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.

"Swarm, a standard set of program libraries, allows users to construct simulations where a collection of heterogeneous independent agents or elements interact through discrete events. This volume offers the first extensive tutorial to the use of these software libraries developed at the Santa Fe Institute as part of the ongoing research into complexity."--BOOK JACKET.

This book presents the latest findings on network theory and agent-based modeling of economic and financial phenomena. In this context, the economy is depicted as a complex system consisting of heterogeneous agents that interact through evolving networks; the aggregate behavior of the economy arises out of billions of small-scale interactions that take place via countless economic agents. The book focuses on analytical modeling, and on the econometric and statistical analysis of the properties emerging from microscopic interactions. In particular, it highlights the latest empirical and theoretical advances, helping readers understand economic and financial networks, as well as new work on modeling behavior using rich, agent-based frameworks. Innovatively, the book combines observational and theoretical insights in the form of networks and agent-based models, both of which have proved to be extremely valuable in understanding non-linear and evolving complex systems. Given its scope, the book will capture the interest of graduate students and researchers from various disciplines (e.g. economics, computer science, physics, and applied mathematics) whose work involves the domain of complexity theory.

Delve into the complex landscape of the informal economy with the Routledge Handbook of the Informal Economy, a groundbreaking volume that transcends conventional economic analysis by contextualizing it within a broader regulatory and social framework. This comprehensive handbook offers cutting-edge categorical, thematic, and regional analyses of the informal, or shadow, economy. An esteemed international ensemble of contributors draws on diverse economic perspectives, exploring a spectrum of definitions and measures, including household, firm-level, and employment-based metrics, alongside perceptional and model-based estimates. Employing a variety of econometric and methodological approaches, the volume provides both regional and global estimates of the informal economy's extent. Beyond conventional boundaries, it unveils various facets of informality, from child labor, tax evasion, and self-employment to precarious and undeclared work. In-depth examinations of the determinants and consequences of informality enhance the volume's robust analysis. As a forward-looking compendium, the handbook also offers insights into the future trajectory of the informal economy as we journey further into the 21st century. This definitive and up-to-date reference work is indispensable for readers in labor economics, development economics, political economy, policy studies, and sociology, offering a nuanced understanding of the multifaceted dimensions and dynamics of the informal economy.

This book studies social phenomena in a new way, by making judicious use of computer technology. The book addresses the entire spectrum of classic studies in social science, from experiments to the computational models, with a multidisciplinary approach. The book is suitable for those who want to get a picture of what it means to do social research today, and also to get an indication of the major open issues. The book is connected to a database of code for simulations, experimental data and allows to activate a subscription to a teaching tool using NetLogo, a programming language widely used in the social studies. The authors are researchers with first-hand experience research projects, both basic and applied. The work will be useful for those who want to understand more of the social, economic and political phenomena via computer applications.

Unlocking what drives tax morale – the intrinsic willingness to pay tax – can greatly assist governments in the design of tax policies and their administration, particularly in developing countries where compliance rates are low. This report builds on previous OECD research to identify some of the key socio-economic and institutional drivers of tax morale across developing countries, and seeks to test for evidence of the social contract by examining the impact of public services on tax morale. It also uses new data on tax certainty as an entry point to explore tax morale in businesses, where existing research is very limited. Finally, the report identifies a range of factors related to the tax system that may affect business decision making, how they vary across regions, and suggests some areas for future research. Overall, the report provides a range of suggestions for further work, and how tax morale considerations can be integrated into holistic tax compliance strategies.

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2019), which was held at Technische Universität Dresden, Germany, on September 4-6, 2019, and was jointly organized by the German Operations Research Society (GOR) the Austrian Operations Research Society (ÖGOR), and the Swiss Operational Research Society (SOR/ASRO). More than 600 scientists, practitioners and students from mathematics, computer science, business/economics and related fields attended the conference and presented more than 400 papers in plenary presentations, parallel topic streams, as well as special award sessions. The respective papers discuss classical mathematical optimization, statistics and simulation techniques. These are complemented by computer science methods, and by tools for processing data, designing and implementing information systems. The book also examines recent advances in information technology, which allow big data volumes to be processed and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Lastly, it includes problems modeled and treated while taking into account uncertainty, risk management, behavioral issues, etc.