IDEAS home Printed from https://ideas.repec.org/a/bla/abacus/v43y2007i3p241-264.html

Forecasting Corporate Bankruptcy: Optimizing the Performance of the Mixed Logit Model

Author

Listed:
  • David A. Hensher
  • Stewart Jones

Abstract

In recent studies, Jones and Hensher (2004, 2005) provide an illustration of the usefulness of advanced probability modelling in the prediction of corporate bankruptcies, insolvencies and takeovers. Mixed logit (or random parameter logit) is the most general of these models and appears to have the greatest promise in terms of underlying behavioural realism, desirable econometric properties and overall predictive performance. It suggests a number of empirical considerations relevant to harnessing the maximum potential from this new model (as well as avoiding some of the more obvious pitfalls associated with its use). Using a three‐state failure model, the unconditional triangular distribution for random parameters offers the best population‐level predictive performance on a hold‐out sample. Further, the optimal performance for a mixed logit model arises when a weighted exogenous sample maximum likelihood (WESML) technique is applied in model estimation. Finally, we suggest an approach for testing the stability of mixed logit models by re‐estimating a selected model using varying numbers of Halton intelligent draws. Our results have broad application to users seeking to apply more accurate and reliable forecasting methodologies to explain and predict sources of firm financial distress better.

Suggested Citation

  • David A. Hensher & Stewart Jones, 2007. "Forecasting Corporate Bankruptcy: Optimizing the Performance of the Mixed Logit Model," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 241-264, September.
    • Handle: RePEc:bla:abacus:v:43:y:2007:i:3:p:241-264
    DOI: 10.1111/j.1467-6281.2007.00228.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-6281.2007.00228.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-6281.2007.00228.x?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
    ---><---

    References listed on IDEAS

    as
    1. Stewart Jones & David A. Hensher, 2007. "Evaluating the Behavioural Performance of Alternative Logit Models: An Application to Corporate Takeovers Research," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(7-8), pages 1193-1220.
    2. Revelt, David & Train, Kenneth, 2000. "Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier," Department of Economics, Working Paper Series qt1900p96t, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    3. Stewart Jones & David A. Hensher, 2007. "Evaluating the Behavioural Performance of Alternative Logit Models: An Application to Corporate Takeovers Research," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(7‐8), pages 1193-1220, September.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, Enero-Abr.
    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. E.I.T, Mouyid Islam & Hernandez, Salvador, 2012. "Multi-vehicle Collisions involving Large Trucks on Highways: An Exploratory Discrete Outcome Analysis," 53rd Annual Transportation Research Forum, Tampa, Florida, March 15-17, 2012 207113, Transportation Research Forum.
    2. Islam, Mouyid, 2015. "Multi-Vehicle Crashes Involving Large Trucks: A Random Parameter Discrete Outcome Modeling Approach," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 54(01).
    3. Esther W. Bekker-Grob & Bas Donkers & Jorien Veldwijk & Marcel F. Jonker & Sylvia Buis & Jan Huisman & Patrick Bindels, 2021. "What Factors Influence Non-Participation Most in Colorectal Cancer Screening? A Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(2), pages 269-281, March.
    4. Villas-Boas, Sofia B & Taylor, Rebecca & Krovetz, Hannah, 2016. "Willingness to Pay for Low Water Footprint Food Choices During Drought," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9vh3x180, Department of Agricultural & Resource Economics, UC Berkeley.
    5. Stephane Hess & John W. Polak, 2004. "An analysis of parking behaviour using discrete choice models calibrated on SP datasets," ERSA conference papers ersa04p60, European Regional Science Association.
    6. Nannan Kang & Erda Wang & Yang Yu, 2019. "Valuing forest park attributes by giving consideration to the tourist satisfaction," Tourism Economics, , vol. 25(5), pages 711-733, August.
    7. Masiero, Lorenzo & Rose, John M., 2013. "The role of the reference alternative in the specification of asymmetric discrete choice models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 83-92.
    8. Drake, Coleman, 2019. "What are consumers willing to pay for a broad network health plan?: Evidence from covered California," Journal of Health Economics, Elsevier, vol. 65(C), pages 63-77.
    9. Krueger, Rico & Bierlaire, Michel & Daziano, Ricardo A. & Rashidi, Taha H. & Bansal, Prateek, 2021. "Evaluating the predictive abilities of mixed logit models with unobserved inter- and intra-individual heterogeneity," Journal of choice modelling, Elsevier, vol. 41(C).
    10. Shi, Wei & Halstead, John & Huang, Ju-Chin, 2016. "Consumers’ Willingness to Pay for Locally Grown Produce: Comparison of New Hampshire and Massachusetts Results," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236109, Agricultural and Applied Economics Association.
    11. Vaiknoras, Kate & Norton, George & Alwang, Jeffrey, 2015. "Farmer preferences for attributes of conservation agriculture in Uganda," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 10(2), pages 1-16.
    12. Lauren Chenarides & Carola Grebitus & Jayson L Lusk & Iryna Printezis, 2022. "A calibrated choice experiment method," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(5), pages 971-1004.
    13. Mauricio Sarrias, 2020. "Random Parameters and Spatial Heterogeneity using Rchoice in R," REGION, European Regional Science Association, vol. 7, pages 1-19.
    14. Ku, Yu-Cheng & Wu, John, 2018. "Measuring respondent uncertainty in discrete choice experiments via utility suppression," Journal of choice modelling, Elsevier, vol. 27(C), pages 1-18.
    15. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.
    16. Yuanyuan Gu & Arne Risa Hole & Stephanie Knox, 2013. "Fitting the generalized multinomial logit model in Stata," Stata Journal, StataCorp LLC, vol. 13(2), pages 382-397, June.
    17. Talevi, Marta & Pattanayak, Subhrendu K. & Das, Ipsita & Lewis, Jessica J. & Singha, Ashok K., 2022. "Speaking from experience: Preferences for cooking with biogas in rural India," Energy Economics, Elsevier, vol. 107(C).
    18. Roemer, Nils & Müller, Sven & Voigt, Guido, 2023. "A choice-based optimization approach for contracting in supply chains," European Journal of Operational Research, Elsevier, vol. 305(1), pages 271-286.
    19. Faccioli, Michela & Czajkowski, Mikołaj & Glenk, Klaus & Martin-Ortega, Julia, 2020. "Environmental attitudes and place identity as determinants of preferences for ecosystem services," Ecological Economics, Elsevier, vol. 174(C).
    20. Tavárez, Héctor & Álamo, Carmen & Cortés,Mildred, . "Differentiated coffees and their potential markets in Puerto Rico: An economic valuation approach," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 20(02).

    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:bla:abacus:v:43:y:2007:i:3:p:241-264. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0001-3072 .

    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.