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

Marcel Ausloos, Roy Cerqueti and Tariq A. Mir

Chaos, Solitons & Fractals, 2017, vol. 104, issue C, 238-256

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: Data science; Benford law; Aggregated income tax; Data manipulation; Italy (search for similar items in EconPapers)
JEL-codes: C82 H71 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:104:y:2017:i:c:p:238-256

DOI: 10.1016/j.chaos.2017.08.012

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