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Show Results For
- All HBS Web
(836)
- News (79)
- Research (641)
- Events (14)
- Multimedia (4)
- Faculty Publications (634)
- 2017
- Working Paper
Identifying Sources of Inefficiency in Health Care
By: Amitabh Chandra and Douglas O. Staiger
In medicine, the reasons for variation in treatment rates across hospitals serving similar patients are not well understood. Some interpret this variation as unwarranted and push standardization of care as a way of reducing allocative inefficiency. However, an... View Details
Keywords: Health Care and Treatment; Performance Efficiency; Performance Productivity; Mathematical Methods
Chandra, Amitabh, and Douglas O. Staiger. "Identifying Sources of Inefficiency in Health Care." NBER Working Paper Series, No. 24035, November 2017.
- Fall 2012
- Article
Innovation Strategy and Entry Deterrence
By: Ozge Turut and Elie Ofek
We model an incumbent's decision to pursue radical or incremental innovation when facing a rival entrant. The radical innovation may yield lucrative financial returns but entails significant technological and market-related uncertainties. It is also particularly... View Details
Turut, Ozge, and Elie Ofek. "Innovation Strategy and Entry Deterrence." Journal of Economics & Management Strategy 12, no. 3 (Fall 2012).
- 2007
- Working Paper
The Political Economy of 'Natural' Disasters
By: Charles Cohen and Eric D. Werker
Natural disasters occur in a political space. Although events beyond our control may trigger a disaster, the level of government preparedness and response greatly determines the extent of suffering incurred by the affected population. We use a political economy model... View Details
Keywords: Policy; Government and Politics; Strategic Planning; Mathematical Methods; Natural Disasters; Welfare or Wellbeing
Cohen, Charles, and Eric D. Werker. "The Political Economy of 'Natural' Disasters." Harvard Business School Working Paper, No. 08-040, December 2007. (Revised November 2008.)
- 20 Dec 2019
- Blog Post
Top 10 MBA Voices Blogs of 2019
introverts). Read More>>> Meet the MBA Class of 2020 Each student that attends HBS has a different story. They are from big cities, small farming villages, and everything in between. Some students have a passion for mathematics... View Details
- Profile
Tessa Vacher-Desvernais
analytics, but truly appreciate aesthetics. I’m very conscious of my inner tension between analytical and creative thinking.” Following her mathematical and sciences baccalaureate, she pursued liberal arts at an all-girl military boarding... View Details
- February 2021
- Article
A Dynamic Theory of Multiple Borrowing
By: Daniel Green and Ernest Liu
Multiple borrowing—a borrower obtains overlapping loans from multiple lenders—is a common phenomenon in many credit markets. We build a highly tractable, dynamic model of multiple borrowing and show that, because overlapping creditors may impose default externalities... View Details
Keywords: Commitment; Multiple Borrowing; Common Agency; Misallocation; Microfinance; Investment; Mathematical Methods
Green, Daniel, and Ernest Liu. "A Dynamic Theory of Multiple Borrowing." Journal of Financial Economics 139, no. 2 (February 2021): 389–404.
- 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.
- January 2021
- Article
Using Models to Persuade
By: Joshua Schwartzstein and Adi Sunderam
We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model... View Details
Keywords: Model Persuasion; Analytics and Data Science; Forecasting and Prediction; Mathematical Methods; Framework
Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." American Economic Review 111, no. 1 (January 2021): 276–323.
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
- May 2011
- Teaching Note
The Morrison Company (Brief Case)
By: Steven C. Wheelwright and Paul Meyers
Teaching Note for 4564. View Details
- October 2011
- Article
The Surprising Power of Age-Dependent Taxes
This article provides a new, empirically driven application of the dynamic Mirrleesian framework by studying a feasible and potentially powerful tax reform: age-dependent labor income taxation. I show analytically how age dependence improves policy on both the... View Details
Weinzierl, Matthew C. "The Surprising Power of Age-Dependent Taxes." Review of Economic Studies 78, no. 4 (October 2011): 1490–1518. (Also Harvard Business School Working Paper, No. 11-114, May 2011.)
- 2011
- Working Paper
Better-reply Dynamics in Deferred Acceptance Games
In this paper we address the question of learning in a two-sided matching mechanism that utilizes the deferred acceptance algorithm. We consider a repeated matching game where at each period agents observe their match and have the opportunity to revise their strategy... View Details
Keywords: Learning; Marketplace Matching; Outcome or Result; Game Theory; Mathematical Methods; Strategy
Haeringer, Guillaume, and Hanna Halaburda. "Better-reply Dynamics in Deferred Acceptance Games." Harvard Business School Working Paper, No. 11-126, June 2011.
- 1992
- Chapter
Thinking Coalitionally: Party Arithmetic, Process Opportunism, and Strategic Sequencing
By: James K. Sebenius and David Lax
- 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.
- 2023
- Article
Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability
By: Usha Bhalla, Suraj Srinivas and Himabindu Lakkaraju
With the increased deployment of machine learning models in various real-world applications, researchers and practitioners alike have emphasized the need for explanations of model behaviour. To this end, two broad strategies have been outlined in prior literature to... View Details
Bhalla, Usha, Suraj Srinivas, and Himabindu Lakkaraju. "Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- May 2020
- Article
Scalable Holistic Linear Regression
By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
- March 2022
- Article
Sensitivity Analysis of Agent-based Models: A New Protocol
By: Emanuele Borgonovo, Marco Pangallo, Jan Rivkin, Leonardo Rizzo and Nicolaj Siggelkow
Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such... View Details
Keywords: Agent-based Modeling; Sensitivity Analysis; Design Of Experiments; Total Order Sensitivity Indices; Organizations; Behavior; Decision Making; Mathematical Methods
Borgonovo, Emanuele, Marco Pangallo, Jan Rivkin, Leonardo Rizzo, and Nicolaj Siggelkow. "Sensitivity Analysis of Agent-based Models: A New Protocol." Computational and Mathematical Organization Theory 28, no. 1 (March 2022): 52–94.
- November 1990 (Revised August 1996)
- Background Note
Sampling and Statistical Inference
An introduction to sampling and statistical inference that covers the main concepts (confidence intervals, tests of statistical significance, choice of sample size) that are needed in making inferences about a population mean or percent. Includes discussion of problems... View Details
Schleifer, Arthur, Jr. "Sampling and Statistical Inference." Harvard Business School Background Note 191-092, November 1990. (Revised August 1996.)
- January 2008 (Revised April 2008)
- Teaching Note
Pilgrim Bank (C): Statistics Review with Data Desk
By: Frances X. Frei
Teaching Note for [602103]. View Details
- 2008
- Working Paper
Unravelling in Two-Sided Matching Markets and Similarity of Preferences
By: Hanna Halaburda
This paper investigates the causes and welfare consequences of unravelling in two-sided matching markets. It shows that similarity of preferences is an important factor driving unravelling. In particular, it shows that under the ex-post stable mechanism (the mechanism... View Details
Halaburda, Hanna. "Unravelling in Two-Sided Matching Markets and Similarity of Preferences." Harvard Business School Working Paper, No. 09-068, November 2008.