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The Resource Agent-Based Modelling of Tax Evasion : Theoretical Aspects and Computational Simulations

Agent-Based Modelling of Tax Evasion : Theoretical Aspects and Computational Simulations

Label
Agent-Based Modelling of Tax Evasion : Theoretical Aspects and Computational Simulations
Title
Agent-Based Modelling of Tax Evasion
Title remainder
Theoretical Aspects and Computational Simulations
Creator
Contributor
Subject
Language
eng
Member of
Cataloging source
MiAaPQ
http://library.link/vocab/creatorName
Hokamp, Sascha
Dewey number
336.20019
LC call number
K4486 .A346 2018
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Gulyas, Laszlo
  • Koehler, Matthew
  • Wijesinghe, Sanith
Series statement
Wiley Series in Computational and Quantitative Social Science Ser
http://library.link/vocab/subjectName
Tax evasion
Label
Agent-Based Modelling of Tax Evasion : Theoretical Aspects and Computational Simulations
Instantiates
Publication
Copyright
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Cover -- Title Page -- Copyright -- Contents -- Notes on Contributors -- Foreword -- Preface -- Part I Introduction -- Chapter 1 Agentâ{u0080}{u0090}Based Modeling and Tax Evasion: Theory and Application -- 1.1 Introduction -- 1.2 Tax Evasion, Tax Avoidance and Tax Noncompliance -- 1.3 Standard Theories of Tax Evasion -- 1.4 Agentâ{u0080}{u0090}Based Models -- 1.5 Standard Protocols to Describe Agentâ{u0080}{u0090}Based Models -- 1.5.1 The Overview, Design Concepts, Details, and Decisionâ{u0080}{u0090}Making Protocol -- 1.5.1.1 Overview of the Model -- 1.5.1.2 Design Concepts -- 1.5.1.3 Details -- 1.5.2 Concluding Remarks on the ODD+D Protocol -- 1.6 Literature Review of Agentâ{u0080}{u0090}Based Tax Evasion Models -- 1.6.1 Public Goods, Governmental Tasks and Back Auditing -- 1.6.2 Replication, Docking, and Calibration Studies -- 1.6.3 Concluding Remarks on Agentâ{u0080}{u0090}Based Tax Evasion Models -- 1.7 Outlook: The Structure and Presentation of the Book -- 1.7.1 Part I Introduction -- 1.7.2 Part II Agentâ{u0080}{u0090}Based Tax Evasion Models -- References -- Chapter 2 How Should One Study Clandestine Activities: Crimes, Tax Fraud, and Other "Dark" Economic Behavior? -- 2.1 Introduction -- 2.2 Why Study Clandestine Behavior At All? -- 2.3 Tools for Studying Clandestine Activities -- 2.4 Networks and the Complexity of Clandestine Interactions -- 2.5 Layers of Analysis -- 2.6 Research Tools and Clandestine Activities -- 2.7 Conclusion -- Acknowledgment -- References -- Chapter 3 Taxpayer's Behavior: From the Laboratory to Agentâ{u0080}{u0090}Based Simulations -- 3.1 Tax Compliance: Theory and Evidence -- 3.2 Research on Tax Compliance: A Methodological Analysis -- 3.3 From Humanâ{u0080}{u0090}Subject to Computationalâ{u0080}{u0090}Agent Experiments -- 3.4 An Agentâ{u0080}{u0090}Based Approach to Taxpayers' Behavior -- 3.4.1 The Macroeconomic Approach -- 3.4.2 The Microeconomic Approach -- 3.4.3 Microâ{u0080}{u0090}Level Dynamics for Macroâ{u0080}{u0090}Level Interactions among Behavioral Types
  • 3.5 Conclusions -- References -- Part II Agentâ{u0080}{u0090}Based Tax Evasion Models -- Chapter 4 Using Agentâ{u0080}{u0090}Based Modeling to Analyze Tax Compliance and Auditing -- 4.1 Introduction -- 4.2 Agentâ{u0080}{u0090}Based Model for Tax Compliance and Audit Research -- 4.2.1 Overview -- 4.2.1.1 Purpose -- 4.2.1.2 Entities, State Variables, and Scales -- 4.2.1.3 Process Overview and Scheduling -- 4.2.2 Design Concepts -- 4.2.2.1 Theoretical and Empirical Background -- 4.2.2.2 Individual Decision Making -- 4.2.2.3 Learning -- 4.2.2.4 Individual Sensing -- 4.2.2.5 Individual Prediction -- 4.2.2.6 Interaction -- 4.2.2.7 Collectives -- 4.2.2.8 Heterogeneity -- 4.2.2.9 Stochasticity -- 4.2.2.10 Observation and Emergence -- 4.2.3 Details -- 4.3 Modeling Individual Compliance -- 4.3.1 Expected Utility -- 4.3.2 Behavioral Models -- 4.3.3 Psychic Costs and Social Customs -- 4.4 Riskâ{u0080}{u0090}Taking and Income Distribution -- 4.5 Attitudes, Beliefs, and Network Effects -- 4.5.1 Networks and Meetings -- 4.5.2 Formation of Beliefs -- 4.5.2.1 Audits and Beliefs -- 4.5.2.2 Information Exchange and Beliefs -- 4.5.2.3 Formation of Attitudes -- 4.6 Equilibrium with Random and Targeted Audits -- 4.7 Conclusions -- Acknowledgments -- References -- Chapter 5 SIMULFIS: A Simulation Tool to Explore Tax Compliance Behavior -- 5.1 Introduction -- 5.2 Model Description -- 5.2.1 Purpose -- 5.2.2 Entities, State Variables, and Scales -- 5.2.3 Process Overview and Scheduling -- 5.2.4 Theoretical and Empirical Background -- 5.2.5 Individual Decision Making -- 5.2.6 Learning -- 5.2.7 Individual Sensing -- 5.2.8 Individual Prediction -- 5.2.9 Interaction -- 5.2.10 Collectives -- 5.2.11 Heterogeneity -- 5.2.12 Stochasticity -- 5.2.13 Observation -- 5.2.14 Implementation Details -- 5.2.15 Initialization -- 5.2.16 Input Data -- 5.2.17 Submodels -- 5.3 Some Experimental Results and Conclusions -- Acknowledgments
  • References -- Chapter 6 TAXSIM: A Generative Model to Study the Emerging Levels of Tax Compliance in a Single Market Sector -- 6.1 Introduction -- 6.2 Model Description -- 6.2.1 Overview -- 6.2.1.1 Purpose -- 6.2.1.2 Entities, State Variables, Scales -- 6.2.1.3 Process Overview and Scheduling -- 6.2.2 Design Concepts -- 6.2.2.1 Theoretical and Empirical Background -- 6.2.2.2 Individual Decisionâ{u0080}{u0090}Making -- 6.2.2.3 Learning -- 6.2.2.4 Individual Sensing -- 6.2.2.5 Individual Prediction -- 6.2.2.6 Interaction -- 6.2.2.7 Collectives -- 6.2.2.8 Heterogeneity -- 6.2.2.9 Stochasticity -- 6.2.3 Observation and Emergence -- 6.2.4 Details -- 6.2.4.1 Initialization -- 6.2.4.2 Input Data -- 6.2.4.3 Submodels -- 6.3 Results -- 6.3.1 Scenarios -- 6.3.1.1 Improving Government Services -- 6.3.1.2 Entrance of Companies with Preferential Taxes -- 6.3.2 Sensitivity Analysis -- 6.3.2.1 The Effect of Governmental Services -- 6.3.3 Adaptive Audit Strategy -- 6.3.4 Minimum Wage Policies -- 6.4 Conclusions -- Acknowledgments -- References -- Chapter 7 Development and Calibration of a Largeâ{u0080}{u0090}Scale Agentâ{u0080}{u0090}Based Model of Individual Tax Reporting Compliance -- 7.1 Introduction -- 7.1.1 Taxpayer Dataset -- 7.1.2 Agents -- 7.1.3 Tax Agency -- 7.1.4 Taxpayer Reporting Behavior -- 7.1.5 Filer Behavioral Response to Tax Audit -- 7.1.6 Model Execution -- 7.2 Model Validation and Calibration -- 7.3 Hypothetical Simulation: Size of the "Gig" Economy and Taxpayer Compliance -- 7.4 Conclusion and Future Research -- Acknowledgments -- References -- 7A.1 Purpose -- 7A.2 Entities, State Variables, and Scales -- 7A.3 Process Overview and Scheduling -- 7A.4 Design Concepts -- 7A.4.1 Basic Principles -- 7A.4.2 Emergence -- 7A.4.3 Adaptation -- 7A.4.4 Objectives -- 7A.4.5 Learning -- 7A.4.6 Prediction -- 7A.4.7 Sensing -- 7A.4.8 Interaction -- 7A.4.9 Stochasticity -- 7A.4.10 Collectives
  • 7A.4.11 Observation -- 7A.5 Initialization -- 7A.6 Input Data -- 7A.7 Submodels -- Chapter 8 Investigating the Effects of Network Structures in Massive Agentâ{u0080}{u0090}Based Models of Tax Evasion -- 8.1 Introduction -- 8.2 Networks and Scale -- 8.3 The Model -- 8.3.1 Overview -- 8.3.1.1 Purpose -- 8.3.1.2 Entities, State Variables, and Scales -- 8.3.1.3 Process Overview and Scheduling -- 8.3.2 Design Concepts -- 8.3.2.1 Theoretical and Empirical Background -- 8.3.2.2 Individual Decisionâ{u0080}{u0090}Making -- 8.3.2.3 Learning -- 8.3.2.4 Individual Sensing -- 8.3.2.5 Individual Prediction -- 8.3.2.6 Interaction -- 8.3.2.7 Collectives -- 8.3.2.8 Heterogeneity -- 8.3.2.9 Stochasticity -- 8.3.2.10 Observation -- 8.3.3 Details -- 8.3.3.1 Implementation Details -- 8.3.3.2 The Agentâ{u0080}{u0090}Based Modeling Framework -- 8.3.3.3 Initialization -- 8.3.3.4 Input Data -- 8.3.3.5 Submodels -- 8.4 The Experiment -- 8.5 Results -- 8.5.1 Impact of Scale -- 8.5.2 Distributing the Model on a Cluster Computer -- 8.6 Conclusion -- References -- Chapter 9 Agentâ{u0080}{u0090}Based Simulations of Tax Evasion: Dynamics by Lapse of Time, Social Norms, Age Heterogeneity, Subjective Audit Probability, Public Goods Provision, and Paretoâ{u0080}{u0090}Optimality -- 9.1 Introduction -- 9.2 The Agentâ{u0080}{u0090}Based Tax Evasion Model -- 9.2.1 Overview of the Model -- 9.2.1.1 Purpose -- 9.2.1.2 Entities, State Variables, and Scales -- 9.2.1.3 Process Overview and Scheduling -- 9.2.2 Design Concepts -- 9.2.2.1 Theoretical and Empirical Background -- 9.2.2.2 Individual Decisionâ{u0080}{u0090}Making -- 9.2.2.3 Learning -- 9.2.2.4 Individual Sensing -- 9.2.2.5 Individual Prediction -- 9.2.2.6 Interaction -- 9.2.2.7 Collective -- 9.2.2.8 Heterogeneity -- 9.2.2.9 Stochastic -- 9.2.2.10 Observation -- 9.2.3 Details -- 9.2.3.1 Implementation Details -- 9.2.3.2 Initialization -- 9.2.3.3 Input Data -- 9.2.3.4 Submodels
  • 9.3 Scenarios, Simulation Results, and Discussion -- 9.3.1 Age Heterogeneity and Social Norm Updating -- 9.3.2 Public Goods Provision and Paretoâ{u0080}{u0090}optimality -- 9.3.3 The Allinghamâ{u0080}{u0090}andâ{u0080}{u0090}Sandmo Approach Reconsidered -- 9.3.3.1 Lapse of Time Effects -- 9.3.3.2 Subjective Audit Probability, Public Goods Provision, Age Heterogeneity, and Social Norm Updating -- 9.3.4 Calibration and Sensitivity Analysis -- 9.4 Conclusions and Outlook -- Acknowledgments -- References -- Chapter 10 Modeling the Coâ{u0080}{u0090}evolution of Tax Shelters and Audit Priorities* -- 10.1 Introduction -- 10.2 Overview -- 10.3 Design Concepts -- 10.3.1 Simulation -- 10.3.1.1 Ownership Network -- 10.3.1.2 Transaction Sequences and Taxable Income -- 10.3.1.3 Audit Score Sheet -- 10.3.1.4 Summary -- 10.3.2 Optimization -- 10.3.2.1 Objective Functions -- 10.3.2.2 Coâ{u0080}{u0090}evolution -- 10.4 Details -- 10.4.1 IBOB -- 10.4.2 Grammar -- 10.4.3 Parameters -- 10.5 Experiments -- 10.5.1 Experiment LimitedAudit: Audit Observables That Do Not Detect IBOB -- 10.5.2 Experiment EffectiveAudit: Audit Observables That Can Detect IBOB -- 10.5.3 Experiment CoEvolution: Sustained Oscillatory Dynamics Of Fitness Values -- 10.6 Discussion -- References -- Chapter 11 From Spins to Agents: An Econophysics Approach to Tax Evasion -- 11.1 Introduction -- 11.2 The Ising Model -- 11.2.1 Purpose -- 11.2.2 Entities, State Variables, and Scales -- 11.2.3 Process Overview and Scheduling -- 11.3 Application to Tax Evasion -- 11.4 Heterogeneous Agents -- 11.5 Relation to Binary Choice Model -- 11.6 Summary and Outlook -- References -- Index -- EULA
Control code
UMKCLawddaEBC5294999
Dimensions
unknown
Extent
1 online resource (373 pages)
Form of item
online
Isbn
9781119155706
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
UMKC Law: DDA record.
Sound
unknown sound
Specific material designation
remote
System control number
  • (MiAaPQ)EBC5294999
  • (Au-PeEL)EBL5294999
  • (CaPaEBR)ebr11512411
  • (OCoLC)1024275787
Label
Agent-Based Modelling of Tax Evasion : Theoretical Aspects and Computational Simulations
Publication
Copyright
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Cover -- Title Page -- Copyright -- Contents -- Notes on Contributors -- Foreword -- Preface -- Part I Introduction -- Chapter 1 Agentâ{u0080}{u0090}Based Modeling and Tax Evasion: Theory and Application -- 1.1 Introduction -- 1.2 Tax Evasion, Tax Avoidance and Tax Noncompliance -- 1.3 Standard Theories of Tax Evasion -- 1.4 Agentâ{u0080}{u0090}Based Models -- 1.5 Standard Protocols to Describe Agentâ{u0080}{u0090}Based Models -- 1.5.1 The Overview, Design Concepts, Details, and Decisionâ{u0080}{u0090}Making Protocol -- 1.5.1.1 Overview of the Model -- 1.5.1.2 Design Concepts -- 1.5.1.3 Details -- 1.5.2 Concluding Remarks on the ODD+D Protocol -- 1.6 Literature Review of Agentâ{u0080}{u0090}Based Tax Evasion Models -- 1.6.1 Public Goods, Governmental Tasks and Back Auditing -- 1.6.2 Replication, Docking, and Calibration Studies -- 1.6.3 Concluding Remarks on Agentâ{u0080}{u0090}Based Tax Evasion Models -- 1.7 Outlook: The Structure and Presentation of the Book -- 1.7.1 Part I Introduction -- 1.7.2 Part II Agentâ{u0080}{u0090}Based Tax Evasion Models -- References -- Chapter 2 How Should One Study Clandestine Activities: Crimes, Tax Fraud, and Other "Dark" Economic Behavior? -- 2.1 Introduction -- 2.2 Why Study Clandestine Behavior At All? -- 2.3 Tools for Studying Clandestine Activities -- 2.4 Networks and the Complexity of Clandestine Interactions -- 2.5 Layers of Analysis -- 2.6 Research Tools and Clandestine Activities -- 2.7 Conclusion -- Acknowledgment -- References -- Chapter 3 Taxpayer's Behavior: From the Laboratory to Agentâ{u0080}{u0090}Based Simulations -- 3.1 Tax Compliance: Theory and Evidence -- 3.2 Research on Tax Compliance: A Methodological Analysis -- 3.3 From Humanâ{u0080}{u0090}Subject to Computationalâ{u0080}{u0090}Agent Experiments -- 3.4 An Agentâ{u0080}{u0090}Based Approach to Taxpayers' Behavior -- 3.4.1 The Macroeconomic Approach -- 3.4.2 The Microeconomic Approach -- 3.4.3 Microâ{u0080}{u0090}Level Dynamics for Macroâ{u0080}{u0090}Level Interactions among Behavioral Types
  • 3.5 Conclusions -- References -- Part II Agentâ{u0080}{u0090}Based Tax Evasion Models -- Chapter 4 Using Agentâ{u0080}{u0090}Based Modeling to Analyze Tax Compliance and Auditing -- 4.1 Introduction -- 4.2 Agentâ{u0080}{u0090}Based Model for Tax Compliance and Audit Research -- 4.2.1 Overview -- 4.2.1.1 Purpose -- 4.2.1.2 Entities, State Variables, and Scales -- 4.2.1.3 Process Overview and Scheduling -- 4.2.2 Design Concepts -- 4.2.2.1 Theoretical and Empirical Background -- 4.2.2.2 Individual Decision Making -- 4.2.2.3 Learning -- 4.2.2.4 Individual Sensing -- 4.2.2.5 Individual Prediction -- 4.2.2.6 Interaction -- 4.2.2.7 Collectives -- 4.2.2.8 Heterogeneity -- 4.2.2.9 Stochasticity -- 4.2.2.10 Observation and Emergence -- 4.2.3 Details -- 4.3 Modeling Individual Compliance -- 4.3.1 Expected Utility -- 4.3.2 Behavioral Models -- 4.3.3 Psychic Costs and Social Customs -- 4.4 Riskâ{u0080}{u0090}Taking and Income Distribution -- 4.5 Attitudes, Beliefs, and Network Effects -- 4.5.1 Networks and Meetings -- 4.5.2 Formation of Beliefs -- 4.5.2.1 Audits and Beliefs -- 4.5.2.2 Information Exchange and Beliefs -- 4.5.2.3 Formation of Attitudes -- 4.6 Equilibrium with Random and Targeted Audits -- 4.7 Conclusions -- Acknowledgments -- References -- Chapter 5 SIMULFIS: A Simulation Tool to Explore Tax Compliance Behavior -- 5.1 Introduction -- 5.2 Model Description -- 5.2.1 Purpose -- 5.2.2 Entities, State Variables, and Scales -- 5.2.3 Process Overview and Scheduling -- 5.2.4 Theoretical and Empirical Background -- 5.2.5 Individual Decision Making -- 5.2.6 Learning -- 5.2.7 Individual Sensing -- 5.2.8 Individual Prediction -- 5.2.9 Interaction -- 5.2.10 Collectives -- 5.2.11 Heterogeneity -- 5.2.12 Stochasticity -- 5.2.13 Observation -- 5.2.14 Implementation Details -- 5.2.15 Initialization -- 5.2.16 Input Data -- 5.2.17 Submodels -- 5.3 Some Experimental Results and Conclusions -- Acknowledgments
  • References -- Chapter 6 TAXSIM: A Generative Model to Study the Emerging Levels of Tax Compliance in a Single Market Sector -- 6.1 Introduction -- 6.2 Model Description -- 6.2.1 Overview -- 6.2.1.1 Purpose -- 6.2.1.2 Entities, State Variables, Scales -- 6.2.1.3 Process Overview and Scheduling -- 6.2.2 Design Concepts -- 6.2.2.1 Theoretical and Empirical Background -- 6.2.2.2 Individual Decisionâ{u0080}{u0090}Making -- 6.2.2.3 Learning -- 6.2.2.4 Individual Sensing -- 6.2.2.5 Individual Prediction -- 6.2.2.6 Interaction -- 6.2.2.7 Collectives -- 6.2.2.8 Heterogeneity -- 6.2.2.9 Stochasticity -- 6.2.3 Observation and Emergence -- 6.2.4 Details -- 6.2.4.1 Initialization -- 6.2.4.2 Input Data -- 6.2.4.3 Submodels -- 6.3 Results -- 6.3.1 Scenarios -- 6.3.1.1 Improving Government Services -- 6.3.1.2 Entrance of Companies with Preferential Taxes -- 6.3.2 Sensitivity Analysis -- 6.3.2.1 The Effect of Governmental Services -- 6.3.3 Adaptive Audit Strategy -- 6.3.4 Minimum Wage Policies -- 6.4 Conclusions -- Acknowledgments -- References -- Chapter 7 Development and Calibration of a Largeâ{u0080}{u0090}Scale Agentâ{u0080}{u0090}Based Model of Individual Tax Reporting Compliance -- 7.1 Introduction -- 7.1.1 Taxpayer Dataset -- 7.1.2 Agents -- 7.1.3 Tax Agency -- 7.1.4 Taxpayer Reporting Behavior -- 7.1.5 Filer Behavioral Response to Tax Audit -- 7.1.6 Model Execution -- 7.2 Model Validation and Calibration -- 7.3 Hypothetical Simulation: Size of the "Gig" Economy and Taxpayer Compliance -- 7.4 Conclusion and Future Research -- Acknowledgments -- References -- 7A.1 Purpose -- 7A.2 Entities, State Variables, and Scales -- 7A.3 Process Overview and Scheduling -- 7A.4 Design Concepts -- 7A.4.1 Basic Principles -- 7A.4.2 Emergence -- 7A.4.3 Adaptation -- 7A.4.4 Objectives -- 7A.4.5 Learning -- 7A.4.6 Prediction -- 7A.4.7 Sensing -- 7A.4.8 Interaction -- 7A.4.9 Stochasticity -- 7A.4.10 Collectives
  • 7A.4.11 Observation -- 7A.5 Initialization -- 7A.6 Input Data -- 7A.7 Submodels -- Chapter 8 Investigating the Effects of Network Structures in Massive Agentâ{u0080}{u0090}Based Models of Tax Evasion -- 8.1 Introduction -- 8.2 Networks and Scale -- 8.3 The Model -- 8.3.1 Overview -- 8.3.1.1 Purpose -- 8.3.1.2 Entities, State Variables, and Scales -- 8.3.1.3 Process Overview and Scheduling -- 8.3.2 Design Concepts -- 8.3.2.1 Theoretical and Empirical Background -- 8.3.2.2 Individual Decisionâ{u0080}{u0090}Making -- 8.3.2.3 Learning -- 8.3.2.4 Individual Sensing -- 8.3.2.5 Individual Prediction -- 8.3.2.6 Interaction -- 8.3.2.7 Collectives -- 8.3.2.8 Heterogeneity -- 8.3.2.9 Stochasticity -- 8.3.2.10 Observation -- 8.3.3 Details -- 8.3.3.1 Implementation Details -- 8.3.3.2 The Agentâ{u0080}{u0090}Based Modeling Framework -- 8.3.3.3 Initialization -- 8.3.3.4 Input Data -- 8.3.3.5 Submodels -- 8.4 The Experiment -- 8.5 Results -- 8.5.1 Impact of Scale -- 8.5.2 Distributing the Model on a Cluster Computer -- 8.6 Conclusion -- References -- Chapter 9 Agentâ{u0080}{u0090}Based Simulations of Tax Evasion: Dynamics by Lapse of Time, Social Norms, Age Heterogeneity, Subjective Audit Probability, Public Goods Provision, and Paretoâ{u0080}{u0090}Optimality -- 9.1 Introduction -- 9.2 The Agentâ{u0080}{u0090}Based Tax Evasion Model -- 9.2.1 Overview of the Model -- 9.2.1.1 Purpose -- 9.2.1.2 Entities, State Variables, and Scales -- 9.2.1.3 Process Overview and Scheduling -- 9.2.2 Design Concepts -- 9.2.2.1 Theoretical and Empirical Background -- 9.2.2.2 Individual Decisionâ{u0080}{u0090}Making -- 9.2.2.3 Learning -- 9.2.2.4 Individual Sensing -- 9.2.2.5 Individual Prediction -- 9.2.2.6 Interaction -- 9.2.2.7 Collective -- 9.2.2.8 Heterogeneity -- 9.2.2.9 Stochastic -- 9.2.2.10 Observation -- 9.2.3 Details -- 9.2.3.1 Implementation Details -- 9.2.3.2 Initialization -- 9.2.3.3 Input Data -- 9.2.3.4 Submodels
  • 9.3 Scenarios, Simulation Results, and Discussion -- 9.3.1 Age Heterogeneity and Social Norm Updating -- 9.3.2 Public Goods Provision and Paretoâ{u0080}{u0090}optimality -- 9.3.3 The Allinghamâ{u0080}{u0090}andâ{u0080}{u0090}Sandmo Approach Reconsidered -- 9.3.3.1 Lapse of Time Effects -- 9.3.3.2 Subjective Audit Probability, Public Goods Provision, Age Heterogeneity, and Social Norm Updating -- 9.3.4 Calibration and Sensitivity Analysis -- 9.4 Conclusions and Outlook -- Acknowledgments -- References -- Chapter 10 Modeling the Coâ{u0080}{u0090}evolution of Tax Shelters and Audit Priorities* -- 10.1 Introduction -- 10.2 Overview -- 10.3 Design Concepts -- 10.3.1 Simulation -- 10.3.1.1 Ownership Network -- 10.3.1.2 Transaction Sequences and Taxable Income -- 10.3.1.3 Audit Score Sheet -- 10.3.1.4 Summary -- 10.3.2 Optimization -- 10.3.2.1 Objective Functions -- 10.3.2.2 Coâ{u0080}{u0090}evolution -- 10.4 Details -- 10.4.1 IBOB -- 10.4.2 Grammar -- 10.4.3 Parameters -- 10.5 Experiments -- 10.5.1 Experiment LimitedAudit: Audit Observables That Do Not Detect IBOB -- 10.5.2 Experiment EffectiveAudit: Audit Observables That Can Detect IBOB -- 10.5.3 Experiment CoEvolution: Sustained Oscillatory Dynamics Of Fitness Values -- 10.6 Discussion -- References -- Chapter 11 From Spins to Agents: An Econophysics Approach to Tax Evasion -- 11.1 Introduction -- 11.2 The Ising Model -- 11.2.1 Purpose -- 11.2.2 Entities, State Variables, and Scales -- 11.2.3 Process Overview and Scheduling -- 11.3 Application to Tax Evasion -- 11.4 Heterogeneous Agents -- 11.5 Relation to Binary Choice Model -- 11.6 Summary and Outlook -- References -- Index -- EULA
Control code
UMKCLawddaEBC5294999
Dimensions
unknown
Extent
1 online resource (373 pages)
Form of item
online
Isbn
9781119155706
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
UMKC Law: DDA record.
Sound
unknown sound
Specific material designation
remote
System control number
  • (MiAaPQ)EBC5294999
  • (Au-PeEL)EBL5294999
  • (CaPaEBR)ebr11512411
  • (OCoLC)1024275787

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