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    • All HBS Web  (1,087)
      • Faculty Publications  (200)

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      • Article

      Do the Right Firms Survive Bankruptcy?

      By: Samuel Antill
      In U.S. Chapter 11 bankruptcy cases, firms are either reorganized, acquired, or liquidated. I show that decisions to liquidate often reduce creditor recovery, costing creditors billions of dollars every year. I exploit the within-district random assignment of...  View Details
      Keywords: Bankruptcy; Bankruptcy Reorganization; Recovery Rate; Structural Estimation; Roy Model; 363 Sales; Insolvency and Bankruptcy; Governing Rules, Regulations, and Reforms
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      Antill, Samuel. "Do the Right Firms Survive Bankruptcy?" Journal of Financial Economics 144, no. 2 (May 2022): 523–546.
      • March 2022
      • Module Note

      Exploratory Data Analysis

      By: Iavor I. Bojinov, Michael Parzen and Paul J. Hamilton
      This module note provides an overview of exploratory data analysis for an introduction to data science course. It begins by defining the term "data", and then describes the different types of data that companies work with (structured v. unstructured, categorical v....  View Details
      Keywords: Data Analysis; Data Science; Statistics; Data Visualization; Analytics and Data Science; Analysis
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      Bojinov, Iavor I., Michael Parzen, and Paul J. Hamilton. "Exploratory Data Analysis." Harvard Business School Module Note 622-098, March 2022.
      • March 2022
      • Module Note

      Prediction & Machine Learning

      By: Iavor I. Bojinov, Michael Parzen and Paul J. Hamilton
      This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...  View Details
      Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation
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      Bojinov, Iavor I., Michael Parzen, and Paul J. Hamilton. "Prediction & Machine Learning." Harvard Business School Module Note 622-101, March 2022.
      • March 2022
      • Module Note

      Statistical Inference

      By: Iavor I. Bojinov, Michael Parzen and Paul J. Hamilton
      This note provides an overview of statistical inference for an introductory data science course. First, the note discusses samples and populations. Next the note describes how to calculate confidence intervals for means and proportions. Then it walks through the logic...  View Details
      Keywords: Data Science; Statistics; Mathematical Methods; Data and Data Sets
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      Bojinov, Iavor I., Michael Parzen, and Paul J. Hamilton. "Statistical Inference." Harvard Business School Module Note 622-099, March 2022.
      • March 2022
      • Article

      Assessing the Impact of the COVID-19 Pandemic on Clinician Ambulatory Electronic Health Record Use

      By: A Jay Holmgren, Lance Downing, Mitchell Tang, Christopher Sharp, Christopher Longhurst and Robert S. Huckman
      Objective: The COVID-19 pandemic changed clinician electronic health record (EHR) work in a multitude of ways. To evaluate how, we measure ambulatory clinician EHR use in the United States throughout the COVID-19 pandemic.

      Materials and Methods: We use EHR...  View Details
      Keywords: Health Care; Electronic Health Records; Productivity; COVID-19 Pandemic; Health Care and Treatment; Health Pandemics; Information Technology; Performance Productivity; United States
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      Holmgren, A Jay, Lance Downing, Mitchell Tang, Christopher Sharp, Christopher Longhurst, and Robert S. Huckman. "Assessing the Impact of the COVID-19 Pandemic on Clinician Ambulatory Electronic Health Record Use." Journal of the American Medical Informatics Association 29, no. 3 (March 2022): 453–460.
      • 2022
      • Chapter

      State-Formation, Statist Islam, and Regime Instability: Evidence from Turkey

      By: Kristin Fabbe
      Religion, and particularly the forces of political Islam and state secularism, have been central to discussions of regime stability in the Turkish case. Intense polarization, political instability, and military interventions have propelled Turkey into crisis about once...  View Details
      Keywords: Ottoman Empire; Regime; State Secularism; Political Islam; Democracy; Autocracy; Religion; Government and Politics; Turkey
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      Fabbe, Kristin. "State-Formation, Statist Islam, and Regime Instability: Evidence from Turkey." In The Oxford Handbook of Politics in Muslim Societies, edited by Melani Cammett and Pauline Jones. New York: Oxford University Press, 2022.
      • 2021
      • Working Paper

      The Luck of the Draw: The Causal Effect of Physicians on Birth Outcomes

      By: Arlen Guarin, Christian Posso, Estefania Saravia and Jorge Tamayo
      Identifying the effect of physicians’ skills on health outcomes is a challenging task due to the nonrandom sorting between physicians and hospitals. We overcome this challenge by exploiting a Colombian government program that randomly assigned 2,126 physicians to 618...  View Details
      Keywords: Physicians' Health Skills; Health Birth Outcomes; Birthing Outcomes; Experimental Evidence; Health Care and Treatment; Competency and Skills; Outcome or Result; Health Industry; Colombia
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      Guarin, Arlen, Christian Posso, Estefania Saravia, and Jorge Tamayo. "The Luck of the Draw: The Causal Effect of Physicians on Birth Outcomes." Harvard Business School Working Paper, No. 22-015, February 2021. (Revised November 2021.)
      • 2021
      • Working Paper

      How Important is Editorial Gatekeeping? Evidence from Top Biomedical Journals

      By: Joshua L. Krieger, Kyle R. Myers and Ariel D. Stern
      We examine editors' influence on the scientific content of academic journals by unpacking the role of three major forces: journals' missions, aggregate supply of and demand for specific topics, and scientific homophily via editorial gatekeeping. In a sample of top...  View Details
      Keywords: Jobs and Positions; Operations; Information Publishing; Analysis
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      Krieger, Joshua L., Kyle R. Myers, and Ariel D. Stern. "How Important is Editorial Gatekeeping? Evidence from Top Biomedical Journals." Harvard Business School Working Paper, No. 22-011, September 2021.
      • August 2021
      • Article

      Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders

      By: Tarun Khanna, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam and Meena Hewett
      This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories project—a mixed-methods approach to revisiting the much-studied historical trauma of the Partition of British...  View Details
      Keywords: Crowdsourcing; Mixed Methods Research; Oral History; History; Research
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      Khanna, Tarun, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam, and Meena Hewett. "Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders." Academy of Management Perspectives 35, no. 3 (August 2021): 384–399.
      • August 2021
      • Article

      Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders

      By: Tarun Khanna, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam and Meena Hewett
      This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories Project—a mixed-methods approach to revisiting the much-studied historical trauma of the Partition of British...  View Details
      Keywords: Mixed Methods; Insider-outsiders; Myth Of Informed Objectivity; Hybrid Research; Oral Narratives; Research; Analysis; India
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      Khanna, Tarun, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam, and Meena Hewett. "Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders." Academy of Management Perspectives 35, no. 3 (August 2021): 384–399.
      • August 2021
      • Article

      Multiple Imputation Using Gaussian Copulas

      By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky
      Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use...  View Details
      Keywords: Missing Data; Bayesian Statistics; Imputation; Categorical Data; Estimation
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      Hollenbach, F.M., I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward, and A. Volfovsky. "Multiple Imputation Using Gaussian Copulas." Special Issue on New Quantitative Approaches to Studying Social Inequality. Sociological Methods & Research 50, no. 3 (August 2021): 1259–1283. (0049124118799381.)
      • June 2021
      • Technical Note

      Introduction to Linear Regression

      By: Michael Parzen and Paul J. Hamilton
      This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical...  View Details
      Keywords: Analysis; Forecasting and Prediction; Risk and Uncertainty; Theory
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      Parzen, Michael, and Paul J. Hamilton. "Introduction to Linear Regression." Harvard Business School Technical Note 621-086, June 2021.
      • 2020
      • Working Paper

      Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective

      By: Srikant Datar, Apurv Jain, Charles C.Y. Wang and Siyu Zhang
      We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the...  View Details
      Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction
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      Datar, Srikant, Apurv Jain, Charles C.Y. Wang, and Siyu Zhang. "Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective." Harvard Business School Working Paper, No. 21-113, December 2020.
      • Mar 2021
      • Conference Presentation

      Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

      By: Seth Neel, Aaron Leon Roth and Saeed Sharifi-Malvajerdi
      We study the data deletion problem for convex models. By leveraging techniques from convex optimization and reservoir sampling, we give the first data deletion algorithms that are able to handle an arbitrarily long sequence of adversarial updates while promising both...  View Details
      Keywords: Machine Learning; Unlearning Algorithm; Mathematical Methods
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      Neel, Seth, Aaron Leon Roth, and Saeed Sharifi-Malvajerdi. "Descent-to-Delete: Gradient-Based Methods for Machine Unlearning." Paper presented at the 32nd Algorithmic Learning Theory Conference, March 2021.
      • 2021
      • Working Paper

      First Law of Motion: Influencer Video Advertising on TikTok

      By: Jeremy Yang, Juanjuan Zhang and Yuhan Zhang
      This paper engineers an intuitive feature that is predictive of the causal effect of influencer video advertising on product sales. We propose the concept of m-score, a summary statistic that captures the extent to which a product is advertised in the most engaging...  View Details
      Keywords: Influencer Advertising; Video Advertising; Computer Vision; Machine Learning; Advertising; Online Technology
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      Yang, Jeremy, Juanjuan Zhang, and Yuhan Zhang. "First Law of Motion: Influencer Video Advertising on TikTok." Working Paper, March 2021.
      • February 2021
      • Tutorial

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael Toffel and Natalie Epstein
      This video describes how to assess the accuracy of machine learning prediction models, primarily in the context of machine learning models that predict binary outcomes, such as logistic regression, random forest, or nearest neighbor models. After introducing and...  View Details
      Keywords: Machine Learning; Statistics; Experiments; Forecasting and Prediction; Performance Evaluation
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      Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021.
      • February 2021
      • Tutorial

      T-tests: Theory and Practice

      By: Michael Parzen, Natalie Epstein, Chiara Farronato and Michael Toffel
      This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with...  View Details
      Keywords: Data Analysis; Data Analytics; Experiment Design; Experimentation; Analytics and Data Science; Analysis
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      Parzen, Michael, Natalie Epstein, Chiara Farronato, and Michael Toffel. T-tests: Theory and Practice. Harvard Business School Tutorial 621-707, February 2021.
      • February 2021
      • Tutorial

      What is AI?

      By: Tsedal Neeley
      This video explores the elements that constitute artificial intelligence (AI). From its mathematical basis to current advances in AI, this video introduces students to data, tools, and statistical models that make a computer 'intelligent.' Through an explanation of...  View Details
      Keywords: Artificial Intelligence; Digital; Technological Innovation; Leadership; AI and Machine Learning
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      Neeley, Tsedal. What is AI? Harvard Business School Tutorial 421-713, February 2021.
      • February 2021
      • Article

      Assessment of Electronic Health Record Use Between U.S. and Non-U.S. Health Systems

      By: A Jay Holmgren, Lance Downing, David W. Bates, Tait D. Shanafelt, Arnold Milstein, Christopher Sharp, David Cutler, Robert S. Huckman and Kevin A. Schulman
      Importance: Understanding how the electronic health record (EHR) system changes clinician work, productivity, and well-being is critical. Little is known regarding global variation in patterns of use.
      Objective: To provide insights into which EHR...  View Details
      Keywords: Electronic Health Records; Health Care and Treatment; Online Technology; Health Industry; Information Technology Industry
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      Holmgren, A Jay, Lance Downing, David W. Bates, Tait D. Shanafelt, Arnold Milstein, Christopher Sharp, David Cutler, Robert S. Huckman, and Kevin A. Schulman. "Assessment of Electronic Health Record Use Between U.S. and Non-U.S. Health Systems." JAMA Internal Medicine 181, no. 2 (February 2021): 251–259.
      • January 2021
      • Case

      The FIRE Savings Calculator

      By: Michael Parzen and Paul J. Hamilton
      This case follows Carol Muñoz, a member of the Financial Independence, Retire Early (FIRE) lifestyle movement. At the age of 45, Carol is considering retiring and living off the $1 million she has accumulated. Using Monte Carlo simulation, Carol forecasts the...  View Details
      Keywords: Analysis; Forecasting and Prediction; Financial Strategy; Investment Portfolio; Investment Return; Personal Finance; Saving; Risk and Uncertainty; Diversification; Theory; Financial Services Industry
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      Parzen, Michael, and Paul J. Hamilton. "The FIRE Savings Calculator." Harvard Business School Case 621-087, January 2021.
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