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Artifactual Uncertainty in Risk Analysis

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  • Louis Anthony Cox

Abstract

The field of comparative risk analysis of electrical energy alternatives has traditionally been plagued by highly uncertain estimates of risk rates, and consequently by conflicting judgements of relative risk. To the extent that this uncertainty arises from traditional sources–imperfect observations or actual variance in the data–it can be brought within a Bayesian statistical framework which allows policy conclusions to be formulted and tested at different levels of confidence. It is shown that there are important methodological or “artifactual” sources of uncertainty, however, that cannot be treated by statistical means; these require conceptual advances for their resolution. By identifying these sources of uncertainty in simple thought experiments and examples, it is shown in what ways the concept of attributable risk, which is the policy‐maker's chief concern, must be sharpened and refined to have unambiguous meaning. The conventional “multilinear” formula for calculating risk indices is challenged as a measure of attributable risk, and directions for further research to improve the methodological foundations of comparative risk analysis are identified.

Suggested Citation

  • Louis Anthony Cox, 1982. "Artifactual Uncertainty in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 2(3), pages 121-135, September.
  • Handle: RePEc:wly:riskan:v:2:y:1982:i:3:p:121-135
    DOI: 10.1111/j.1539-6924.1982.tb01375.x
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    References listed on IDEAS

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    1. Mayshar, Joram, 1977. "Should Government Subsidize Risky Private Projects?," American Economic Review, American Economic Association, vol. 67(2), pages 20-28, March.
    2. Chris Whipple, 1981. "Energy Production Risks: What Perspective Should We Take?," Risk Analysis, John Wiley & Sons, vol. 1(1), pages 29-35, March.
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