Dynamics of tax evasion through an epidemic-like model

TL;DR

This paper models tax evasion dynamics using an epidemic-like framework, analyzing how social interactions and enforcement influence the emergence of evaders across different network structures.

Contribution

It introduces a novel epidemic-inspired model of tax evasion incorporating social influence and government enforcement, analyzing phase transitions on various network types.

Findings

Tax evasion emergence linked to phase transition in certain networks

No phase transition observed in scale-free networks

Model simulates social and enforcement effects on evasion dynamics

Abstract

In this work we study a model of tax evasion. We considered a fixed population divided in three compartments, namely honest tax payers, tax evaders and a third class between the mentioned two, which we call \textit{susceptibles} to become evaders. The transitions among those compartments are ruled by probabilities, similarly to a model of epidemic spreading. These probabilities model social interactions among the individuals, as well as the government's fiscalization. We simulate the model on fully-connected graphs, as well as on scale-free and random complex networks. For the fully-connected and random graph cases we observe that the emergence of tax evaders in the population is associated with an active-absorbing nonequilibrium phase transition, that is absent in scale-free networks.