Mechanism Design with Aftermarkets: Cutoff Mechanisms
I study a mechanism design problem of allocating a single good to one of several agents. The mechanism
is followed by an aftermarket, that is, a post-mechanism game played between the agent who acquired the good and third-party
market participants. The designer has preferences over final outcomes, but she cannot redesign the aftermarket. However,
she can influence its information structure by disclosing information elicited by the mechanism.
I introduce a class of allocation and disclosure rules, called cutoff rules, that disclose information about the buyer's type
only by revealing information about the random threshold (cutoff) that she had to outbid to win the object. A rule is implementable
regardless of the form of the aftermarket and the underlying distribution of types if and only if it is a cutoff rule.
Cutoff mechanisms are tractable, and admit an indirect implementation that often makes them easy to use in practice.
I provide sufficient conditions for particularly simple designs, such as a second-price auction with disclosure of the price,
to be optimal within the class of cutoff mechanisms.
The theory is illustrated with an application to the design of trading rules and post-transaction transparency in financial
over-the-counter markets. Online Appendix
Mechanism Design with Aftermarkets: On the Optimality of Cutoff Mechanisms (Preliminary)
My job market paper introduces a class of cutoff mechanisms, characterizes their properties, and derives the optimal mechanism within the class.
In this paper, under the assumption that the aftermarket payoffs are determined by a binary decision of the third party, I provide sufficient conditions
for optimality of cutoff mechanisms.
I also analyze a version of the model in which cutoff mechanisms are sometimes suboptimal. I derive robust payoff bounds on their performance,
and show that by using a cutoff mechanism the designer can often guarantee a large fraction of the payoff of the optimal (non-cutoff) mechanism.
Mechanism Design with Aftermarkets: On the Impossibility of Pure Information Intermediation (Preliminary)
A mediator, with no prior information and no control over the market protocol, attempts to redesign the information structure in the market by running an
information intermediation mechanism with transfers that first elicits information from an agent, and then discloses information to another market participant
(third party). The note establishes a general impossibility result: If the third party has full bargaining power in the interaction with the agent,
all incentive-compatible information intermediation mechanisms are uninformative about the agent's type.
Benchmarks in Search Markets (with Darrell Duffie and Haoxiang Zhu)
The Journal of Finance, 72: 1983–2044, 2017
We characterize the price-transparency role of benchmarks in over-the-counter markets. A benchmark
can, under conditions, raise social surplus by increasing the volume of beneficial trade, facilitating
more efficient matching between dealers and customers, and reducing search costs. Although
the market transparency promoted by benchmarks reduces dealers’ profit margins, dealers may
nonetheless introduce a benchmark to encourage greater market participation by investors. Lowcost
dealers may also introduce a benchmark to increase their market share relative to high-cost
dealers. We construct a revelation mechanism that maximizes welfare subject to search frictions,
and show conditions under which it coincides with announcing the benchmark.
A non-technical summary at VOX: In Support of Transparent Financial Benchmarks
Deferred Acceptance with Compensation Chains
Best Paper with Student Lead Author award at the EC'16 conference
I introduce a class of algorithms called Deferred Acceptance with Compensation Chains (DACC). DACC algorithms generalize the DA algorithms by Gale and Shapley (1962)
by allowing both sides of the market to make offers. The main result is a characterization of the set of stable matchings: a matching is stable if and only if it is
the outcome of a DACC algorithm.
A version of this paper has been accepted for publication (abstract) at EC'16: EC version
The Simple Economics of Optimal Persuasion (with Giorgio Martini)
We study Bayesian persuasion problems in which the Sender's preferences depend only on the mean of posterior beliefs.
In this environment, the economics of optimal persuasion are simple: Given a price schedule for posterior means,
the Sender faces a consumer-like choice problem, purchasing posterior means using the prior distribution as her endowment.
We propose a verification tool for optimality and characterize the structure of prices that support the optimal solution.
Our approach provides a tractable solution method for persuasion problems with infinite state and action spaces,
and yields a necessary and sufficient condition on the Sender's objective function under which the optimal persuasion mechanism
can be guaranteed to have a monotone partitional structure.
Previously circulated under the title "A Duality Approach to Bayesian Persuasion."
The Effects of Post-Auction Bargaining between Bidders
An additional award in the Best Paper Prize for Young Economists category at the 2015 WIEM conference
I study an auction model in which the auction is followed by bargaining between bidders. Bidders with multi-unit demand bid for an object and then bargain over additional units.
In the presence of post-auction interaction between players, equilibrium bidding strategies are sensitive to the amount and nature of information about bidders’ valuations
revealed by the auction. Standard auctions fail to allocate the good efficiently if some bids are announced. If the post-auction market is small enough, a first-price
sealed-bid auction with no revelation of bids achieves efficiency. By choosing an optimal announcement policy the auctioneer can increase expected revenue.
Robust Benchmark Design (with Darrell Duffie)
Recent scandals over the manipulation of LIBOR and foreign exchange benchmarks have spurred policy discussions of the appropriate design of financial benchmarks.
We solve a version of the problem faced by a financial benchmark administrator. Acting as a mechanism designer, the benchmark administrator constructs a “fixing,”
meaning an estimator of a market value or reference rate based on transactions or other submission data. The data are generated by agents whose profits depend on the
realization of the estimator (the benchmark fixing). Agents can misreport, or trade at distorted prices, in order to manipulate the fixing. We characterize the best
linear unbiased benchmark fixing.
A non-technical summary at VOX: Robust Financial Market Benchmarks
Implementability, Walrasian Equilibria, and Efficient Matchings (with Anthony Lee Zhang)
Economics Letters, 2017, 153, 57 -- 60.
In general screening problems, implementable allocation rules correspond exactly to Walrasian equilibria of an economy in which types are consumers with quasilinear
utility and unit demand. Due to the welfare theorems, an allocation rule is implementable if and only if it induces an efficient matching between types and goods.