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Fighting Fire with Fire - Overcoming Ambiguity Aversion by Introducing more Ambiguity

Author

Listed:
  • Dirk van Straaten

    (Paderborn University)

  • René Fahr

    (Paderborn University)

Abstract

Ambiguity aversion guides decision makers to choose a risky rather than an ambiguous prospect, a pattern that is not always beneficial. For example, even nowadays, private pensions often build on savings accounts, which are risky prospects with known probabilities, instead of stocks as the former ensure safe returns with fixed interest rates. In comparison, expected returns of stocks, which are ambiguous prospects with unknown probabilities, are significantly higher. This study aims at facilitating a better understanding of ambiguity aversion and suggests measures to improve decision-making. In our experiment, subjects are confronted with either decisions under risk or decisions under ambiguity. Controlling for risk attitudes, we estimate category weights in both domains and find significant differences, which indicate the present of ambiguity aversion. Contrary to our predictions on the amplifying effect of multiple sources of ambiguity, we find that category weights of ambiguity and risk converge each other when a second source of ambiguity is implemented. That is, we point out another option to deal with ambiguity when people have to choose between risky and ambiguous prospects. Instead of minimizing ambiguity, the introduction of a second source of ambiguity might help to compare alternatives with less biases through ambiguity aversion.

Suggested Citation

  • Dirk van Straaten & René Fahr, 2021. "Fighting Fire with Fire - Overcoming Ambiguity Aversion by Introducing more Ambiguity," Working Papers Dissertations 73, Paderborn University, Faculty of Business Administration and Economics.
  • Handle: RePEc:pdn:dispap:73
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    References listed on IDEAS

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    More about this item

    Keywords

    Unknown source credibility; Risk; Ambiguity aversion; Uncertainty; Customer ratings;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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