Agent-Based Simulation of Tax Reporting Compliance
| dc.contributor.advisor | Axtell, Robert L. | |
| dc.contributor.author | Bloomquist, Kim Michael | |
| dc.creator | Bloomquist, Kim Michael | |
| dc.date | 2012-07-20 | |
| dc.date.accessioned | 2012-09-17T19:29:35Z | |
| dc.date.available | NO_RESTRICTION | |
| dc.date.available | 2012-09-17T19:29:35Z | |
| dc.date.issued | 2012-09-17 | |
| dc.description.abstract | Following the global financial crisis of 2008 many national governments have a renewed urgency to collect taxes not paid by noncompliant taxpayers. However, despite decades of theoretical and applied research progress has lagged on the development of computational tools to help tax administrators devise effective compliance improvement strategies. This study aims to bridge this gap by introducing the Individual Reporting Compliance Model (IRCM), an agent-based computational model that simulates tax reporting compliance in a community of 85,000 individual taxpayers, their employers and tax preparers. The model uses detailed tax return information yet maintains taxpayer anonymity by replacing actual tax returns with cases from the Statistics of Income (SOI) Public Use File [Weber 2004]. After reviewing the theoretical and empirical literature on taxpayer compliance, this study describes the development of the IRCM and demonstrates its capabilities in several simulation experiments. | |
| dc.identifier.uri | https://hdl.handle.net/1920/7927 | |
| dc.language.iso | en | |
| dc.subject | Agent-based model | |
| dc.subject | Tax gap | |
| dc.subject | Tax compliance | |
| dc.subject | Internal revenue service | |
| dc.subject | Social simulation | |
| dc.subject | Taxpayer reporting behavior | |
| dc.title | Agent-Based Simulation of Tax Reporting Compliance | |
| dc.type | Dissertation | |
| thesis.degree.discipline | Computational Social Science | |
| thesis.degree.grantor | George Mason University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | PhD in Computational Social Science |