Data science for assessing possible tax income manipulation: The case of Italy

Marcel Ausloos, Roy Cerqueti and Tariq A. Mir

Papers from arXiv.org

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.

Date: 2017-09
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 (12)

Published in Chaos, Solitons & Fractals 104 (2017) 238-256

Downloads: (external link)
http://arxiv.org/pdf/1709.02129 Latest version (application/pdf)

Related works:
Journal Article: Data science for assessing possible tax income manipulation: The case of Italy (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

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 ().