Calibration dilemmas in the ethics of distribution
Jacob M. Nebel (University of Southern California) and H. Orri Stefánsson (Stockholm University and Swedish Collegium for Advanced Study)
GPI Working Paper No. 10-2021, published in Economics & Philosophy
This paper was the basis for the Parfit Memorial Lecture 2021.
The recording of the Parfit Memorial Lecture is now available to view here.
Other working papers
In defence of fanaticism – Hayden Wilkinson (Australian National University)
Consider a decision between: 1) a certainty of a moderately good outcome, such as one additional life saved; 2) a lottery which probably gives a worse outcome, but has a tiny probability of a far better outcome (perhaps trillions of blissful lives created). Which is morally better? Expected value theory (with a plausible axiology) judges (2) as better, no matter how tiny its probability of success. But this seems fanatical. So we may be tempted to abandon expected value theory…
The weight of suffering – Andreas Mogensen (Global Priorities Institute, University of Oxford)
How should we weigh suffering against happiness? This paper highlights the existence of an argument from intuitively plausible axiological principles to the striking conclusion that in comparing different populations, there exists some depth of suffering that cannot be compensated for by any measure of well-being. In addition to a number of structural principles, the argument relies on two key premises. The first is the contrary of the so-called Reverse Repugnant Conclusion…
Choosing the future: Markets, ethics and rapprochement in social discounting – Antony Millner (University of California, Santa Barbara) and Geoffrey Heal (Columbia University)
This paper provides a critical review of the literature on choosing social discount rates (SDRs) for public cost-benefit analysis. We discuss two dominant approaches, the first based on market prices, and the second based on intertemporal ethics. While both methods have attractive features, neither is immune to criticism. …