Piotr Dworczak

Department of Economics

Northwestern University

Global Hub 3389

Evanston, IL 60208


Curriculum Vitae

I am an Assistant Professor in the Department of Economics at Northwestern University. 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.


What’s new:



Research (by topic)



Mechanism and Information Design 

Are Simple Mechanisms Optimal when Agents are Unsophisticated? (with Jiangtao Li)

We study the design of mechanisms involving agents that have limited strategic sophistication. The literature has identified several notions of simple mechanisms in which agents can determine their optimal strategy even if they lack cognitive skills such as predicting other agents’ strategies (strategy-proof mechanisms), contingent reasoning (obviously strategy-proof mechanisms), or foresight (strongly obviously strategy-proof mechanisms). We examine whether it is optimal for the mechanism designer who faces strategically unsophisticated agents to offer a mechanism from the corresponding class of simple mechanisms. We show that when the designer uses a mechanism that is not simple, while she loses the ability to predict play, she may nevertheless be better off no matter how agents resolve their strategic confusion.


Preparing for the Worst but Hoping for the Best: Robust (Bayesian) Persuasion (with Alessandro Pavan)

We propose a robust solution concept for Bayesian persuasion that accounts for the Sender’s concern that her Bayesian belief about the environment—which we call the conjecture—may be false. Specifically, the Sender is uncertain about the exogenous sources of information the Receivers may learn from, and about equilibrium selection. Thus, she first identifies all information policies that yield the largest payoff in the “worst-case scenario,” i.e., when Nature provides information and coordinates the Receivers’ play to minimize the Sender’s payoff. Then, she uses the conjecture to pick the optimal policy among the worst-case optimal ones. We characterize properties of robust solutions, identify conditions under which robustness requires separation of certain states, and qualify in what sense robustness calls for more information disclosure than standard Bayesian persuasion. Finally, we discuss how some of the results in the Bayesian persuasion literature change once robustness is accounted for.


The Persuasion Duality (with Anton Kolotilin)

We present a unified duality approach to Bayesian persuasion. The optimal dual variable, interpreted as a price function, is shown to be a supergradient of the concave closure of the objective function at the prior belief. Under regularity conditions, our general duality result implies known results for the case when the objective function depends only on the expected state. We apply our approach to characterize the optimal signal in the case when the state is two-dimensional.


Mechanism Design with Aftermarkets: Cutoff Mechanisms

Forthcoming 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. When there is a single agent in the mechanism, I show that the optimal cutoff mechanism offers full privacy to the agent. In contrast, when there are multiple agents, the optimal cutoff mechanism may disclose information about the winner’s type; I provide sufficient conditions for optimality of simple designs. I also characterize aftermarkets for which restricting attention to cutoff mechanisms is without loss of generality in a subclass of all feasible mechanisms satisfying additional conditions.

Older version with additional results


The Simple Economics of Optimal Persuasion (with Giorgio Martini)

Journal of Political Economy, 2019

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.


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. Online Appendix


Mechanism Design with Aftermarkets: On the Impossibility of Pure Information Intermediation

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.


The Effects of Post-Auction Bargaining between Bidders

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


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.



Market Design 

Redistributive Allocation Mechanisms (with Mohammad Akbarpour and Scott Duke Kominers)

Many scarce public resources are allocated at below-market-clearing prices, and sometimes for free. Such “non-market” mechanisms necessarily sacrifice some surplus, yet they can potentially improve equity. In this paper, we develop a model of mechanism design with redistributive concerns. Agents are characterized by a privately observed social welfare weight and willingness to pay for quality, as well as a publicly observed label. A market designer controls allocation and pricing of a set of objects of heterogeneous quality, and maximizes the expectation of a welfare function defined by the social welfare weights. We derive structural insights about the form of the optimal mechanism, leading to a framework for determining how and when to use non-market mechanisms. The key determinant is the strength of the statistical correlation of the unobserved social welfare weights with the label and the willingness to pay that the designer can, respectively, directly observe or elicit through the mechanism.


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

Forthcoming at Econometrica

Policymakers frequently use price regulations as a response to inequality in the markets they control. In this paper, we examine the optimal structure of such policies from the perspective of mechanism design. We study a buyer-seller market in which agents have private information about both their valuations for an indivisible object and their marginal utilities for money. The planner seeks a mechanism that maximizes agents’ total utilities, subject to incentive and market-clearing constraints. We uncover the constrained Pareto frontier by identifying the optimal trade-off between allocative efficiency and redistribution. 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.


Deferred Acceptance with Compensation Chains

Forthcoming 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.


Modelling and optimisation in European Kidney Exchange Programmes (with Péter Biró, Joris van der Klundert, David Manlove et al.)

European Journal of Operational Research, 2019

An overview of state of the art of models and methods practiced in European kidney exchange programs.



Financial Markets

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


Robust Benchmark Design (with Darrell Duffie)

Accepted at Journal of Financial Economics

Scandals over the manipulation of Libor, foreign exchange benchmarks, and other financial benchmarks have spurred policy discussions over the appropriate design of benchmark fixings. We introduce a framework for the design of a benchmark fixing as an estimator of fair market value. The fixing data are the reports or transactions of agents whose profits depend on the fixing, and who may therefore have incentives to manipulate the fixing. We focus on linear fixings, which are weighted sums of transaction prices, with weights that depend on transaction sizes. We derive the optimal fixing under a simplifying assumption that weights are unidimensional, and we axiomatically characterize the unique benchmark that is robust to a certain form of collusion among traders. Our analysis provides a foundation for the commonly used volume-weighted average price (VWAP) and for a variant of VWAP based on unidimensional size weights. We characterize the relative advantages of these fixing designs, depending on the market characteristics.

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


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