IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v56y2019i1d10.1007_s00181-017-1356-9.html
   My bibliography  Save this article

Optimal auditing of social benefit fraud: a case study

Author

Listed:
  • Leif Appelgren

    (Linkoping University)

Abstract

The aim of this paper is to study the effect of different audit strategies on fraud in one particular social benefit system in Sweden. The efficiency of different audit strategies is compared using a computer-based optimization algorithm. Two types of audit strategies are used. One is to adapt the audit intensity to the propensity for errors and fraud in different segments of the group studied. This type of strategy is denoted segmentation strategy. The second type of audit strategy is based on adaptation of behaviour through information. The model developed by Erard and Feinstein for tax auditing is adapted for benefit fraud. In this model, the audit intensity is controlled by a variable, and the auditees are informed of the relationship between control variable and audit intensity. The control variable used in this paper is the benefit amount claimed during a certain period. As the audit intensity increases with the claim amount, the rational fraudster understands that reducing the amount of fraud decreases the risk of being audited. This type of strategy is denoted information strategy. One main result is that the Erard and Feinstein model can be successfully adapted to benefit fraud. Using coarse estimates of audit unit costs, the result of the study is that all persons should be audited. For higher audit costs, it is shown that the information strategy is much more effective when compared to the segmentation strategy.

Suggested Citation

  • Leif Appelgren, 2019. "Optimal auditing of social benefit fraud: a case study," Empirical Economics, Springer, vol. 56(1), pages 203-231, January.
    • Handle: RePEc:spr:empeco:v:56:y:2019:i:1:d:10.1007_s00181-017-1356-9
    DOI: 10.1007/s00181-017-1356-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-017-1356-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00181-017-1356-9?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. Anastasopoulos, Nikolaos P. & Anastasopoulos, Markos P., 2012. "The evolutionary dynamics of audit," European Journal of Operational Research, Elsevier, vol. 216(2), pages 469-476.
    2. Henrik Jacobsen Kleven & Martin B. Knudsen & Claus Thustrup Kreiner & Søren Pedersen & Emmanuel Saez, 2011. "Unwilling or Unable to Cheat? Evidence From a Tax Audit Experiment in Denmark," Econometrica, Econometric Society, vol. 79(3), pages 651-692, May.
    3. Allingham, Michael G. & Sandmo, Agnar, 1972. "Income tax evasion: a theoretical analysis," Journal of Public Economics, Elsevier, vol. 1(3-4), pages 323-338, November.
    4. Reinganum, Jennifer F & Wilde, Louis L, 1986. "Equilibrium Verification and Reporting Policies in a Model of Tax Compliance," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 27(3), pages 739-760, October.
    5. John Hasseldine & Peggy Hite & Simon James & Marika Toumi, 2007. "Persuasive Communications: Tax Compliance Enforcement Strategies for Sole Proprietors," Contemporary Accounting Research, John Wiley & Sons, vol. 24(1), pages 171-194, March.
    6. Slemrod, Joel & Blumenthal, Marsha & Christian, Charles, 2001. "Taxpayer response to an increased probability of audit: evidence from a controlled experiment in Minnesota," Journal of Public Economics, Elsevier, vol. 79(3), pages 455-483, March.
    7. Yaniv, Gideon, 1997. "Welfare fraud and welfare stigma," Journal of Economic Psychology, Elsevier, vol. 18(4), pages 435-451, June.
    8. Gerty J. L. M. Lensvelt‐Mulders & Peter G. M. Van Der Heijden & Olav Laudy & Ger Van Gils, 2006. "A validation of a computer‐assisted randomized response survey to estimate the prevalence of fraud in social security," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(2), pages 305-318, March.
    9. Brian Erard & Jonathan S. Feinstein, 1994. "Honesty and Evasion in the Tax Compliance Game," RAND Journal of Economics, The RAND Corporation, vol. 25(1), pages 1-19, Spring.
    10. Douglas Wolf & David Greenberg, 1986. "The Dynamics of Welfare Fraud: An Econometric Duration Model in Discrete Time," Journal of Human Resources, University of Wisconsin Press, vol. 21(4), pages 437-455.
    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. Appelgren, Leif, 2020. "A survey of models for determining optimal audit strategies," Advances in accounting, Elsevier, vol. 48(C).
    2. Eduardo Zilberman, 2016. "Audits or Distortions: The Optimal Scheme to Enforce Self-Employment Income Taxes," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 18(4), pages 511-544, August.
    3. Phillips, Mark D., 2014. "Deterrence vs. gamesmanship: Taxpayer response to targeted audits and endogenous penalties," Journal of Economic Behavior & Organization, Elsevier, vol. 100(C), pages 81-98.
    4. Colin C. Williams, 2014. "Confronting the Shadow Economy," Books, Edward Elgar Publishing, number 15370.
    5. Giulia Mascagni, 2018. "From The Lab To The Field: A Review Of Tax Experiments," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 273-301, April.
    6. Dina Pomeranz & José Vila-Belda, 2019. "Taking State-Capacity Research to the Field: Insights from Collaborations with Tax Authorities," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 755-781, August.
    7. Castro, Lucio & Scartascini, Carlos, 2015. "Tax compliance and enforcement in the pampas evidence from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 65-82.
    8. James Alm & Lilith Burgstaller & Arrita Domi & Amanda März & Matthias Kasper, 2023. "Nudges, Boosts, and Sludge: Using New Behavioral Approaches to Improve Tax Compliance," Economies, MDPI, vol. 11(9), pages 1-22, September.
    9. Pickhardt, Michael & Prinz, Aloys, 2014. "Behavioral dynamics of tax evasion – A survey," Journal of Economic Psychology, Elsevier, vol. 40(C), pages 1-19.
    10. Biddle, Nicholas & Fels, Katja M. & Sinning, Mathias, 2018. "Behavioral insights on business taxation: Evidence from two natural field experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 18(C), pages 30-49.
    11. Belnap, Andrew & Welsch, Anthony & Williams, Braden, 2023. "Remote tax authority," Journal of Accounting and Economics, Elsevier, vol. 75(2).
    12. Justin E. Holz & John A. List & Alejandro Zentner & Marvin Cardoza & Joaquin Zentner, 2020. "The $100 Million Nudge: Increasing Tax Compliance of Businesses and the Self-Employed using a Natural Field Experiment," NBER Working Papers 27666, National Bureau of Economic Research, Inc.
    13. Biddle, Nicholas & Fels, Katja & Sinning, Mathias, 2017. "Behavioral insights and business taxation: Evidence from two randomized controlled trials," Ruhr Economic Papers 698, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    14. Dong, Sarah Xue & Sinning, Mathias, 2022. "Trying to Make a Good First Impression: A Natural Field Experiment to Engage New Entrants to the Tax System," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 100(C).
    15. Battiston, Pietro & Gamba, Simona, 2016. "The impact of social pressure on tax compliance: A field experiment," International Review of Law and Economics, Elsevier, vol. 46(C), pages 78-85.
    16. Alm, James & Shimshack, Jay, 2014. "Environmental Enforcement and Compliance: Lessons from Pollution, Safety, and Tax Settings," Foundations and Trends(R) in Microeconomics, now publishers, vol. 10(4), pages 209-274, December.
    17. Sinning, Mathias & Zhang, Yinjunjie, 2023. "Social norms or enforcement? A natural field experiment to improve traffic and parking fine compliance," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 43-60.
    18. Pietro Battiston & Simona Gamba, 2013. "Is Tax Compliance a Social Norm? A Field Experiment," Working Papers 249, University of Milano-Bicocca, Department of Economics, revised Jul 2013.
    19. Barbara Hartl & Eva Hofmann & Katharina Gangl & Martina Hartner-Tiefenthaler & Erich Kirchler, 2015. "Does the Sole Description of a Tax Authority Affect Tax Evasion? - The Impact of Described Coercive and Legitimate Power," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-19, April.
    20. Bag, Parimal K. & Wang, Peng, 2021. "Income tax evasion and audits under common and idiosyncratic shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 99-116.

    More about this item

    Keywords

    Auditing; Fraud; Mathematical models; Social welfare programs;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing

    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:spr:empeco:v:56:y:2019:i:1:d:10.1007_s00181-017-1356-9. 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.springer.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.