Attitudes Toward Catastrophe

Abstract

In light of climate change and other global threats, policy commentators sometimes urge that society should be more concerned about catastrophes. This paper reflects on what society’s attitude toward low-probability, high-impact events is, or should be. We first argue that catastrophe risk can be conceived of as a spread in the distribution of losses. Based on this conception, we review studies from decision sciences, psychology, and behavioral economics that explore people’s attitudes toward various social risks. Contray to popular belief, we find more evidence against than in favor of catastrophe aversion—the preference for a mean-preserving contraction of the loss distribution—and discuss a number of possible behavioral explanations. Next, we turn to social choice theory and examine how various social welfare functions handle catastrophe risk. We explain why catastrophe aversion may be in conflict with equity concerns and other-regarding preferences. Finally, we discuss current approaches to evaluate and regulate catastrophe risk.

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Notes

  1. 1.

    Key words and journals included in the bibliometric analysis appear in the “Appendix”. Note that our analysis includes all kinds of catastrophic events including natural disasters and climate change, but also warfare and financial crises.

  2. 2.

    We note that our definition of catastrophe risk is similar to Fishburn and Sarin’s (1991) definition of ex post risk equity.

  3. 3.

    Keeney was not the first to allude to society’s fear of catastrophic events. In the 1970s, nuclear engineers started to argue that society’s apparent acceptance of daily hazards and its concern for possibly catastrophic hazards suggests catastrophe aversion. The argument was based on the idea that a consistent relationship exists between the severity and frequency of fatal accidents that would somehow reflect social attitudes toward risk (Starr 1969).

  4. 4.

    In risky situations involving only two individuals, minimax, minimal variance, and catastrophe averse preferences are strictly equivalent (Bernard et al. 2015).

  5. 5.

    Individuals’ risk of dying was described as independent so that there was only a tiny probability (\(10^{-20}\)) of 100 deaths, but a significant probability (0.264) of observing two or more deaths.

  6. 6.

    In these games, two players face a coin-flip risk between prospects \(\mathcal {A}\) and \(\mathcal {B}\). For example, both prospects may pay either $5 or $50 but outcomes are positively or negatively correlated. Using obvious notations, we have: \(\mathcal {A}:\,\frac{1}{2}(5,5)\oplus \frac{1}{2}(50,50)\) vs \(\mathcal {B}:\,\frac{1}{2}(5,50)\oplus \frac{1}{2}(50,5)\). If player 1 dislikes unequal outcomes, she will prefer prospect \(\mathcal {A}\) over prospect \(\mathcal {B}\) although she faces the same personal risk under both prospects.

  7. 7.

    Prominent criticism includes that of Diamond (1967), Sen (1970), Myerson (1981), Broome (1984), Epstein and Segal (1992), Ben-Porath et al. (1997), and Fleurbaey (2010).

  8. 8.

    See Fleurbaey (2010: 658) and Bovens and Fleurbaey (2012: 242–243) for a response to these objections.

  9. 9.

    One important limitation of Keeney’s theorem is that it assumes individual risks to be statistically independent. It is possible to relax the independence assumption whenever a risk transfer from the more exposed to the less exposed person does not decrease the statistical correlation between their risks (Bernard et al. 2015).

  10. 10.

    For the sake of simplicity, we assume \(W_{EPT}\) with \(\varphi (x)=x\).

  11. 11.

    The term “value of statistical life” is somewhat controversial (Cameron 2010) and U.K. regulators therefore use the term “value of prevented fatality” (VPF) instead. In any case, the metric refers to an individual’s marginal rate of substitution between income and mortality risk.

  12. 12.

    Adler (2005) provides an extensive discussion and critique of different environmental risk assessment approaches.

  13. 13.

    FN-criteria are used in various European countries (see Rheinberger 2010; Bedford 2013).

  14. 14.

    A catastrophe accepting regulator would, of course, adopt a slope criterion \(\gamma <1\).

  15. 15.

    Bedford (2013) argues that the approximation is mistaken for rare events (involving large n) and therefore difficult to defend in settings such as climate catastrophes. Instead, he proposes a two-parameter disutility function that extends the above approach to account for uncertainty in \(\pi _{k}\).

  16. 16.

    Bohnenblust and Slovic (1998) propose to marry the expected disutility criterion with standard CBA by multiplying for each policy option the expectation over the weighted number of deaths \(\mathsf {E}\left[ f(\tilde{d})\right] \) rather than the expected number of deaths \(\mathsf {E}\left[ \tilde{d}\right] \) by the VSL, obtaining a money measure of the disutility of lives lost.

  17. 17.

    The issue of whose perceptions should ultimately count in public policy is analyzed in Portney (1992), Pollack (1998), Johansson-Stenman (2008), and Salanie and Treich (2009) among others.

  18. 18.

    Wiener notes that blockbuster movies like Deep Impact or The Day After Tomorrow do little to alleviate the unavailability heuristic since the public tends to perceive such movies as what they are: good entertainment.

  19. 19.

    In the aftermath of the Fukushima accident, von Hippel (2011) commented in a New York Times op-ed: “Nuclear power is a textbook example of the problem of ‘regulatory capture’ [...which] can be countered only by vigorous public scrutiny and Congressional oversight [...].”

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Correspondence to Christoph M. Rheinberger.

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The research in this paper was funded by the Foundation for an Industrial Safety Culture (FonCSI), and the French Ministry of Ecology, Sustainable Development and Energy in the context of the SAFERA-NET (FP7/2007-2013, grant no. 291812). We are grateful for discussions with and valuable comments by Matthew Adler, James Hammitt, Kerry Krutilla, Eric Marsden, Chris Olivola, Paul Slovic, Olga Spackova, and Jonathan Wiener. The views expressed in this paper are solely ours and do not represent the views or position of the European Chemicals Agency.

Appendix

Appendix

The bibliometric analysis depicted in Fig. 1 is based on a query of the Web of ScienceT M. The query words catastrophe, catastrophes, catastrophic, disaster, disasters, and disastrous were used to search through abstracts, titles and key words of articles published between 1974 and 2014 in the following list of economics journals: American Economic Journal: Applied Economics, American Economic Journal: Economic Policy, American Economic Journal: Macroeconomics, American Economic Journal: Microeconomics, American Economic Review, Econometrica, Economic Journal, European Economic Review, Games and Economic Behavior, International Economic Review, Journal of Econometrics, Journal of Economic Theory, Journal of Finance, Journal of Financial Economics, Journal of International Economics, Journal of Labor Economics, Journal of Monetary Economics, Journal of Political Economy, Journal of Public Economics, Journal of the European Economic Association, Rand Journal of Economics, Review of Economics and Statistics, Review of Economic Studies, Quantitative Economics, Quarterly Journal of Economics, Theoretical Economics, American Journal of Agricultural Economics, Ecological Economics, Energy Economics, Environmental and Development Economics, Environmental and Resource Economics, Journal of Agricultural and Resource Economics, Journal of Environmental Management and Economics, Land Economics, Review of Environmental Economics and Policy.

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Rheinberger, C.M., Treich, N. Attitudes Toward Catastrophe. Environ Resource Econ 67, 609–636 (2017). https://doi.org/10.1007/s10640-016-0033-3

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Keywords

  • Catastrophe
  • Social risks
  • Framing
  • Risk aversion
  • Equity concerns