Rare disasters and risk attitudes: international differences and implications for integrated assessment modeling.

Journal Article (Journal Article)

Evaluation of public policies with uncertain economic outcomes should consider society's preferences regarding risk. However, the preference models used in most integrated assessment models, including those commonly used to inform climate policy, do not adequately characterize the risk attitudes revealed by typical investment decisions. Here, we adopt an empirical approach to risk preference description using international historical data on investment returns and the occurrence of rare economic disasters. We improve on earlier analyses by employing a hierarchical Bayesian inference procedure that allows for nation-specific estimates of both disaster probabilities and preference parameters. This provides a stronger test of the underlying investment model than provided by previous calibrations and generates some compelling hypotheses for further study. Specifically, results suggest that society is substantially more averse to risk than typically assumed in integrated assessment models. In addition, there appear to be systematic differences in risk preferences among nations. These results are likely to have important implications for policy recommendations: higher aversion to risk increases the precautionary value of taking action to avoid low-probability, high-impact outcomes. However, geographically variable attitudes toward risk indicate that this precautionary value could vary widely across nations, thereby potentially complicating the negotiation of transboundary agreements focused on risk reduction.

Full Text

Duke Authors

Cited Authors

  • Ding, P; Gerst, MD; Bernstein, A; Howarth, RB; Borsuk, ME

Published Date

  • November 2012

Published In

Volume / Issue

  • 32 / 11

Start / End Page

  • 1846 - 1855

PubMed ID

  • 22816316

Electronic International Standard Serial Number (EISSN)

  • 1539-6924

International Standard Serial Number (ISSN)

  • 0272-4332

Digital Object Identifier (DOI)

  • 10.1111/j.1539-6924.2012.01872.x


  • eng