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A coefficient of risk vulnerability

Author

Listed:
  • Philomena M. Bacon

    (Aviva UK & Ireland)

  • Anna Conte

    (University of Westminster)

  • Peter G. Moffatt

    (University of East Anglia)

Abstract

Panel data from the German SOEP is used to test for risk vulnerability (RV) in the wider population. Two different survey responses are analysed: the response to the question about willingness-to-take risk in general; and the chosen investment in a hypothetical lottery. A con- venient indicator of background risk is the VDAX index, an established measure of volatility in the German stock market. This is used as an explanatory variable in conjunction with HDAX, the stock market index, which proxies wealth. The impacts of these measures on risk attitude are identifiable by exploiting the time dimension of the panel, and matching survey months with corresponding observations from these time-varying factors. Both of the survey responses allow us to test for decreasing absolute risk aversion (DARA); in one case we find strong evidence of DARA, while in the other, we do not. Both survey responses also allow us to test for RV, and in both cases we find strong evidence. In the case of the hypothetical lottery response we are also able to estimate a "coefficient of risk vulnerability" (CRV). This is defined as the absolute amount by which absolute risk aversion rises in response to a doubling of background risk. We estimate CRV to be between 1.03 and 1.27.

Suggested Citation

  • Philomena M. Bacon & Anna Conte & Peter G. Moffatt, 2016. "A coefficient of risk vulnerability," University of East Anglia School of Economics Working Paper Series 2016-01, School of Economics, University of East Anglia, Norwich, UK..
    • Handle: RePEc:uea:ueaeco:2016_01
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    References listed on IDEAS

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    More about this item

    Keywords

    risk vulnerability; background risk; panel data; survey data;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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