caa a22 4500 606210296 CHVBK 20210128101032.0 cr unu---uuuuu 210128e20150501xx s 000 0 eng 10.1007/s10101-014-0152-7 doi (NATIONALLICENCE)springer-10.1007/s10101-014-0152-7 Modeling tax evasion with genetic algorithms [Elektronische Daten] [Geoffrey Warner, Sanith Wijesinghe, Uma Marques, Osama Badar, Jacob Rosen, Erik Hemberg, Una-May O'Reilly] The U.S. tax gap is estimated to exceed $450 billion, most of which arises from non-compliance on the part of individual taxpayers(GAO 2012; IRS 2006). Much is hidden in innovative tax shelters combining multiple business structures such as partnerships, trusts, and S-corporations into complex transaction networks designed to reduce and obscure the true tax liabilities of their individual shareholders. One known gambit employed by these shelters is to offset real gains in one part of a portfolio by creating artificial capital losses elsewhere through the mechanism of "inflated basis” (TaxAnalysts 2005), a process made easier by the relatively flexible set of rules surrounding "pass-through” entities such as partnerships(IRS 2009). The ability to anticipate the likely forms of emerging evasion schemes would help auditors develop more efficient methods of reducing the tax gap. To this end, we have developed a prototype evolutionary algorithm designed to generate potential schemes of the inflated basis type described above. The algorithm takes as inputs a collection of asset types and tax entities, together with a rule-set governing asset exchanges between these entities. The schemes produced by the algorithm consist of sequences of transactions within an ownership network of tax entities. Schemes are ranked according to a "fitness function” (Goldberg in Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Boston, 1989); the very best schemes are those that afford the highest reduction in tax liability while incurring the lowest expected penalty. Springer-Verlag Berlin Heidelberg, 2014 Tax evasion nationallicence Genetic algorithms nationallicence Agent-based modeling nationallicence Warner Geoffrey The MITRE Corporation, 7515 Colshire Drive, 22102, McLean, VA, USA aut Wijesinghe Sanith The MITRE Corporation, 7515 Colshire Drive, 22102, McLean, VA, USA aut Marques Uma The MITRE Corporation, 7515 Colshire Drive, 22102, McLean, VA, USA aut Badar Osama Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Mass. Ave, 02139, Cambridge, MA, USA aut Rosen Jacob Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Mass. Ave, 02139, Cambridge, MA, USA aut Hemberg Erik Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Mass. Ave, 02139, Cambridge, MA, USA aut O'Reilly Una-May Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Mass. Ave, 02139, Cambridge, MA, USA aut Economics of Governance Springer Berlin Heidelberg 16/2(2015-05-01), 165-178 1435-6104 16:2<165 2015 16 10101 https://doi.org/10.1007/s10101-014-0152-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10101-014-0152-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Warner Geoffrey The MITRE Corporation, 7515 Colshire Drive, 22102, McLean, VA, USA aut NATIONALLICENCE 700 1- Wijesinghe Sanith The MITRE Corporation, 7515 Colshire Drive, 22102, McLean, VA, USA aut NATIONALLICENCE 700 1- Marques Uma The MITRE Corporation, 7515 Colshire Drive, 22102, McLean, VA, USA aut NATIONALLICENCE 700 1- Badar Osama Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Mass. Ave, 02139, Cambridge, MA, USA aut NATIONALLICENCE 700 1- Rosen Jacob Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Mass. Ave, 02139, Cambridge, MA, USA aut NATIONALLICENCE 700 1- Hemberg Erik Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Mass. Ave, 02139, Cambridge, MA, USA aut NATIONALLICENCE 700 1- O'Reilly Una-May Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Mass. Ave, 02139, Cambridge, MA, USA aut NATIONALLICENCE 773 0- Economics of Governance Springer Berlin Heidelberg 16/2(2015-05-01), 165-178 1435-6104 16:2<165 2015 16 10101