Delegating Experiments (with Nathan Yoder):
A principal wants information to help her decide whether or not to approve a project. She delegates costly experimentation to an agent, who wants her to approve the project and has private information about the state. The principal can influence experimentation only by restricting the experiments that the agent can undertake: she cannot commit to approval, and no transfers are possible. For example, the FDA may select a set of clinical trials that are acceptable for testing a new drug, but cannot pay drug companies or weaken its threshold for approval. We show that the principal can screen the agent -- and thus learn his private information -- by offering a menu of experiments that differ in conditional expected payoffs across states. Doing so is always optimal: screening dominates pooling. Private information distorts the optimal menu by making the false negative rate inefficiently high. In our drug approval application, too many good drugs are rejected.
Search and matching increasingly takes place on online platforms. These platforms have elements of centralized and decentralized matching; platforms can alter the search process for its users, but are unable to eliminate search frictions entirely. I study a model where platforms can change the distribution of potential partners that an agent searches over and characterize search equilibria on platforms. When agents possess private information about their match characteristics and the platform designer acts as a profit maximizing monopolist, I characterize the optimal platform. If match characteristics are complementary and utility is transferable, I show that the solution to this screening problem is efficient, despite the presence of hidden information and market power. Matching under the optimal platform is perfectly assortative --- there is no equilibrium mismatch.
What Slips the Mind Stalls the Deal, Delay in Bargaining with Absentmindedness:
In finite-horizon bargaining, deals are often made "on the courthouse steps", just before the deadline. Most classic finite-horizon bargaining models fail to generate deadline effects, or even delay, in equilibrium. Players foresee the future path of play, and come to a deal immediately to circumvent bargaining frictions. We propose a novel source of bargaining delay: absentmindedness. A bargainer who does not know the calendar time may rationally reject an "ultimatum offer" as the trade deadline looms. Rational confusion is a source of bargaining power for the absentminded player, as it induces the other party to make fair offers near the trade deadline to prevent negotiations from breaking down. The absentminded party may reject greedier offers in hope of receiving a fair offer closer to the deadline. If any offer is feasible, there are equilibria which feature delay if and only if players are patient. Such equilibria always involve history-dependent strategies. I provide a necessary and sufficient condition for there to exist a Markov perfect equilibrium with delay: the space of feasible offers must be sufficiently disconnected.
Dynamic Data Markets:
A firm can flexibly acquire information (or data) about the quality of a project at a cost, and acts as a monopolist. Buyers can sequentially purchase data before making an irreversible investment decision regarding the project, and are privately informed about their value of information. I show when the support of the buyer value distribution is bounded away from the marginal cost of information acquisition, the market clears in finite time. The skimming property fails --- high buyer types remain in the market to purchase additional information and low types wait for prices to fall. Despite this, the Coase conjecture holds; monopoly profits approach the value of serving only the lowest type consumer in the patient limit. I also show that privacy regulations, such as differential privacy, can function as commitment devices, enabling the seller to obtain supranormal profits by credibly limiting future disclosure.