Data science for assessing possible tax income manipulation: The case of Italy
journal contributionposted on 2018-03-22, 15:46 authored by Marcel Ausloos, Roy Cerqueti, Tariq A. Mir
This paper explores a real-world fundamental theme under a data science perspective. It specifically discusses whether fraud or manipulation can be observed in and from municipality income tax size distributions, through their aggregation from citizen fiscal reports. The study case pertains to official data obtained from the Italian Ministry of Economics and Finance over the period 2007–2011. All Italian (20) regions are considered. The considered data science approach concretizes in the adoption of the Benford first digit law as quantitative tool. Marked disparities are found, - for several regions, leading to unexpected “conclusions”. The most eye browsing regions are not the expected ones according to classical imagination about Italy financial shadow matters.
CitationChaos, Solitons and Fractals, 2017, 104, pp. 238-256
Author affiliation/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/School of Management
- AM (Accepted Manuscript)