IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v61y2010i3d10.1057_jors.2009.160.html
   My bibliography  Save this article

Likelihood-ratio changepoint features for consumer-behaviour models

Author

Listed:
  • A R Brentnall

    (Wolfson Institute of Preventive Medicine, Queen Mary University of London)

  • M J Crowder

    (Institute for Mathematical Sciences, Imperial College London)

  • D J Hand

    (Institute for Mathematical Sciences, Imperial College London
    Imperial College London)

Abstract

Some predictive models for customer value management might benefit from information about certain changes in individual-consumer behaviour. We take changepoint methods as the first step in producing a model-input feature for this purpose. An unusual feature in the application of changepoint methods to consumer data is there are as many streams of data as there are customers. This property is used to help decide whether an individual has changed their behaviour by ordering likelihood-ratio statistics from the changepoint models. Following a review of changepoint methods, the approach is demonstrated on cash machine transactions. Models for the amount, location and time of transaction are used and accounts exhibiting large evidence of change are examined in detail. For the data set used the approach performs sensibly. The worth of likelihood-ratio statistics to rank evidence for change is considered more generally through some of the literature.

Suggested Citation

  • A R Brentnall & M J Crowder & D J Hand, 2010. "Likelihood-ratio changepoint features for consumer-behaviour models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 462-472, March.
  • Handle: RePEc:pal:jorsoc:v:61:y:2010:i:3:d:10.1057_jors.2009.160
    DOI: 10.1057/jors.2009.160
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jors.2009.160
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/jors.2009.160?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
    2. repec:bla:jorssc:v:57:y:2008:i:1:p:43-59 is not listed on IDEAS
    3. Bradley P. Carlin & Alan E. Gelfand & Adrian F. M. Smith, 1992. "Hierarchical Bayesian Analysis of Changepoint Problems," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(2), pages 389-405, June.
    4. Ashish Sen & S. Srivastava, 1975. "On tests for detecting change in mean when variance is unknown," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 27(1), pages 479-486, December.
    5. G. Yi & S. Coleman & Q. Ren, 2006. "CUSUM method in predicting regime shifts and its performance in different stock markets allowing for transaction fees," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(7), pages 647-661.
    6. Peter S. Fader & Bruce G. S. Hardie & Chun-Yao Huang, 2004. "A Dynamic Changepoint Model for New Product Sales Forecasting," Marketing Science, INFORMS, vol. 23(1), pages 50-65, October.
    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. David M. Ritzwoller & Joseph P. Romano, 2019. "Uncertainty in the Hot Hand Fallacy: Detecting Streaky Alternatives to Random Bernoulli Sequences," Papers 1908.01406, arXiv.org, revised Apr 2021.
    2. 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.
    3. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "Testing Many Moment Inequalities," CeMMAP working papers 65/13, Institute for Fiscal Studies.
    4. Fitzpatrick, Matthew, 2014. "Geometric ergodicity of the Gibbs sampler for the Poisson change-point model," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 55-61.
    5. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    6. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    7. Rute M. Caeiro & Pedro C. Vicente, 2020. "Knowledge of vitamin A deficiency and crop adoption: Evidence from a field experiment in Mozambique," Agricultural Economics, International Association of Agricultural Economists, vol. 51(2), pages 175-190, March.
    8. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio-Codina, 2020. "Estimating the Production Function for Human Capital: Results from a Randomized Controlled Trial in Colombia," American Economic Review, American Economic Association, vol. 110(1), pages 48-85, January.
    9. Bhalotra, Sonia & Clarke, Damian & Mühlrad, Hanna & Palme, Mårten, 2021. "Health and Labor Market Impacts of Twin Birth : Evidence from a Swedish IVF Policy Mandate," The Warwick Economics Research Paper Series (TWERPS) 1391, University of Warwick, Department of Economics.
    10. John M. Maheu & Stephen Gordon, 2008. "Learning, forecasting and structural breaks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 553-583.
    11. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    12. Jaschke Philipp & Sulin Sardoschau & Marco Tabellini, 2021. "Scared Straight? Threat and Assimilation of Refugees in Germany," RF Berlin - CReAM Discussion Paper Series 2136, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    13. Yanwen Wang & Chunhua Wu & Ting Zhu, 2019. "Mobile Hailing Technology and Taxi Driving Behaviors," Marketing Science, INFORMS, vol. 38(5), pages 734-755, September.
    14. Henning Hermes & Philipp Lergetporer & Fabian Mierisch & Frauke Peter & Simon Wiederhold, 2023. "Discrimination on the Child Care Market: A Nationwide Field Experiment," Working Papers 225, Bavarian Graduate Program in Economics (BGPE).
    15. Orazio Attanasio & Helen Baker-Henningham & Raquel Bernal & Costas Meghir & Diana Pineda & Marta Rubio-Codina, 2022. "Early Stimulation and Nutrition: The Impacts of a Scalable Intervention," Journal of the European Economic Association, European Economic Association, vol. 20(4), pages 1395-1432.
    16. Grácio, Matilde & Vicente, Pedro C., 2021. "Information, get-out-the-vote messages, and peer influence: Causal effects on political behavior in Mozambique," Journal of Development Economics, Elsevier, vol. 151(C).
    17. Narayanaswamy Balakrishnan & Laurent Bordes & Christian Paroissin & Jean-Christophe Turlot, 2016. "Single change-point detection methods for small lifetime samples," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(5), pages 531-551, July.
    18. Bill Russell & Dooruj Rambaccussing, 2019. "Breaks and the statistical process of inflation: the case of estimating the ‘modern’ long-run Phillips curve," Empirical Economics, Springer, vol. 56(5), pages 1455-1475, May.
    19. Pierfrancesco Rolla & Patricia Justino, 2022. "The social consequences of organized crime in Italy," WIDER Working Paper Series wp-2022-106, World Institute for Development Economic Research (UNU-WIDER).
    20. Chicu, Mark & Masten, Matthew A., 2013. "A specification test for discrete choice models," Economics Letters, Elsevier, vol. 121(2), pages 336-339.

    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:pal:jorsoc:v:61:y:2010:i:3:d:10.1057_jors.2009.160. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    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.