The Bounds of Reason: Game Theory and the Unification of the Behavioral Sciences

By Herbert Gintis | Go to book overview

1
Decision Theory and Human Behavior

People are not logical. They are psychological.

Anonymous

People often make mistakes in their maths.
This does not mean that we should abandon
arithmetic.

Jack Hirshleifer

Decision theory is the analysis of the behavior of an individual facing nonstrategic uncertainty—that is, uncertainty that is due to what we term “Nature” (a stochastic natural event such as a coin flip, seasonal crop loss, personal illness, and the like) or, if other individuals are involved, their behavior is treated as a statistical distribution known to the decision maker. Decision theory depends on probability theory, which was developed in the seventeenth and eighteenth centuries by such notables as Blaise Pascal, Daniel Bernoulli, and Thomas Bayes.

A rational actor is an individual with consistent preferences (§1.1). A rational actor need not be selfish. Indeed, if rationality implied selfishness, the only rational individuals would be sociopaths. Beliefs, called subjective priors in decision theory, logically stand between choices and payoffs. Beliefs are primitive data for the rational actor model. In fact, beliefs are the product of social processes and are shared among individuals. To stress the importance of beliefs in modeling choice, I often describe the rational actor model as the beliefs, preferences and constraints model, or the BPC model. The BPC terminology has the added attraction of avoiding the confusing and value-laden term “rational.”

The BPC model requires only preference consistency, which can be defended on basic evolutionary grounds. While there are eminent critics of preference consistency, their claims are valid in only a few narrow areas. Because preference consistency does not presuppose unlimited informationprocessing capacities and perfect knowledge, even bounded rationality (Si

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The Bounds of Reason: Game Theory and the Unification of the Behavioral Sciences
Table of contents

Table of contents

  • Title Page iii
  • Contents vii
  • Preface xiii
  • 1: Decision Theory and Human Behavior 1
  • 2: Game Theory: Basic Concepts 30
  • 3: Game Theory and Human Behavior 45
  • 4: Rationalizability and Common Knowledge of Rationality 83
  • 5: Extensive Form Rationalizability 102
  • 6: The Mixing Problem 121
  • 7: Bayesian Rationality and Social Epistemology 132
  • 8: Common Knowledge and Nash Equilibrium 146
  • 9: Reflective Reason and Equilibrium Refinements 164
  • 10: The Analytics of Human Sociality 181
  • 11: The Evolution of Property Rights 201
  • 12: The Unification of the Behavioral Sciences 221
  • 13: Summary 248
  • 14: Table of Symbols 250
  • Symbols for Chapter 11 251
  • References 253
  • Index 283
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