Delong Meng
Job Market Candidate
Stanford University
Department of Economics
579 Serra Mall
Stanford, CA 94305
6176396371
delong13@stanford.edu




Job Market Paper
Optimal Mechanisms for Repeated Communication
We study repeated communication between a longrun sender and a longrun receiver. In each period the sender observes the state of the world  which is i.i.d. across time  and reports the state to the receiver. The receiver takes an action based on the history of the sender's reports and public randomization signals. The receiver fully commits to her action at each point in history, and the sender commits to nothing. We allow arbitrary state space, action space, and preferences. We characterize the set of possible payoffs for the sender and the receiver when both are infinitely patient  i.e., as the discount factor goes to one. We also study the payoff set when the discount factor is less than (but close to) one. In particular we bound the rate of convergence to points on the frontier of the limit payoff set; the rate of convergence differs radically for discrete and continuous models, and we provide a unified view of the rate of convergence results based on the shape of the frontier of the limit payoff set. We discuss three applications of our results. First for dynamic CEO compensation we characterize the firm's revenue from the optimal contract as the interest rate goes to zero. Second we show that dynamic delegation  a common problem in agencies  is equivalent to our model. Third we study a reputation problem where the sender's preference is unknown, and we give a lower bound for the receiver's expected payoff as the discount factor goes to one.

Journal Publications
Robust Contracting with Additive Noise (with Gabriel Carroll)
Journal of Economic Theory 166, 2016, 586604.
We investigate the idea that linear contracts are reliable because they give the same incentives for effort at every point along the contract. We ask whether this reliability leads to a microfoundation for linear contracts, when the principal is profitmaximizing. We consider a principalagent model with risk neutrality and limited liability, in which the agent observes the realization of a meanzero shock to output before choosing how much effort to exert. We show that such a model can indeed provide a foundation for reliable contracts, and illustrate what elements are required. In particular, we must assume that the principal knows a lower bound, but not an upper bound, on the shocks.
Locally Robust Contracts for Moral Hazard (with Gabriel Carroll)
Journal of Mathematical Economics 62, 2016, 3651.
We consider a moral hazard problem in which the principal has a slight uncertainty about how the agent's actions translate into output. An incentive contract can be made robust against an ε amount of uncertainty, at the cost of a loss to the principal on the order of √ε, by refunding a small fraction of profit to the agent. We show that as ε goes to zero, this construction is essentially optimal, in the sense of minimizing the worstcase loss, among all modifications to the contract that do not depend on the details of the environment.

Working Papers
Learning from LikeMinded People
We study a social learning model in which people choose who to talk to and strategically exchange information. Agents start with heterogeneous priors about an unknown state of the world. First each agent chooses a partner. Then everyone observes a private i.i.d. signal and sends a message to her partner. Finally everyone takes an action based on her prior, her private signal, and her partner's message. Our main finding is that when the signal space and action space are binary, assortative matching arises in equilibrium, but it is generally inefficient for social welfare and information aggregation. In addition we construct counterexamples (nonassortative matching) in the case of multiple signals or multiple actions.
How to Set a Deadline for Auctioning a House? (with Alina Arefeva)
Presented at the American Economic Assocation Meeting, Chicago, 2017.
We investigate the optimal choice of an auction deadline by a seller who commits to this deadline prior to the arrival of any buyers. In our model buyers have evolving outside options, and their bidding behaviors change over time. We find that if the seller runs an optimal auction, then she should choose a longer deadline. However, if the seller runs a secondprice auction, then a shorter deadline could potentially help her. Moreover, the seller can extract information about buyers' outside options by selling them contracts similar to European call options. Finally, the optimal dynamic mechanism is equivalent to setting a longer deadline and running an auction in the last day.

Work in Progress
A Dynamic Model of College Admission
We propose a model of college admission in which a university wants to maximize its total contribution to society's intellectual capital. A university is facing a budget constraint, so donors' preferences influence its admission and financial aid policy. A university must balance the tradeoff between pleasing current donors and producing future donors (today's students become future donors). Our model helps explain why universities give preferential treatment to legacy, athletes, and underrepresented minorities. We characterize the optimal admission and financial aid policy, and we analyze the comparative statics of donors' preferences. We also discuss the implications of our model, particularly on affirmative action.
Community and Motivated Belief (with Daniel Walton)
We explore a model of motivated belief where a person chooses their community, and the community affects their belief. In the first period everyone is born in some community. Thereafter everyone could choose to join a different community at some switching cost. Once a person joins a community they adjust their beliefs according to the beliefs of everyone else in the community. A person's utility depends on the distance between their belief and the beliefs of others in the same community, and they could put different weights on different members (e.g. more weights on family and friends). We characterize the steady state community formation as well as the stead state beliefs. Applications include religious conversion and political affiliation.

