RAND's Interdisciplinary Behavioral and Social Science Agent-Based Model of Income Tax Evasion
Technical Report
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Income tax evasion is a problem that poses considerable challenges for tax authorities and governments at the local, state, federal levels, as well as internationally. Its causes and implications are both economic and social, and therefore it is of enormous importance in policy design. We built an agent-based computational simulation model of income tax evasion. Within the simulation, individuals' compliance behavior changes through an adaptation process based on their past experiences with audits and tax evasion penalties, their perception of the fairness in taxation rates and social interactions with people in their social networks. To inform the model we have conducted a survey on a nationally representative sample on the perceptions of tax fairness. The specific purpose of our survey was to guide the model construction, test our model assumptions, as well as inform behavioral parameter values and the calibration procedure. In addition, the survey provides novel insights into the social dynamics of risk and fairness perceptions, including how they are influenced by perceptions and experiences of social network contacts and in community at large.
Here, we present technical details that describe our model and how it was informed by our survey. In our first two sections we provide a brief introduction to the problem and an overview of past agent-based models of tax compliance. Sections 3 to 11 provide a description of our agent based model following the overview, design concepts, and details protocol [69, 70]. Section 12 to 15 provides description of our survey and focuses only on the analyses that helped inform the model and in particular the behavioral mechanisms and parameter values. Sections 17 to 20 described model verification, validation and calibration. Sections 21 and 22 describes results from possible intervention policy. Finally, Sections 23 and 24 provide a discussion of our results and describe limitations and future work.
Table of Contents
Chapter One
Introduction
Chapter Two
Understanding social drivers of tax evasion
Chapter Three
Overview of ABMs and Past Models of Tax Compliance
Chapter Four
Purpose
Chapter Five
Entities, State variables, and Scales
Chapter Six
Model Overview and Scheduling
Chapter Seven
Specifications of the Taxpayer's Behavioral Model Components
Chapter Eight
Specifications and Initialization of the IRS Model Components
Chapter Nine
Specifications of the Governing State (GS) Components
Chapter Ten
Design concepts
Chapter Eleven
Population Heterogeneities and Initialization
Chapter Twelve
Input data
Chapter Thirteen
Overview to the ALP Survey on Tax Compliance
Chapter Fourteen
Using the ALP Survey to inform the model parameters
Chapter Fifteen
Using the ALP Survey to inform the network of social interactions
Chapter Sixteen
Using the ALP Survey to inform the taxpayer's behavioral attributes
Chapter Seventeen
Model Verification and Validation
Chapter Eighteen
Model Outputs for Analyses and Calibration
Chapter Nineteen
Uncertainty and Sensitivity Analyses
Chapter Twenty
Model Calibration
Chapter Twenty-One
Simple intervention and "what if" scenarios
Chapter Twenty-Two
Combining fiscal and deterrence intervention policies
Chapter Twenty-Three
Summary and Discussion
Chapter Twenty-Four
Limitations
Appendix A
Experience Discounting and the EWMA process
Appendix B
Eliciting social influence parameters for tax compliance behavior using the results from Alm et al. 2009
Appendix C
Program Evaluation and Review Technique (PERT) distribution
Appendix D
Survey Questions of the American Life PanelWell Being 456
Appendix E
Fitting data to an S-Curve
Appendix F
Estimating Tax Rate, Audit Rate, Penalty Rate Elasticities and the S-Curve Parameters
Appendix G
Media Effect Factor on the Motivation to Comply
Appendix H
Assortativity odds ratio measure
Appendix I
Testing the model dynamics for stationarity
Appendix J
CART and Random Forest methods
Appendix K
Code and Data Repository
Appendix L
Interactive Tool
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