Barriers and Bounds to Rationality
Essays on Economic Complexity and Dynamics in Interactive Systems
1st Edition
Published on 10. January 2022
296 pages
978-0-691-23758-9 (ISBN)
Description
Peter Albin is known for his seminal work in applying the concepts of adaptive dynamical systems, first developed by biologists and physicists, to the study of economic systems. This book is a collection of his pathbreaking articles on the application of cellular automata and complexity theory to economic problems. Duncan Foley provides a thoughtful introduction in which he reviews the disparate analytical sources of Albin's work in the theories of nonlinear dynamical systems, economic dynamics, cellular automata, linguistic and computational complexity, and bounded rationality.
Albin has analyzed economic systems as interactions of highly complex components (i.e., intelligent human beings). He uses the theories of generative linguistics and cellular automata to establish that the complexity level of economic systems is, in principle at least, that of a Turing machine or general-purpose computer, establishing that classic economic approaches to the problems of household and firm choice, macroeconomic prediction, and policy evaluation may give rise to undecidable propositions and uncomputable functions. He develops simple models of dynamic economic interaction based on cellular automata which illustrate the inherent complexity of economic interactions and the resulting challenge they pose to traditional theories of rational economic behavior. These models explore the dynamics of the business cycle, decentralized market trading, and the emergence of cooperation in a novel local-interaction version of the repeated prisoners' dilemma game. Albin's work provides a unique and important perspective on economic systems.
Albin has analyzed economic systems as interactions of highly complex components (i.e., intelligent human beings). He uses the theories of generative linguistics and cellular automata to establish that the complexity level of economic systems is, in principle at least, that of a Turing machine or general-purpose computer, establishing that classic economic approaches to the problems of household and firm choice, macroeconomic prediction, and policy evaluation may give rise to undecidable propositions and uncomputable functions. He develops simple models of dynamic economic interaction based on cellular automata which illustrate the inherent complexity of economic interactions and the resulting challenge they pose to traditional theories of rational economic behavior. These models explore the dynamics of the business cycle, decentralized market trading, and the emergence of cooperation in a novel local-interaction version of the repeated prisoners' dilemma game. Albin's work provides a unique and important perspective on economic systems.
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Peter S. Albin | Duncan K. Foley
Barriers and Bounds to Rationality
Essays on Economic Complexity and Dynamics in Interactive Systems
Book
04/1998
Princeton University Press
€197.50
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Persons
Peter S. Albin, Professor Emeritus of Economics at the City University of New York, is author of The Analysis of Complex Socio-Economic Systems and Progress without Poverty. Duncan K. Foley is Professor of Economics at Barnard College of Columbia University. His books include Understanding Capital and Money, Accumulation and Crisis.
Content
- Cover Page
- Half-title Page
- Title Page
- Copyright Page
- Dedication Page
- Contents
- Preface
- Acknowledgments
- 1. Introduction
- 1.1 Dynamical systems
- 1.1.1 Linear dynamical systems
- 1.1.2 Nonlinear dynamical systems
- 1.1.3 Cellular automata as models of nonlinear dynamical systems
- 1.2 Dynamical systems in social and physical science
- 1.2.1 Local and global interaction
- 1.2.2 Topology and geometry in physical and social models
- 1.2.3 Time and causality
- 1.2.4 Identity and diversity
- 1.3 Economic models of fully rational behavior
- 1.3.1 The rational choice program
- 1.3.2 Individual decision models-intertemporal optimization
- 1.3.3 The finite-horizon Ramsey problem
- 1.3.4 Market models
- 1.3.5 Game theory models
- 1.4 Definitions and measures of complexity
- 1.4.1 Computational complexity
- 1.4.2 Linguistic complexity
- 1.4.3 Machine complexity
- 1.4.4 Decidability, computational complexity, and rationality
- 1.4.5 Dynamical systems and computational complexity
- 1.5 Complexity in cellular automata
- 1.5.1 Complexity types
- 1.5.2 Computability, predictability, and complexity in cellular automata
- 1.6 Modeling complex social and economic interactions
- 1.6.1 Self-referencing individual agents
- 1.6.2 Organizations
- 1.6.3 Industries and economies
- 1.6.4 Markets
- 1.6.5 The local interaction multiperson Prisoners' Dilemma
- 1.7 Complexity, rationality, and social interaction
- 1.7.1 How complex are social systems?
- 1.7.2 How smart do agents need to be?
- 1.8 Toward a robust theory of action and society
- 2. The Metalogic of Economic Predictions, Calculations,and Propositions
- 2.1 Introduction
- 2.2 Preliminaries: Automata and structural formations
- 2.2.1 Finite automata
- 2.2.2 Finite formations
- 2.2.3 Generalized formations and finite surrogates
- 2.2.4 General computation and computability
- 2.3 Undecidability in generalized formations
- 2.3.1 An economy with finite automaton components
- 2.3.2 Structural properties of a finite economy
- 2.3.3 Archival expansion: An economy with Turing machine components
- 2.3.4 Conditional forecasting: Economies with universal machine components
- 2.3.5 Undecidability propositions
- 2.3.6 General comments
- 2.4 Social welfare evaluations
- 2.4.1 The decision setting
- 2.4.2 The political process
- 2.4.3 The computability of a political program
- 2.4.4 Predictability of restricted programs
- 2.5 Conclusions
- Appendix: Proof of Theorem 2.5
- 3. Microeconomic Foundations of Cyclical Irregularities or "Chaos
- 3.1 Introduction
- 3.2 The research problem
- 3.2.1 The meaning of "chaos" in dynamic systems
- 3.2.2 Nonlinearities and underlying microeconomic interactions
- 3.3 A model of microeconomic interaction
- 3.3.1 Specification of interaction neighborhoods
- 3.3.2 Specification of interaction conventions
- 3.3.3 Simulation of firm behavior
- 3.3.4 Classification of simulated time series
- 3.3.5 Preliminary indications
- 3.4 Interpretations
- 3.4.1 The background model
- 3.4.2 The computation irreducibility hypothesis
- 3.4.3 Reexamination of economic implications
- 3.5 Extensions and applications
- 4. Qualitative Effects of Monetary Policy in "Rich" Dynamic Systems
- 4.1 Introduction
- 4.2 The experimental setting
- 4.3 Complexity classification of dynamic behaviors
- 4.3.1 Qualitative types of dynamic behavior
- 4.3.2 Projective properties
- 4.3.3 Modeling considerations
- 4.3.4 Dynamics and expectations
- 4.3.5 Industry structure
- 4.4 Policy interventions
- 4.4.1 Simulating monetary interventions
- 4.4.2 Properties of the system and experimental protocols
- 4.5 Results and preliminary interpretations
- 4.5.1 Incomplete stabilization
- 4.5.2 Economic implications
- 5.Decentralized, Dispersed Exchange without an Auctioneer: A Simulation Study
- 5.1 Introduction
- 5.2 A model of dispersed exchange
- 5.2.1 Endowments and utilities
- 5.2.2 Advertising neighborhoods, information costs,and trade protocol: The rules of the game
- 5.3 Strategies of agents
- 5.3.1 Boundedly rational agents of fully rational players
- 5.3.2 Truthful disclosure
- 5.3.3 The agent's computational capacity
- 5.3.4 The candidate algorithm
- 5.3.5 The expected gain from signaling
- 5.3.6 Estimating the likelihood of neighbor actions
- 5.3.7 Simulation procedures
- 5.3.8 The coefficient of resource utilization
- 5.4 Simulation results
- 5.4.1 Reporting format
- 5.4.2 Illustrative results
- 5.4.3 Trader accounts
- 5.4.4 Comment
- 5.4.5 A second illustrative example
- 5.5 Information cost and efficiency
- 5.5.1 Interactions of advertising cost and neighborhood size
- 5.5.2 Interpretations
- 5.6 Concluding comments
- 6. Approximations of Cooperative Equilibria in Multiperson Prisoners' Dilemma Played by Cellular Automata
- 6.1 Introduction
- 6.2 The model
- 6.2.1 Subgame and sub-subgame structure of MPD
- 6.2.2 Threshold conditions for equilibria in repeated play
- 6.3 Strategic equivalence and the complexity of cellular automaton rules
- 6.3.1 Digression: Study of cellular automaton complexity properties
- 6.4 The complexity of bounded-rationality forms
- 6.4.1 Classes of strategic equivalence in multiperson games
- 6.5 A theorem on "Nash-like" equilibria in MPD
- 6.6 A "Nash-like" solution to MPD
- 6.7 Conclusions
- Appendix
- 7. The Complexity of Social Groups and Social Systems Described by Graph Structures
- 7.1 Introduction
- 7.2 Directed graphs and their representation: An overview
- 7.2.1 Arbitrary system functions:"Structure generators
- 7.2.2 Analysis of the undirected graph
- 7.2.3 Parameters of the undirected graph
- 7.2.4 The function "rumor transmission with recorded path
- 7.2.5 Complexity of the rumor propagating machine
- 7.3 The directed graph
- 7.3.1 The graph that is less than total
- 7.3.2 Complexity measurement for the directed graph
- 7.3.3 Case example: Complexity of organizational structures
- 7.4 Conclusion
- Works Cited
- Index
