Abstract
This paper discusses ethical issues surrounding Integrated Assessment Models (IAMs) of the economic effects of climate change, and how climate economists acting as policy advisors ought to represent the uncertain possibility of catastrophe. Some climate economists, especially Martin Weitzman, have argued for a precautionary approach where avoiding catastrophe should structure climate economists’ welfare analysis. This paper details ethical arguments that justify this approach, showing how Weitzman’s “fat tail” probabilities of climate catastrophe pose ethical problems for widely used IAMs. The main claim is that economists who ignore or downplay catastrophic risks in their representations of uncertainty likely fall afoul of ethical constraints on scientists acting as policy advisors. Such scientists have duties to honestly articulate uncertainties and manage (some) inductive risks, or the risks of being wrong in different ways.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The definition of ‘fat tail’ used by Weitzman (2009) is that a probability density function has a fat tail if the tail approaches 0 more slowly than exponentially, i.e. when its moment-generating function is infinite.
The Ramsey equation explicitly encodes value judgments about intertermporal equity insofar as it attempts to determine the optimal social discount rate for welfare analysis. It also implicitly encodes value judgments about intratemporal equity because the parameter for the elasticity of marginal utility of consumption, often interpreted as a measure of inequity aversion, could be applied to the intratemporal case. But as Frisch (2017) points out, IAMs that simply ignore intratemporal inequality (i.e. global wealth inequality and resulting unequal vulnerability) by modeling society as a series of representative consumers, thereby arguably encode non-egalitarian value judgments as well, since decisions made on their basis would likely tend to maintain such inequalities.
Determining which outcomes count as “catastrophic” is as much a value judgment as determining what counts as “dangerous anthropogenic interference with the climate system.” For the purposes of this paper, I need not precisely define ‘catastrophe.’ The kind of outcomes that are relevant to Weitzman’s argument, involving “unlimited downside exposure,” collapse of civilization, etc., would be agreed by all reasonable parties to be catastrophic.
As Nordhaus (2012) points out, this follows from Weitzman’s definition of a “fat tailed” distribution as one whose moment-generating function is infinite, i.e. its expectation is infinite.
Technically, the decision-maker’s utility function exhibits “Constant Relative Risk Aversion”.
Thus in this context I am putting aside, for example, the popular objections that the problem of value incommensurability dooms CBA as a policy-making tool (Anderson 1993; Steel 2015) or claims that welfare cannot be adequately represented by a CBA (see Frisch 2013, Sect. 4, and references therein).
For a discussion of the limits of this Jeffreyan ideal in the context of a case study of natural scientific climate modeling, see Frank (2017).
However, see Longino (1996) for an argument that this distinction ultimately breaks down. I thank an anonymous reviewer for pushing this point.
References
Anderson, E. (1993). Value in ethics and economics. Cambridge: Harvard University Press.
Betz, G. (2013). In defense of the value free ideal. European Journal for Philosophy of Science, 3, 207–220.
Burke, M., Hsiang, S. M., & Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527, 235–239.
Dietz, S. (2011). High impact, low probability? An empirical analysis of risk in the economics of climate change. Climatic Change, 108, 519–541.
Douglas, H. (2000). Inductive risk and values in science. Philosophy of Science, 67, 559–579.
Douglas, H. (2003). The moral responsibilities of scientists: tensions between autonomy and responsibility. American Philosophical Quarterly, 40(1), 59–68.
Douglas, H. (2009). Science, policy, and the value-free ideal. Pittsburgh: University of Pittsburgh Press.
Elliott, K. C. (2011). Is a little pollution good for you? Incorporating societal values in environmental research. New York: Oxford University Press.
Frank, D. M. (2017). Making uncertainties explicit: The Jeffreyan value-free ideal and its limits. In K. C. Elliott & T. Richards (Eds.), Exploring inductive risk. New York: Oxford University Press.
Frisch, M. (2013). Modeling climate policies: A critical look at integrated assessment models. Philosophy & Technology, 26, 117–137.
Frisch, M. (2017). Climate policy in the age of trump. Kennedy Institute of Ethics Journal, 27, 2.
Greenstone, M., Kopits, E., & Wolverton, A. (2011). Estimating the social cost of carbon for use in U.S. federal rulemakings: A summary and interpretation. Center for Energy and Environmental Policy Research Working Paper.
Interagency Working Group on Social Cost of Carbon. (2010). Technical support document: Social cost of carbon for regulatory impact analysis under executive order 12866. https://www.epa.gov/sites/production/files/2016-12/documents/scc_tsd_2010.pdf. Retrieved June 26, 2017.
Jamieson, D. (2014). Reason in a dark time: Why the struggle against climate change failed and what it means for our future. New York: Oxford University Press.
Jeffrey, R. C. (1956). Valuation and acceptance of scientific hypotheses. Philosophy of Science, 22, 237–246.
Longino, H. (1996). Cognitive and non-cognitive values in science: Rethinking the dichotomy. In L. H. Nelson & J. Nelson (Eds.), Feminism, science, and the philosophy of science (pp. 39–58). Dordrecht: Kluwer.
Nordhaus, W. (2012). Economic policy in the face of severe tail events. Journal of Public Economic Theory, 14(2), 197–219.
Nordhaus, W. (2013). The climate casino: Risk, uncertainty, and econoimcs for a warming world. New Haven: Yale University Press.
Oreskes, N., & Conway, E. M. (2010). Merchants of doubt: How a handful of scientists obscured the truth on issues from tobacco smoke to global warming. New York: Bloomsbury Press.
Oreskes, N., & Conway, E. (2014). The collapse of Western civilization: A view from the future. New York: Columbia University Press.
Pindyck, R. S. (2013). Climate change policy: What do the models tell us? Journal of Economic Literature, 51(3), 860–872.
Rudner, R. (1953). The scientist qua scientist makes value judgments. Philosophy of Science, 20, 1–6.
Shamoo, A., & Resnik, D. (2015). Responsible conduct of research (3rd ed.). New York: Oxford University Press.
Steel, D. (2015). Philosophy and the precautionary principle: Science, evidence, and environmental policy. New York: Cambridge University Press.
Steele, K. (2012). The scientist qua policy advisor makes value judgments. Philosophy of Science, 79, 893–904.
Tol, R. (2012). On the uncertainty about the total economic impact of climate change. Environmental and Resource Economics, 53(1), 97–116.
Wagner, G., & Weitzman, M. L. (2015). Climate shock: The economic consequences of a hotter planet. Princeton, NJ: Princeton University Press.
Weitzman, M. L. (2007). A review of the Stern Review on the economics of climate change. Journal of Economic Literature, XLV, 703–724.
Weitzman, M. L. (2009). On modeling and interpreting the economics of catastrophic climate change. Review of Economics and Statistics, 91(1), 1–19.
Weitzman, M. L. (2012). GHG targets as insurance against catastrophic climate damages. Journal of Public Economic Theory, 14(2), 221–244.
Weitzman, M. L. (2014). Fat tails and the social cost of carbon. American Economic Review: Papers and Proceedings, 104(5), 544–546.
Acknowledgements
Thanks to audiences and colleagues at the University of North Carolina, Chapel Hill and Duke University, and two anonymous reviewers for helping to significantly improve this paper.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Frank, D.M. Ethics of the scientist qua policy advisor: inductive risk, uncertainty, and catastrophe in climate economics. Synthese 196, 3123–3138 (2019). https://doi.org/10.1007/s11229-017-1617-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11229-017-1617-3