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CAREER: A Foundation Model for Labor Sequence Data
Labor economists regularly analyze employment data by fitting predictive models to small, carefully constructed longitudinal survey datasets.…
Digital Interventions and Habit Formation in Educational Technology
We evaluate a contest-based intervention intended to increase the usage of an educational app that helps children in India learn to read English.…
Impact Matters for Giving at Checkout
We conducted two experiments on PayPal’s Give at Checkout feature to learn about the effect of 1) information about charity outcomes on donations…
Optimal Experimental Design for Staggered Rollouts
In this paper, we study the design and analysis of experiments conducted on a set of units over multiple time periods where the starting time of…
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-…
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…
What Kinds of Incentives Encourage Participation in Democracy? Evidence from a Massive Online Governance Experiment
How can we democratically govern the AI, social media, and online platforms of the future? Today, low participation is a major barrier to…
Can Personalized Digital Counseling Improve Consumer Search for Modern Contraceptive Methods?
This paper analyzes a randomized controlled trial of a personalized digital counseling intervention addressing informational constraints and…
Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal
In many settings, interventions may be more effective for some individuals than others, so that targeting interventions may be beneficial. We…
Policy Learning with Adaptively Collected Data
In a wide variety of applications, including healthcare, bidding in first price auctions, digital recommendations, and online education, it can be…
Federated Causal Inference in Heterogeneous Observational Data
We are interested in estimating the effect of a treatment applied to individuals at multiple sites, where data is stored locally for each site.…
Machine-Learning-Based High-Benefit Approach versus Conventional High-Risk Approach in Blood Pressure Management
In medicine, clinicians treat individuals under an implicit assumption that high-risk patients would benefit most from the treatment (‘high-risk…
The Heterogeneous Earnings Impact of Job Loss Across Workers, Establishments, and Markets
Using generalized random forests and rich Swedish administrative data, we show that the earnings effects of job displacement due to establishment…
Market Re-Design of Framework Agreements in Chile Reduces Government Procurement Spending
Framework agreements (FAs) are procurement mechanisms used in private and public organizations by which a central procurement agency selects an…
On Frequentist Regret of Linear Thompson Sampling
This paper studies the stochastic linear bandit problem, where a decision-maker chooses actions from possibly time-dependent sets of vectors in ℝd…
The Evolving Battlefronts of Shareholder Activism
In this Closer Look, we consider current trends in shareholder activism and their potential impact. We examine the introduction of universal…
The Design of Optimal Pay-as-Bid Procurement Mechanisms
Problem definition: We consider the mechanism design problem of finding an optimal pay-as-bid mechanism in which the platform chooses an…
Analytics Saves Lives During the COVID-19 Crisis in Chile
Franz Edelman Award 2022, Winning Project
During the COVID-19 crisis, the Chilean Ministry of Health and the Ministry of Sciences…
Battling the Coronavirus Infodemic Among Social Media Users in Africa
During a global pandemic, how can we best prompt social media users to demonstrate discernment in sharing information online? We ran a contextual…
Digital Public Health Interventions at Scale: The Impact of Social Media Advertising on Beliefs and Outcomes Related to COVID Vaccines
Public health organizations increasingly use social media advertising campaigns in pursuit of public health goals. In this paper, we evaluate the…
Expanding Capacity for Vaccines against COVID-19 and Future Pandemics: A Review of Economic Issues
We review economic arguments for using public policy to accelerate vaccine supply during a pandemic. Rapidly vaccinating a large share of the…
Effective and Scalable Programs to Facilitate Labor Market Transitions for Women in Technology
We describe the design, implementation, and evaluation of a low-cost and scalable program that supports women in Poland in transitioning into jobs…
2022 Survey of Investors, Retirement Savings, and ESG
In summer 2022, Stanford Graduate School of Business, the Hoover Institution Working Group on Corporate Governance at Stanford University, and…
Emotion- Versus Reasoning-Based Drivers of Misinformation Sharing: A Field Experiment Using Text Message Courses in Kenya
Two leading hypotheses for why individuals unintentionally share misinformation are that 1) they are unable to recognize that a post contains…