Publications

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…

In spring 2025, the Corporate Governance Research Initiative at Stanford Graduate School of Business, Arthur and Toni Rembe Rock Center for Corporate Governance, Governance of Organizations Working Group at the Hoover Institution at Stanford…

In spring 2025, the Corporate Governance Research Initiative at Stanford Graduate School of Business, Arthur and Toni Rembe Rock Center for Corporate Governance, Governance of Organizations Working Group at the Hoover Institution at Stanford…

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…

We examine the economic implications of digital traffic on firms’ financial performance, stock valuation, and financial surprises. Our analysis shows that timely flows of digital traffic are contemporaneous and leading indicators of firms’…

Econometric analysis typically focuses on the statistical properties of fixed estimators and ignores researcher choices. In this article, I instead approach the analysis of experimental data as a mechanism‐design problem that acknowledges that…

Traffic stops are common and consequential for citizens’ legal socialization and for racial gaps in police-community trust. Efforts to change the tenor of police interactions, however, may discount the discretionary context of stops —…

Economic activity requires motivating and coordinating individuals to work toward a common goal. These aims are the purview of managers. What, however, do managers actually do? We outline three defining principles of economic research on managers…

We investigate whether the membership of a non-profit hospital’s CEO on its board of directors is associated with CEO pay and several measures of hospital performance, including price, operating margin, quality, and service to low-income patients…

Rendering the visual appearance of moving humans from occluded monocular videos is a challenging task. Most existing research renders 3D humans under ideal conditions, requiring a clear and unobstructed scene. Those previous methods cannot be…

Local-thinking bias, wherein agents overweight information that comes readily to mind, is a prominent finding in cognitive psychology. In this study, we investigate local-thinking bias in the context of sell-side analysts and measure each analyst…