Bayesian Analysis and Uncertainty in Economic Theory
We began this research with the objective of applying Bayesian methods of analysis to various aspects of economic theory. We were attracted to the Bayesian approach because it seemed the best analytic framework available for dealing with decision making u
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BAYESIAN ANALYSIS AND UNCERT AINTY IN ECONOMIC THEORY
RICHARD M. CYERT MORRIS H. DeGROOT Carnegie Mellon University
CHAPMAN AND HALL LONDON
First published 1987 by Chapman and Hall Limited II New Fetter Lane, London EC4P 4EE Copyright © 1987 Softcover reprint of the hardcover 1st edition 1987 Richard M. Cyert and Morris H. DeGroot ISBN -13: 978-94-010-7922-8 DOl: 10.1007/978-94-009-3163-3 All rights reserved
e-ISBN-13: 978-94-009-3163-3
To our wives, Margaret S. Cyert and Marilyn D. DeGroot, whose indifference to this work was deeply appreciated by us.
Contents
Preface Acknow ledgments
IX
xiii
1
Introduction
2
Bayesian Decision Theory
3
Behavioral and Control Theory of the Firm
27
4
Bayesian Analysis and Duopoly Theory
41
5
Multiperiod Decision Models with Alternating Choice as a Solution to the Duopoly Problem
57
6
Cooperation and Learning in a Duopoly Context
74
7
Interfirm Learning and the Kinked Demand Curve
93
8
Sequential Strategies in Dual Control Problems
109
9
Adaptive Utility
127
10
Some Examples of Adaptive Utility
144
11
Sequential Investment Decisions
152
12
Capital Allocation within Firms
162
13
Rational Expectations
171
14
Epilogue
186
7
References
189
Author Index
199
Subject Index
203
Preface
We began this research with the objective of applying Bayesian methods of analysis to various aspects of economic theory. We were attracted to the Bayesian approach because it seemed the best analytic framework available for dealing with decision making under uncertainty, and the research presented in this book has only served to strengthen our belief in the appropriateness and usefulness of this methodology. More specifically, we believe that the concept of organizational learning is fundamental to decision making under uncertainty in economics and that the Bayesian framework is the most appropriate for developing that concept. The central and unifying theme of this book is decision making under uncertainty in microeconomic theory. Our fundamental aim is to explore the ways in which firms and households make decisions and to develop models that have a strong empirical connection. Thus, we have attempted to contribute to economic theory by formalizing models of the actual process of decision making under uncertainty. Bayesian methodology provides the appropriate vehicle for this formalization. We recognize that the topic of decision making under uncertainty is a wide one, and one that is actively being studied from many different perspectives. In particular, we applaud the work done by many economists in attempting to model oligopolies through the use of supergames and games of incomplete information. We are concerned, however, that the expectational assumptions of game theory, including dynamic "supergames" with imperfect information, have a weak empirical basis. The ongoing development of game theory through the use of more sophisticated mathematical models, we believe, is at best tangential to the actual process of decision making under uncertai
