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Taxpayer Behavior When Audit Rules Are Known: Evidence from Italy

Author

Listed:
  • Alessandro Santoro

    (University of Milan-Bicocca and Econpubblica, Milan, Italy, alessandro.santoro@unimib.it)

  • Carlo V. Fiorio

    (University of Milan and Econpubblica, Milan, Italy)

Abstract

Italy adopted in 1998 a peculiar audit scheme (Studi di Settore), for small and medium enterprises and the self-employed. This scheme is based on a particular interaction between the tax agency and taxpayers, where the agency unveils only part of the information used to develop its audit rule. The authors study this scheme by means of a simple theoretical model and they test it using a sample of 23,000 firms in manufacturing sectors in the 2005 tax year. A number of theoretically relevant relations are confirmed. In particular, reports made by taxpayers seem to be positively associated to the firm’s size. When taxpayers know that the probability to be audited decreases, they tend to report less. Other factors that are expected to influence the behavior of taxpayers have no or an ambiguous impact on reporting behavior.

Suggested Citation

  • Alessandro Santoro & Carlo V. Fiorio, 2011. "Taxpayer Behavior When Audit Rules Are Known: Evidence from Italy," Public Finance Review, , vol. 39(1), pages 103-123, January.
    • Handle: RePEc:sae:pubfin:v:39:y:2011:i:1:p:103-123
    DOI: 10.1177/1091142110386214
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    References listed on IDEAS

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    Cited by:

    1. Ferrara, Giancarlo & Bucci, Valeria & Campagna, Arianna, 2023. "Audit, presumptive taxation and efficiency: An integrated approach for tax compliance analysis," Economic Systems, Elsevier, vol. 47(3).
    2. Carlo Fiorio & Stefano Iacus & Alessandro Santoro, 2013. "Taxpaying response of small firms to an increased probability of audit: some evidence from Italy," Working Papers 251, University of Milano-Bicocca, Department of Economics, revised Jul 2013.
    3. Battiston, Pietro & Gamba, Simona & Santoro, Alessandro, 2024. "Machine learning and the optimization of prediction-based policies," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    4. Pickhardt, Michael & Prinz, Aloys, 2014. "Behavioral dynamics of tax evasion – A survey," Journal of Economic Psychology, Elsevier, vol. 40(C), pages 1-19.
    5. Michele Rabasco & Pietro Battiston, 2023. "Predicting the deterrence effect of tax audits. A machine learning approach," Metroeconomica, Wiley Blackwell, vol. 74(3), pages 531-556, July.

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