2026-09-18T19:46:08Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/985412022-01-31T21:33:17Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Una-May O'Reilly and Erik Hemberg.
Rosen, Jacob (Jacob Benjamin)
Massachusetts Institute of Technology. Technology and Policy Program.
Massachusetts Institute of Technology. Engineering Systems Division
Technology and Policy Program
2015-09-17T17:41:21Z
2015-09-17T17:41:21Z
2015
2015
http://hdl.handle.net/1721.1/98541
920470093
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2015.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Title as it appears in MIT Commencement Exercises program, June 5, 2015: Computer aided tax evasion policy analysis: partnership calculation. Includes bibliographical references (pages 81-83).
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.
by Jacob Rosen.
S.M. in Technology and Policy
83 pages
eng
Massachusetts Institute of Technology
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.
http://dspace.mit.edu/handle/1721.1/7582
Engineering Systems Division.
Technology and Policy Program.
Computer aided tax avoidance policy analysis
Computer aided tax evasion policy analysis: partnership calculation
Thesis
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<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.</Abstract>
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