Publications

We study mechanism design when agents have private preferences and private information about a common payoff-relevant state. We show that standard message-driven mechanisms cannot implement socially efficient allocations when agents have multidimensional types, even under favorable conditions.

To overcome this limitation, we propose data-driven mechanisms that leverage additional post-allocation information, modeled as an estimator of the payoff-relevant state. Our data-driven mechanisms extend the classic Vickrey-Clarke-Groves class. We show that they achieve exact implementation in posterior equilibrium when the state is either fully revealed or the utility is affine in an unbiased estimator. We also show that they achieve approximate implementation with a consistent estimator, converging to exact implementation as the estimator converges, and present bounds on the convergence rate.

We demonstrate applications to digital advertising auctions and large language model (LLM)-based mechanisms, where user engagement naturally reveals relevant information.

We analyze a nonlinear pricing model where the seller controls both product pricing (screening) and buyer information about their own values (persuasion).

We prove that the optimal mechanism always consists of finitely many signals and items, even with a continuum of buyer values. The seller optimally pools buyer values and reduces product variety to minimize informational rents.

We show that value pooling is optimal even for finite value distributions if their entropy exceeds a critical threshold. We also provide sufficient conditions under which the optimal menu restricts offering to a single item.

We study the impact of supply chain disruptions on U.S. firms based on the universe of seaborne shipment-level import transactions from 2013 to 2023. The granularity of the data allows us to build an index of firm-level disruptions of international suppliers and introduce a comprehensive set of stylized facts for supply chain relationships in the cross-section of firms. We build a general equilibrium heterogeneous firms model with two types of capital stocks—physical and international supplier capitals. Accumulation of supplier capital is an important endogenous margin of adjustment, and limiting this ability substantially delays recovery, especially in financially constrained firms.

We characterize the extreme points of multidimensional monotone functions from [0,1]^n to [0,1], as well as the extreme points of the set of one-dimensional marginals of these functions. These characterizations lead to new results in various mechanism design and information design problems, including public good provision with interdependent values; interim efficient bilateral trade mechanisms; asymmetric reduced form auctions; and optimal private private information structure. As another application, we also present a mechanism anti-equivalence theorem for two-agent, two-alternative social choice problems: A mechanism is payoff-equivalent to a deterministic DIC mechanism if and only if they are ex-post equivalent.

We study the robust sequential screening problem of a monopolist seller of multiple cloud computing services facing a buyer who has private information about his demand distribution for these services. At the time of contracting, the buyer knows the distribution of his demand of various services and the seller simply knows the mean of the buyer’s total demand. We show that a simple “committed spend mechanism” is robustly optimal: it provides the seller with the highest profit guarantee against all demand distributions that have the known total mean demand. This mechanism requires the buyer to commit to a minimum total usage and a corresponding base payment; the buyer can choose the individual quantities of each service and is free to consume additional units (over the committed total usage) at a fixed marginal price. This result provides theoretical support for prevalent cloud computing pricing practices while highlighting the robustness of simple pricing schemes in environments with complex uncertainty.

We estimate causal effects of 121 graduate degrees on log earnings. The returns average 0.159 but vary widely across fields, with a standard deviation of 0.176. Experience profiles of the returns also vary and are particularly steep for medicine. Internal rates of return, which account for program length, tuition, and in-school earnings, are sizable but vary less across fields. Earnings effects are higher for women, lower for part time students, and depend on undergraduate major. Students from lower-paying undergraduate majors benefit more from an MBA or JD. School specific returns are higher for higher ranked JD and MBA programs.

We consider a seller who offers services to a buyer with multi-unit demand. Prior to the realization of demand, the buyer receives a noisy signal of their future demand, and the seller can design contracts based on the reported value of this signal. Thus, the buyer can contract with the service provider for an unknown level of future consumption, such as in the market for cloud computing resources or software services. We characterize the optimal dynamic contract, extending the classic sequential screening framework to a nonlinear and multi-unit setting. The optimal mechanism gives discounts to buyers who report higher signals, but in exchange they must provide larger fixed payments. We then describe how the optimal mechanism can be implemented by two common forms of contracts observed in practice, the two-part tariff and the committed spend contract. Finally, we use extensions of our base model to shed light on policy-focused questions, such as analyzing how the optimal contract changes when the buyer faces commitment costs, or when there are liquid spot markets.

This paper examines the history of U.S. infrastructure since 1929 and in the process reports an interesting fact about the U.S. economy. Infrastructure stock as a percent of GDP began a steady decline around 1970, and the government budget deficit became positive and large at roughly the same time. The infrastructure pattern in other countries does not mirror that in the United States, so the United States appears to be a special case. The overall results suggest that the United States became less future oriented beginning around 1970, an increase in the social discount rate. This change has persisted. This is the interesting fact. The paper contains speculation on possible causes.

We develop an economic framework to analyze the optimal pricing and product design of Large Language Models (LLM). Our framework captures several key features of LLMs: variable operational costs of processing input and output tokens; the ability to customize models through fine-tuning; and high-dimensional user heterogeneity in terms of task requirements and error sensitivity. In our model, a monopolistic seller offers multiple versions of LLMs through a menu of products. The optimal pricing structure depends on whether token allocation across tasks is contractible and whether users face scale constraints. Users with similar aggregate value-scale characteristics choose similar levels of fine-tuning and token consumption. The optimal mechanism can be implemented through menus of two-part tariffs, with higher markups for more intensive users. Our results rationalize observed industry practices such as tiered pricing based on model customization and usage levels.

We fully solve a sorting problem with heterogeneous firms and multiple heterogeneous workers whose skills are imperfect substitutes. We show that optimal sorting, which we call mixed and countermonotonic, is comprised of two regions. In the first region, mediocre firms sort with mediocre workers and coworkers such that the output losses are equal across all these teams (mixing). In the second region, a high-skill worker sorts with low-skill coworkers and a high-productivity firm (countermonotonicity). We characterize the equilibrium wages and firm values. Quantitatively, our model can generate the dispersion of earnings within and across US firms.

This paper provides a framework in which a multiproduct ecosystem competes with many single-product firms in both price and innovation. The ecosystem is able to use data collected on one product to improve the quality of its other products. We study the impact of data regulation which either restricts the ecosystem's cross-product data usage, or which requires it to share data with small firms. Each policy induces small firms to innovate more and set higher prices; it also dampens data spillovers within the ecosystem, reduces the ecosystem's incentive to collect data and innovate, and potentially increases its prices. As a result, data regulation has an ambiguous impact on consumers, and is more likely to benefit consumers when small firms are relatively more efficient in innovation. A data cooperative among small firms, which helps them to share data with each other, does not necessarily benefit small firms and can even harm consumers.

In this paper we develop a novel approach to measuring individual welfare within households, recognizing that individuals may have both different preferences (particularly regarding public consumption) and differential access to resources. We construct a money metric measure of welfare that accounts for public goods (by using personalized prices) and the allocation of time. We then use our conceptual framework to analyse intrahousehold inequality in Japan, allowing for the presence of two public goods: expenditures on children and other public goods including housing. We show empirically that women have much stronger preferences for both public goods and this has critical implications for the distribution of welfare in the household.

We study the intergenerational effect of education policy on crime. We use Swedish administrative data that links outcomes across generations with crime records, and we show that the comprehensive school reform, gradually implemented between 1949 and 1962, reduced conviction rates both for the generation directly affected by the reform and for their sons. The reduction in conviction rates occurred in many types of crime. The key mediators of this reduction in child generation are an increase in education and household income and a decrease in crime among their fathers.

Welfare depends on the quantity, quality, and range of goods consumed. We use trade data, which report the quantities and prices of the individual goods that countries exchange, to learn about how the gains from trade and growth break down into these different margins. Our general equilibrium model, in which both quality and quantity contribute to consumption and to production, captures (i) how prices increase with importer and exporter per capita income, (ii) how the range of goods traded rises with importer and exporter size, and (iii) how products traveling longer distances have higher prices. Our framework can deliver a standard gravity formulation for total trade flows and for the gains from trade. We find that growth in the extensive margin contributes to about half of overall gains. Quality plays a larger role in the welfare gains from international trade than from economic growth due to selection.

This article provides a general framework to study the role of production networks in international GDP comovement. We first derive an additive decomposition of bilateral GDP comovement into components capturing shock transmission and shock correlation. We quantify this decomposition in a parsimonious multi-country, multi-sector dynamic network propagation model, using data for the G7 countries over the period 1978–2007. Our main finding is that while the network transmission of shocks is quantitatively important, it accounts for a minority of observed comovement under the estimated range of structural elasticities. Contemporaneous responses to correlated shocks in the production network are more successful at generating comovement than intertemporal propagation through capital accumulation. Extensions with multiple shocks, nominal rigidities, and international financial integration leave our main result unchanged. A combination of TFP and labour supply shocks is quantitatively successful at reproducing the observed international business cycle.