Publications

We examine the spillover effect of public firm innovation disclosures on the patent trading market. Relative to equity markets, the patent market is decentralized and rife with information frictions, yet it serves as an important mechanism…

In August 2021, up to 30% of Americans were uncertain about taking the COVID-19 vaccine, including some healthcare personnel (HCP). Our objective was to identify barriers and facilitators of the Veterans Health Administration (VHA) HCP…

As the world’s overall population skews older, the workforce is aging as well, with more older adults working well beyond what used to be considered the typical retirement age. Older adults are the fastest-growing segment of the American…

Current pain management recommendations emphasize leveraging interdisciplinary teams. We aimed to identify key features of interdisciplinary team structures and processes associated with improved pain outcomes for patients experiencing chronic…

Background: For low- and middle-income countries, the forecasted incremental value to society created by a class of new prescription drugs would be a useful criterion to prioritize the licensing, subsidization, and provision of…

Introduction: This research examined the perspective of the Huntington’s Disease (HD) community regarding the use of predictive biomarkers as endpoints for regulatory approval of therapeutics to prevent or delay the onset of…

Extraverts are often characterized as highly social individuals who are highly invested in their interpersonal interactions. We propose that extraverts’ interaction partners hold a different view—that extraverts are highly social, but not highly…

Adding domain knowledge to a learning system is known to improve results. In multiparameter Bayesian frameworks, such knowledge is incorporated as a prior. On the other hand, the various model parameters can have different learning rates in real-…

Do women and men differ in their brokering behavior? Integrating the literatures on gender, self-construal, and social networks, we theorize that gender differences in relational interdependence produce different patterns of helpful brokering…

In an empirical Bayes analysis, we use data from repeated sampling to imitate inferences made by an oracle Bayesian with extensive knowledge of the data-generating distribution. Existing results provide a comprehensive characterization of when…

Recent growing adoption of experimentation in practice has led to a surge of attention to multiarmed bandits as a technique to reduce the opportunity cost of online experiments. In this setting, a decision-maker sequentially chooses among a set…

In an increasing number of domains, people interact with automated agents (such as algorithms, robots, and computers) instead of humans. Across five studies, we explore the role of authenticity in shaping people’s reactions to automated…

We study how investment fees vary within private-capital funds. Net-of-fee return clustering suggests that most funds have two tiers of fees, and we decompose differences across tiers into both management and performance-based fees. Managers of…

We examine the relation between corporate cash holdings and tax net operating loss carryforwards (NOLs). The literature demonstrates that firms should distribute cash to shareholders rather than retain it and generate passive investment income…

With rising access to electronic health record data, application of artificial intelligence to create clinical risk prediction models has grown. A key component in designing these models is feature generation. Methods used to generate features…

A growing body of research in economics focuses on whether cultural differences in social norms affect economic outcomes. Here we examine how differences in the strength of social norms — or tightness-looseness (TL) — across countries can explain…

We study a Bayesian k-armed bandit problem in many-armed regime, when k ≥ √ T, with T the time horizon. We first show that subsampling is critical for designing optimal policies. Specifically, the standard UCB…

We propose and describe a corporate carbon reporting framework intended to strengthen the credibility and transparency of the existing net-zero pledges. We refer to this framework as the Time-Consistent Corporate Carbon Reporting (TCCR…