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The Distribution of Ambiguity Attitudes

Author

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

Abstract

This paper analyzes the stability and distribution of ambiguity attitudes using a broad population sample. Using high-powered incentives, we collected six waves of data on ambiguity attitudes about financial markets—our main application—and climate change. Estimating a structural stochastic choice model, we obtain three individual-level parameters: Ambiguity aversion, likelihood insensitivity, and the magnitude of decision errors. These parameters are very heterogeneous in the population. At the same time, they are stable over time and largely stable across domains. We summarize heterogeneity in these three dimensions using a discrete classification approach with four types. Each group makes up 20-30% of the sample. One group comes close to the behavior of expected utility maximizers. Two types are characterized by high likelihood insensitivity; one of them is ambiguity averse and the other ambiguity seeking. Members of the final group have large error parameters; robust conclusions about their ambiguity attitudes are difficult. Observed characteristics vary between groups in plausible ways. Ambiguity types predict risky asset holdings in the expected fashion, even after controlling for many covariates.

Suggested Citation

  • Hans-Martin von Gaudecker & Axel Wogrolly & Christian Zimpelmann, 2022. "The Distribution of Ambiguity Attitudes," CESifo Working Paper Series 10079, CESifo.
  • Handle: RePEc:ces:ceswps:_10079
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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10079.pdf
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    Cited by:

    1. Henkel, Luca, 2024. "Experimental evidence on the relationship between perceived ambiguity and likelihood insensitivity," Games and Economic Behavior, Elsevier, vol. 145(C), pages 312-338.
    2. Lotito Gianna & Maffioletti Anna & Santoni Michele, 2023. "Testing Source Influence on Ambiguity Reaction: Preference and Insensitivity," Working papers 083, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    3. Cédric Gutierrez & Emmanuel Kemel, 2024. "Measuring natural source dependence," Experimental Economics, Springer;Economic Science Association, vol. 27(2), pages 379-416, April.

    More about this item

    Keywords

    ambiguity attitudes; temporal stability; domain specificity; sociodemographic factors; cluster analysis; household portfolio choice;
    All these keywords.

    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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