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Clarifying Types of Uncertainty: When Are Models Accurate, and Uncertainties Small?

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  • Louis Anthony (Tony) Cox, Jr.

Abstract

Professor Aven has recently noted the importance of clarifying the meaning of terms such as “scientific uncertainty” for use in risk management and policy decisions, such as when to trigger application of the precautionary principle. This comment examines some fundamental conceptual challenges for efforts to define “accurate” models and “small” input uncertainties by showing that increasing uncertainty in model inputs may reduce uncertainty in model outputs; that even correct models with “small” input uncertainties need not yield accurate or useful predictions for quantities of interest in risk management (such as the duration of an epidemic); and that accurate predictive models need not be accurate causal models.

Suggested Citation

  • Louis Anthony (Tony) Cox, Jr., 2011. "Clarifying Types of Uncertainty: When Are Models Accurate, and Uncertainties Small?," Risk Analysis, John Wiley & Sons, vol. 31(10), pages 1530-1533, October.
  • Handle: RePEc:wly:riskan:v:31:y:2011:i:10:p:1530-1533
    DOI: 10.1111/j.1539-6924.2011.01706.x
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    References listed on IDEAS

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    1. Terje Aven, 2011. "On Different Types of Uncertainties in the Context of the Precautionary Principle," Risk Analysis, John Wiley & Sons, vol. 31(10), pages 1515-1525, October.
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