A new conceptual framework for the age-old prescriptivism-versus-descriptivism debate
Abstract:
The question of how to discount the distant future has long been at the core of climate economics. It has also divided economists. Some argue for prescriptivist approaches to discounting, often calling for social discount rates of as low as 1% per year. Others argue strongly for descriptivist approaches and rates as high as 5% or more. A look to financial economics has since added another wrinkle, by pointing to the need to separate risk aversion from intertemporal substitution to calibrate real-world behavior, at times lowering effective descriptivist rates close to prescriptivist ones.
We attempt to reconcile some of these methodological differences by identifying three types of prescriptivism. Economists are frequently uncomfortable with what we term parameter prescriptivism, while being comfortable with both axiom and policy prescriptivism. That faces theoretical challenges. We argue that if a priori moral reasoning is not allowed to influence parameter values, then the results of one’s analysis should not be framed as a prescriptive policy ‘recommendation’. While descriptivist analysis is relevant to policy, we must be clear that it can only inform policy choices, not determine them. We use our framework to evaluate recent proposals in climate economics to replace the standard isoelastic utility function with Epstein-Zin preferences to allow for the separate treatment of risk aversion and intertemporal substitution.
JEL codes: D6, H43, Q5.
Keywords: Discounting, Descriptivism, Prescriptivism.
Full text: “Prescriptivism, risk aversion, and intertemporal substitution in climate economics” (published version: Annals of Economics and Statistics; prior versions presented at: Workshop on Frontiers in Environmental Economics, Paris, December 2017; Climate Change, Ethics and Risk Workshop, Princeton, April 2018)
Citation:
Kelleher, J. Paul and Gernot Wagner. “Prescriptivism, risk aversion, and intertemporal substitution in climate economics.” Annals of Economics and Statistics No. 132 (December 2018): 129-49.