Piotr Dworczak

Department of Economics

Northwestern University

Global Hub 3389

Evanston, IL 60208

piotr.dworczak@northwestern.edu

Curriculum Vitae

I am an Assistant Professor in the Department of Economics at Northwestern University. I received my PhD in 2017 from Stanford GSB under the supervision of Andy Skrzypacz and Paul Milgrom.

I work on Mechanism and Information Design, trying to combine research in pure theory with more applied interests in financial over-the-counter markets. I am also interested in (broadly understood) Market Design. 

Research

Redistribution through Markets (with Scott Duke Kominers and Mohammad Akbarpour)

R&R at Econometrica

When macroeconomic tools fail to respond to wealth inequality optimally, regulators can still seek to mitigate inequality within individual markets. A social planner with distributional preferences might distort allocative efficiency to achieve a more desirable split of surplus, for example, by setting higher prices when sellers are poor—effectively, using the market as a redistributive tool.
In this paper, we seek to understand how to design goods markets optimally in the presence of inequality. Using a mechanism design approach, we uncover the constrained Pareto frontier by identifying the optimal trade-off between allocative efficiency and redistribution in a setting where the second welfare theorem fails because of private information and participation constraints. We find that competitive equilibrium allocation is not always optimal. Instead, when there is substantial inequality across sides of the market, the optimal design uses a tax-like mechanism, introducing a wedge between the buyer and seller prices, and redistributing the resulting surplus to the poorer side of the market via lump-sum payments. When there is significant within-side inequality, meanwhile, it may be optimal to impose price controls even though doing so induces rationing.

Mechanism Design with Aftermarkets: Cutoff Mechanisms

R&R at Econometrica

I study a mechanism design problem in which a designer allocates a single good to one of several agents, and the mechanism is followed by an aftermarket — 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 design the aftermarket. However, she can influence its information structure by disclosing information elicited from the agents 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 realization of a 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 prior distribution of types if and only if it is a cutoff rule. I characterize aftermarkets for which restricting attention to cutoff mechanisms is without loss of generality in a subclass of all feasible mechanisms. Optimization within the class of cutoff mechanisms is tractable; I provide sufficient conditions for optimality of simple designs. Online AppendixOlder version with additional results

Mechanism Design with Aftermarkets: Optimal Mechanisms under Binary Actions 

I study a mechanism design problem of allocating a single good to an agent when the mechanism is followed by a post-mechanism game (aftermarket) played between the agent and a third-party. The aftermarket is beyond the direct control of the designer. However, she can influence the information structure of the post-mechanism game by disclosing information about the agent’s type elicited by the mechanism. Under the simplifying assumption that the third party takes a binary action, I characterize the optimal Bayesian mechanism for a large set of objective functions of the mechanism designer. I relate optimal transparency of the mechanism to the properties of the aftermarket game.

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, 2017, awarded the Amundi Smith Breeden First Prize

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. Low-cost 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. Online Appendix

A non-technical summary at VOX: In Support of Transparent Financial Benchmarks

Deferred Acceptance with Compensation Chains

R&R at Operations Research, Best Paper with Student Lead Author award at the EC’16 conference (EC version)

I introduce a class of algorithms called Deferred Acceptance with Compensation Chains (DACC). DACC algorithms generalize the DA algorithms of 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. An earlier version with some additional results.

The Simple Economics of Optimal Persuasion (with Giorgio Martini)

Journal of Political Economy, forthcoming

Consider a Bayesian persuasion problem in which the Sender’s preferences depend only on the mean of posterior beliefs. We show that there exists a price schedule for posterior means such that the Sender’s problem becomes a consumer-like choice problem: The Sender purchases posterior means using the prior distribution as her endowment. Prices are determined in equilibrium of a Walrasian economy with the Sender as the only consumer and a single firm that has the technology to garble the state. Welfare theorems provide a verification tool for optimality of a persuasion scheme, and characterize the structure of prices that support the optimal solution. This price-theoretic approach yields a tractable solution method for persuasion problems with infinite state spaces. As an application, we provide a necessary and sufficient condition for optimality of a monotone partitional signal. We show that the approach extends to competition in persuasion and persuasion problems with no restrictions on Sender’s utility.

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. Online Appendix

Robust Benchmark Design (with Darrell Duffie)

R&R at Journal of Financial Economics

Recent scandals over the manipulation of LIBOR, foreign exchange benchmarks, and other financial benchmarks have spurred policy discussions over their appropriate design. We characterize the optimal fixing of a benchmark as an estimator of a market value or reference rate. The fixing data are the reports or transactions of agents whose profits depend on the fixing, and who may therefore have incentives to manipulate it. If the benchmark administrator cannot detect or deter the strategic splitting of trades, we show that the best linear unbiased fixing is the commonly used volume-weighted average price (VWAP).

A non-technical summary at VOX: Robust Financial Market Benchmarks

Implementability, Walrasian Equilibria, and Efficient Matchings (with Anthony Lee Zhang)
Economics Letters, 2017.

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.

Other papers and activities

I am involved in designing the Polish kidney exchange program, read more here: Zywy Dawca Nerki (in Polish).
The team has received the 2015 Golden Scalpel award of the Puls Medycyny magazine: News Article

Older papers:
Optimal Constants in a LlogL Inequality for Continuous Martingales (in Polish), Undergraduate Thesis in Mathematics, 2012
Fiscal Policy Under Rational Inattention, Undergraduate Thesis in Economics, 2011