Dynamic public good provision under time preference heterogeneity

Philip Trammell (Global Priorities Institute and Department of Economics, University of Oxford)

GPI Working Paper No. 9-2021

I explore the implications of time preference heterogeneity for the private funding of public goods. The assumption that players use a common discount rate is knife-edge: relaxing it yields substantially different equilibria, for two reasons. First, time preference heterogeneity motivates intertemporal polarization, analogous to the polarization seen in a static public good game. In the simplest settings, more patient players spend nothing early in time and less patient players spending nothing later. Second, and consequently, time preference heterogeneity gives less patient players a “first-mover advantage”. Departures from the common-discounting assumption are economically significant: a patient player’s payoff in equilibrium, relative to that obtained when he is constrained to act according to a higher discount rate, typically grows unboundedly as his share of the initial budget falls to zero. Finally I discuss applications of these results to the debate over legal disbursement minima.

Other working papers

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Should you be willing to forego any sure good for a tiny probability of a vastly greater good? Fanatics say you should, anti-fanatics say you should not. Anti-fanaticism has great intuitive appeal. But, I argue, these intuitions are untenable, because satisfying them in their full generality is incompatible with three very plausible principles: acyclicity, a minimal dominance principle, and the principle that any outcome can be made better or worse. This argument against anti-fanaticism can be…

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Greaves and MacAskill (2019) argue for strong longtermism, according to which, in a wide class of decision situations, the option that is ex ante best, and the one we ex ante ought to choose, is the option that makes the very long-run future go best. One important aspect of their argument is the claim that strong longtermism is compatible with a wide range of ethical assumptions, including plausible non-consequentialist views. In this essay, I challenge this claim…

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Some worry that advanced artificial agents may resist being shut down. The Incomplete Preferences Proposal (IPP) is an idea for ensuring that does not happen. A key part of the IPP is using a novel ‘Discounted Reward for Same-Length Trajectories (DReST)’ reward function to train agents to (1) pursue goals effectively conditional on each trajectory-length (be ‘USEFUL’), and (2) choose stochastically between different trajectory-lengths (be ‘NEUTRAL’ about trajectory-lengths). In this paper, we propose…