A Bayesian Framework for the Precautionary Principle⇤

A common misconception is that precautionary motives in public policy cannot be justified within the Bayesian rational-choice framework, and that decision criteria that appeal to ambiguity and pessimism are needed. This paper critically evaluates these claims, arguing that a rational policy process must be Bayesian in order to avoid paradoxical, even absurd, recommendations, such as policies that depend on sunk cost or that suppress costless information. The paper also argues that the distinction between measurable risk and fundamental, or Knightian, uncertainty can be made within the standard framework of Bayesian rationality. Finally, a simple model is proposed to highlight situations where precautionary action may be normatively justified. Forthcoming in: Journal of Legal Studies. ⇤I thank David Weisbach for his invitation to present this paper at the Conference on Developing Regulatory Policy in the Context of Deep Uncertainty at the University of Chicago Law School, and for his valuable comments as discussant. I also thank participants at the Workshop on Model Inadequacy in Policy Making at LSE, and at seminars in CERGE-EI, Prague, and the University of Vienna. I benefited from many discussions about decision theory with Jonathan Weinstein. Finally, I thank Luciano Pomatto for his comments and research assistance. † Department of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University, Evanston IL 60208. Research Page: http://www.kellogg.northwestern.edu/faculty/alnajjar/htm/index.html.