JSM 2005 Online Program

Abstract #303361

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	475
Type:	Topic Contributed
Date/Time:	Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor:	Section on Government Statistics
Abstract - #303361
Title:	A Cluster Analysis Approach to Describing Tax Return Data
Author(s):	Brian Raub*+
Companies:	U.S. Internal Revenue Service
Address:	Statistics of Income Division, Washington, DC, 20013, United States
Keywords:	corporations ; foriegn tax credit ; cluster analysis ; clustering ; tax data
Abstract:	Most studies within the Statistics of Income Division display aggregate tax form data by variables such as industry, type of transaction, or size of assets. One alternative is to analyze the data in terms of distinct clusters of taxpayers who share a similar reporting pattern. We use hierarchical clustering techniques to reduce the Corporate Foreign Tax Credit data file into distinct clusters of taxpayers. The Corporate Foreign Tax Credit was claimed by more than 4,000 U.S.-based multinational corporations to offset U.S. taxes paid on income earned abroad. We describe the "average" taxpayer within each cluster in terms of the variables measured and assess how the clusters relate to standard ways of describing the data file. We also gauge the usefulness of cluster analysis as a tool for describing tax return data and enhancing understanding of the population of firms claiming a foreign tax credit.

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