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Efficient Committed Budget for Implementing Target Audit Probability for Many Inspectees

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  • Andrew Yim

    () (Department of Accountancy, Tilburg University, 5037 AB Tilburg, The Netherlands)

Abstract

Strategic models of auditor-inspectee interaction have neglected implementation details in multiple-inspectee settings. With multiple inspectees, the target audit probability derived from the standard analysis can be implemented with sampling plans differing in the budgets committed to support them. Overly committed audit budgets tie up unneeded resources that could have been allocated for better uses. This paper studies the minimum committed budget required to implement a target audit probability when (i) the audit sample can be contingent on "red flags" due to signals of inspectees' private information (e.g., from self-reporting) and (ii) the number of inspectees is large. It proposes an audit rule called bounded simple random sampling (SRS), which is shown to require no more committed budget to support than two other rules naturally generalized from the one-to-one analysis. When the number of inspectees is large enough, bounded SRS is nearly as good as any efficient audit rule, which demands the lowest committed budget necessary to implement the target audit probability. The results offer insights on how audit sampling plans may be formulated to reduce inefficiency and what budget usage ratios should be expected accordingly.

Suggested Citation

  • Andrew Yim, 2009. "Efficient Committed Budget for Implementing Target Audit Probability for Many Inspectees," Management Science, INFORMS, vol. 55(12), pages 2000-2018, December.
  • Handle: RePEc:inm:ormnsc:v:55:y:2009:i:12:p:2000-2018
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    File URL: http://dx.doi.org/10.1287/mnsc.1090.1083
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    References listed on IDEAS

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    Cited by:

    1. Konrad, Kai A. & Lohse, Tim & Qari, Salmai, 2014. "Deception choice and self-selection – The importance of being earnest," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 25-39.
    2. Bruno Chiarini & Simona Monteleone, 2016. "Discretionary policy, strategic complementarity and tax evasion: a strategic analysis of the Italian audit mechanism," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 33(1), pages 99-117, April.
    3. 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.
    4. Laitinen, Erkki K. & Laitinen, Teija, 2015. "A probability tree model of audit quality," European Journal of Operational Research, Elsevier, vol. 243(2), pages 665-677.
    5. DeFond, Mark & Zhang, Jieying, 2014. "A review of archival auditing research," Journal of Accounting and Economics, Elsevier, vol. 58(2), pages 275-326.
    6. Tan, Fangfang & Yim, Andrew, 2014. "Can strategic uncertainty help deter tax evasion? An experiment on auditing rules," Journal of Economic Psychology, Elsevier, vol. 40(C), pages 161-174.
    7. Lohse, Tim & Konrad, Kai A. & Qari, Salmai, 2014. "Deception Choice and Audit Design - The Importance of Being Earnest," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100577, Verein für Socialpolitik / German Economic Association.

    More about this item

    Keywords

    audit sampling plan; audit budget; tax audit; tax compliance; tax evasion; inspection game; appropriation and rescission;

    JEL classification:

    • H72 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Budget and Expenditures
    • K34 - Law and Economics - - Other Substantive Areas of Law - - - Tax Law
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing
    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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