Eduardo Perez-Richet

We propose a mechanism design framework that incorporates both soft information, which can be freely manipulated, and semi-hard information, which entails a cost for falsification. The framework captures various contexts such as school choice, public housing, organ transplant and manipulations of classification algorithms. We first provide a canonical class of mechanisms for these settings. The key idea is to treat the submission of hard information as an observable and payoff-relevant action and the contractible part of the mechanism as a mapping from submitted scores to a distribution over decisions (a score-based decision rule). Each type report triggers a distribution over score submission requests and a distribution over decision rules. We provide conditions under which score-based mechanisms are without loss of generality. In other words, situations under which the agent does not make any type reports and decides without a mediator what score to submit in a score-based decision rule. We proceed to characterize optimal approval mechanisms in the presence of manipulable hard information. In several leading settings optimal mechanisms are score-based (and thus do not rely on soft information) and involve costly screening. The solution methodology we employ is suitable both for concave cost functions and quadratic costs and is applicable to a wide range of contexts in economics and in computer science.

A principal designs an information structure and chooses transfers to an agent that are contingent on the action of a receiver. The principal faces a trade-off between, on the one hand, designing an information structure maximizing non-monetary payoffs, and on the other hand, minimizing the information rent that must be conceded to the agent in order to implement the information structure which the principal designed. We examine how this trade-off shapes communication. Our model can be applied to study the relationship between, e.g.: political organizations and the public relations companies that campaign on their behalf, firms and the companies marketing their products, consultancies and the analysts they employ.

We provide the first analysis of the risk-sharing implications of altruism networks. Agents are embedded in a fixed network and care about each other. We explore whether altruistic transfers help smooth consumption and how this depends on the shape of the network. We find that altruism networks have a first-order impact on risk. Altruistic transfers generate efficient insurance when the network of perfect altruistic ties is strongly connected. We uncover two specific empirical implications of altruism networks. First, bridges can generate good overall risk sharing, and, more generally, the quality of informal insurance depends on the average path length of the network. Second, large shocks are well-insured by connected altruism networks. By contrast, large shocks tend to be badly insured in models of informal insurance with frictions. We characterize what happens for shocks that leave the structure of giving relationships unchanged. We further explore the relationship between consumption variance and centrality, correlation in consumption streams across agents, and the impact of adding links.

We consider a general information design problem in which the task of running a procedure generating information for a continuation game is performed by an agent. A moral hazard problem therefore emerges in which the principal faces a trade-off between generating information that is persuasive in the continuation game, and efficiently incentivizing the agent to comply with the procedure designed. Standard concavification techniques do not apply in this environment. We provide a general methodology to tackle such problems, and examine the way in which moral hazard affects the optimal procedure of the principal.