Abstract
We generalize the classic Allingham and Sandmo’s model of tax evasion considering heterogeneous agents with different degrees of tax morale and matchable, as opposed to non-matchable, income. The Tax Agency evolves its control scheme, maximizing the revenues from fines, and takes into account some minimal information on the taxpayers. We compare different audit policies and find that the most effective scheme remarkably depends on the way agents update the subjective probability of being audited, on the distribution of matchable income in the population as well as on the level of tax morale. Hence, different features of societies and taxpayers’ behaviors not only affect the compliance rate, as expected, but require the Tax Agency to alter its audit policy in a context-dependent way. In particular, high revenues are obtained performing random audits when agents think they are directed towards peculiar individuals and, conversely, should be biased towards low declarations when taxpayers believe audits are nonspecific or random.
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Notes
- 1.
We independently and uniformly sample the k neighbors from the whole population at each time and for each agent.
- 2.
The objective of the TA, the maximization of the sum of the fines imposed in qN audits, is a stochastic function of \(p_{1},p_{2},p_{3}\) and the approximate solution depends also on the “givens” of the society. This is to say that different enhanced schemes are likely to be developed in different societies or when agents behave differently. We mimic the TA’s search for good triplets of \(p_{1},p_{2},p_{3}\) by means of an Evolution Strategies algorithm, which is stopped after 30 functions’ evaluations and prematurely halts. Therefore, the process should be interpreted as a somewhat realistic quest by a boundedly rational TA of an audit scheme that is tailored to the society and capable of improving the revenues from fines. For additional details on Evolution Strategies see [4], for implementation details see [11].
- 3.
Technically, we obtain correlated marginals as follows: we sample from a 3-dimensional multivariate normal with the given correlations; once we have a normal vector \((z_{j}^{(I)},z_{j}^{(\rho )},z_{j}^{(\beta )})\) for each agent, we invert the appropriate cumulative probability distribution (log-normal, uniform and beta, respectively) to obtain \((I_{j},\rho _{j},\beta _{j})\) with the desired approximate correlations.
- 4.
We thank an anonymous referee for this remark.
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Acknowledgements
We thank Matteo Richiardi and Dino Rizzi for useful discussions and suggestions. The financial support of PRIN 20103S5RN3 “Robust decision making in markets and organization” is acknowledged.
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Calimani, S., Pellizzari, P. (2014). Tax Enforcement in an Agent-Based Model with Endogenous Audits. In: Leitner, S., Wall, F. (eds) Artificial Economics and Self Organization. Lecture Notes in Economics and Mathematical Systems, vol 669. Springer, Cham. https://doi.org/10.1007/978-3-319-00912-4_4
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DOI: https://doi.org/10.1007/978-3-319-00912-4_4
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