March 13, 2019
12:50 p.m.
CORE, room C035
Network effects in an Agent-Based Model of tax evasion with social influence
Fernando Garcia Alvarado, Ca'Foscari University Venice, University Paris 1 Panthéon-Sorbonne
An Agent-Based Model accounting for tax-morale and loss-aversion was implemented over different network systems with social interactions at the local level to study the phenomenon of tax evasion. This ABM is an innovative model which integrates endogenous characteristics of heterogeneous agents and proposes a more relaxed assumption on the information exchanged between agents as compared to previous social models. Notwithstanding, the ABM manages to replicate both individual and aggregate results from previous empirical and computational models of tax evasion. Moreover, the study gives an insight on the possibility that choosing specific network structures may yield to more realistic outcomes. A clearcut novelty might be the non-linear channel through which the network centrality enhances a positive effect on the aggregated level of tax compliance. There is a large area of action for public policy makers to further research how audit rates, fines and tax morale non-linearly increase income disclosure, whereas tax rates have a non-linear negative impact on tax compliance.
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