[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v33y1985i6p1203-1214.html
   My bibliography  Save this article

Testing the Adequacy of Markov Chain and Mover-Stayer Models as Representations of Credit Behavior

Author

Listed:
  • Halina Frydman

    (New York University, New York, New York)

  • Jarl G. Kallberg

    (New York University, New York, New York)

  • Duen-Li Kao

    (New York University, New York, New York)

Abstract
We summarize methodology for testing the compatibility of discrete time stochastic processes—stationary and nonstationary Markov chains and an extension, the mover-stayer model—with longitudinal data from an unknown empirical process. We apply this methodology to determine the suitability of these models to represent the payment behavior of a sample of retail revolving credit accounts. We are led to reject stationary and also nonstationary Markov chain models for our data and for our state space definition in favor of the mover-stayer model. The mover-stayer model, in contrast to Markov chains, incorporates a simple form of population heterogeneity. Stationary Markov chains have been used extensively in finance literature to model payment behavior of credit accounts. Our empirical study suggests, however, that stationary Markov chains may not appropriately model payment behavior. It also indicates that incorporating heterogeneity in modeling payment behavior may be more important than incorporing nonstationarity.

Suggested Citation

  • Halina Frydman & Jarl G. Kallberg & Duen-Li Kao, 1985. "Testing the Adequacy of Markov Chain and Mover-Stayer Models as Representations of Credit Behavior," Operations Research, INFORMS, vol. 33(6), pages 1203-1214, December.
    • Handle: RePEc:inm:oropre:v:33:y:1985:i:6:p:1203-1214
    DOI: 10.1287/opre.33.6.1203
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.33.6.1203
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.33.6.1203?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

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


    Cited by:

    1. So, Meko M.C. & Thomas, Lyn C., 2011. "Modelling the profitability of credit cards by Markov decision processes," European Journal of Operational Research, Elsevier, vol. 212(1), pages 123-130, July.
    2. Robert Till & David Hand, 2003. "Behavioural models of credit card usage," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1201-1220.
    3. Legrand D. F, Saint-Cyr, 2017. "Farm heterogeneity and agricultural policy impacts on size dynamics: evidence from France," Working Papers SMART 17-04, INRAE UMR SMART.
    4. Camilla Ferretti & Giampaolo Gabbi & Piero Ganugi & Federica Sist & Pietro Vozzella, 2019. "Credit Risk Migration and Economic Cycles," Risks, MDPI, vol. 7(4), pages 1-18, October.
    5. Alexandra Schwarz, 2011. "Measurement, Monitoring, and Forecasting of Consumer Credit Default Risk - An Indicator Approach Based on Individual Payment Histories," Schumpeter Discussion Papers sdp11004, Universitätsbibliothek Wuppertal, University Library.
    6. Jonathan Crook & Tony Bellotti, 2010. "Time varying and dynamic models for default risk in consumer loans," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 283-305, April.
    7. Legrand D. F. Saint-Cyr & Laurent Piet, 2017. "Movers and stayers in the farming sector: accounting for unobserved heterogeneity in structural change," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 777-795, August.
    8. Legrand D. F. Saint‐Cyr, 2022. "Heterogeneous farm‐size dynamics and impacts of subsidies from agricultural policy: Evidence from France," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 893-923, September.
    9. Saint-Cyr, Legrand D. F. & Piet, Laurent, 2014. "Movers and Stayers in the Farming Sector: Another Look at Heterogeneity in Structural Change," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 183068, European Association of Agricultural Economists.
    10. Dariusz Wędzki, 2007. "Trade credit portfolio selection – a markovian approach," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 17(2), pages 105-119.
    11. Sanjeev Mittal & Pankaj Gupta & K. Jain, 2011. "Neural network credit scoring model for micro enterprise financing in India," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 3(3), pages 224-242, October.

    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:inm:oropre:v:33:y:1985:i:6:p:1203-1214. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.