Publications

We examine the labor market consequences of the 2020 Regulation S-K requiring human capital disclosure in 10K filings. Using large-sample job-level data and a Generative Large Language Model (GLLM), we observe that public firms subject…

The knockoff filter of (Ann. Statist.43 (2015) 2055–2085) is a flexible framework for multiple testing in supervised learning models, based on introducing synthetic predictor variables to control the false discovery…

Banks’ lending technology hinges on their handling of soft and hard information in dealing with different types of credit demand. Through assembling a novel dataset on banks’ investment in information technologies (IT), this paper provides…

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…

Exchange-traded funds (ETFs) are typically viewed as passive index trackers. In contrast, we show that corporate bond ETFs actively manage their portfolios, trading off index tracking against liquidity transformation. In our model, ETFs optimally…

Policy-relevant treatment effect estimation in a marketplace setting requires assessing both the direct treatment benefit and spillovers induced by changes to the market equilibrium. We show how to identify and estimate policy-relevant treatment…

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…

A common challenge in estimating the long-term impacts of treatments (e.g., job training programs) is that the outcomes of interest (e.g., lifetime earnings) are observed with a long delay. We address this problem by combining several short-term…

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…

We survey 262 chief executive officer (CEO) alumni of Harvard Business School and gather evidence on three aspects of each executive’s strategy practice: how formalized it is, how it is developed, and how it is implemented. We report three main…

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…

Sharing knowledge is a basic tenet of the scientific community, yet publication bias arising from the reluctance or inability to publish negative or null results remains a long-standing and deep-seated problem, albeit one that varies in severity…

Employees voice their concerns in the hope that leaders will change their behavior. But how do employees evaluate these changes? In the present research, we highlight the rate of behavior change as a key factor in determining leader…

We introduce markup equilibrium—an extension of Walrasian equilibrium in which consumers pay a fixed percentage markup over producer prices. In quasilinear markets, markup equilibria exist despite nonconvexities. They are resource-…

I survey the benefits of keeping players in the dark about payoff- or strategy-relevant variables in dynamic games. Topics include repeated games with private monitoring, stochastic games with incomplete information, and repeated/stochastic games…

Online marketplaces have adopted new quality control mechanisms that can accommodate a flexible pool of providers. In the context of ride-hailing, we measure the effectiveness of these mechanisms, which include ratings, incentives, and behavioral…

Background

Innovation readiness is crucial for transformative changes and enhanced performance in health care and depends on multiple factors including trust, training, and unit dynamics.

Purposes

We develop and validate…

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…