全球智库信息集成服务系统(G2TT): Measuring Disclosure Risk and an Examination of the Possibilities of Using Synthetic Data in the Individual Income Tax Return Public Use File

G2TT

来源类型	Publication
	Measuring Disclosure Risk and an Examination of the Possibilities of Using Synthetic Data in the Individual Income Tax Return Public Use File
	Sonya Vartivarian; John L. Czajka,; Michael Weber
发表日期	2007-07-31
出版者	Salt Lake City, UT: Joint Statistical Meetings
出版年	2007
语种	英语
概述	The Statistics of Income Division (SOI) currently measures disclosure risk through a distance-based technique that compares the public use file (PUF) against the population of all tax returns and uses top-coding, subsampling and multivariate microaggregation as disclosure avoidance techniques.",
摘要	The Statistics of Income Division (SOI) currently measures disclosure risk through a distance-based technique that compares the public use file (PUF) against the population of all tax returns and uses top-coding, subsampling and multivariate microaggregation as disclosure avoidance techniques. SOI is interested in exploring the use of other techniques that prevent disclosure while providing less data distortion. Synthetic or simulated data may be such a technique. But while synthetic data may be the ultimate in disclosure protection, creating a synthetic dataset that preserves the key characteristics of the source data presents a significant challenge. Additional constraints in creating synthetic data for the SOI PUF are found in maintaining the accounting relationships among numerous income, deduction, and tax items that appear on a tax return, and the nonlinear relationships involved in the tax rate structure.
URL	https://www.mathematica.org/our-publications-and-findings/publications/measuring-disclosure-risk-and-an-examination-of-the-possibilities-of-using-synthetic-data-in-the-individual-income-tax-return-public-use-file
来源智库	Mathematica Policy Research (United States)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/485782
推荐引用方式 GB/T 7714	Sonya Vartivarian,John L. Czajka,,Michael Weber. Measuring Disclosure Risk and an Examination of the Possibilities of Using Synthetic Data in the Individual Income Tax Return Public Use File. 2007.

条目包含的文件
文件名称/大小	资源类型	版本类型	开放类型	使用许可
measuringdisclosurer（50KB）	智库出版物		限制开放	CC BY-NC-SA	浏览