Agent-based Modeling of Tax Evasion (eBook, PDF)

Theoretical Aspects and Computational Simulations
Redaktion: Hokamp, Sascha; Wijesinghe, Sanith; Koehler, Matthew; Gulyas, Laszlo

• Format: PDF

Produktbeschreibung

The only single-source guide to understanding, using, adapting, and designing state-of-the-art agent-based modelling of tax evasion

A computational method for simulating the behavior of individuals or groups and their effects on an entire system, agent-based modeling has proven itself to be a powerful new tool for detecting tax fraud. While interdisciplinary groups and individuals working in the tax domain have published numerous articles in diverse peer-reviewed journals and have presented their findings at international conferences, until Agent-based Modelling of Tax Evasion there was no authoritative, single-source guide to state-of-the-art agent-based tax evasion modeling techniques and technologies.

Featuring contributions from distinguished experts in the field from around the globe, Agent-Based Modelling of Tax Evasion provides in-depth coverage of an array of field tested agent-based tax evasion models. Models are presented in a unified format so as to enable readers to systematically work their way through the various modeling alternatives available to them. Three main components of each agent-based model are explored in accordance with the Overview, Design Concepts, and Details (ODD) protocol, each section of which contains several sub elements that help to illustrate the model clearly and that assist readers in replicating the modeling results described.

• Presents models in a unified and structured manner to provide a point of reference for readers interested in agent-based modelling of tax evasion
• Explores the theoretical aspects and diversity of agent-based modeling through the example of tax evasion
• Provides an overview of the characteristics of more than thirty agent-based tax evasion frameworks
• Functions as a solid foundation for lectures and seminars on agent-based modelling of tax evasion

The only comprehensive treatment of agent-based tax evasion models and their applications, this book is an indispensable working resource for practitioners and tax evasion modelers both in the agent-based computational domain and using other methodologies. It is also an excellent pedagogical resource for teaching tax evasion modeling and/or agent-based modeling generally.

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Produktdetails

• Verlag: John Wiley & Sons
• Erscheinungstermin: 12. Februar 2018
• Englisch
• ISBN-13: 9781119155690
• Artikelnr.: 54230033

Autorenporträt

Sascha Hokamp, PhD is a member of the Research Unit for Sustainability and Global Change (FNU) and of the Center for Earth System Research and Sustainability (CEN), Universität Hamburg. His research topics include illicit activities (tax evasion and doping in elite sports) and the shadow economy. László Gulyás, PhD is Assistant Professor at Eötvös Loránd University, Budapest. He is a former Head of Division at AITIA International, Inc. He has been doing research on agent-based modeling and multi-agent systems since 1996. Matthew Koehler, PhD is the Applied Complexity Sciences Area Lead for US Treasury/Internal Revenue Service, US Commerce, and Social Security Administration Program Division at The MITRE Corporation. Sanith Wijesinghe, PhD is Chief Engineer of the Model Based Analytics department at The MITRE Corporation.

Inhaltsangabe

Notes on Contributors xiii

Foreword xxi

Preface xxvii

Part I INTRODUCTION

1 Agent-Based Modeling and Tax Evasion: Theory and Application 3
Sascha Hokamp, László Gulyás, Matthew Koehler and H. Sanith Wijesinghe

1.1 Introduction 3

1.2 Tax Evasion, Tax Avoidance and Tax Noncompliance 4

1.3 Standard Theories of Tax Evasion 5

1.4 Agent-Based Models 10

1.5 Standard Protocols to Describe Agent-Based Models 11

1.5.1 The Overview, Design Concepts, Details, and Decision-Making Protocol 13

1.5.2 Concluding Remarks on the ODD+D Protocol 17

1.6 Literature Review of Agent-Based Tax Evasion Models 18

1.6.1 Public Goods, Governmental Tasks and Back Auditing 22

1.6.2 Replication, Docking, and Calibration Studies 25

1.6.3 Concluding Remarks on Agent-Based Tax Evasion Models 26

1.7 Outlook: The Structure and Presentation of the Book 27

1.7.1 Part I Introduction 28

1.7.2 Part II Agent-Based Tax Evasion Models 28

References 31

2 How Should One Study Clandestine Activities: Crimes, Tax Fraud, and Other "Dark" Economic Behavior? 37
Aloys L. Prinz

2.1 Introduction 37

2.2 Why Study Clandestine Behavior At All? 38

2.3 Tools for Studying Clandestine Activities 40

2.4 Networks and the Complexity of Clandestine Interactions 42

2.5 Layers of Analysis 45

2.6 Research Tools and Clandestine Activities 48

2.7 Conclusion 55

Acknowledgment 56

References 56

3 Taxpayer's Behavior: From the Laboratory to Agent-Based Simulations 59
Luigi Mittone and Viola L. Saredi

3.1 Tax Compliance: Theory and Evidence 59

3.2 Research on Tax Compliance: A Methodological Analysis 62

3.3 From Human-Subject to Computational-Agent Experiments 68

3.4 An Agent-Based Approach to Taxpayers' Behavior 73

3.4.1 The Macroeconomic Approach 74

3.4.2 The Microeconomic Approach 77

3.4.3 Micro-Level Dynamics for Macro-Level Interactions among Behavioral Types 80

3.5 Conclusions 83

References 84

Part II AGENT-BASED TAX EVASION MODELS

4 Using Agent-Based Modeling to Analyze Tax Compliance and Auditing 91
Nigar Hashimzade and Gareth Myles

4.1 Introduction 91

4.2 Agent-Based Model for Tax Compliance and Audit Research 93

4.2.1 Overview 93

4.2.2 Design Concepts 94

4.2.3 Details 98

4.3 Modeling Individual Compliance 98

4.3.1 Expected Utility 98

4.3.2 Behavioral Models 101

4.3.3 Psychic Costs and Social Customs 102

4.4 Risk-Taking and Income Distribution 106

4.5 Attitudes, Beliefs, and Network Effects 111

4.5.1 Networks and Meetings 113

4.5.2 Formation of Beliefs 113

4.6 Equilibrium with Random and Targeted Audits 115

4.7 Conclusions 119

Acknowledgments 122

References 122

Appendix 4A 123

5 SIMULFIS: A Simulation Tool to Explore Tax Compliance Behavior 125
Toni Llacer, Francisco J. Miguel Quesada, José A. Noguera and Eduardo Tapia Tejada

5.1 Introduction 125

5.2 Model Description 126

5.2.1 Purpose 127

5.2.2 Entities, State Variables, and Scales 127

5.2.3 Process Overview and Scheduling 131

5.2.4 Theoretical and Empirical Background 131

5.2.5 Individual Decision Making 132

5.2.6 Learning 135

5.2.7 Individual Sensing 136

5.2.8 Individual Prediction 136

5.2.9 Interaction 137