Knowledge that Transforms

Differences in preferences are important to explain variation in individuals' behavior. There is, however, no consensus on how to take these differences into account when evaluating policies. While prominent in the economic literature, the standard utilitarian criterion is controversial. According to some, interpersonal comparability of utilities involves value judgments with little objective basis. Others argue that social justice is primarily about the distribution of commodities assigned to individuals, rather than their subjective satisfaction or happiness. In this paper, we propose and axiomatically characterize a criterion, named opportunity-equivalent utilitarian, that addresses these claims. First, our criterion ranks social alternatives on the basis of individuals' ordinal preferences. Second, it compares individuals based on the fairness of their assignments. Opportunity-equivalent utilitarianism requires society to maximize the sum of specific indices of well-being that are cardinal, interpersonally comparable, and represent each individual's preferences.

We explore the impact of private information in sealed-bid first-price auctions. For a given symmetric and arbitrarily correlated prior distribution over values, we characterize the lowest winning-bid distribution that can arise across all information structures and equilibria. The information and equilibrium attaining this minimum leave bidders indifferent between their equilibrium bids and all higher bids. Our results provide lower bounds for bids and revenue with asymmetric distributions over values. We also report further characterizations of revenue and bidder surplus including upper bounds on revenue. Our work has implications for the identification of value distributions from data on winning bids and for the informationally robust comparison of alternative auction mechanisms.

I study repeated competition among oligopolists. The only novelty is that firms may go bankrupt and permanently exit: the probability that a firm survives a price war depends on its financial strength, which varies stochastically over time. Under some conditions including no entry, an anti‐folk theorem holds: when firms are patient, so that strength levels change relatively quickly, every Nash equilibrium involves an immediate price war that lasts until at most one firm remains. Surprisingly, the possibility of entry may facilitate collusion, as may impatience. The model can explain some observed patterns of collusion and predation.

The theory of continuous time games (Simon and Stinchcombe (1989), Bergin and MacLeod (1993)) shows that continuous time interactions can generate very different equilibrium behavior than conventional discrete time interactions. We introduce new laboratory methods that allow us to eliminate natural inertia in subjects' decisions in continuous time experiments, thereby satisfying critical premises of the theory and enabling a first‐time direct test. Applying these new methods to a simple timing game, we find strikingly large gaps in behavior between discrete and continuous time as the theory suggests. Reintroducing natural inertia into these games causes continuous time behavior to collapse to discrete time‐like levels in some settings as predicted by subgame perfect Nash equilibrium. However, contra this prediction, the strength of this effect is fundamentally shaped by the severity of inertia: behavior tends towards discrete time benchmarks as inertia grows large and perfectly continuous time benchmarks as it falls towards zero. We provide evidence that these results are due to changes in the nature of strategic uncertainty as inertia approaches the continuous limit.

What does contract negotiation look like when some parties hold private information and negotiation frictions are negligible? This paper analyzes the above question and provides a foundation for renegotiation-proof contracts in a related environment. The model extends the framework of the Coase conjecture to situations in which the quantity or quality of the good is endogenously determined and to more general environments in which the traded goods are complements or substitutes. All equilibria converge to a unique outcome as frictions become negligible, which is separating, efficient, and straightforward to characterize.

This paper studies the impact of time-varying idiosyncratic risk at the establishment level on aggregate unemployment fluctuations and on the labor market over the period 1972-2009. I build a tractable search-and-matching model of the labor market with firm dynamics and heterogeneity in productivity and sizes, in which I introduce time-varying idiosyncratic volatility. The model features directed search and allows for endogenous separations, entry and exit of establishments, and job-to-job transitions. I show, first, that the model can replicate salient features of the behavior of firms at the microeconomic level. Second, I find that the introduction of time-varying idiosyncratic volatility improves the fit of search-and-matching models for a range of business cycle moments. In a series of counterfactual experiments, I then show that time-varying idiosyncratic risk is important to account for the magnitude of fluctuations in aggregate unemployment for past US recessions, including in particular the recessions of 1990-1991 and 2001. Though the model can account for about 40% of the total increase in unemployment for the 2007-2009 recession, uncertainty alone does not seem sufficient to explain the magnitude and persistence of unemployment observed during that period.

We provide the first analysis of altruism in networks. Agents are connected through a fixed, weighted network and care about the well-being of their network neigh-bors. Given some initial distribution of incomes, agents may provide financial support to their poorer friends. We characterize the Nash equilibria of this transfer game for general networks and utility functions. We show that equilibria solve a well-behaved maximization program, related to classical problems of optimal transportation on networks. We build on this reformulation and establish existence, uniqueness in consumptions and generic uniqueness in transfers. We show that transfers are affected by the geometry of the altru-istic network. They flow through shortest paths and chains of transfers emerge when the network is not transitive. We analyze the effects of changes in incomes and in the network. When an agent suffers a negative income shock, the equilibrium consumption of every agent decreases weakly. We characterize the impact of small redistributions and show that decreasing income inequality may increase consumption inequality. We also characterize the impact of a small increase in altruism. While altruistic networks reduce inequality, more altruism may lead to more inequality.

Owing to the worldwide shortage of deceased‐donor organs for transplantation, living donations have become a significant source of transplant organs. However, not all willing donors can donate to their intended recipients because of medical incompatibilities. These incompatibilities can be overcome by an exchange of donors between patients. For kidneys, such exchanges have become widespread in the last decade with the introduction of optimization and market design techniques to kidney exchange. A small but growing number of liver exchanges have also been conducted. Over the last two decades, a number of transplantation procedures emerged where organs from two living donors are transplanted to a single patient. Prominent examples include dual‐graft liver transplantation, lobar lung transplantation, and simultaneous liver‐kidney transplantation. Exchange, however, has been neither practiced nor introduced in this context. We introduce dual‐donor organ exchange as a novel transplantation modality, and through simulations show that living‐donor transplants can be significantly increased through such exchanges. We also provide a simple theoretical model for dual‐donor organ exchange and introduce optimal exchange mechanisms under various logistical constraints.

This paper empirically investigates how sentences to be assigned at trial impact plea bargaining. The analysis is based on the model of bargaining with asymmetric information by Bebchuk, 1984. I provide conditions for the nonparametric identification of the model, propose a consistent nonparametric estimator, and implement it using data on criminal cases from North Carolina. Employing the estimated model, I evaluate how different sentencing reforms affect the outcome of criminal cases. My results indicate that lower mandatory minimum sentences could greatly reduce the total amount of incarceration time assigned by the courts, but may increase conviction rates. In contrast, the broader use of non‐incarceration sentences for less serious crimes reduces the number of incarceration convictions, but has a very small effect over the total assigned incarceration time. I also consider the effects of a ban on plea bargains. Depending on the case characteristics, over 20 percent of the defendants who currently receive incarceration sentences would be acquitted if plea bargains were forbidden.

I introduce a model of undirected dyadic link formation which allows for assortative matching on observed agent characteristics (homophily) as well as unrestricted agent-level heterogeneity in link surplus (degree heterogeneity). Like in fixed effects panel data analyses, the joint distribution of observed and unobserved agent-level characteristics is left unrestricted. Two estimators for the (common) homophily parameter, ?0, are developed and their properties studied under an asymptotic sequence involving a single network growing large. The first, tetrad logit (TL), estimator conditions on a sufficient statistic for the degree heterogeneity. The second, joint maximum likelihood (JML), estimator treats the degree heterogeneity \{Ai0\}i = 1N as additional (incidental) parameters to be estimated. The TL estimate is consistent under both sparse and dense graph sequences, whereas consistency of the JML estimate is shown only under dense graph sequences.