Abstract A monopolist seller of multiple goods screens a buyer whose type vector is initially unknown to both but drawn from a commonly known prior distribution. The seller chooses a mechanism to maximize her worst-case profits against all possible signals from which the buyer can learn about his values for the goods. We show that it is robustly optimal for the seller to bundle goods with identical demands (these are goods that can be permuted without changing the buyer’s prior type distribution). Consequently, pure bundling is robustly optimal for exchangeable prior distributions. For exchangeable priors, pure bundling is also optimal for the seller in the information environment (with the reverse timing) where an information designer, with the objective of maximizing consumer surplus, first selects a signal for the buyer, and then the seller chooses an optimal mechanism in response. We derive a formal relationship between the seller’s problem in both information environments.

We study dominant strategy incentive compatibility in a mechanism design setting with contingent contracts where the payoff of each agent is observed by the principal and can be contracted upon. Our main focus is on the class of linear contracts (one of the most commonly used contingent contracts) which consist of a transfer and a flat rate of profit sharing. We characterize outcomes implementable by linear contracts and provide a foundation for them by showing that, in finite type spaces, every social choice function that can be implemented using a more general nonlinear contingent contract can also be implemented using a linear contract. We then qualitatively describe the set of implementable outcomes. We show that a general class of social welfare criteria can be implemented. This class contains social choice functions (such as the Rawlsian) which cannot be implemented using (uncontingent) transfers. Under additional conditions, we show that only social choice functions in this class are implementable.

Abstract To determine the welfare implications of price changes in demand data, we introduce a revealed preference relation over prices. We show that the absence of cycles in this relation characterizes a consumer who trades off the utility of consumption against the disutility of expenditure. Our model can be applied whenever a consumer’s demand over a strict subset of all available goods is being analysed; it can also be extended to settings with discrete goods and non-linear prices. To illustrate its use, we apply our model to a single-agent data set and to a data set with repeated cross-sections. We develop a novel test of linear hypotheses on partially identified parameters to estimate the proportion of the population who are revealed better off due to a price change in the latter application. This new technique can be used for non-parametric counterfactual analysis more broadly.

Motivated by the question of how one should evaluate professional election forecasters, we study a novel dynamic mechanism design problem without transfers. A principal who wishes to hire only high-quality forecasters is faced with an agent of unknown quality. The agent privately observes signals about a publicly observable future event, and may strategically misrepresent information to inflate the principal’s perception of his quality. We show that the optimal deterministic mechanism is simple and easy to implement in practice: it evaluates a single, optimally timed prediction. We study the generality of this result and its robustness to randomization and noncommitment. (JEL C53, D72, D82)

The aim of this paper is to develop revealed preference tests for Cournot equilibrium. The tests are akin to the widely used revealed preference tests for consumption, but have to take into account the presence of strategic interaction in a game-theoretic setting. The tests take the form of linear programs, the solutions to which also allow us to recover cost information on the firms. To check that these nonparametric tests are sufficiently discriminating to reject real data, we apply them to the market for crude oil.