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This report addresses one aspect of how probabilistic risk assessment (PRA) studies should be integrated into the regulatory process. Intended for use by the Nuclear Regulatory Commission staff, it looks specifically at how uncertainty in risk estimates is to be factored into regulatory decisionmaking. Section II defines "confidence in risk"--a simple measure of the degree to which a goal or regulation is likely to be met. In Section III the authors apply the confidence in risk measure to some selected nonnuclear technologies. Section IV examines some PRAs for the Zion and Indian Point nuclear power plants; compares the estimated risks to proposed safety goals; and applies the confidence in risk measure to the frequency of core melt, and the societal risk in terms of acute or prompt deaths and latent (cancer) deaths. Section V develops some decision rules for dealing with uncertainty. Finally, some recommendations regarding the implementation of the findings are offered.
Decision making. --- Risk. --- Uncertainty.
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Technology --- Risk assessment --- Congresses
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Risk --- Risk management --- Risque --- Gestion du risque --- Risk. --- Risk management. --- Economics --- Uncertainty --- Probabilities --- Profit --- Risk-return relationships --- Insurance --- Management
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In this paper we extend the recent work on the choice of input mix under uncertainty. In particular, we demonstrate that the qualitative nature of the disturbance term, along with the decision sequence, is a crucial determinant of the overall effect of uncertainty on the optimal input mix of a firm. Using general demand and production functions in conjunction with a mean-variance framework for financial valuation, we demonstrate the differential effects of systematic and non-systematic risk on the firm's choice of an optimal input mix. Consistent with earlier work in economics, this analysis demonstrates that uncertainty, regardless of the source, has important implications for the firm's choice of technology.
Risk --- Capital --- Capital investments --- Mathematical models.
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