英文标题：
《Data science for assessing possible tax income manipulation: The case of
Italy》
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作者：
Marcel Ausloos, Roy Cerqueti, Tariq A. Mir
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最新提交年份：
2017
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英文摘要：
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.
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中文摘要：
本文从数据科学的角度探讨了一个现实世界的基本主题。它特别讨论了是否可以通过公民财政报告的汇总，在市政所得税规模分配中或从市政所得税规模分配中观察到欺诈或操纵。研究案例涉及2007-2011年期间从意大利经济和财政部获得的官方数据。所有意大利（20）个地区都被考虑在内。经过深思熟虑的数据科学方法具体化为采用本福德第一位数定律作为定量工具。在几个地区发现了明显的差异，导致了意想不到的“结论”。根据对意大利金融阴影问题的经典想象，最引人注目的区域并不是预期的区域。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类：Physics 物理学
二级分类：Physics and Society 物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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