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Publications

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      • Faculty Publications  (248)

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      • October 2023
      • Article

      What Does the Inflation Reduction Act Mean for Patients and Physicians?

      By: Amitabh Chandra and Benedic Ippolito
      The debate around prescription drug measures in the recently passed U.S. Inflation Reduction Act (IRA), which limit some patients’ out-of-pocket costs, has not fully addressed their effect on physicians and patients via their effect on payers. Reducing patients’ costs... View Details
      Keywords: Government Legislation; Price; Health Care and Treatment
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      Chandra, Amitabh, and Benedic Ippolito. "What Does the Inflation Reduction Act Mean for Patients and Physicians?" NEJM Catalyst Innovations in Care Delivery 4, no. 10 (October 2023).
      • 2023
      • Working Paper

      The Effects of Inconsistent Work Schedules on Employee Lateness and Absenteeism

      By: Caleb Kwon and Ananth Raman
      Problem Definition: Employee lateness and absenteeism pose challenges for businesses, particularly in the retail industry, where punctuality is vital for optimal store operations and customer service. This paper relates employee lateness and absenteeism with... View Details
      Keywords: Behavior; Employees; Human Capital; Retail Industry
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      Kwon, Caleb, and Ananth Raman. "The Effects of Inconsistent Work Schedules on Employee Lateness and Absenteeism." Working Paper, August 2023.
      • July 2023
      • Article

      Before or After? The Effects of Payment Decision Timing in Pay-What-You-Want Contexts

      By: Raghabendra P. KC, Vincent Mak and Elie Ofek
      We study how payment decision timing—before versus after product delivery—influences consumer payment under pay-what-you-want pricing. We focus on situations where there is minimal change in consumer uncertainty regarding the product before versus after receiving it.... View Details
      Keywords: Price; Behavior; Valuation; Philanthropy and Charitable Giving
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      KC, Raghabendra P., Vincent Mak, and Elie Ofek. "Before or After? The Effects of Payment Decision Timing in Pay-What-You-Want Contexts." Journal of Marketing 87, no. 4 (July 2023): 618–635.
      • 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
      Keywords: Switchback Experiments; Design; Analysis; Mathematical Methods
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      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
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      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.
      • June 2023
      • Simulation

      Artea Dashboard and Targeting Policy Evaluation

      By: Ayelet Israeli and Eva Ascarza
      Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details
      Keywords: Algorithm Bias; Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
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      Israeli, Ayelet, and Eva Ascarza. "Artea Dashboard and Targeting Policy Evaluation." Harvard Business School Simulation 523-707, June 2023.
      • June 2023
      • Article

      Do Job Seekers Value Diversity Information? Evidence from a Field Experiment and Human Capital Disclosures

      By: Jung Ho Choi, Joseph Pacelli, Kristina M. Rennekamp and Sorabh Tomar
      We examine how information about the diversity of a potential employer's workforce affects individuals’ job-seeking behavior. We embed a field experiment in job recommendation emails from a leading career advice agency in the U.S. The experimental treatment involves... View Details
      Keywords: Diversity; Job Search; Employees; Corporate Disclosure
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      Choi, Jung Ho, Joseph Pacelli, Kristina M. Rennekamp, and Sorabh Tomar. "Do Job Seekers Value Diversity Information? Evidence from a Field Experiment and Human Capital Disclosures." Journal of Accounting Research 61, no. 3 (June 2023): 695–735.
      • 2023
      • Article

      Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators

      By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
      Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
      Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning
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      Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
      • May 2023 (Revised June 2023)
      • Case

      Novartis (A): Reimagining Medicine

      By: Ramon Casadesus-Masanell, Claudio Feser, Karolin Frankenberger and David Redaschi
      This case unfolds around the first-ever approved personalized cancer treatment, how Novartis wrapped it into a new business model design, and how Novartis scaled it. Novartis — one of the largest pharmaceutical companies in the world — is, among other ventures,... View Details
      Keywords: Health Care and Treatment; Business Model; Leadership; Pharmaceutical Industry; Switzerland
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      Casadesus-Masanell, Ramon, Claudio Feser, Karolin Frankenberger, and David Redaschi. "Novartis (A): Reimagining Medicine." Harvard Business School Case 723-443, May 2023. (Revised June 2023.)
      • May 2023 (Revised June 2023)
      • Supplement

      Novartis (B): Reimagining Medicine

      By: Ramon Casadesus-Masanell, Claudio Feser, Karolin Frankenberger and David Redaschi
      This case unfolds around the first-ever approved personalized cancer treatment, how Novartis wrapped it into a new business model design, and how Novartis scaled it. Novartis — one of the largest pharmaceutical companies in the world — is, among other ventures,... View Details
      Keywords: Health Care and Treatment; Business Model; Production; Business Strategy; Pharmaceutical Industry
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      Casadesus-Masanell, Ramon, Claudio Feser, Karolin Frankenberger, and David Redaschi. "Novartis (B): Reimagining Medicine." Harvard Business School Supplement 723-444, May 2023. (Revised June 2023.)
      • May 2023 (Revised June 2023)
      • Supplement

      Novartis (C): Reimagining Medicine

      By: Ramon Casadesus-Masanell, Claudio Feser, Karolin Frankenberger and David Redaschi
      This case unfolds around the first-ever approved personalized cancer treatment, how Novartis wrapped it into a new business model design, and how Novartis scaled it. Novartis — one of the largest pharmaceutical companies in the world — is, among other ventures,... View Details
      Keywords: Health Testing and Trials; Health Care and Treatment; Business Model; Problems and Challenges; Pharmaceutical Industry; Switzerland
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      Casadesus-Masanell, Ramon, Claudio Feser, Karolin Frankenberger, and David Redaschi. "Novartis (C): Reimagining Medicine." Harvard Business School Supplement 723-445, May 2023. (Revised June 2023.)
      • March–April 2023
      • Article

      Pricing for Heterogeneous Products: Analytics for Ticket Reselling

      By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
      Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
      Keywords: Price; Demand and Consumers; AI and Machine Learning; Investment Return; Entertainment and Recreation Industry; Sports Industry
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      Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
      • 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
      Keywords: AI and Machine Learning; Mathematical Methods
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      Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.
      • February 2023
      • Article

      OTC Intermediaries

      By: Andrea L. Eisfeldt, Bernard Herskovic, Sriram Rajan and Emil Siriwardane
      We study the effect of dealer exit on prices and quantities in a model of an over-the-counter (OTC) market featuring a core-periphery network with bilateral trading costs. The model is calibrated using regulatory data on the entire U.S. credit default swap (CDS) market... View Details
      Keywords: OTC Markets; Intermediaries; Dealers; Credit Default Swaps; Risk Sharing; Financial Markets; Networks; Price; Risk and Uncertainty
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      Eisfeldt, Andrea L., Bernard Herskovic, Sriram Rajan, and Emil Siriwardane. "OTC Intermediaries." Review of Financial Studies 36, no. 2 (February 2023): 615–677.
      • 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
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      Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
      • September 2022
      • Technical Note

      Addressing Social Determinants of Health in the American Landscape

      By: Susanna Gallani and Jacob Riegler
      Social determinants of health (SDOH) have gained significant attention in recent years. A growing body of research shows that a person’s health is influenced by a large number of non-genetic factors, most of which operate outside the realm of health care and are... View Details
      Keywords: Socioeconomic Determinants Of Health; Social Determinants Of Health; Population Health; Health; Health Care and Treatment; Social Issues; Health Industry; Insurance Industry; Medical Devices and Supplies Industry; United States
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      Gallani, Susanna, and Jacob Riegler. "Addressing Social Determinants of Health in the American Landscape." Harvard Business School Technical Note 123-023, September 2022.
      • September 2022
      • Article

      Giving a Buck or Making a Buck? Donations by Pharmaceutical Manufacturers to Independent Patient Assistance Charities

      By: Leemore Dafny, Christopher Ody and Teresa Rokos
      The federal Anti-Kickback Statute prohibits biopharmaceutical manufacturers from directly covering Medicare enrollees’ out-of-pocket spending for the drugs they manufacture, but manufacturers may donate to independent patient assistance charities and earmark donations... View Details
      Keywords: Cost Sharing; Prescription Drugs; Drug Spending; Medicare; Dual Eligibility; Cost; Health Care and Treatment; Philanthropy and Charitable Giving; Pharmaceutical Industry
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      Dafny, Leemore, Christopher Ody, and Teresa Rokos. "Giving a Buck or Making a Buck? Donations by Pharmaceutical Manufacturers to Independent Patient Assistance Charities." Health Affairs 41, no. 9 (September 2022).
      • September 2022
      • Article

      The Impact of Financial Assistance Programs on Health Care Utilization: Evidence from Kaiser Permanente

      By: Alyce S. Adams, Raymond Kluender, Neale Mahoney, Jinglin Wang, Francis Wong and Wesley Yin
      Most hospitals have financial assistance programs for low-income patients. We use administrative data from Kaiser Permanente to study the effects of financial assistance on health care utilization. Using a regression discontinuity design based on an income threshold... View Details
      Keywords: Healthcare; Utilization; Financial Assistance; Health Care and Treatment; Social Issues; Poverty; Health Industry
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      Adams, Alyce S., Raymond Kluender, Neale Mahoney, Jinglin Wang, Francis Wong, and Wesley Yin. "The Impact of Financial Assistance Programs on Health Care Utilization: Evidence from Kaiser Permanente." American Economic Review: Insights 4, no. 3 (September 2022): 389–407.
      • 2022
      • Working Paper

      Banking on Transparency for the Poor: Experimental Evidence from India

      By: Erica M. Field, Natalia Rigol, Charity M. Troyer Moore, Rohini Pande and Simone G. Schaner
      Do information frictions limit the benefits of financial inclusion drives for the rural poor? We evaluate an experimental intervention among recently banked poor Indian women receiving government cash transfers via direct deposit. Treated women were provided automated... View Details
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      Field, Erica M., Natalia Rigol, Charity M. Troyer Moore, Rohini Pande, and Simone G. Schaner. "Banking on Transparency for the Poor: Experimental Evidence from India." NBER Working Paper Series, No. 30289, July 2022.
      • July 2022
      • Article

      The Passionate Pygmalion Effect: Passionate Employees Attain Better Outcomes in Part Because of More Preferential Treatment by Others

      By: Ke Wang, Erica R. Bailey and Jon M. Jachimowicz
      Employees are increasingly exhorted to “pursue their passion” at work. Inherent in this call is the belief that passion will produce higher performance because it promotes intrapersonal processes that propel employees forward. Here, we suggest that the pervasiveness of... View Details
      Keywords: Passion; Self-fufilling Prophecy; Lay Beliefs; Interpersonal Processes; Employees; Performance; Attitudes; Organizational Culture; Social Psychology
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      Wang, Ke, Erica R. Bailey, and Jon M. Jachimowicz. "The Passionate Pygmalion Effect: Passionate Employees Attain Better Outcomes in Part Because of More Preferential Treatment by Others." Journal of Experimental Social Psychology 101 (July 2022).
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