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This title brings together frontier research on complex economic systems, heterogeneous interacting agents, bounded rationality, and nonlinear dynamics in economics. The book contains the proceedings of the CEF2015 (21st Computing in Economics in Finance), held 20-22 June 2015 in Taipei, Taiwan, and addresses some of the important driving forces for various emergent properties in economies, when viewed as complex systems. The breakthroughs reported in this book are a result of an interdisciplinary approach and simulation remains the unifying theme for these papers as they deal with a wide range of topics in economics. The text is a valuable addition to the efforts in promoting the complex systems view in economic science. The computational experiments reported in the book are both transparent and replicable. Complex System Modeling and Simulation in Economics and Finance is useful for graduate courses of complex systems, with particular focus on economics and finance. At the same time it serves as a good overview for researchers who are interested in the topic.
This book approaches economic problems from a systems thinking and feedback perspective. By introducing system dynamics methods (including qualitative and quantitative techniques) and computer simulation models, the respective contributions apply feedback analysis and dynamic simulation modeling to important local, national, and global economics issues and concerns. Topics covered include: an introduction to macro modeling using a system dynamics framework; a system dynamics translation of the Phillips machine; a re-examination of classical economic theories from a feedback perspective; analyses of important social, ecological, and resource issues; the development of a biophysical economics module for global modelling; contributions to monetary and financial economics; analyses of macroeconomic growth, income distribution and alternative theories of well-being; and a re-examination of scenario macro modeling. The contributions also examine the philosophical differences between the economics and system dynamics communities in an effort to bridge existing gaps and compare methods. Many models and other supporting information are provided as online supplementary files. Consequently, the book appeals to students and scholars in economics, as well as to practitioners and policy analysts interested in using systems thinking and system dynamics modeling to understand and improve economic systems around the world. "Clearly, there is much space for more collaboration between the advocates of post-Keynesian economics and system dynamics! More generally, I would like to recommend this book to all scholars and practitioners interested in exploring the interface and synergies between economics, system dynamics, and feedback thinking." Comments in the Foreword by Marc Lavoie, Emeritus Professor, University of Ottawa and University of Sorbonne Paris Nord
Although technology and productivity has changed much of engineering, many topics are still taught in very similarly to how they were taught in the 70s. Using a new approach to engineering economics, Systems Life Cycle Costing: Economic Analysis, Estimation, and Management presents the material that a modern engineer must understand to work as a practicing engineer conducting economic analysis. Organized around a product development process that provides a framework for the material, the book presents techniques such as engineering economics and simulation-based costing (SBC), with a focus on total life cycle understanding and perspective and introduces techniques for detailed analysis of modern complex systems. The author includes rules of thumb for estimation grouped with the methods, processes, and tools (MPTs) for conducting a detailed engineering buildup for costing. He presents the estimating costing of complex systems and software and then explores concepts such as design to cost (DTC), cost as an independent variable (CAIV), the role of commercial off-the-shelf technology, cost of quality, and the role of project management in LCC management. No product or services are immune from cost, performance, schedule, quality, risks, and tradeoffs. Yet engineers spend most of their formal education focused on performance and most of their professional careers worrying about resources and schedule. Too often, the design stage becomes about the technical performance without considering the downstream costs that contribute to the tota1 life cycle costs (LCC) of a system. This text presents the methods, processes, and tools needed for the economic analysis, estimation, and management that bring these costs in line with the goals of pleasing the customer and staying within budget.
This book allows the reader to acquire step-by-step in a time-efficient and uncomplicated the knowledge in the formation and construction of dynamic models using Vensim. Many times, the models are performed with minimal current data and very few historical data, the simulation models that the student will design in this course accommodate these analyses, with the construction of realistic hypotheses and elaborate behavior models. That's done with the help of software Vensim that helps the construction of the models as well as performing model simulations. At the end of the book, the reader is able to: - Describe the components of a complex system. - Diagnose the natural evolution of the system under analysis. - Create a model of the system and present it using the simulation software. - Carry out simulations with the model, in order to predict the behavior of the system. Content Environmental Area 1. Population Growth 2. Ecology of a Natural Reserve 3. Effects of the Intensive Farming 4. The Fishery of Shrimp 5. Rabbits and Foxes 6. A Study of Hogs 7. Ingestion of Toxins 8. The Barays of Angkor 9. The Golden Number Management Area 10. Production and Inventory 11. CO2 Emissions 12. How to Work More and Better 13. Faults 14. Project Dynamics 15. Innovatory Companies 16. Quality Control 17. The impact of a Business Plan Social Area 18. Filling a Glass 19. A Catastrophe Study 20. The Young Ambitious Worker 21. Development of an Epidemic 22. The Dynamics of Two Clocks Mechanical Area 23. The Tank 24. Study of the Oscillatory Movements 25. Design of a Chemical Reactor 26. The Butterfly Effect 27. The Mysterious Lamp Advanced Exercises (Vensim PLE PLUS) 28. Import data from an Excel file 29. Building Games and Learning Labs 30. Interactive models 31. Input Output Controls 32. Sensitivity Analysis Annex I. Guide to creating a model II. Functions, Tables and Delays III. Frequently Asked Questions FAQs IV. Download the models of this book The author Juan Martín García is teacher and a worldwide recognized expert in System Dynamics, with more than twenty years of experience in this field. Ph.D. Industrial Engineer (Spain) and Postgraduated Diploma in Business Dynamics at Massachusetts Institute of Technology MIT (USA). He teaches Vensim online courses in http://vensim.com/vensim-online-courses/ based on System Dynamics.
Beginning with realistic mathematical or verbal models of physical or biological phenomena, the author derives tractable models for further mathematical analysis or computer simulations. For the most part, derivations are based on perturbation methods, and the majority of the text is devoted to careful derivations of implicit function theorems, the method of averaging, and quasi-static state approximation methods. The duality between stability and perturbation is developed and used, relying heavily on the concept of stability under persistent disturbances. Relevant topics about linear systems, nonlinear oscillations, and stability methods for difference, differential-delay, integro-differential and ordinary and partial differential equations are developed throughout the book. For the second edition, the author has restructured the chapters, placing special emphasis on introductory materials in Chapters 1 and 2 as distinct from presentation materials in Chapters 3 through 8. In addition, more material on bifurcations from the point of view of canonical models, sections on randomly perturbed systems, and several new computer simulations have been added.
Simulation has become a tool difficult to substitute in many scientific areas like manufacturing, medicine, telecommunications, games, etc. Finance is one of such areas where simulation is a commonly used tool; for example, we can find Monte Carlo simulation in many financial applications like market risk analysis, portfolio optimization, credit risk related applications, etc. Simulation in Computational Finance and Economics: Tools and Emerging Applications presents a thorough collection of works, covering several rich and highly productive areas of research including Risk Management, Agent-Based Simulation, and Payment Methods and Systems, topics that have found new motivations after the strong recession experienced in the last few years. Despite the fact that simulation is widely accepted as a prominent tool, dealing with a simulation-based project requires specific management abilities of the researchers. Economic researchers will find an excellent reference to introduce them to the computational simulation models. The works presented in this book can be used as an inspiration for economic researchers interested in creating their own computational models in their respective fields.
This user’s reference is a companion to the separate book also titled “Guide to Modelling and Simulation of Systems of Systems.” The principal book explicates integrated development environments to support virtual building and testing of systems of systems, covering in some depth the MS4 Modelling EnvironmentTM. This user’s reference provides a quick reference and exposition of the various concepts and functional features covered in that book. The topics in the user’s reference are grouped in alignment with the workflow displayed on the MS4 Modeling EnvironmentTM launch page, under the headings Atomic Models, System Entity Structure, Pruning SES, and Miscellaneous. For each feature, the reference discusses why we use it, when we should use it, and how to use it. Further comments and links to related features are also included.
The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems. This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field. New for the second edition: “Programming-language agnostic” presentation using pseudocode. New chapter 1 covering conceptual issues concerning Markov chains such as ergodicity and stability. New focus in chapter 2 on algorithms and techniques for program design and high-performance computing. New focus on household problems rather than optimal growth in material on dynamic programming. Solutions to many exercises, code, and other resources available on a supplementary website.