Modeling Aggregate Behavior and Fluctuations in Economics: Stochastic Views of Interacting Agents / Edition 1

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Overview

This book analyzes how a large but finite number of agents interact, and what sorts of macroeconomic statistical regularities or patterns may evolve from these interactions. By keeping the number of agents finite, the book examines situations such as fluctuations about equilibria, multiple equilibria and asymmetrical cycles of models which are caused by model states stochastically moving from one basin of attraction to another. All of these are not tractable using traditional deterministic modeling approaches. The book also discusses how agents may form clusters with stationary distributions of cluster sizes. These have important applications in analyzing volatilities of asset returns.
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Editorial Reviews

From the Publisher
'This is a most welcome treatment of stochastic dynamics in economic models, and its significance for theoretical and applied economics … Professor Aoki has provided a self-contained description of all necessary and relevant concepts of the modelling toolbox, including key stochastic dynamics concepts such as the Master Equation (the backward Kolmogorov-Chapman Equation), the Fokker Planck equation, Jump Markov Processes, Random Partitions and Combinatorial Randomness.' Asia Pacific Journal of Management

'Once again Masanao Aoki has written a book ahead of its time. This time he applies techniques popular in the hard sciences, but alien to most economists, to analyse the dynamic interaction of a large (finite) number of agents (or entities.) He characterises types of agents by their decisions and the movement between types as endogenous transition probabilities. Aoki uses random combinatorial analysis to describe the distribution of types, and the backward Chapman-Kolmogorov equations to describe the aggregate dynamics. This is an innovative approach to characterise a complicated dynamic stochastic economic environment.' Roger Craine, University of California, Berkeley

'In recent years, the economics profession has experienced a growing interest in modelling economic phenomena as the outcome of the interactions of heterogeneous individuals. Although interaction and heterogeneity appear to be natural and pervasive features of modern economies, the formerly dominating tradition of modelling representative agents has eschewed both to a large extent. However, the increasing awareness of the importance of these features also requires the adaptation or development of appropriate technical tools. Professor Aoki has done a great service to the profession by providing a unified treatment of methods for stochastic modelling of large collections of heterogeneous agents. As a companion and sequel to his seminal New Approaches to Macroeconomic Modeling, the present volume both adds advanced material and demonstrates the power of the statistical approach by applying it to important classes of economic models. With its unique coverage and rigourous presentation, the book will immediately become a standard reference in the exciting new area of interacting agent modelling in economics.' Thomas Lux, University of Kiel

'Economists have long taken optimization as first principles in economics. This belief has lead many to the Walrasian or the intertemporal utility maximization model, and has fundamentally changed macroeconomics. Unfortunately, the standard model such as real business cycle theory looks hopelessly unrealistic. It may sound like a paradox that the model which is based on explicit maximization of the representative agent is so unsatisfactory as a macro model. Professor Aoki's book gives us a good answer to this question, and at the same time, provides us with a new methodology in macroeconomics. He convincingly argues that Jump Markov Process is a powerful and fruitful tool in macroeconomics. Professor Aoki explains the method, and also provides examples. The book will be remembered as a landmark.' Hiroshi Yoshikawa, University of Tokyo

Booknews
Discussing both stochastic dynamics and stochastic random combinatorial analysis, Aoki (emeritus, economics, U. of California in Los Angeles) attempts to reformulate macroeconomic models employed by mainstream economists. He argues that models with finite numbers of agents in stochastic contexts reveal economic phenomena that fail to show in deterministic models with infinite number of agents. His approach emphasizes that an outcome of interactions of a large number of agents facing idiosyncratic shocks cannot be described by traditional approaches. He formulates and analyzes a large but finite number of interacting economic agents as continuous-time Markov chains with discrete spaces. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780521781268
  • Publisher: Cambridge University Press
  • Publication date: 12/28/2001
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 280
  • Product dimensions: 5.98 (w) x 8.98 (h) x 0.75 (d)

Meet the Author

Masanao Aoki is Professor Emeritus in the Department of Economics at the University of California, Los Angeles. He also held professorial appointments at the Institute for Social and Economic Research at Osaka University, Tokyo Institute of Technology, and the University of Illinois. Professor Aoki is a past President of the Society for Economic Dynamics and Control, a Fellow of the Econometric Society, and a Fellow of the IEEE Control Systems Society. Currently Associate Editor of the journal Macroeconomic Dynamics published by Cambridge University Press, he also served as Editor of the Journal of Economic Dynamics and Control and the International Economic Review, and Associate Editor of the IEEE's Transaction of Automatic Control, Information Sciences, and the Journal of Mathematical Analysis and Application. Professor Aoki is the author or editor of ten books, including New Approaches to Macroeconomic Modeling: Evolutionary Stochastic Dynamics, Multiple Equilibria, and Externalities as Field Effects (Cambridge University Press, 1996).
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Table of Contents

1. Overview; 2. Setting up dynamic models; 3. The master equation; 4. Introductory simple and simplified models; 5. Aggregate dynamics and fluctuations of simple models; 6. Evaluation of alternatives; 7. Solving non-stationary master equations; 8. Growth and business cycle models; 9. Example: a new look at the diamond search model; 10. Interaction patterns of agents and distributions of cluster sizes; 11. Example: share markets with two dominant types of participants in a market.
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