Description

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This course is anchored on the seven main sections associated with the key Economics areas where the complex systems studies approach to economy has been known to have important influence. These sections are: Section I: A Philosophical and Methodological approach to Economy using Complexity Sciences; Section II: The structure of interaction; Section III: Macroeconomics and Growth; Section IV: Financial Markets; Section V: International and Monetary Economy Dynamics; Section VI: Regional Economic Systems; Section VII: Evolutionary Economic Dynamics. Other than discussing the literature, the students will be invited to model, implement and discuss some of the underlying mentioned models using social simulation programming libraries, such as NetLogo.


About the Professor(s)

Professor Bruno Gaminha Assistant Research Professor of Complexity in Economics at the IIT-Gandhinagar

Professor Jorge Louçã teaches Computer Science at the IUL - Lisbon University Institute, where he runs the Master and Doctoral Programs in Complexity Sciences. His PhD is in Artificial Intelligence. He coordinates The Observatorium research team and his research interests concern modelling complex social systems through intensive data collection and analysis. He is particularly interested by knowledge generation models in large-scale communication networks. Recently he participated in the creation of the Unitwin network for the Complex Systems Digital Campus, involving institutions from Africa, Latin America and Europe.

Bibliography

Complex Economics: Individual and Collective Rationality

The economic crisis is also a crisis for economic theory. Most analyses of the evolution of the crisis invoke three themes, contagion, networks and trust, yet none of these play a major role in standard macroeconomic models. What is needed is a theory in which these aspects are central. The direct interaction between individuals, firms and banks does not simply produce imperfections in the functioning of the economy but is the very basis of the functioning of a modern economy. This book suggests a way of analysing the economy which takes this point of view. The economy should be considered as a complex adaptive system in which the agents constantly react to, influence and are influenced by, the other individuals in the economy. In such systems which are familiar from statistical physics and biology for example, the behaviour of the aggregate cannot be deduced from the behaviour of the average, or "representative" individual. Just as the organised activity of an ants nest cannot be understood from the behaviour of a "representative ant" so macroeconomic phenomena should not be assimilated to those associated with the "representative agent". This book provides examples where this can clearly be seen. The examples range from Schelling's model of segregation, to contributions to public goods, the evolution of buyer seller relations in fish markets, to financial models based on the foraging behaviour of ants. The message of the book is that coordination rather than efficiency is the central problem in economics. How do the myriads of individual choices and decisions come to be coordinated? How does the economy or a market, "self organise" and how does this sometimes result in major upheavals, or to use the phrase from physics, "phase transitions"? The sort of system described in this book is not in equilibrium in the standard sense, it is constantly changing and moving from state to state and its very structure is always being modified. The economy is not a ship sailing on a well-defined trajectory which occasionally gets knocked off course. It is more like the slime described in the book "emergence", constantly reorganising itself so as to slide collectively in directions which are neither understood nor necessarily desired by its components.

Lectures on Behavioral Macroeconomics

In mainstream economics, and particularly in New Keynesian macroeconomics, the booms and busts that characterize capitalism arise because of large external shocks. The combination of these shocks and the slow adjustments of wages and prices by rational agents leads to cyclical movements. In this book, Paul De Grauwe argues for a different macroeconomics model--one that works with an internal explanation of the business cycle and factors in agents' limited cognitive abilities. By creating a behavioral model that is not dependent on the prevailing concept of rationality, De Grauwe is better able to explain the fluctuations of economic activity that are an endemic feature of market economies. This new approach illustrates a richer macroeconomic dynamic that provides for a better understanding of fluctuations in output and inflation. De Grauwe shows that the behavioral model is driven by self-fulfilling waves of optimism and pessimism, or animal spirits. Booms and busts in economic activity are therefore natural outcomes of a behavioral model. The author uses this to analyze central issues in monetary policies, such as output stabilization, before extending his investigation into asset markets and more sophisticated forecasting rules. He also examines how well the theoretical predictions of the behavioral model perform when confronted with empirical data. Develops a behavioral macroeconomic model that assumes agents have limited cognitive abilities Shows how booms and busts are characteristic of market economies Explores the larger role of the central bank in the behavioral model Examines the destabilizing aspects of asset markets

The Sciences of the Artificial

"People sometimes ask me what they should read to find out about artificial intelligence. Herbert Simon's book The Sciences of the Artificial is always on the list I give them. Every page issues a challenge to conventional thinking, and the layman who digests it well will certainly understand what the field of artificial intelligence hopes to accomplish. I recommend it in the same spirit that I recommend Freud to people who ask about psychoanalysis, or Piaget to those who ask about child psychology: If you want to learn about a subject, start by reading its founding fathers." -- George A. Miller, "Complex Information Processing" Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial intelligence adds a chapter that sorts out the current themes and tools -- chaos, adaptive systems, genetic algorithms -- for analyzing complexity and complex systems.

Discovering artificial economics: how agents learn and economies evolve

Discovering Artificial Economics is an informal introduction to the ideas of modern systems theory and self-organization as they apply to problems in the economic realm. David Batten interleaves anecdotes and stories with technical discussions, in order to provide the general reader with a good feel for how economies function and change. Using a wealth of examples from evolutionary game theory, to stock markets, to urban and traffic planning, Batten shows how economic agents interact to produce the behavior we have come to recognize as economic life. Despite the book's easy-to-read style, Batten's message is quite profound. Strongly interactive groups of agents can produce unexpected collective behavior, emergent features which are lawful in their own right. These patterns of emergent behavior are the hallmark of a complex, self-organizing economy.Batten discards many traditional axioms of economic behavior. Far from displaying perfectly deductive rationality to achieve a predictable economic equilibrium, his agents face an economy that is open and dynamic. There we find evolution, heterogeneity and instabilities; stochastic and deterministic phenomena; unexpected regularities as well as equally unexpected, large-scale fluctuations. Interacting agents are forced to be intuitive and adaptive, because they must respond to a continuously changing economic landscape. Because complexity theory attempts to study a large number of agents, and their changing interaction patterns, it often gets too difficult for a mathematical solution. Thus, many of the anecdotes and results discussed in the book have emerged from agent-based computer simulations. The message is that the social sciences are poised on the verge of a new scientific era, one in which economists will conduct experiments inside their own computers. Welcome to the new age of Artificial Economics.

Social and Economic Networks

Networks of relationships help determine the careers that people choose, the jobs they obtain, the products they buy, and how they vote. The many aspects of our lives that are governed by social networks make it critical to understand how they impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. In Social and Economic Networks, Matthew Jackson offers a comprehensive introduction to social and economic networks, drawing on the latest findings in economics, sociology, computer science, physics, and mathematics. He provides empirical background on networks and the regularities that they exhibit, and discusses random graph-based models and strategic models of network formation. He helps readers to understand behavior in networked societies, with a detailed analysis of learning and diffusion in networks, decision making by individuals who are influenced by their social neighbors, game theory and markets on networks, and a host of related subjects. Jackson also describes the varied statistical and modeling techniques used to analyze social networks. Each chapter includes exercises to aid students in their analysis of how networks function. This book is an indispensable resource for students and researchers in economics, mathematics, physics, sociology, and business.

Lessons and resources