IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-00176083.html
   My bibliography  Save this paper

Mixing Kohonen Algorithm, Markov Switching Model and Detection of Multiple Change-Points: An Application to Monetary History

Author

Listed:
  • Marie-Thérèse Boyer-Xambeu

    (LED - Laboratoire d'Economie Dionysien - UP8 - Université Paris 8 Vincennes-Saint-Denis)

  • Ghislain Deleplace

    (LED - Laboratoire d'Economie Dionysien - UP8 - Université Paris 8 Vincennes-Saint-Denis)

  • Patrice Gaubert

    (SAMOS - Statistique Appliquée et MOdélisation Stochastique - UP1 - Université Paris 1 Panthéon-Sorbonne, ERUDITE - Equipe de Recherche sur l’Utilisation des Données Individuelles en lien avec la Théorie Economique - UPEM - Université Paris-Est Marne-la-Vallée - UPEC UP12 - Université Paris-Est Créteil Val-de-Marne - Paris 12)

  • Lucien Gillard

    (LED - Laboratoire d'Economie Dionysien - UP8 - Université Paris 8 Vincennes-Saint-Denis)

  • Madalina Olteanu

    (SAMOS - Statistique Appliquée et MOdélisation Stochastique - UP1 - Université Paris 1 Panthéon-Sorbonne, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

The present paper aims at locating the breakings of the integration process of an international system observed during about 50 years in the 19th century. A historical study could link them to special events, which operated as exogenous shocks on this process. The indicator of integration used is the spread between the highest and the lowest among the London, Hamburg and Paris gold-silver prices. Three algorithms are combined to study this integration: a periodization obtained with the SOM algorithm is confronted to the estimation of a two-regime Markov switching model, in order to give an interpretation of the changes of regime; in the same time change-points are identified over the whole period providing a more precise interpretation of the various types of regulation.

Suggested Citation

  • Marie-Thérèse Boyer-Xambeu & Ghislain Deleplace & Patrice Gaubert & Lucien Gillard & Madalina Olteanu, 2007. "Mixing Kohonen Algorithm, Markov Switching Model and Detection of Multiple Change-Points: An Application to Monetary History," Post-Print hal-00176083, HAL.
  • Handle: RePEc:hal:journl:hal-00176083
    Note: View the original document on HAL open archive server: https://hal.science/hal-00176083
    as

    Download full text from publisher

    File URL: https://hal.science/hal-00176083/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marie Cottrell & Patrice Gaubert & Patrick Letremy & Patrick Rousset, 1999. "Analyzing and representing multidimensional quantitative and qualitative data: Demographic study of the Rhône valley. The domestic consumption of the Canadian families," Cahiers de la Maison des Sciences Economiques r99009, Université Panthéon-Sorbonne (Paris 1).
    2. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    3. Marie Cottrell & Patrice Gaubert & Patrick Letremy & Patrick Rousset, 1999. "Analyzing and representing multidimensional quantitative and qualitative data: Demographic study of the Rhône valley. The domestic consumption of the Canadian families," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03707207, HAL.
    4. Cottrell, M. & Gaubert, P. & Rousset, P. & Letremy, P., 1999. "Analyzing and Representing Multidimentional Quantitative an Qualitative Data: Demographic Study of the Rhone Valley. The Domestic Consumption of the Canadian Families," Papiers d'Economie Mathématique et Applications 1999-09, Université Panthéon-Sorbonne (Paris 1).
    Full references (including those not matched with items on IDEAS)

    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. Marie-Th'er`ese Boyer-Xambeu & Ghislain Deleplace & Patrice Gaubert & Lucien Gillard & Madalina Olteanu, 2007. "Mixing Kohonen Algorithm, Markov Switching Model and Detection of Multiple Change-Points: An Application to Monetary History," Papers 0710.0745, arXiv.org.
    2. Marie Cottrell & Patrice Gaubert, 2003. "Efficient estimators : the use of neural networks to construct pseudo panels," Post-Print hal-00122817, HAL.
    3. Marie Cottrell & Patrice Gaubert, 2003. "Efficient estimators : the use of neural networks to construct pseudo panels," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00122817, HAL.
    4. Patrick Letrémy & Marie Cottrell & Patrice Gaubert & Joseph Rynkiewicz, 2007. "Dynamical Equilibrium, trajectories study in an economical system. The case of the labor market," Post-Print hal-00141463, HAL.
    5. Milan Kumar Das & Anindya Goswami, 2019. "Testing of binary regime switching models using squeeze duration analysis," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-20, March.
    6. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    7. Chkili, Walid & Nguyen, Duc Khuong, 2014. "Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 31(C), pages 46-56.
    8. Manuela Goretti, 2005. "The Brazilian currency turmoil of 2002: a nonlinear analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(4), pages 289-306.
    9. David Andolfatto & Paul Gomme, 2003. "Monetary Policy Regimes and Beliefs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(1), pages 1-30, February.
    10. Valentina Aprigliano & Danilo Liberati, 2021. "Using Credit Variables to Date Business Cycle and to Estimate the Probabilities of Recession in Real Time," Manchester School, University of Manchester, vol. 89(S1), pages 76-96, September.
    11. DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    12. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    13. Xi, Xiaojing & Mamon, Rogemar, 2011. "Parameter estimation of an asset price model driven by a weak hidden Markov chain," Economic Modelling, Elsevier, vol. 28(1-2), pages 36-46, January.
    14. Anne Morrison Piehl & Suzanne J. Cooper & Anthony A. Braga & David M. Kennedy, 2003. "Testing for Structural Breaks in the Evaluation of Programs," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 550-558, August.
    15. Sarah Arndt & Zeno Enders, 2023. "The Transmission of Supply Shocks in Different Inflation Regimes," CESifo Working Paper Series 10839, CESifo.
    16. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    17. Perron, Pierre & Wada, Tatsuma, 2016. "Measuring business cycles with structural breaks and outliers: Applications to international data," Research in Economics, Elsevier, vol. 70(2), pages 281-303.
    18. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    19. Carol Alexander & Anca Dimitriu, 2003. "Equity Indexing: Conitegration and Stock Price Dispersion: A Regime Switiching Approach to market Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2003-02, Henley Business School, University of Reading.
    20. Nemati, Mehdi & Saghaian, Sayed H., 2016. "Dynamics of Price Adjustment in Qualitatively Differentiated Markets in the U.S.: The Case of Organic and Conventional Apples," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 229950, Southern Agricultural Economics Association.

    More about this item

    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:hal:journl:hal-00176083. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.