Doctoral Research in Taxation.
本文提出一种利用纳税人申报数据中数字频率推断逃税的新方法，将逃税分为计划性和非计划性两类，并开发了量化收入或扣除项目操纵方向与程度的扭曲因子模型。
Abstract This article focuses on a research that focuses on a new approach to assessing taxpayer compliance. Unaudited taxpayer data were used to infer evasion based on the frequencies of the digits of the numbers used on returns. Tax evasion was classified as either planned or unplanned. Under Planned Evasion the intention to evade exists early in the year and the taxpayer takes preplanned steps to hide an audit trail and fabricate supporting documents. Under Unplanned Evasion (UPE) the intention to evade occurs while the return is being prepared. UPE constitutes a blatant adjustment through the invention of a number for a line item, and is focused on items thought unlikely to be detected if the return is not audited. Benford's Law describes some expected attributes of natural tabulated data. These attributes include the expected frequencies of the digits in tabulated data. Income or deduction items that are free of evasion should, when tabulated for all taxpayers, follow the expected frequencies. A Distortion Factor model that quantifies the direction and magnitude of manipulation in an income or deduction field was developed. The assumption was made that UPE in an income deduction field is evidenced by an