T25 - State of the Art in Using Economics in Risk Analysis, Part 2Mojave 3:30 - 5:00 pm
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| Chair(s): Christine McLaughlin, Curtis Haymore
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T25.1 Cost, Risk, and Option Value in Weapons Procurement. S. Farrow; U.S. General Accounting Office farrows@gao.gov
Abstract: Cost estimation for weapons procurement has its own methods and jargon. Probabilistic risk assessment of the costs using simulation methods is a relatively new recommended practice in this area that would be familiar to members of the Society for Risk Analysis. There are technological uncertainties, exogenous changes in prices and other factors that add risk to the cost (and schedule) of developing and producing weapons systems that can cost tens of billions of dollars. Two elements of weapons project management that are frequently used are Earned Value Management and rebasing of costs. Earned Value Management tracks measures related to estimated and actual costs, although there is infrequent integration with risk estimates. Rebasing is a managerial response to significant changes in estimated cost that leads to a form of re-authorization, or conceivably to cancellation of a program. Standard practice for cost estimation is reviewed for its similarities and differences with risk based benefits assessment and the value of a real option.
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T25.2 Policy Implications of Uncertainty Inherent in Dose Response Functions and Regulatory Effectiveness. J.B. Brown; Food and Drug Administration bradley.brown@cfsan.fda.gov
Abstract: Risk analysis has become an important tool in policy analysis. The emerging science has shown that simply studying a piece of the puzzle without considering the other pieces leads to uninformed policy. Furthermore, it has become obvious that the uncertainty and variability inherent in complicated systems of risk must also be considered when weighing the benefits, costs, and effectiveness of different policy choices. This paper uses the fact that human dose response functions inherently contain a large degree of uncertainty to show that regulations aimed at reducing the population exposed to harmful agents are generally more effective than regulations aimed at reducing the marginal dose. A simple theoretical model shows that uncertainty in the dose response function, particularly when there is relatively little confidence in both the slope and the linearity of the function, make regulations that effectively reduce the population exposed more attractive than regulations that effectively reduce the marginal exposure. When uncertainty in the effectiveness of the policy achieving its target is considered, the general results are dampened slightly. The results of the theoretical model are compared with the results of a case study. The results from the theoretical model and case study have important implications for weighing policy alternatives. In many cases, an information-based policy aimed at educating high risk populations on risks or making it easy to identify the risk via labeling is more desirable than a command and control policy targeting marginal reductions of the environmental levels of the risky agent.
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T25.3 A Framework for Combining Risk Analysis With Cost-Benefit and Environmental Analysis to Improve Regulatory Analysis. C. A. * Narrod, L. C. Abbott, W.T. Disney, J. W. Glauber, J. D. Schaub; US Department of Agriculture cnarrod@oce.usda.gov
Abstract: USDA agencies devote considerable resources to analyses – risk, cost-benefit, environmental - in support of policies designed to prevent animal and plant disease and human food-borne illness. E.O. 12866, P.L.103-354 and NEPA require cost-benefit, risk and environmental analyses, but there is no mechanism ensuring consistency. Supporting analyses are often developed within tight deadlines required by policy officials. Analyses may be conducted under separate chains of command and may analyze divergent alternatives. Lack of consistency between various regulatory analyses may open the rule to general criticism and legal challenges. Critics of the rulemaking process have identified inconsistencies in the premises, options considered, assumptions made, facts used, and conclusions. Lack of consistency can lead to confusion and lags during rulemaking as various reviewing agencies identify critical gaps in the analyses. Over 25 USDA rules have been challenged both domestically and by the international community for a variety of reasons including faulty science and insufficient cost-benefit and/or risk assessments and/or insufficient NEPA analyses. This paper highlights some of the costs of these challenges and proposes a conceptual framework to integrate various regulatory analyses and ensuring consistency between them. USDA uses a variety of modeling methods to analyze risks, economics, and environmental aspects of diseases such as Karnal Bunt, foot-and-mouth disease, BSE, E. coli O157, and avian influenza. These methods include stochastic simulation models, discounted cost models, and value of information techniques. The strengths and weaknesses of these methods as a part of an integrated systematic approach to analyses are compared. The conceptual framework integrates these methods, ensuring the method used is appropriate for the question and that the results are in a consistent format for use in any of the regulatory analyses. Using this conceptual framework, we structure a model and apply it to a hypothetical animal disease.
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T25.4 A discussion of the principles of cost-benefit analyses . E.B. Abrahamsen, T. Aven; University of Stavanger eirik.b.abrahamsen@tn.his.no
Abstract: To evaluate the goodness of alternative safety measures, many analysts, policy makers and decision makers see cost-benefit analyses and related type of analyses such as cost-effectiveness analyses, as the most suitable tool. But there is no consensus on how such analyses should be carried out. Fundamental issues are being discussed, such as the use of a specific value for a statistical life, determining the “correct” discount rates, the search for objectivity, the application of principles such as willingness to pay, treatment of uncertainties and the way of dealing with intangibles. Some see cost-benefit analyses as a tool for providing decisions, others see the analyses as providing decision making support, leaving the decision makers to apply decision processes outside the direct applications of the cost-benefit analyses.
In this paper we address the above challenges related to the understanding and use of cost-benefit analyses and related type of analyses, for evaluating alternative safety measures. Compared to much of the earlier discussion of this topic, the paper has a higher level of precision on the way uncertainty, probability and expected values are understood and measured. Such a precision level is required to give the necessary sharpness on what cost-benefit analyses and related type of analyses can do and not do. The paper links theories from economics, social sciences as well as from the safety field, and it is seen as a contribution of the paper to give a decision making framework that is holistic, in the sense that all essential relevant perspectives are included.
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