Funding public projects: A Case for the Nash product rule

Florian Brandl (University of Bonn), Felix Brandt (Technische Universität München), Matthias Greger (Technische Universität München), Dominik Peters (University of Toronto), Christian Stricker (Technische Universität München) and Warut Suksompong (National University of Singapore)

GPI Working Paper No. 14-2021, published in Journal of Mathematical Economics

We study a mechanism design problem where a community of agents wishes to fund public projects via voluntary monetary contributions by the community members. This serves as a model for public expenditure without an exogenously available budget, such as participatory budgeting or voluntary tax programs, as well as donor coordination when interpreting charities as public projects and donations as contributions. Our aim is to identify a mutually beneficial distribution of the individual contributions. In the preference aggregation problem that we study, agents report linear utility functions over projects together with the amount of their contributions, and the mechanism determines a socially optimal distribution of the money. We identify a specific mechanism—the Nash product rule—which picks the distribution that maximizes the product of the agents’ utilities. This rule is Pareto efficient, and we prove that it satisfies attractive incentive properties: it spends each agent’s contribution only on projects the agent finds acceptable, and agents are strongly incentivized to participate.

Other working papers

Tough enough? Robust satisficing as a decision norm for long-term policy analysis – Andreas Mogensen and David Thorstad (Global Priorities Institute, Oxford University)

This paper aims to open a dialogue between philosophers working in decision theory and operations researchers and engineers whose research addresses the topic of decision making under deep uncertainty. Specifically, we assess the recommendation to follow a norm of robust satisficing when making decisions under deep uncertainty in the context of decision analyses that rely on the tools of Robust Decision Making developed by Robert Lempert and colleagues at RAND …

Against Willing Servitude: Autonomy in the Ethics of Advanced Artificial Intelligence – Adam Bales (Global Priorities Institute, University of Oxford)

Some people believe that advanced artificial intelligence systems (AIs) might, in the future, come to have moral status. Further, humans might be tempted to design such AIs that they serve us, carrying out tasks that make our lives better. This raises the question of whether designing AIs with moral status to be willing servants would problematically violate their autonomy. In this paper, I argue that it would in fact do so.

The case for strong longtermism – Hilary Greaves and William MacAskill (Global Priorities Institute, University of Oxford)

A striking fact about the history of civilisation is just how early we are in it. There are 5000 years of recorded history behind us, but how many years are still to come? If we merely last as long as the typical mammalian species…