Decision under Normative Uncertainty

Economics & Philosophy, Cambridge University Press

23 Pages Posted: 28 Oct 2019 Last revised: 7 Oct 2021

See all articles by Franz Dietrich

Franz Dietrich

Paris School of Economics & CNRS

Brian Jabarian

Princeton University - Department of Economics; Paris School of Economics (PSE)

Date Written: 2021

Abstract

While ordinary decision theory focuses on empirical uncertainty, real decision-makers also face normative uncertainty: uncertainty about value itself. From a purely formal perspective, normative uncertainty is comparable to (Harsanyian or Rawlsian) identity uncertainty in the 'original position', where one's future values are unknown. A comprehensive decision theory must address twofold uncertainty -- normative and empirical. We present a simple model of twofold uncertainty, and show that the most popular decision principle -- maximising expected value ('Expectationalism') -- has different formulations, namely Ex-Ante Expectationalism, Ex-Post Expectationalism, and hybrid theories. These alternative theories recommend different decisions, reasoning modes, and attitudes to risk. But they converge under an interesting (necessary and sufficient) condition.

Keywords: Normative uncertainty, normative vs empirical uncertainty, Harsanyi, Rawls, original position, expected value, ex ante vs ex post criteria

JEL Classification: D8, D9, D46

Suggested Citation

Dietrich, Franz and Jabarian, Brian and Jabarian, Brian, Decision under Normative Uncertainty (2021). Economics & Philosophy, Cambridge University Press, Available at SSRN: https://ssrn.com/abstract=3466833 or http://dx.doi.org/10.2139/ssrn.3466833

Franz Dietrich

Paris School of Economics & CNRS ( email )

48 Boulevard Jourdan
Paris, 75014 75014
France

HOME PAGE: http://www.franzdietrich.net

Brian Jabarian (Contact Author)

Princeton University - Department of Economics ( email )

Princeton, NJ 08544-1021
United States

Paris School of Economics (PSE) ( email )

48 Boulevard Jourdan
Paris, 75014 75014
France

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