Nathan Hancart

Department of Economics
University College London

Nathan Hancart

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About me

Hello, I'm a PhD candidate in Economics at University College London. I will be on the 2022/23 job market.

My interests are in Microeconomic theory with a focus on Information and Behavioural Economics.

You can find information on my research and my CV here.


Job Market Paper: Designing the Optimal Menu of Tests (Draft coming soon)

A decision-maker (DM) must accept or reject a privately informed agent. Prior to taking his decision, he can perform one test from a restricted set of feasible tests. The agent always wants to be accepted while the DM wants to accept a subset of types. The DM designs a menu of test and lets the agent choose a test from the menu. The choice itself then serves as an additional source of information. I provide a characterisation of the DM-optimal menu for arbitrary type structures and feasible tests. I also show that the DM does not benefit from committing ex-ante to a strategy. Using these results, I characterise the optimal menu when the set of feasible tests contains a most informative test. I give conditions on the DM's preferences under which a strictly less informative test is included in the menu. I also characterise the optimal menu when types are multidimensional or when tests vary in their difficulty.

Managing the Expectations of Buyers with Reference-Dependent Preferences, 2021, R&R at Journal of Economic Theory
[draft][24 minutes presentation]

I consider a model of monopoly pricing where a risk-neutral firm makes an offer to a buyer with reference-dependent preferences. The reference point is the ex-ante probability of trade and the buyer exhibits an attachment effect: the higher his expectations to buy, the higher his willingness-to-pay. When the buyer’s valuation is private information, a unique equilibrium exists where the firm plays a mixed strategy and its profits are the same as in the reference-independent benchmark. The equilibrium always entails inefficiencies: even as the firm’s information converges to complete information, it mixes on a non-vanishing support and the probability of no trade is greater than zero. Finally, I show that when the firm can obtain costless signals on the buyer’s valuation, it can do strictly better than in the reference-independent benchmark by leveraging the uncertainty generated by a noisy learning strategy. However, this advantage vanishes as the attachment effect grows large.

The (No) Value of Commitment (Draft coming soon)

I provide a sufficient condition under which a principal does not benefit from commitment in economic situations that can be described by a constrained maximisation problem. I show that commitment has no value when the marginal contribution of the constraints is null. I then apply this condition in a mechanism design setting. A designer does not benefit from being able to contract over actions when his preferences are partially aligned with the agent's. Verifying the condition does not necessitate verifying explicitly that the strategy under commitment is a best-response to the information revealed in the economic problem.