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Massachusetts Institute of Technology

Computer aided tax avoidance policy analysis

Abstract

dc:description.abstract

his thesis presents a three part methodology for analyzing the ow of taxable income in large partnership structures. The method forms the basis for prototypical software which would clarify many complicated basis adjustment issues associated with partnership taxation. Partnerships, the most common form of "flow-through" tax entities, have rapidly increased in size, complexity and economic relevance between 2005 to 2015, as well as resulting in an estimated $91 billion in underreported income. Many of these partnerships have upwards of one million direct and indirect partners, as well as 100 tiers of additional large partnerships. This surge in the number of partnerships, combined with the highly complicated nature of US partnership taxation law, requires novel techniques to evaluate the tax consequences of increasingly complex financial activity. A computational methodology is presented in this thesis for understanding and analyzing the allocation of taxable income in large partnership structures, with particular focus on characterizing abusive tax behavior. First, a formal notation is established to fully describe how taxable income is allocated in partnerships, forming the basis of a functioning partnership tax calculator. Next, a simulation is described that processes transaction sequences through partnership structures, as well as a method for assigning audit likelihood to potentially suspicious combinations of financial activity. Finally, a means by which to optimize a) transaction sequences that minimize both tax liability and audit likelihood and b) auditing procedures that characterize abusive tax behavior in a compact form is established. The proposed methodology offers taxpayers, auditors and policy-makers a computational approach to resolve uncertainty in partnership taxation, lower the cost of the auditing process through automation and provide a conceptual exploration of tax policy implications.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Engineering Systems Division
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Rosen, Jacob (Jacob Benjamin)
Advisor dc:contributor.advisor
  • Una-May O'Reilly and Erik Hemberg.

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/98541
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/98541

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Rosen, Jacob (Jacob Benjamin). Computer aided tax avoidance policy analysis. Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98541