Data science for assessing possible tax income manipulation: The case of Italy
Marcel Ausloos (),
Roy Cerqueti () and
Tariq A. Mir
Papers from arXiv.org
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.
New Economics Papers: this item is included in nep-eur and nep-pbe
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed
Published in Chaos, Solitons & Fractals 104 (2017) 238-256
Downloads: (external link)
http://arxiv.org/pdf/1709.02129 Latest version (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1709.02129
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().