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Errors in Probabilistic Reasoning and Judgment Biases

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  • Daniel J. Benjamin

    () (University of Southern California and NBER)

Abstract

Errors in probabilistic reasoning have been the focus of much psychology research and are among the original topics of modern behavioral economics. This chapter reviews theory and evidence on this topic, with the goal of facilitating more systematic study of belief biases and their integration into economics. The chapter discusses biases in beliefs about random processes, biases in belief updating, the representativeness heuristic as a possible unifying theory, and interactions between biased belief updating and other features of the updating situation. Throughout, I aim to convey how much evidence there is for (and against) each putative bias, and I highlight when and how different biases may be related to each other. The chapter ends by drawing general lessons for when people update too much or too little, reflecting on modeling challenges, pointing to areas of economics to which the biases are relevant, and highlighting some possible directions for future work.

Suggested Citation

  • Daniel J. Benjamin, 2018. "Errors in Probabilistic Reasoning and Judgment Biases," GRU Working Paper Series GRU_2018_023, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
  • Handle: RePEc:cth:wpaper:gru_2018_023
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    More about this item

    Keywords

    Gambler’s fallacy; Law of Small Numbers; hot hand; partition dependence; sample-size neglect; non-belief in the Law of Large Numbers; conservatism bias; Base-rate neglect; Representativeness heuristic; Confirmation bias;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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