fr/pub/mse/CES2012/12023R.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ramsey James B. & Lampart Camille, 1998. "The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-22, April.
    2. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    3. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro area," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00423890, HAL.
    4. Michael ARTIS & Massimiliano MARCELLINO & Tommaso PROIETTI, 2002. "Dating the Euro Area Business Cycle," Economics Working Papers ECO2002/24, European University Institute.
    5. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    6. Sichel, Daniel E, 1993. "Business Cycle Asymmetry: A Deeper Look," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 224-236, April.
    7. Addo, Peter Martey & Billio, Monica & Guégan, Dominique, 2013. "Nonlinear dynamics and recurrence plots for detecting financial crisis," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 416-435.
    8. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Understanding Exchange Rates Dynamics," Documents de travail du Centre d'Economie de la Sorbonne 13023, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. 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 13025, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    10. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    11. Peter Martey Addo & Monica Billio & Dominique Guegan, 2011. "A test for a new modelling : The Univariate MT-STAR Model," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00659158, HAL.
    12. Ashley, Richard A & Patterson, Douglas M, 1989. "Linear versus Nonlinear Macroeconomies: A Statistical Test," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 685-704, August.
    13. Jensen Mark J., 1999. "An Approximate Wavelet MLE of Short- and Long-Memory Parameters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(4), pages 1-17, January.
    14. Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
    15. repec:bla:econom:v:64:y:1997:i:255:p:441-60 is not listed on IDEAS
    16. 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.
    17. Wesley Clair Mitchell, 1927. "Business Cycles: The Problem and Its Setting," NBER Books, National Bureau of Economic Research, Inc, number mitc27-1.
    18. Jacques Anas & Monica Billio & Laurent Ferrara & Gian Luigi Mazzi, 2008. "A System For Dating And Detecting Turning Points In The Euro Area," Manchester School, University of Manchester, vol. 76(5), pages 549-577, September.
    19. Brock, William A. & Sayers, Chera L., 1988. "Is the business cycle characterized by deterministic chaos?," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 71-90, July.
    20. Francisco Craveiro Dias, 2003. "Nonlinearities over the Business Cycle: an Application of the Smooth Transition Autoregressive Model to characterize GDP dynamics for the Euro-area and Portugal," Working Papers w200309, Banco de Portugal, Economics and Research Department.
    21. Wesley Clair Mitchell, 1927. "Introductory pages to "Business Cycles: The Problem and Its Setting"," NBER Chapters, in: Business Cycles: The Problem and Its Setting, pages -23, National Bureau of Economic Research, Inc.
    22. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emmanuel Numapau Gyamfi & Kwabena A. Kyei, 2016. "Modeling Stock Market Returns under Self-exciting Threshold Autoregressive Model: Evidence from West Africa," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1194-1199.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Sandberg, Rickard, 2016. "Trends, unit roots, structural changes, and time-varying asymmetries in U.S. macroeconomic data: the Stock and Watson data re-examined," Economic Modelling, Elsevier, vol. 52(PB), pages 699-713.
    3. Alejandro López-Vera & Andrés D. Pinchao-Rosero & Norberto Rodríguez-Niño, 2018. "Non-Linear Fiscal Multipliers for Public Expenditure and Tax Revenue in Colombia," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 36(85), pages 48-64, November.
    4. Rodriguez Gabriel, 2007. "Application of Three Alternative Approaches to Identify Business Cycles in Peru," Working Papers 2007-007, Banco Central de Reserva del Perú.
    5. Steven Cook & Alan Speight, 2006. "International Business Cycle Asymmetry and Time Irreversible Nonlinearities," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(10), pages 1051-1065.
    6. Sinclair Tara M, 2009. "Asymmetry in the Business Cycle: Friedman's Plucking Model with Correlated Innovations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-31, December.
    7. Marlon Fritz & Thomas Gries & Yuanhua Feng, 2019. "Growth Trends and Systematic Patterns of Booms and Busts‐Testing 200 Years of Business Cycle Dynamics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(1), pages 62-78, February.
    8. McKay, Alisdair & Reis, Ricardo, 2008. "The brevity and violence of contractions and expansions," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 738-751, May.
    9. Kamel Helali, 2022. "Markov Switching-Vector AutoRegression Model Analysis of the Economic and Growth Cycles in Tunisia and Its Main European Partners," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 656-686, March.
    10. Arango, Luis E. & Melo, Luis F., 2006. "Expansions and contractions in Brazil, Colombia and Mexico: A view through nonlinear models," Journal of Development Economics, Elsevier, vol. 80(2), pages 501-517, August.
    11. Travis Berge & Òscar Jordà, 2013. "A chronology of turning points in economic activity: Spain, 1850–2011," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 4(1), pages 1-34, March.
    12. Knüppel, Malte, 2014. "Can Capacity Constraints Explain Asymmetries Of The Business Cycle?," Macroeconomic Dynamics, Cambridge University Press, vol. 18(1), pages 65-92, January.
    13. Basistha, Arabinda & Nelson, Charles R., 2007. "New measures of the output gap based on the forward-looking new Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 498-511, March.
    14. Clements, Michael P & Krolzig, Hans-Martin, 2003. "Business Cycle Asymmetries: Characterization and Testing Based on Markov-Switching Autoregressions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 196-211, January.
    15. Kiani, Khurshid M., 2016. "On business cycle fluctuations in USA macroeconomic time series," Economic Modelling, Elsevier, vol. 53(C), pages 179-186.
    16. Herrerias, M.J. & Ordóñez, J., 2014. "If the United States sneezes, does the world need “pain-killers”?," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 159-170.
    17. Martínez-García, Enrique & Grossman, Valerie & Mack, Adrienne, 2015. "A contribution to the chronology of turning points in global economic activity (1980–2012)," Journal of Macroeconomics, Elsevier, vol. 46(C), pages 170-185.
    18. repec:oxf:wpaper:2000-w36.2 is not listed on IDEAS
    19. Banu Tanrıöver & Rahmi Yamak, 2015. "Business Cycle Asymmetry: Deepness and Steepness in Turkey," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 18(58), pages 81-96, December.
    20. Gries Thomas & Fritz Marlon & Feng Yuanhua, 2017. "Slow Booms and Deep Busts: 160 Years of Business Cycles in Spain," Review of Economics, De Gruyter, vol. 68(2), pages 153-166, August.
    21. repec:grm:wpaper:201609 is not listed on IDEAS
    22. Liu, Yamei, 2000. "Overfitting and forecasting: linear versus non-linear time series models," ISU General Staff Papers 2000010108000014914, Iowa State University, Department of Economics.

    More about this item

    Keywords

    Business cycle; Delay Vector Variance (DVV) method; nonlinearity; surrogates wavelets;
    All these keywords.

    JEL classification:

    • 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; Diffusion Processes
    • 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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mse:cesdoc:12023r. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lucie Label (email available below). General contact details of provider: https://edirc.repec.org/data/cenp1fr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.