Data science for assessing possible tax income manipulation: The case of Italy
Abstract
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.
Keywords
Cite
@article{arxiv.1709.02129,
title = {Data science for assessing possible tax income manipulation: The case of Italy},
author = {Marcel Ausloos and Roy Cerqueti and Tariq A. Mir},
journal= {arXiv preprint arXiv:1709.02129},
year = {2018}
}
Comments
38 pages, 22 figures. To be published in Chaos, Solitons and Fractals