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
Economic growth under transformative AI – Philip Trammell (Global Priorities Institute, Oxford University) and Anton Korinek (University of Virginia)
Industrialized countries have long seen relatively stable growth in output per capita and a stable labor share. AI may be transformative, in the sense that it may break one or both of these stylized facts. This review outlines the ways this may happen by placing several strands of the literature on AI and growth within a common framework. We first evaluate models in which AI increases output production, for example via increases in capital’s substitutability for labor…
Cassandra’s Curse: A second tragedy of the commons – Philippe Colo (ETH Zurich)
This paper studies why scientific forecasts regarding exceptional or rare events generally fail to trigger adequate public response. I consider a game of contribution to a public bad. Prior to the game, I assume contributors receive non-verifiable expert advice regarding uncertain damages. In addition, I assume that the expert cares only about social welfare. Under mild assumptions, I show that no information transmission can happen at equilibrium when the number of contributors…
Measuring AI-Driven Risk with Stock Prices – Susana Campos-Martins (Global Priorities Institute, University of Oxford)
We propose an empirical approach to identify and measure AI-driven shocks based on the co-movements of relevant financial asset prices. For that purpose, we first calculate the common volatility of the share prices of major US AI-relevant companies. Then we isolate the events that shake this industry only from those that shake all sectors of economic activity at the same time. For the sample analysed, AI shocks are identified when there are announcements about (mergers and) acquisitions in the AI industry, launching of…