Modeling the Impact of Information on Audits on Taxpayer Risk Profiles and Evasions

One of the most significant functions of the tax system, which characterize its various activities, includes fiscal, social, regulatory, distributive, stimulative, and control functions. For the proper functioning of each of these roles, tax monitoring is essential, a significant part of which is tax audits. However, earlier studies have shown that conducting tax audits with optimal probability is a costly procedure. Given the limited budget of tax authorities, such audits aren't always feasible. Hence, to increase tax collection, it's essential to use additional methods to encourage taxpayers to pay their taxes honestly. This study investigates a tax monitoring model that considers spreading information about potential tax audits among taxpayers as an additional incentive. Within the evolutionary approach to modeling, taxpayers are viewed as agents of the population with different risk profiles: risk-prone, risk-neutral, and risk-averse. The idea of disseminating information in the population was studied based on a Markov process in networks with varying structures. The study examined the influence of this information on the final distribution of risk profiles and taxpayer evasions. A series of experiments on modeling networks and the process of information dissemination within them was conducted. Models with artificially introduced influence centers and without them were considered. A comparative analysis of the obtained results is presented.

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