August 2025, in American Economic Review, 115(8), 2449–87.
Economists routinely make functional form assumptions on demand curves to derive welfare conclusions. How sensitive are these conclusions to such assumptions? In this paper, we develop robustness measures that quantify the extent to which the true demand curve must deviate from common functional form assumptions in order to overturn a welfare conclusion. We parametrize this variability in terms of the gradient and curvature of the demand curve. By leveraging tools from information design, we show that our measures are easy to compute. Our measures are also flexible and easy to use, as we illustrate through empirical applications.
This paper studies how topping up—allowing recipients of in-kind transfers to supplement subsidized consumption in a private market—affects optimal redistribution. Consumers can access a competitive private market, while a social planner offers an alternative nonlinear price schedule. We show that the effect of topping up depends on the correlation between redistributive priority and demand. When the correlation is positive, topping up does not affect the optimal mechanism. When the correlation is negative, topping up weakens screening and reduces redistribution. At the extensive margin, topping up reduces the set of environments in which intervention is optimal. At the intensive margin, topping up reduces both the scope of a free public option and the mass of consumers served. We characterize the optimal mechanisms and show how topping up changes comparative statics with respect to redistributive priorities.
This paper revisits the classic instrument choice problem in a setting with consumption externalities, through the lens of robust mechanism design. A regulator can implement any incentive-compatible policy but is uncertain about how individual demand is correlated with marginal externalities, and evaluates policies by worst-case welfare. The optimal policy is a quantity control: a floor for positive externalities and a ceiling for negative externalities. If the sign of the correlation is known, a uniform tax or subsidy can be optimal. The framework also applies to regulatory uncertainty and costly screening, providing a welfare-based explanation for the prevalence of non-price policies.
We study corporate "public alignment": firm speech that echoes the rhetoric of an autocratic regime. We develop a theoretical model in which public alignment sustains political risk-sharing between firms and the regime: by tying their payoffs to the regime's, aligned firms credibly commit to undertake costly, regime-favored actions in adverse states, and in return the regime becomes less likely to expropriate them. We construct an empirical measure of public alignment using a general, replicable index based on regime-specific phrases in annual reports and implement it for Chinese listed firms. We use this to validate both the model's predictions and its key assumption that alignment links firm and regime payoffs. More-aligned firms take more regime-favored actions during periods of unrest and earn lower profits, and alignment increases following heightened expropriation risk. These patterns hold after controlling for other forms of state proximity (state ownership, political connections, and Party cells) and are difficult to reconcile with alternative explanations such as cheap talk or simple patronage.
This paper studies the regulation of a good that generates different amounts of an externality on consumption. Direct taxation of the externality is assumed to be infeasible; instead, the good itself is taxed to indirectly regulate the externality. I show that the deadweight loss due to any nonlinear tax on the good is equal to the Bregman divergence between the allocation that the tax induces and the first-best allocation. This yields a regression-based method to derive the deadweight loss-minimizing tax. I use this method to show that quantity controls, such as bans and mandates, can be optimal. I quantify the welfare gains of using a nonlinear tax over a linear tax. Finally, I illustrate policy implications by applying my results to the taxation of vehicle miles traveled to regulate automobile externalities.
This paper examines how the equilibrium effects of a public option on the private market impact its optimal design. I develop a model in which a policymaker can choose the quality and allocation of the public option, which affect the prices of private goods (and vice versa) in equilibrium. I demonstrate how these equilibrium effects change both the optimal quality and optimal allocation: they create new incentives to distort quality in either direction depending on the policymaker's redistributive objective and provide a new justification for rationing the public option rather than using market-clearing prices. Finally, I show how my results can accommodate additional frictions in the private market and additional policy instruments.
We study a platform that sells productive inputs (such as e-commerce and distribution services) to a fringe of producers in an upstream market, while also selling its own output in the corresponding downstream market. The platform faces a tradeoff: any output that it sells downstream increases competition with the fringe of producers and lowers the downstream price, which in turn reduces demand for the platform’s productive inputs and decreases upstream revenue. Adopting a mechanism design approach, we characterize the optimal menu of contracts the platform offers in the upstream market. These contracts involve price discrimination in the form of nonlinear pricing and quantity discounts. If the platform is a monopoly in the upstream market, then we show that the tradeoff always resolves in favor of consumers and at the expense of producers. However, if the platform faces competition in the upstream market, then it has an incentive to undermine this competition by engaging in activities, such as “killer” acquisitions and exclusive dealing, that harm both consumers and producers.
August 2021, in Proceedings of the 2022 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA '22), pp. 2964–2985.
We consider the bilateral trade problem, in which two agents trade a single indivisible item. It is known that the only dominant-strategy truthful mechanism is the fixed-price mechanism: given commonly known distributions of the buyer's value $B$ and the seller's value $S$, a price $p$ is offered to both agents and trade occurs if $S \leq p \leq B$. The objective is to maximize either expected welfare, $\mathbb{E}\!\left[S + (B-S) \mathbf{1}_{S \leq p \leq B}\right]$, or expected gains from trade, $\mathbb{E}\!\left[(B-S) \mathbf{1}_{S \leq p \leq B}\right]$.
We improve the approximation ratios for several welfare maximization variants of this problem. When the agents' distributions are identical, we show that the optimal approximation ratio for welfare is $(2+\sqrt{2})/4$. With just one prior sample from the common distribution, we show that a $3/4$-approximation to welfare is achievable. When agents' distributions are not required to be identical, we show that a previously best-known $(1-1/e)$-approximation can be strictly improved, but $1-1/e$ is optimal if only the seller's distribution is known.
September 2019, partially superseded by "Fixed-Price Approximations in Bilateral Trade" (with Francisco Pernice and Jan Vondrák).
This paper studies fixed-price mechanisms in bilateral trade with ex ante symmetric agents. We show that the optimal price is particularly simple: it is exactly equal to the mean of the agents’ distribution. The optimal price guarantees a worst-case performance of at least 1/2 of the first-best gains from trade, regardless of the agents’ distribution. We also show that the worst-case performance improves as the number of agents increases, and is robust to various extensions. Our results offer an explanation for the widespread use of fixed-price mechanisms for size discovery, such as in workup mechanisms and dark pools.
