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The Distribution of Ambiguity Attitudes

Author

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  • Hans-Martin von Gaudecker
  • Axel Wogrolly
  • Christian Zimpelmann

Abstract

This paper analyses the stability and distribution of ambiguity attitudes using a broad population sample. We employ four waves of data from a survey instrument with high-powered incentives. Structural estimation of random utility models yields three individual-level parameters: Ambiguity aversion, likelihood insensitivity or perceived level of ambiguity, and the variance of decision errors. We demonstrate that these parameters are very heterogeneous but fairly stable over time and across domains. These contexts span financial markets—our main application—and climate change. The ambiguity parameters are interdependent in their interpretation and the precision of their estimates depends on decision errors. To describe heterogeneity in these three dimensions, we adopt a discrete classification approach. A third of our sample comes rather close to the behaviour of expected utility maximisers. Half of the sample is characterized by a high likelihood insensitivity, with thirty per cent ambiguity-averse and twenty per cent making ambiguity-seeking choices for most events. For the remaining eighteen per cent, we estimate sizeable error parameters, which implies that no robust conclusions about their ambiguity attitudes are possible. Predicting group membership with a large number of observed characteristics shows reasonable patterns.

Suggested Citation

  • Hans-Martin von Gaudecker & Axel Wogrolly & Christian Zimpelmann, 2021. "The Distribution of Ambiguity Attitudes," CRC TR 224 Discussion Paper Series crctr224_2021_272, University of Bonn and University of Mannheim, Germany.
  • Handle: RePEc:bon:boncrc:crctr224_2021_272
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    File URL: https://www.crctr224.de/research/discussion-papers/archive/dp272
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    Cited by:

    1. Lotito Gianna & Maffioletti Anna & Santoni Michele, 2023. "Testing Source Influence on Ambiguity Reaction: Preference and Insensitivity," Working papers 083, Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.

    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance

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