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Neighborhood-Based Information Costs

Author

Listed:
  • Benjamin M. Hébert
  • Michael Woodford

Abstract

We propose a new measure of the cost of information structures in rational inattention problems, the "neighborhood-based" cost functions, given that many applications involve states with a topological structure. These cost functions summarize the results of a sequential information sampling problem, and also capture a notion of perceptual distance. This second property allows neighborhood-based cost functions, unlike mutual information, to make accurate predictions about behavior in perceptual experiments. We compare the implications of our neighborhood-based cost functions with those of a mutual-information cost function in a series of applications: security design, global games, modeling perceptual judgments, and linear-quadratic-Gaussian problems.

Suggested Citation

  • Benjamin M. Hébert & Michael Woodford, 2020. "Neighborhood-Based Information Costs," NBER Working Papers 26743, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:26743
    Note: ME TWP
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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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