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Disclosing a Random Walk
We examine a dynamic disclosure model in which the value of a firm follows a random walk. Every period, with some probability, the manager learns the firm’s value and decides whether to disclose it. The manager maximizes the market perception of…
Dynamic Trade Finance in the Presence of Information Frictions and FinTech
Problem Definition: The paper focuses on an innovative bank-intermediated trade finance contract, which we call dynamic trade finance DTF, under which banks dynamically adjust loan interest rates as an order passes…
Effects of a U.S. Supreme Court Ruling to Restrict Abortion Rights
Previous research focused on popular U.S. Supreme Court rulings expanding rights; however, less is known about rulings running against prevailing public opinion and restricting rights. We examine the impact of the Dobbs v. Jackson Women’s…
Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects
There are a number of available methods for selecting whom to prioritize for treatment, including ones based on treatment effect estimation, risk scoring, and handcrafted rules. We propose rank-weighted average treatment effect (RATE) metrics as…
Financing the Gig Economy
Unlike traditional firm production, gig economy workers provide their own physical capital. As a consequence, the low-income households for whom gig economy opportunities are most valuable often borrow to participate. In the context of ride share…
Fiscal Capacity: An Asset Pricing Perspective
This review revisits the literature on fiscal capacity using modern tools from asset pricing. We find that properly accounting for aggregate risk substantially reduces fiscal capacity. In this environment, the gap between the risk-free rate and…
General Manager and Head Coach Exits in the NBA and the NFL
Purpose
This article seeks to enhance the understanding as to why head coaches and general managers (GMs) in the National Basketball Association (NBA) and the National Football League (NFL) exit from their positions.
Design/…
Generative AI at Work
New AI tools have the potential to change the way workers perform and learn, but little is known about their impacts on the job. In this paper, we study the staggered introduction of a generative AI-based conversational assistant using data from…
Informing Entrepreneurs? Initial Public Offerings and New Business Formation
We examine the relationship between public firm disclosure and aggregate new business formation. Consistent with the notion that public company disclosures provide information spillovers that reduce the extent of uncertainty about new…
Low-Intensity Fires Mitigate the Risk of High-Intensity Wildfires in California’s Forests
The increasing frequency of severe wildfires demands a shift in landscape management to mitigate their consequences. The role of managed, low-intensity fire as a driver of beneficial fuel treatment in fire-adapted ecosystems has drawn interest in…
Monitor Reputation and Transparency
We study the disclosure policy of a regulator overseeing a monitor with reputation concerns. The monitor faces a manager, who chooses how much to manipulate based on the monitor’s reputation. Reputational incentives are strongest for intermediate…
Novelty in Content Creation: Experimental Results Using Image Recognition on a Large Social Network
Social networks utilize award recognition and front pages to motivate user content creation, facilitate consumer discovery of content, and provide attention and recognition to the best content. Past research shows that such attention and…
Preparing for Generative AI in the 2024 Election: Recommendations and Best Practices Based on Academic Research
The rapid development of generative AI technology is transforming the political landscape, presenting both challenges and opportunities for the 2024 US election. This document provides a research-based overview of the potential impact of…
Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization
In many applications, e.g. in healthcare and e-commerce, the goal of a contextual bandit may be to learn an optimal treatment assignment policy at the end of the experiment. That is, to minimize simple regret. However, this objective remains…
Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization
In many applications, e.g. in healthcare and e-commerce, the goal of a contextual bandit may be to learn an optimal treatment assignment policy at the end of the experiment. That is, to minimize simple regret. However, this objective remains…
Revealed versus Potential Spatial Accessibility of Healthcare and Changing Patterns during the COVID-19 Pandemic
Spatial access to healthcare facilities (i.e., how long people need to travel to reach care) is important for understanding public health, but hard to measure. Most research so far has focused on theoretical (potential) travel times. Using…
Ripple Effects of Hospital Team Faultlines on Patient Outcomes
Medical errors are rampant across healthcare settings, imposing a significant burden on patient safety. Here, we examined the ripple effects of diversity splits, or faultlines, within hospital teams on patient safety and care. Hospitals consist…
The Design of Macroprudential Stress Tests
We study the design of stress tests that provide information about aggregate and idiosyncratic risk in banks’ portfolios and impose contingent capital requirements. In the optimal static test, an adverse scenario fails all weak and some strong…
The Rest of the World’s Dollar-Weighted Return on U.S. Treasurys
Since 1980, foreign investors have timed their purchases and sales of U.S. Treasurys to yield particularly low returns. Their annual “dollar-weighted” returns, measured by the internal rate of return on their purchases and sales of Treasury bonds…
Trends in State and Local Pension Funds
Unfunded public pension obligations represent the largest liability for state and local governments in the United States. As of fiscal year 2021, the total reported unfunded liabilities of these plans are $1.076 trillion. In contrast, the market…