Modelling Agents' Risk Perception

One of the open issues in risk literature is the difference between risk perception and effective risk, especially when the risk is clearly defined and measured. Until now, the main focus has been given on the behaviour of individuals and the evidences of their biases according to some stimulus. Consequently, it is important to analyse what are the main reasons for those biases and identify the dimensions and mechanisms involved. To that purpose, we tackle the classic problem of tax fraud as a case study. In this paper, we will look into how agent based modelling methodology can help unfold the reasons why individuals commit errors of judgment when risk is involved.

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