COMPUTATIONAL SOCIAL SCIENCE

Department of Computational Social Science Seminar Abstract

Friday, May 6 - 3:00 pm

Agent-based Simulation of Tax Reporting Compliance

Kim Bloomquist
PhD Candidate, CSS
George Mason University

Abstract: I describe the development of the Individual Tax Compliance Model (ITCM), a hybrid multi-agent simulation (MAS) test bed for evaluating alternatives to improve income tax reporting compliance. ITCM simulates the tax reporting behavior of individual taxpayers, including their formal economic relationships (e.g., employers, commercial tax preparers) and informal reference groups, for a mid-sized community in tax year 2001. In all, the full model has nearly 85,000 taxpayers, 3,300 employers, 2,100 tax preparers, and 21 geographic zones.

To comply with IRS rules on nondisclosure of taxpayer data, while also permitting external model validation and verification, I create a dataset of artificial taxpayers by replacing actual tax returns with cases from the Statistics of Income (SOI) Public Use File. To this dataset I impute income and offset misreporting using random audit data from the National Research Program. I calibrate the model to tax return data and random audit results.

The model is implemented in native Java and uses Repast Simphony software libraries for random number generation and chart creation. Finally, I present several hypothetical scenarios that explore the impact on tax compliance of alternative tax administration proposals.