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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
- 2025
- Working Paper
Why Most Resist AI Companions
By: Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp and Stefano Puntoni
AI companion applications—designed to serve as synthetic interaction partners—have recently
become capable enough to reduce loneliness, a growing public health concern. However,
behavioral research has yet to fully explain the barriers to adoption of such AI and... 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
- Working Paper
The Returns to Skills During the Pandemic: Experimental Evidence from Uganda
By: Livia Alfonsi, Vittorio Bassi, Imran Rasul and Elena Spadini
The Covid-19 pandemic represents one of the most significant labor market shocks to the world economy in recent times. We present evidence from a field experiment to understand whether and why skilled and unskilled workers were differentially impacted by the shock, in... View Details
- July, 2024
- Article
Consumer Protection in an Online World: An Analysis of Occupational Licensing
By: Chiara Farronato, Andrey Fradkin, Bradley Larsen and Erik Brynjolfsson
We study the demand and supply implications of occupational licensing using transaction-level data from a large online platform for home improvement services. We find that demand is more responsive to a professional's reviews than to the professional's... View Details
- July 2024
- Article
Whether to Apply
By: Katherine B. Coffman, Manuela Collis and Leena Kulkarni
Labor market outcomes depend, in part, upon an individual’s willingness to put herself forward for different opportunities. We use a series of experiments to explore gender differences in willingness to apply for higher return, more challenging work. We find that, in... 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
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... 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
- 2025
- Working Paper
Choosing and Using Information in Evaluation Decisions
By: Katherine Baldiga Coffman, Scott Kostyshak and Perihan O. Saygin
We use a controlled experiment to study how information acquisition impacts candidate evaluations. We provide evaluators with group-level information on performance and the opportunity to acquire additional, individual-level performance information before making a... 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
- 2024
- Working Paper
Platform Information Provision and Consumer Search: A Field Experiment
By: Lu Fang, Yanyou Chen, Chiara Farronato, Zhe Yuan and Yitong Wang
Despite substantial efforts to help consumers search in more intuitive ways, text search remains the predominant tool for product discovery online. In this paper, we explore the effects of visual and textual cues for search refinement on consumer search and purchasing... View Details