A Stackelberg game for the Italian tax evasion problem

Autor: Daniele Gervasio, Gianfranco Gambarelli, Daniel Faccini, Francesca Maggioni
Rok vydání: 2021
Předmět:
Zdroj: Computational Management Science. 19:295-307
ISSN: 1619-6988
1619-697X
DOI: 10.1007/s10287-021-00416-6
Popis: In this paper, we consider the problem of tax evasion, which occurs whenever an individual or business ignores tax laws. Fighting tax evasion is the main task of the Economic and Financial Military Police, which annually performs fiscal controls to track down and prosecute evaders at national level. Due to limited financial resources, the tax inspector is unable to audit the population entirely. In this article, we propose a model to assist the Italian tax inspector (Guardia di Finanza, G.d.F.) in allocating its budget among different business clusters, via a controller-controlled Stackelberg game. The G.d.F. is seen as the leader, while potential evaders are segmented into classes according to their business sizes, as set by the Italian regulatory framework. Numerical results on the real Italian case for fiscal year 2015 are provided. Insights on the optimal number of controls the inspector will have to perform among different business clusters are discussed and compared to the strategy implemented by the G.d.F.
Databáze: OpenAIRE