Publications

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

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

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

April–June 2022
Other Article

Commentary on 'Causal Decision Making and Causal Eﬀect Estimation Are Not the Same... and Why It Matters'

By: Edward McFowland III

There has been a substantial discussion in various methodological and applied literatures around causal inference; especially in the use of machine learning and statistical models to understand heterogeneity in treatment effects and to make optimal decision... View Details

Keywords: Causal Inference; Treatment Effect Estimation; Treatment Assignment Policy; Human-in-the-loop; Decision Making; Fairness

March 2014 (Revised September 2014)
Supplement

Cancer Treatment Centers of America® (B)

By: Regina E. Herzlinger and Natalie Kindred

This case, a follow-up to Cancer Treatment Centers of America (A), HBS No. 313-012, begins with the debate over New Hampshire's certificate-of-need (CON) law, which restricts hospital expansion. This debate ignited significant public criticism of Cancer Treatment... View Details

Keywords: Cancer; Cancer Treatment; Accountability; Outcomes; Outcomes Reporting; Outcomes Measurement; Survival; For-profit Hospitals; Health Care; Healthcare; Hospital; Certificate Of Need; Health Care and Treatment; Outcome or Result; Corporate Accountability; Policy; Health Industry; United States

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... View Details

August 2012 (Revised August 2014)
Case

Cancer Treatment Centers of America® (A)

By: Regina E. Herzlinger and Natalie Kindred

Cancer Treatment Centers of America (CTCA), a U.S. network of four privately owned oncology focused factory hospitals, was weighing options for growth. CTCA was entirely cancer focused and specialized in treating patients with complex and advanced-stage cancers, who... View Details

Educators

October 2013
Case

FasterCures: Removing Barriers to Treatments

By: Richard G. Hamermesh and James Weber

In mid-2013, as FasterCures celebrated its 10th anniversary as a center of the Milken Institute, Executive Director Margaret Anderson thought about what the organization should do to ensure it had even more impact in its next 10 years. FasterCures was a non-profit... View Details

Educators

December 2021
Article

Trade Policy Uncertainty and Stock Returns

By: Marcelo Bianconi, Federico Esposito and Marco Sammon

A recent literature has documented large real effects of trade policy uncertainty (TPU) on trade, employment, and investment, but there is little evidence that investors are compensated for bearing such risk. To quantify the risk premium associated with TPU, we exploit... View Details

Keywords: Trade Policy; Uncertainty; Stock Returns; Risk Premium; Tariff Rates; Portfolio Analysis; Trade; Policy; Risk and Uncertainty; Stocks; Investment Return

SSRN

April 2020
Article

Designs for Estimating the Treatment Effect in Networks with Interference

By: Ravi Jagadeesan, Natesh S. Pillai and Alexander Volfovsky

In this paper, we introduce new, easily implementable designs for drawing causal inference from randomized experiments on networks with interference. Inspired by the idea of matching in observational studies, we introduce the notion of considering a treatment... View Details

Keywords: Experimental Design; Network Inference; Neyman Estimator; Symmetric Interference Model; Homophily

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

Keywords: AI and Machine Learning; Research

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

Keywords: AI and Machine Learning; Mathematical Methods; Analytics and Data Science

October 1994 (Revised November 1995)
Case

N.V. Philips Electronics - Currency Hedging Policies

By: Richard F. Meyer

Describes Philips Electronics' policies and problems relating to foreign exchange risk and hedging. Explains centralization versus decentralization of currency hedging, economic role versus transaction role, the difficulties of capturing the necessary information... View Details

Keywords: Business Divisions; Currency Exchange Rate; International Finance; Globalization; Policy; Information Management; Management; Problems and Challenges; Risk and Uncertainty

Web

Policies | MBA

Policies Application Process As you prepare your application to Harvard Business School, please be aware of the following policies: All applications and recommendations must be submitted online. Each applicant is responsible for ensuring... View Details

2012
Article

Conflict Policy and Advertising Agency-Client Relations: The Problem of Competing Clients Sharing a Common Agency

By: Alvin J. Silk

What restrictions should be placed on advertising agencies with respect to serving accounts or clients that are competitors of one another in order to avoid conflicts of interest? In recent decades, the advertising and marketing services industry has undergone a number... View Details

Keywords: Advertising Agency; Competitors; Marketing Services Industry; Structural Changes; Agency-client Relationships; Hybrid Conflict Policies; Safeguards; Advertising; Advertising Industry; Europe; Latin America; North and Central America

Web

Instagram Takeover Policy | About

Instagram Takeover Policy Thank you for agreeing to share your HBS experience on one of our HBS branded Instagram accounts. To make your Stories takeover as fun (and responsible) as possible, we’ve created some guidelines you will find... View Details

February 2018
Article

Development and Feasibility of Bundled Payments for the Multidisciplinary Treatment of Head and Neck Cancer: A Pilot Program

By: Tracy Spinks, Alexis Guzman, Beth M. Beadle, Seohyun Lee, Ron Walters, Jim Incalcaterra, Ehab Hanna, Amy Hessel, Randal Weber, Sandra Denney, Lee Newcomer and Thomas W. Feeley

Purpose: Despite growing interest in bundled payments to reduce the costs of care, this payment method remains largely untested in cancer. This 3-year pilot tested the feasibility of a 1-year bundled payment for the multidisciplinary treatment of head and neck... View Details

Keywords: Health Care and Treatment; Cost Management