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- 2023
- Working Paper
Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection
By: Edward McFowland III, Sriram Somanchi and Daniel B. Neill
In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention’s effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides... View Details
Keywords: Causal Inference; Program Evaluation; Algorithms; Distributional Average Treatment Effect; Treatment Effect Subset Scan; Heterogeneous Treatment Effects
McFowland III, Edward, Sriram Somanchi, and Daniel B. Neill. "Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection." Working Paper, 2023.
- 2025
- Working Paper
Enhancing Treatment Effect Prediction on Privacy-Protected Data: An Honest Post-Processing Approach
By: Ta-Wei Huang and Eva Ascarza
As firms increasingly rely on customer data for personalization, concerns over privacy and regulatory compliance have grown. Local Differential Privacy (LDP) offers strong individual-level protection by injecting noise into data before collection. While... View Details
Keywords: Targeted Intervention; Conditional Average Treatment Effect Estimation; Differential Privacy; Honest Estimation; Post-processing; Analytics and Data Science; Consumer Behavior; Marketing
Huang, Ta-Wei, and Eva Ascarza. "Enhancing Treatment Effect Prediction on Privacy-Protected Data: An Honest Post-Processing Approach." Harvard Business School Working Paper, No. 24-034, December 2023. (Revised March 2025.)
- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
- 2023
- Article
Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
- Article
Treatment Of Opioid Use Disorder Among Commercially Insured U.S. Adults, 2008–17
By: Karen Shen, Eric Barrette and Leemore S. Dafny
There is abundant literature on efforts to reduce opioid prescriptions and misuse, but comparatively little on the treatment provided to people with opioid use disorder (OUD). Using claims data representing 12–15 million nonelderly adults covered through commercial... View Details
Keywords: Opioid Treatment; Medication-assisted Treatment; Substance Use Disorder; Private Insurance; Health Disorders; Health Care and Treatment; Insurance; United States
Shen, Karen, Eric Barrette, and Leemore S. Dafny. "Treatment Of Opioid Use Disorder Among Commercially Insured U.S. Adults, 2008–17." Health Affairs 39, no. 6 (June 2020): 993–1001.
- 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.
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to... View Details
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- July 2021
- Article
The Effect of Price on Firm Reputation
By: Michael Luca and Oren Reshef
While a business's reputation can affect its pricing, prices can also affect its reputation. To explore the effect of prices on reputation, we investigate daily data on menu prices and online ratings from a large rating and ordering platform. We find that a price... View Details
Keywords: Pricing; Reputation Systems; IT Policy And Management; Economics Of Digital Platforms; Business Ventures; Reputation; Price; Consumer Behavior; Analysis
Luca, Michael, and Oren Reshef. "The Effect of Price on Firm Reputation." Management Science 67, no. 7 (July 2021): 4408–4419.
- September–October 2013
- Article
The Dynamic Advertising Effect of Collegiate Athletics
By: Doug J. Chung
I measure the spillover effect of intercollegiate athletics on the quantity and quality of applicants to institutions of higher education in the United States, popularly known as the "Flutie Effect." I treat athletic success as a stock of goodwill that decays over... View Details
Keywords: Choice Modeling; Entertainment Marketing; Heterogeneity; Panel Data; Structural Modeling; Rights; Analytics and Data Science; Higher Education; Ethics; Consumer Behavior; Advertising; Sports; Advertising Industry; Education Industry
Chung, Doug J. "The Dynamic Advertising Effect of Collegiate Athletics." Marketing Science 32, no. 5 (September–October 2013): 679–698. (Lead article. Featured in HBS Working Knowledge.)
- February 2018
- Article
Retention Futility: Targeting High-Risk Customers Might Be Ineffective.
By: Eva Ascarza
Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models... View Details
Keywords: Retention/churn; Proactive Churn Management; Field Experiments; Heterogeneous Treatment Effect; Machine Learning; Customer Relationship Management; Risk Management
Ascarza, Eva. "Retention Futility: Targeting High-Risk Customers Might Be Ineffective." Journal of Marketing Research (JMR) 55, no. 1 (February 2018): 80–98.
- Article
Performance Effects of Setting a High Reference Point for Peer‐Performance Comparison
By: Henry Eyring and V.G. Narayanan
We conduct a field experiment, based on a registered report accepted by the Journal of Accounting Research, to test performance effects of setting a high reference point for peer‐performance comparison. Relative to providing the median as a reference point for... View Details
Keywords: Relative Performance Evaluation; Reference Points; Social Comparison; Field Experiment; Performance; Performance Evaluation; Education
Eyring, Henry, and V.G. Narayanan. "Performance Effects of Setting a High Reference Point for Peer‐Performance Comparison." Journal of Accounting Research 56, no. 2 (May 2018): 581–615.
- 2017
- Working Paper
Salience through Information Technology: The Effect of Balance Availability on the Smoothing of SNAP Benefits
By: Andrew Hillis
Recipients of the Supplemental Nutrition Assistance Program (SNAP) run out of most benefits before halfway through a benefit deposit cycle. I study the introduction of a mobile software application, Fresh EBT, that enables beneficiaries to check their available balance... View Details
Hillis, Andrew. "Salience through Information Technology: The Effect of Balance Availability on the Smoothing of SNAP Benefits." Harvard Business School Working Paper, No. 18-038, October 2017.
- November 2021
- Article
Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective
By: Iavor Bojinov, Ashesh Rambachan and Neil Shephard
In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative... View Details
Keywords: Panel Data; Dynamic Causal Effects; Potential Outcomes; Finite Population; Nonparametric; Mathematical Methods
Bojinov, Iavor, Ashesh Rambachan, and Neil Shephard. "Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective." Quantitative Economics 12, no. 4 (November 2021): 1171–1196.
- 2010
- Working Paper
Evaluating the Effects of Large-Scale Health Interventions in Developing Countries: The Zambian Malaria Initiative
By: Nava Ashraf, Gunther Fink and David N. Weil
Since 2003, Zambia has been engaged in a large-scale, centrally coordinated national anti-malaria campaign which has become a model in sub-Saharan Africa. This paper aims at quantifying the individual and macro level benefits of this campaign, which involved mass... View Details
Keywords: Cost vs Benefits; Developing Countries and Economies; Health Care and Treatment; Health Disorders; Performance Evaluation; Programs; Health Industry; Zambia
Ashraf, Nava, Gunther Fink, and David N. Weil. "Evaluating the Effects of Large-Scale Health Interventions in Developing Countries: The Zambian Malaria Initiative." NBER Working Paper Series, No. 16069, June 2010.
- 2016
- Chapter
Evaluating the Effects of Large Scale Health Interventions in Developing Countries: The Zambian Malaria Initiative
By: Nava Ashraf, Gunther Fink and David N. Weil
Since 2003, Zambia has been engaged in a large-scale, centrally coordinated national anti-Malaria campaign, which has become a model in sub-Saharan Africa. This paper aims at quantifying the individual and macro-level benefits of this campaign, which involved mass... View Details
Ashraf, Nava, Gunther Fink, and David N. Weil. "Evaluating the Effects of Large Scale Health Interventions in Developing Countries: The Zambian Malaria Initiative." Chap. 1 in African Successes, Volume 2: Human Capital, edited by Sebastian Edwards, Simon Johnson, and David N. Weil. University of Chicago Press, 2016.
- 2023
- Working Paper
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine... View Details
Keywords: Large Language Model; AI and Machine Learning; Performance Efficiency; Performance Improvement
Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details
Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.
- Article
A Feasibility Study Using Time-driven Activity-based Costing as a Management Tool for Provider Cost Estimation: Lessons from the National TB Control Program in Zimbabwe in 2018
By: J. Chirenda, B. Nhlema Simwaka, C. Sandy, K. Bodnar, S. Corbin, P. Desai, T. Mapako, S. Shamu, C. Timire, E. Antonio, A. Makone, A. Birikorang, T. Mapuranga, M. Ngwenya, T. Masunda, M. Dube, E. Wandwalo, L. Morrison and R. S. Kaplan
Background: This study used process maps and time-driven activity-based costing to document TB service delivery processes. The analysis identified the resources required to sustain TB services in Zimbabwe, as well as several opportunities for more effective and... View Details
Keywords: Time-Driven Activity-Based Costing; Provider Cost; Health Care and Treatment; Cost Management; Activity Based Costing and Management; Zimbabwe
Chirenda, J., B. Nhlema Simwaka, C. Sandy, K. Bodnar, S. Corbin, P. Desai, T. Mapako, S. Shamu, C. Timire, E. Antonio, A. Makone, A. Birikorang, T. Mapuranga, M. Ngwenya, T. Masunda, M. Dube, E. Wandwalo, L. Morrison, and R. S. Kaplan. "A Feasibility Study Using Time-driven Activity-based Costing as a Management Tool for Provider Cost Estimation: Lessons from the National TB Control Program in Zimbabwe in 2018." BMC Health Services Research 21, no. 242 (2021).
- 2022
- Working Paper
A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure
By: Jesse M. Shapiro and Liyang Sun
Linear panel models featuring unit and time fixed effects appear in many areas of empirical economics. An active literature studies the interpretation of the ordinary least squares estimator of the model, commonly called the two-way fixed effects (TWFE) estimator, in... View Details
Shapiro, Jesse M., and Liyang Sun. "A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure." NBER Working Paper Series, No. 29976, April 2022.
- August 2020
- Article
Workplace Knowledge Flows
By: Jason Sandvik, Richard Saouma, Nathan Seegert and Christopher Stanton
We conducted a field experiment in a sales firm to test whether improving knowledge flows between coworkers affects productivity. Our design allows us to compare different management practices and to isolate whether frictions to knowledge transmission primarily reside... View Details
Keywords: Knowledge Sharing; Interpersonal Communication; Employees; Performance Productivity; Sales; Motivation and Incentives
Sandvik, Jason, Richard Saouma, Nathan Seegert, and Christopher Stanton. "Workplace Knowledge Flows." Quarterly Journal of Economics 135, no. 3 (August 2020): 1635–1680.