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Heterogeneity in risk attitudes across domains: A bivariate random preference approach

Author

Listed:
  • Anna Conte

    (University of Westminster)

  • Peter G. Moffatt

    (University of East Anglia)

  • Mary Riddel

    (University of Nevada)

Abstract

In a series of field experiments, we elicit risk preferences for financial, life-duration, and environmental domains using sequential multiple price-list auctions. We intentionally oversample subjects who frequently engage in activities that increase their mortality risk. We analyze the data using a bivariate Random Preference approach. Under the assumption that subjects are Rank Dependent Utility maximizers, we estimate the joint distribution of the CRRA and probability weighting coefficients. We find that the experienced risk takers are less likely than the student control group to overweight small probability, extreme events in their decision making. This is true in all three domains. We find that the tendency of women to be more risk averse in the financial domain than men arises from probability weighting rather than differences in the utility function. Finally, we show that a significant minority of subjects deviate from the type of s-inverse probability weighting typically observed in experiments.

Suggested Citation

  • Anna Conte & Peter G. Moffatt & Mary Riddel, 2015. "Heterogeneity in risk attitudes across domains: A bivariate random preference approach," Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) 15-10, School of Economics, University of East Anglia, Norwich, UK..
  • Handle: RePEc:uea:wcbess:15-10
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D0 - Microeconomics - - General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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