IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v37y2005i7p841-848.html
   My bibliography  Save this article

Binary choice models for rare events data: a crop insurance fraud application

Author

Listed:
  • Yufei Jin
  • Roderick Rejesus
  • Bertis Little

Abstract

This study implements a recently proposed score test that could help guide insurance fraud researchers in deciding whether to use a logit or a probit model in predicting insurance fraud probabilities, especially when the occurrence of ones in the dependent variable is much less than zeros. The test is easily implemented in a crop insurance fraud context and seems to be a promising method that could be applicable to analysing and detecting potentially fraudulent claims in various lines of insurance.

Suggested Citation

  • Yufei Jin & Roderick Rejesus & Bertis Little, 2005. "Binary choice models for rare events data: a crop insurance fraud application," Applied Economics, Taylor & Francis Journals, vol. 37(7), pages 841-848.
    • Handle: RePEc:taf:applec:v:37:y:2005:i:7:p:841-848
    DOI: 10.1080/0003684042000337433
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/0003684042000337433
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0003684042000337433?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. Dionne, Georges & Gagne, Robert, 2002. "Replacement Cost Endorsement and Opportunistic Fraud in Automobile Insurance," Journal of Risk and Uncertainty, Springer, vol. 24(3), pages 213-230, May.
    2. Artis, Manuel & Ayuso, Mercedes & Guillen, Montserrat, 1999. "Modelling different types of automobile insurance fraud behaviour in the Spanish market," Insurance: Mathematics and Economics, Elsevier, vol. 24(1-2), pages 67-81, March.
    3. Rejesus, Roderick M. & Lovell, Ashley C. & Little, Bertis B. & Cross, Mike H., 2003. "Determinants of Anomalous Prevented Planting Claims: Theory and Evidence from Crop Insurance," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 32(2), pages 1-15, October.
    4. J. M. C. Santos Silva, 2001. "A score test for non-nested hypotheses with applications to discrete data models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 577-597.
    5. El Bachir Belhadji & George Dionne & Faouzi Tarkhani, 2000. "A Model for the Detection of Insurance Fraud*," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 25(4), pages 517-538, October.
    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. Blackman, Allen & Guerrero, Santiago, 2012. "What drives voluntary eco-certification in Mexico?," Journal of Comparative Economics, Elsevier, vol. 40(2), pages 256-268.
    2. Damian Przekop, 2020. "Feature Engineering for Anti-Fraud Models Based on Anomaly Detection," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(3), pages 301-316, September.
    3. Ashok Mishra & Barry Goodwin, 2006. "Revenue insurance purchase decisions of farmers," Applied Economics, Taylor & Francis Journals, vol. 38(2), pages 149-159.
    4. M. Ritter & O. Mußhoff & M. Odening, 2014. "Minimizing Geographical Basis Risk of Weather Derivatives Using A Multi-Site Rainfall Model," Computational Economics, Springer;Society for Computational Economics, vol. 44(1), pages 67-86, June.
    5. Lu Fan & Swarn Chatterjee, 2019. "Financial Socialization, Financial Education, and Student Loan Debt," Journal of Family and Economic Issues, Springer, vol. 40(1), pages 74-85, March.
    6. Maria Figueroa-Armijos & John P. Berns, 2022. "Vulnerable Populations and Individual Social Responsibility in Prosocial Crowdfunding: Does the Framing Matter for Female and Rural Entrepreneurs?," Journal of Business Ethics, Springer, vol. 177(2), pages 377-394, May.
    7. Bayerstadler, Andreas & van Dijk, Linda & Winter, Fabian, 2016. "Bayesian multinomial latent variable modeling for fraud and abuse detection in health insurance," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 244-252.
    8. Qimeng Pan & Lysa Porth & Hong Li, 2022. "Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications," Sustainability, MDPI, vol. 14(11), pages 1-24, June.
    9. Jessica Pesantez-Narvaez & Montserrat Guillen & Manuela Alcañiz, 2021. "RiskLogitboost Regression for Rare Events in Binary Response: An Econometric Approach," Mathematics, MDPI, vol. 9(5), pages 1-21, March.
    10. Denisa BANULESCU-RADU & Meryem YANKOL-SCHALCK, 2021. "Fraud detection in the era of Machine Learning: a household insurance case," LEO Working Papers / DR LEO 2904, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    11. Sharma, S. & Walters, C., 2018. "Influence of Farm and Lease Type on Crop Insurance Returns," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277399, International Association of Agricultural Economists.
    12. Erda Wang & Zuozhi Li & Bertis B. Little & Yu Yang, 2009. "The Economic Impact of Tourism in Xinghai Park, China: A Travel Cost Value Analysis Using Count Data Regression Models," Tourism Economics, , vol. 15(2), pages 413-425, June.
    13. Theuer, Sebastian & Gottschalk, Sandra, 2008. "Die Auswirkungen des demografischen Wandels auf das Gründungsgeschehen in Deutschland," ZEW Discussion Papers 08-032, ZEW - Leibniz Centre for European Economic Research.
    14. Shenan Wu & Barry K. Goodwin & Keith Coble, 2020. "Moral hazard and subsidized crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 131-142, January.

    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. Georges Dionne & Florence Giuliano & Pierre Picard, 2009. "Optimal Auditing with Scoring: Theory and Application to Insurance Fraud," Management Science, INFORMS, vol. 55(1), pages 58-70, January.
    2. Viaene, Stijn & Ayuso, Mercedes & Guillen, Montserrat & Van Gheel, Dirk & Dedene, Guido, 2007. "Strategies for detecting fraudulent claims in the automobile insurance industry," European Journal of Operational Research, Elsevier, vol. 176(1), pages 565-583, January.
    3. Pierre Picard, 2012. "Economic Analysis of Insurance Fraud," Working Papers hal-00725561, HAL.
    4. G. Dionne & F. Giuliano & P. Picard, 2002. "Optimal auditing for insurance fraud," THEMA Working Papers 2002-32, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    5. Stijn Viaene & Guido Dedene, 2004. "Insurance Fraud: Issues and Challenges," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 29(2), pages 313-333, April.
    6. Dionne, Georges, 2012. "The empirical measure of information problems with emphasis on insurance fraud and dynamic data," Working Papers 12-10, HEC Montreal, Canada Research Chair in Risk Management.
    7. Lammers, Frauke & Schiller, Jörg, 2010. "Contract design and insurance fraud: An experimental investigation," FZID Discussion Papers 19-2010, University of Hohenheim, Center for Research on Innovation and Services (FZID).
    8. Bermúdez, Ll. & Pérez, J.M. & Ayuso, M. & Gómez, E. & Vázquez, F.J., 2008. "A Bayesian dichotomous model with asymmetric link for fraud in insurance," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 779-786, April.
    9. M. Martin Boyer, 2007. "Resistance (to Fraud) Is Futile," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 74(2), pages 461-492, June.
    10. Hyojoung Kim & Doyoung Kim & Subin Im & James W. Hardin, 2009. "Evidence of Asymmetric Information in the Automobile Insurance Market: Dichotomous Versus Multinomial Measurement of Insurance Coverage," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(2), pages 343-366, June.
    11. Silva João M. C. Santos & Tenreyro Silvana & Windmeijer Frank, 2015. "Testing Competing Models for Non-negative Data with Many Zeros," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 1-18, January.
    12. Botond Benedek & Balint Zsolt Nagy, 2023. "Traditional versus AI-Based Fraud Detection: Cost Efficiency in the Field of Automobile Insurance," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 22(2), pages 77-98.
    13. M. Dahchour & G. Dionne, 2002. "Pricing of Automobile Insurance Under Asymmetric Information : a Study on Panel Data," THEMA Working Papers 2002-12, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    14. Boyer, Martin, 2001. "Les clauses de valeur à neuf sont-elles optimales?," L'Actualité Economique, Société Canadienne de Science Economique, vol. 77(1), pages 53-74, mars.
    15. Segovia-Gonzalez, M.M. & Guerrero, F.M. & Herranz, P., 2009. "Explaining functional principal component analysis to actuarial science with an example on vehicle insurance," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 278-285, October.
    16. Dionne, Georges & Wang, Kili, 2011. "Does opportunistic fraud in automobile theft insurance fluctuate with the business cycle?," Working Papers 11-4, HEC Montreal, Canada Research Chair in Risk Management.
    17. Joao Santos Silva Santos Silva & Silvana Tenreyro & Frank Windmeijer, 2010. "Is it different for zeros? Discriminating between models for non-negative data with many zeros," CeMMAP working papers CWP20/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Bae, Taehan & Kim, Changki & Kulperger, Reginald J., 2009. "Securitization of motor insurance loss rate risks," Insurance: Mathematics and Economics, Elsevier, vol. 44(1), pages 48-58, February.
    19. Georges Dionne & Pierre-Carl Michaud & Maki Dahchour, 2004. "Separating Moral Hazard from Adverse Selection in Automobile Insurance: Longitudinal Evidence from France," Cahiers de recherche 0420, CIRPEE.
    20. Jing Ai & Patrick L. Brockett & Linda L. Golden & Montserrat Guillén, 2013. "A Robust Unsupervised Method for Fraud Rate Estimation," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(1), pages 121-143, March.

    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:taf:applec:v:37:y:2005:i:7:p:841-848. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.