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.

38 pages, 22 figures. To be published in Chaos, Solitons and Fractals

References in corpus (4)

• Benford's law and Theil transform of financial data
• Breakdown of Benford's Law for Birth Data
• Benford's law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions
• Regularities and Discrepancies of Credit Default Swaps: a Data Science approach through Benford's Law

Cited by in corpus (5)

• Benford's law first significant digit and distribution distances for testing the reliability of financial reports in developing countries
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• Benford's laws tests on S&P500 daily closing values and the corresponding daily log-returns both point to huge non-conformity
• Intriguing behavior when testing the impact of quotation marks usage in Google search results
• Data on the annual aggregated income taxes of the Italian municipalities over the quinquennium 2007-2011