文章基本信息

标题：Risk Assessment under Ambiguity: Precautionary Learning vs. Research Pessimism
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作者：Daniel Heyen ; Timo Goeschl ; Boris Wiesenfarth 等
期刊名称：Discussion Paper Series / Universität Heidelberg, Department of Economics
出版年度：2015
出版社：Universität Heidelberg, Department of Economics
摘要：Agencies charged with regulating complex risks such as food safety or novel substances frequently need to take decisions on risk assessment and risk manage- ment under conditions of ambiguity, i.e. where probabilities cannot be assigned to possible outcomes of regulatory actions. What mandates should so ciety write for such agencies. Two approaches stand out in the current discussion. One charges the agency to apply welfare economics based on expected utility theory. This ap- proach underpins conventional cost-benet analysis (CBA). The other requires that an ambiguity-averse decision-rule – of which maxmin expected utility (MEU) is the best known – be applied in order to build a margin of safety in accordance with the Precautionary Principle (PP). The contribution of the present paper is a relative assessment of how a CBA and a PP mandate impact on the regulatory task of risk assessment. In our parsimonious mo del, a decision maker can decide on the preci- sion of a signal which provides noisy information on a payo.-relevant parameter. We find a complex interplay of MEU on information acquisition shap ed by two coun- tervailing forces that we dub 'Precautionary Learning' and 'Research Pessimism'. We find that – contrary to intuition – a mandate of PP rather than CBA will often give rise to a less informed regulator. PP can therefore lead to a higher likelihood of regulatory mistakes, such as the approval of harmful new substances
关键词：scientific uncertainty; ambiguity; learning; risk assessment; precau- ; tionary principle; active information acquisition; regulatory mandates