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- 2025
- Working Paper
Healthcare Provider Bankruptcies
By: Samuel Antill, Ashvin Gandhi, Jessica Bai and Adrienne Sabety
Healthcare firms are filing for Chapter 11 bankruptcy at record rates. We find that bankruptcies increase healthcare staff turnover, worsen care, and harm patients. Using a difference-in-differences design, we estimate that a bankruptcy filing immediately increases... View Details
- 2025
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
- 2024
- Working Paper
The Wade Test: Generative AI and CEO Communication
By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
Can generative artificial intelligence (Gen-AI) transform the role of the CEO? This study investigates
whether Gen-AI can mimic a human CEO and whether employees display aversion to Gen-AI
communication. We present a framework of Gen-AI aversion that distinguishes... View Details
- 2024
- Article
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
By: Michael Lingzhi Li and Kosuke Imai
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across... View Details
- 2025
- Working Paper
Evaluations Amid Measurement Error: Determining the Optimal Timing for Workplace Interventions
By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
Researchers have embraced factorial experiments to simultaneously evaluate multiple treatments, each with different levels. Typically, in large-scale factorial experiments, the primary objective is identifying the treatment with the largest causal effect, especially... View Details
- April 2024
- Article
Pay-As-You-Go Insurance: Experimental Evidence on Consumer Demand and Behavior
By: Raymond Kluender
Pay-as-you-go contracts reduce minimum purchase requirements which may increase market participation. We randomize the introduction and price(s) of a novel pay-as-you-go contract to the California auto insurance market where 17 percent of drivers are uninsured. The... View Details
- 2024
- Working Paper
The Effects of Medical Debt Relief: Evidence from Two Randomized Experiments
By: Raymond Kluender, Neale Mahoney, Francis Wong and Wesley Yin
Two in five Americans have medical debt, nearly half of whom owe at least $2,500. Concerned by this burden, governments and private donors have undertaken large, high-profile efforts to relieve medical debt. We partnered with RIP Medical Debt to conduct two randomized... View Details
- 2024
- Working Paper
Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference
By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
- 2024
- Working Paper
Design of Panel Experiments with Spatial and Temporal Interference
By: Tu Ni, Iavor Bojinov and Jinglong Zhao
One of the main practical challenges companies face when running experiments (or A/B tests) over a panel is interference, the setting where one experimental unit's treatment assignment at one time period impacts another's outcomes, possibly at the following time... View Details
Keywords: Research
- 2023
- Working Paper
Design-Based Inference for Multi-arm Bandits
By: Dae Woong Ham, Iavor I. Bojinov, Michael Lindon and Martin Tingley
Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire to use the available... View Details
- 2021
- Working Paper
Quantifying the Value of Iterative Experimentation
By: Iavor I Bojinov and Jialiang Mao
Over the past decade, most technology companies and a growing number of conventional firms have adopted online experimentation (or A/B testing) into their product development process. Initially, A/B testing was deployed as a static procedure in which an experiment was... View Details
- March 2024
- Article
Human Capital Affects Religious Identity: Causal Evidence from Kenya
By: Livia Alfonsi, Michal Bauer, Julie Chytilová and Edward Miguel
We study how human capital and economic conditions causally affect the choice of religious denomination. We utilize a longitudinal dataset monitoring the religious history of more than 5,000 Kenyans over 20 years, in tandem with a randomized experiment (deworming) that... View Details
- 2024
- Working Paper
Does Pension Automatic Enrollment Increase Debt? Evidence from a Large-Scale Natural Experiment
By: John Beshears, Matthew Blakstad, James J. Choi, Christopher Firth, John Gathergood, David Laibson, Richard Notley, Jesal D. Sheth, Will Sandbrook and Neil Stewart
Does automatic enrollment into retirement saving increase household debt? We study the randomized roll-out of automatic enrollment pensions to ~160,000 employers in the United Kingdom with 2-29 employees. We find that the additional savings generated through automatic... View Details
- January 2024
- Article
Helping Children Catch Up: Early Life Shocks and the PROGRESA Experiment
By: Achyuta Adhvaryu, Theresa Molina, Anant Nyshadham and Jorge Tamayo
Can investing in children who faced adverse events in early childhood help them catch up? We answer this question using two orthogonal sources of variation – resource availability at birth (local rainfall) and cash incentives for school enrollment – to identify the... View Details
- January 2024
- Article
Population Interference in Panel Experiments
By: Kevin Wu Han, Guillaume Basse and Iavor Bojinov
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit’s outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in... View Details
- 2023
- Working Paper
Money, Time, and Grant Design
By: Kyle Myers and Wei Yang Tham
The design of research grants has been hypothesized to be a useful tool for
influencing researchers and their science. We test this by conducting two thought
experiments in a nationally representative survey of academic researchers. First,
we offer participants a... View Details
- 2024
- Working Paper
The Uneven Impact of Generative AI on Entrepreneurial Performance
By: Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning
Scalable and low-cost AI assistance has the potential to improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it difficult to know whether recent AI advances can help business owners make... View Details
- September 2023
- Article
Addressing Vaccine Hesitancy: Experimental Evidence from Nine Countries during the COVID-19 Pandemic
By: Vincenzo Galasso, Vincent Pons, Paola Profeta, Martin McKee, David Stuckler, Michael Becher, Sylvain Brouard and Martial Foucault
We study the impact of public health messages on intentions to vaccinate and vaccination uptakes, especially among hesitant groups. We performed an experiment comparing the effects of egoistic and altruistic messages on COVID-19 vaccine intentions and behaviour. We... View Details
- 2023
- Working Paper
Much Ado About Nothing? Overreaction to Random Regulatory Audits
By: Samuel Antill and Joseph Kalmenovitz
Regulators often audit firms to detect non-compliance. Exploiting a natural experiment in the lobbying industry, we show that firms overreact to audits and this response distorts prices and reduces welfare. Each year, federal regulators audit a random sample of... View Details
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details