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A Model of Nonbelief in the Law of Large Numbers

Author

Listed:
  • Daniel J. Benjamin
  • Matthew Rabin
  • Collin Raymond

Abstract

People believe that, even in very large samples, proportions of binary signals might depart significantly from the population mean. We model this “nonbelief in the Law of Large Numbers” by assuming that a person believes that proportions in any given sample might be determined by a rate different than the true rate. In prediction, a nonbeliever expects the distribution of signals will have fat tails. In inference, a nonbeliever remains uncertain and influenced by priors even after observing an arbitrarily large sample. We explore implications for beliefs and behavior in a variety of economic settings.

Suggested Citation

  • Daniel J. Benjamin & Matthew Rabin & Collin Raymond, 2016. "A Model of Nonbelief in the Law of Large Numbers," Journal of the European Economic Association, European Economic Association, vol. 14(2), pages 515-544.
    • Handle: RePEc:oup:jeurec:v:14:y:2016:i:2:p:515-544.
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    File URL: http://hdl.handle.net/10.1111/jeea.12139
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    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • B49 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Other

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