Knowledge that Transforms

Advances in medical technology have made kidney transplants over the blood group barrier feasible. This article investigates how such technology should be implemented when designing pairwise kidney exchange programs. The possibility to receive a kidney transplant from a blood group incompatible donor motivates an extension of the preference domain, allowing patients to distinguish between compatible donors and half-compatible donors (i.e. blood group incompatible donors that only become compatible after undergoing an immunosuppressive treatment). It is demonstrated that the number of transplants can be substantially increased by providing an incentive for patients with half-compatible donors to participate in kidney exchange programs. The results also suggest that the technology is beneficial for patient groups that are traditionally disadvantaged in kidney exchange programs (e.g. blood group O patients). The positive effect of allowing transplants over the blood group barrier is larger than the corresponding effects of including altruistic patient–donor pairs or of allowing three-way exchanges in addition to pairwise exchanges.

We study the effects of monetary announcements when agents face Knightian uncertainty about the commitment capacity of the monetary authority. Households are ambiguity averse and differentially exposed to inflation due to differences in wealth. In response to the announcement of a future monetary loosening, only wealthy households (creditors) act as if the announcement will be fully implemented, due to the potential wealth losses from future inflation. As a result the economy responds as if aggregate net wealth falls, which attenuates the effects of the announcement. Redistributing from super-wealthy to middle-wealthy households makes the announcement more expansionary, in the extreme as expansionary as under a fully credible announcement.

Insurance benefit design has important implications for consumer welfare. In this article, we model insurer behaviour in the Medicare prescription drug coverage market and show that strategic private insurer incentives impose a fiscal externality on the traditional Medicare program. We document that plans covering medical expenses have more generous drug coverage than plans that are only responsible for prescription drug spending, which translates into higher drug utilization by enrolees. The effect is driven by drugs that reduce medical expenditure and treat chronic conditions. Our equilibrium model of benefit design endogenizes plan characteristics and accounts for asymmetric information; the model estimates confirm that differential incentives to internalize medical care offsets can explain disparities across plans. Counterfactuals show that strategic insurer incentives are as important as asymmetric information in determining benefit design.

U.S. monetary policy shocks induce comovements in the international financial variables that characterize the “Global Financial Cycle.” A single global factor that explains an important share of the variation of risky asset prices around the world decreases significantly after a U.S. monetary tightening. Monetary contractions in the US lead to significant deleveraging of global financial intermediaries, a decline in the provision of domestic credit globally, strong retrenchments of international credit flows, and tightening of foreign financial conditions. Countries with floating exchange rate regimes are subject to similar financial spillovers.

We generalize the scope of random allocation mechanisms, in which the mechanism first identifies a feasible “expected allocation” and then implements it by randomizing over nearby feasible integer allocations. The previous literature has shown that the cases in which this is possible are sharply limited. We show that if some of the feasibility constraints can be treated as goals rather than hard constraints, then, subject to weak conditions that we identify, any expected allocation that satisfies all the constraints and goals can be implemented by randomizing among nearby integer allocations that satisfy all the hard constraints exactly and the goals approximately. By defining ex post utilities as goals, we are able to improve the ex post properties of several classic assignment mechanisms, such as the random serial dictatorship. We use the same approach to prove the existence of ε-competitive equilibrium in large markets with indivisible items and feasibility constraints.

Markets have an exposure problem when getting to the optimal allocation requires a sequence of transactions which if started but not completed leaves at least one trader with losses. We use laboratory experiments to evaluate the effect of the exposure problem on alternative market mechanisms. The continuous double auction performs poorly: efficiency is only 20% when exposure is high and 55% when it is low. A package market effectively eliminates the exposure problem: in low and high-exposure treatments efficiency is 82% and 89%, respectively. Building on stability notions from matching theory we introduce the concept of mechanism stability. A model of trade that combines mechanism stability with noisy best responses and imperfect foresight explains the difference in market performance. Finally, decentralized bargaining with contingent contracts performs well with perfect information and communication but not in the more realistic case when traders’ preferences are privately known.

We surveyed a large sample of Swedish lottery players about their psychological well-being 5–22 years after a major lottery event and analysed the data following pre-registered procedures. Relative to matched controls, large-prize winners experience sustained increases in overall life satisfaction that persist for over a decade and show no evidence of dissipating over time. The estimated treatment effects on happiness and mental health are significantly smaller. Follow-up analyses of domain-specific aspects of life satisfaction implicate financial life satisfaction as an important mediator for the long-run increase in overall life satisfaction.

We conduct field experiments to investigate dynamic inconsistency and commitment demand in food choice. In two home grocery delivery programs, we document substantial dynamic inconsistency between advance and immediate choices. When given the option to commit to their advance choices, around half of subjects take it up. Commitment demand is negatively correlated with dynamic inconsistency, suggesting those with larger self-control problems are less likely to be aware thereof. We evaluate the welfare consequences of dynamic inconsistency and commitment policies with utility measures based on advance, immediate, and unambiguous choices. Simply offering commitment has limited welfare (and behavioural) consequences under all measures.

The basic assumption of a structural vector autoregressive moving average (SVARMA) model is that it is driven by a white noise whose components are uncorrelated or independent and can be interpreted as economic shocks, called “structural” shocks. When the errors are Gaussian, independence is equivalent to non-correlation and these models face two identification issues. The first identification problem is “static” and is due to the fact that there is an infinite number of linear transformations of a given random vector making its components uncorrelated. The second identification problem is “dynamic” and is a consequence of the fact that, even if a SVARMA admits a non-invertible moving average (MA) matrix polynomial, it may feature the same second-order dynamic properties as a VARMA process in which the MA matrix polynomials are invertible (the fundamental representation). The aim of this article is to explain that these difficulties are mainly due to the Gaussian assumption, and that both identification challenges are solved in a non-Gaussian framework if the structural shocks are assumed to be instantaneously and serially independent. We develop new parametric and semi-parametric estimation methods that accommodate non-fundamentalness in the MA dynamics. The functioning and performances of these methods are illustrated by applications conducted on both simulated and real data.

Aggregate shocks affect most households’ and firms’ decisions. Using three stylized models, we show that inference based on cross-sectional data alone generally fails to correctly account for decision making of rational agents facing aggregate uncertainty. We propose an econometric framework that overcomes these problems by explicitly parameterizing the agents’ decision problem relative to aggregate shocks. Our framework and examples illustrate that the cross-sectional and time-series aspects of the model are often interdependent. Therefore, estimation of model parameters in the presence of aggregate shocks requires the combined use of cross-sectional and time-series data. We provide easy-to-use formulas for test statistics and confidence intervals that account for the interaction between the cross-sectional and time-series variation. Lastly, we perform Monte Carlo simulations that highlight the properties of the proposed method and the risks of not properly accounting for the presence of aggregate shocks.