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The use of agent-based modelling to investigate tax compliance

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  • Nigar Hashimzade
  • Gareth Myles
  • Frank Page
  • Matthew Rablen

Abstract

Agent-based modelling can be used to investigate the behavioural and social aspects of tax compliance. We illustrate the approach with two models. The first model emphasises the role of occupational choice in tax compliance, and explores the effect of non-compliance on risk-taking and income distribution. The modelling of the compliance decision is discussed with an emphasis on decision-making under uncertainty and social interaction. We then add to the model a social network which governs the transmission of information on attitudes and beliefs, and investigate alternative audit strategies. A strategy of auditing a fixed number of taxpayers from each occupation dominates alternative strategies (including random and focussed strategies) in the sense of first-order stochastic dominance. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Nigar Hashimzade & Gareth Myles & Frank Page & Matthew Rablen, 2015. "The use of agent-based modelling to investigate tax compliance," Economics of Governance, Springer, vol. 16(2), pages 143-164, May.
    • Handle: RePEc:spr:ecogov:v:16:y:2015:i:2:p:143-164
    DOI: 10.1007/s10101-014-0151-8
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    References listed on IDEAS

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    Cited by:

    1. Felix Schmutz, 2016. "Measuring the Invisible: An Overview of and Outlook for Tax Non-Compliance Estimates and Measurement Methods for Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 152(II), pages 125-177, June.
    2. Victor Suslov & Tatyana Novikova & Alexander Tsyplakov, 2016. "Simulation of the Role of Government in Spatial Agent-Based Model," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 951-965.
    3. Jana Zausinová & Martin Zoričak & Marcel Vološin & Vladimír Gazda, 2020. "Aspects of complexity in citizen–bureaucrat corruption: an agent-based simulation model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 527-552, April.
    4. Di Gioacchino, Debora & Fichera, Domenico, 2020. "Tax evasion and tax morale: A social network analysis," European Journal of Political Economy, Elsevier, vol. 65(C).
    5. Felix Schmutz, 2016. "Measuring the Invisible: An Overview of and Outlook for Tax Non-Compliance Estimates and Measurement Methods for Switzerland," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 152(2), pages 125-177, April.
    6. Feng Xiong & Shaojie Xiang & Peng Jin, 2019. "Study On Computational Experiments Of C2c Tax Compliance Based On Information Of Cybermediaries," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(02), pages 1-29, March.
    7. Diego d’Andria, 2019. "Tax policy and entrepreneurial entry with information asymmetry and learning," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(5), pages 1211-1229, October.
    8. V.A. Molodykh, 2021. "Impact of Short-Term Exogenous Shocks on Taxpayer Behavior and Tax Evasion," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(2), pages 241-268.
    9. Duccio Gamannossi degl’Innocenti & Matthew D. Rablen, 2017. "Tax avoidance and optimal income tax enforcement," IFS Working Papers W17/08, Institute for Fiscal Studies.

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    More about this item

    Keywords

    Agent-based modelling; Tax evasion; Attitudes; Beliefs; Social network; Occupational choice; H26; D85; C63;
    All these keywords.

    JEL classification:

    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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