Working Papers

Policymakers often distort goods markets to effect redistribution—for example, via price controls, differential taxation, or in-kind transfers. We investigate the optimality of such policies alongside the (optimally-designed) income tax. In our…

We examine how patent disclosures influence technology classification decisions by patent examiners and how firms strategically tailor these disclosures to affect classification outcomes. Using a novel machine learning approach, we construct a…

We use a play-by-play dataset from the game show “Jeopardy!” to study the hot hand phenomenon, whereby people appear to exhibit “hot” states of elevated performance in domains with repeat trials. We first demonstrate that Jeopardy contestants…

We study poverty minimization via direct transfers, framing this as a statistical learning problem while retaining the information constraints faced by real-world programs. Using nationally representative household consumption surveys from 23…

A persistent puzzle throughout the cognitive and social sciences is how people manage to learn social conventions from the sparse and noisy behavioral data of diverse actors, without explicit instruction. Here, we show that the dominant theories…

Modern recommender systems rely on black-box machine learning models to predict consumer choices. However, because these models do not explicitly represent the underlying data-generating process (DGP), they often struggle to generalize beyond…

Online social networks have transformed the ways in which political mobilization messages are disseminated, raising new questions about how peer influence operates at scale. Building on the landmark 61-million-person Facebook experiment, we…

As increasingly capable agents are deployed, a central safety challenge is how to retain meaningful human control without modifying the underlying system. We study a minimal control interface in which an agent chooses whether to act autonomously…

This paper develops and estimates a structural model of the labor market for accountants that integrates forward-looking lifetime occupational choices with oligopsonistic employer demand. Using longitudinal resume data covering career transitions…

In collaboration with Feeding America, we aim to redesign Real-Time—a tool on its food sourcing and rescue platform, MealConnect—that facilitates the connection of ad-hoc, time-sensitive food donations to local agencies (e.g., meal programs)…

An enduring challenge in contagion theory is that the pathways contagions follow through social networks exhibit emergent complexities that are difficult to predict using network structure. Here, we address this challenge by developing a causal…

Insights from psychology suggest competitive interference: when a firm advertises, consumers are less likely to think of its competitor, benefiting the advertiser by keeping it top of mind and suppressing competitor recall. We empirically…

This paper studies partisan differences in medical practice over 1999-2019. I link physicians in the Medicare claims data with campaign contributions to identify party alignment. In 1999, there are no partisan differences in medical expenditure…

We compute the cross-country transfers that result from unconventional monetary policy in the Eurozone. The ECB funds the expansion of its aggregate balance sheet mostly by issuing bank reserves and cash in core countries. The national central…

The recent elimination of the United States de minimis exemption for import tariffs has been reported to have a significant impact on ultra-fresh fashion companies such as Shein and Temu. This paper develops a game-theoretic model to investigate…

During the Covid-19 pandemic, the United States effectively “spent” about 4 percent of GDP — via reduced economic activity — to address a mortality risk of around 0.3 percent. Many experts believe that catastrophic risks from advanced A.I. over…

We study how Russian oligarch-affiliated companies operate globally and respond to sanctions. We construct a dataset tracking 70 companies, 1,800 international subsidiaries, and their institutional investors between 2009 and 2023. These companies…

Over the past decade, the use of machine learning (ML) models in healthcare applications has rapidly increased. Despite high performance, modern ML models do not always capture patterns the end user requires. For example, a model may predict a…

Building on the canonical “bottleneck” model of Vickrey (1969), we show that carpooling and road pricing are highly complementary in addressing traffic congestion: they can be much more effective jointly than each one separately, and can improve…