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The use of agent-based modelling to investigate tax compliance


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.

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  1. The computer code for the simulations we report is available on the SpringerPlus website. The code is written for Matlab but can be easily converted to run with Scilab.

  2. The advantage of the beta distribution is in the flexible choice of parameters, allowing density functions with required skewness to be obtained, and the finite support ensures robust convergence of the numerical integration.

  3. A matrix that is not symmetric captures uni-directional links. This can be used to investigate the effect of a “celebrity”.

  4. It is assumed tax authority knows that in paid employment income tax is fully deducted at source, and there is no opportunity for earning additional income that could be concealed. This assumption could be modified in a more general model to allow an additional income for individuals in employment and a possibility to evade tax on that income.

  5. In this context, strategy \(A\) dominates strategy \(B\) in the sense of first-order stochastic dominance, if for every level of revenue, \(R\), the probability of collecting at least \(R\) is higher under \(A\) than under \(B\). Equivalently, the empirical cdf of revenues collected under \(A\) is everywhere below (or to the right from) the empirical cdf of revenues collected under \(B\).


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Correspondence to Gareth D. Myles.

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Thanks are due to the ESRC for financial support under grant ES/K005944/1. Previous versions of the paper were presented at the Ottawa Workshop on Compliance and at shadow2013 in Münster. Gareth Myles worked on the paper during a visit to Bogazici University; their hospitality is appreciated.

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Hashimzade, N., Myles, G.D., Page, F. et al. The use of agent-based modelling to investigate tax compliance. Econ Gov 16, 143–164 (2015).

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