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- 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
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
- 2024
- Working Paper
The Wade Test: Generative AI and CEO Communication
By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
Can generative artificial intelligence (AI) transform the role of the CEO by effectively automating CEO
communication? This study investigates whether AI can mimic a human CEO and whether employees’
perception of the communication’s source matter. In a field... View Details
Choudhury, Prithwiraj, Bart S. Vanneste, and Amirhossein Zohrehvand. "The Wade Test: Generative AI and CEO Communication." Harvard Business School Working Paper, No. 25-008, August 2024.
- 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
Li, Michael Lingzhi, and Kosuke Imai. "Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules." Journal of Causal Inference 12, no. 1 (2024).
- 2024
- Working Paper
Winner Take All: Exploiting Asymmetry in Factorial Designs
By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
Researchers and practitioners have embraced factorial experiments to simultaneously test multiple treatments, each with different levels. With the rise of technologies like Generative AI, factorial experimentation has become even more accessible: it is easier than ever... View Details
Keywords: Factorial Designs; Fisher Randomizations; Rank Estimators; Employer Interventions; Causal Inference; Mathematical Methods; Performance Improvement
DosSantos DiSorbo, Matthew, Iavor I. Bojinov, and Fiammetta Menchetti. "Winner Take All: Exploiting Asymmetry in Factorial Designs." Harvard Business School Working Paper, No. 24-075, June 2024.
- 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
Kluender, Raymond. "Pay-As-You-Go Insurance: Experimental Evidence on Consumer Demand and Behavior." Review of Financial Studies 37, no. 4 (April 2024): 1118–1148.
- 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
Kluender, Raymond, Neale Mahoney, Francis Wong, and Wesley Yin. "The Effects of Medical Debt Relief: Evidence from Two Randomized Experiments." NBER Working Paper Series, No. 32315, April 2024.
- 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
Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
- 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
Ni, Tu, Iavor Bojinov, and Jinglong Zhao. "Design of Panel Experiments with Spatial and Temporal Interference." Harvard Business School Working Paper, No. 24-058, March 2024.
- 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
Ham, Dae Woong, Iavor I. Bojinov, Michael Lindon, and Martin Tingley. "Design-Based Inference for Multi-arm Bandits." Harvard Business School Working Paper, No. 24-056, March 2024.
- 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
Bojinov, Iavor I., and Jialiang Mao. "Quantifying the Value of Iterative Experimentation." Harvard Business School Working Paper, No. 24-059, March 2024.
- 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
Alfonsi, Livia, Michal Bauer, Julie Chytilová, and Edward Miguel. "Human Capital Affects Religious Identity: Causal Evidence from Kenya." Art. 103215. Journal of Development Economics 167 (March 2024).
- 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
Keywords: Retirement; Saving; Personal Finance; Borrowing and Debt; Credit; Compensation and Benefits
Beshears, John, Matthew Blakstad, James J. Choi, Christopher Firth, John Gathergood, David Laibson, Richard Notley, Jesal D. Sheth, Will Sandbrook, and Neil Stewart. "Does Pension Automatic Enrollment Increase Debt? Evidence from a Large-Scale Natural Experiment." Working Paper, October 2024.
- 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
Adhvaryu, Achyuta, Theresa Molina, Anant Nyshadham, and Jorge Tamayo. "Helping Children Catch Up: Early Life Shocks and the PROGRESA Experiment." Economic Journal 134, no. 657 (January 2024): 1–22.
- 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
Han, Kevin Wu, Guillaume Basse, and Iavor Bojinov. "Population Interference in Panel Experiments." Journal of Econometrics 238, no. 1 (January 2024).
- 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
Myers, Kyle, and Wei Yang Tham. "Money, Time, and Grant Design." Harvard Business School Working Paper, No. 24-037, December 2023.
- 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
Keywords: AI and Machine Learning; Performance Improvement; Small Business; Decision Choices and Conditions; Kenya
Otis, Nicholas G., Rowan Clarke, Solène Delecourt, David Holtz, and Rembrand Koning. "The Uneven Impact of Generative AI on Entrepreneurial Performance." Harvard Business School Working Paper, No. 24-042, December 2023.
- 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
Keywords: COVID-19; Vaccination; Vaccine Hesitancy; Information Campaigns; Health Pandemics; Behavior; Information
Galasso, Vincenzo, Vincent Pons, Paola Profeta, Martin McKee, David Stuckler, Michael Becher, Sylvain Brouard, and Martial Foucault. "Addressing Vaccine Hesitancy: Experimental Evidence from Nine Countries during the COVID-19 Pandemic." BMJ Global Health 8, no. 9 (September 2023).
- 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
Antill, Samuel, and Joseph Kalmenovitz. "Much Ado About Nothing? Overreaction to Random Regulatory Audits." Working Paper, August 2023.
- 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
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Management Science 69, no. 7 (July 2023): 3759–3777.
- July 2023
- Article
So, Who Likes You? Evidence from a Randomized Field Experiment
By: Ravi Bapna, Edward McFowland III, Probal Mojumder, Jui Ramaprasad and Akhmed Umyarov
With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by... View Details
Keywords: Online Dating; Internet and the Web; Analytics and Data Science; Gender; Emotions; Social and Collaborative Networks
Bapna, Ravi, Edward McFowland III, Probal Mojumder, Jui Ramaprasad, and Akhmed Umyarov. "So, Who Likes You? Evidence from a Randomized Field Experiment." Management Science 69, no. 7 (July 2023): 3939–3957.