Abstract: I present a theory of measurement of preference intensity and use this measure as a foundation for utilitarianism. To do this, I suppose each alternative is experienced over time. An individual has preferences over such experiences. I present axioms under which preferences are represented by an experienced utility function equal to the integral of instantaneous preference intensity over time and unique up to a positive scalar. I propose an ethical postulate under which social preferences are utilitarian in experienced utilities.

Abstract: I consider a classic public good provision problem when the government has the power to tax its citizens. In this environment, participation constraints need not be satisfied. I replace such participation constraints with a weaker condition, which I call no-extortion, that limits the ability of the government to extract funds from its citizens. It is well known that there does not exist any strategy-proof, efficient, and budget-balanced mechanism. In fact, any strategy-proof and efficient mechanism that additionally satisfies individual-rationality or universal-participation fails to raise any revenue in large populations. However, replacing these conditions with no-extortion yields a positive result. There exists a simple, detail-free mechanism that is strategy-proof, efficient, extortion-free, and (asymptotically) budget-balanced in large populations. Furthermore, among all strategy-proof, efficient, and extortion-free mechanisms, this mechanism is undominated and uniquely maximizes ex-post revenue (minimizing any potential, though unlikely, budget deficit).

Abstract: It is a common fallacy to view preferences under risk and uncertainty as a direct measure of preference intensity. Indeed, it is not unreasonable to imagine an individual with risk loving preferences over lotteries and diminishing marginal preference intensities over constant outcomes. It is then natural to wonder when an expected utility maximizer is in fact maximizing her expected preference intensity. Moreover, when this is the case, the decision maker is arguably neutral to risk—any concavity/convexity in her expected utility function comes entirely from her decreasing/increasing marginal preference intensity. This motivates a new definition of risk attitude that is net of the effect of preference intensities. In a recent paper, Fryxell (2019) shows how we may leverage preferences over experiences to measure preference intensity. I characterize preferences that admit an expected experienced utility representation (EEU), both in the case of (objective) risk and in the case of (subjective) uncertainty. I then propose a definition of risk attitude (for non-EEU maximizers) which is net of the individual’s experienced utilities.

Abstract: I propose a general framework with which to analyze the optimal response to crime. Each criminal act, detected with some probability, generates a random piece of evidence and a consequent probability of guilt for each citizen. I consider a utilitarian planner with no artificial moral constraints. In particular, I assume no upper bound on punishment—such a bound can only rise endogenously from the utilitarian objective. I first consider pure (costless) punishment. If citizens are expected utility maximizers, a repugnant conclusion is reached—it is optimal to punish only with the realization of the most incriminating evidence. Allowing for more general behavior yields a weaker but more satisfactory result—optimal punishment is always decreasing in the quality of evidence. (I also consider pure rehabilitation, pure incapacitation, and general sentences that combine punishment, rehabilitation, and incapacitation. Analysis in progress.)

Abstract: When agents have private, unrestricted values and quasilinear utilities, every strategyproof mechanism has an affine maximizing decision rule. For any affine maximizing decision rule, I construct the unique (ex post) revenue-maximizing mechanism subject to strategyproofness and a flexible participation constraint. When the decision rule is efficient and the outside option payoff for agent i is the payoff from the implemented alternative had i not participated, the unique revenue-maximizing mechanism is the pivotal mechanism.

Abstract: Fryxell (2019) presents a theory of experienced utility and shows how it may be used as a foundation for utilitarianism. I elaborate on this approach and provide a commentary on existing theories, discussions, and critiques of utilitarianism with a particular focus on Harsanyi’s Impartial Observer Theorem.