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      • Faculty Publications  (96)

      Forecasting ModelsRemove Forecasting Models →

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      • January–February 2023
      • Article

      Forecasting COVID-19 and Analyzing the Effect of Government Interventions

      By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas
      We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details
      Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction
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      Li, Michael Lingzhi, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis, and Dimitris Bertsimas. "Forecasting COVID-19 and Analyzing the Effect of Government Interventions." Operations Research 71, no. 1 (January–February 2023): 184–201.
      • January–February 2023
      • Article

      Data-Driven COVID-19 Vaccine Development for Janssen

      By: Dimitris Bertsimas, Michael Lingzhi Li, Xinggang Liu, Jennings Xu and Najat Khan
      The COVID-19 pandemic has spurred extensive vaccine research worldwide. One crucial part of vaccine development is the phase III clinical trial that assesses the vaccine for safety and efficacy in the prevention of COVID-19. In this work, we enumerate the first... View Details
      Keywords: COVID-19; Health Testing and Trials; Forecasting and Prediction; AI and Machine Learning; Research; Pharmaceutical Industry
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      Bertsimas, Dimitris, Michael Lingzhi Li, Xinggang Liu, Jennings Xu, and Najat Khan. "Data-Driven COVID-19 Vaccine Development for Janssen." INFORMS Journal on Applied Analytics 53, no. 1 (January–February 2023): 70–84.
      • October–December 2022
      • Article

      Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

      By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
      Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
      Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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      Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
      • April 12, 2022
      • Article

      Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States

      By: Estee Y. Cramer, Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li and et al.
      Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models... View Details
      Keywords: COVID-19; Forecasting and Prediction; Health Pandemics; Mathematical Methods; Partners and Partnerships
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      Cramer, Estee Y., Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li, and et al. "Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States." e2113561119. Proceedings of the National Academy of Sciences 119, no. 15 (April 12, 2022). (See full author list here.)
      • March 2022 (Revised May 2022)
      • Case

      Winning Business at Russell Reynolds (A)

      By: Ethan Bernstein and Cara Mazzucco
      In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and... View Details
      Keywords: Compensation; Collaboration; Executive Search Firms; Consulting Firms; Compensation and Benefits; Restructuring; Human Resources; Human Capital; Management Practices and Processes; Organizational Culture; Organizational Change and Adaptation; Social and Collaborative Networks; Recruitment; Selection and Staffing; Talent and Talent Management; Consulting Industry; Employment Industry; Asia; Europe; Latin America; Middle East; North and Central America; South America; Oceania
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      Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds (A)." Harvard Business School Case 422-045, March 2022. (Revised May 2022.)
      • March 2022
      • Supplement

      Winning Business at Russell Reynolds (B)

      By: Ethan Bernstein and Cara Mazzucco
      In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and... View Details
      Keywords: Compensation; Collaboration; Executive Search Firms; Consulting Firms; Compensation and Benefits; Restructuring; Human Resources; Human Capital; Management Practices and Processes; Organizational Culture; Organizational Change and Adaptation; Social and Collaborative Networks; Recruitment; Selection and Staffing; Talent and Talent Management; Consulting Industry; Employment Industry; Asia; Europe; Latin America; Middle East; North and Central America; South America; Oceania
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      Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds (B)." Harvard Business School Supplement 422-046, March 2022.
      • March 2022
      • Article

      Where to Locate COVID-19 Mass Vaccination Facilities?

      By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero
      The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details
      Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods
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      Bertsimas, Dimitris, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li, and Alessandro Previero. "Where to Locate COVID-19 Mass Vaccination Facilities?" Naval Research Logistics Quarterly 69, no. 2 (March 2022): 179–200.
      • February 2022 (Revised January 2024)
      • Supplement

      Winning Business at Russell Reynolds (C)

      By: Ethan Bernstein and Cara Mazzucco
      In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting—and... View Details
      Keywords: Restructuring; Talent and Talent Management; Compensation and Benefits; Growth and Development Strategy; Organizational Change and Adaptation; Organizational Culture; Performance Evaluation; Motivation and Incentives; Consulting Industry
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      Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds (C)." Harvard Business School Spreadsheet Supplement 422-703, February 2022. (Revised January 2024.)
      • January 2022
      • Background Note

      Residual Income Valuation Model

      By: Charles C.Y. Wang and Albert Shin
      This note explains the residual income valuation model (RIM), how it relates to "traditional" valuation models, the intuition behind its use, and empirical research related to its value relevance. RIM is theoretically equivalent to the dividend discount model and the... View Details
      Keywords: Residual Income Valuation; Valuation; Research; Theory; Measurement and Metrics; Performance; Financial Management; Business Strategy
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      Wang, Charles C.Y., and Albert Shin. "Residual Income Valuation Model." Harvard Business School Background Note 122-070, January 2022.
      • August 2021 (Revised February 2024)
      • Case

      Data Science at the Warriors

      By: Iavor I. Bojinov and Michael Parzen
      The case explores the development and early growth of a data science team at the Golden State Warriors, an NBA team based in San Francisco. The case begins by explaining the initial rationale for investing in data science, then covers a debate on the appropriate team... View Details
      Keywords: Digital Marketing; Analysis; Forecasting and Prediction; Technological Innovation; Information Technology; Analytics and Data Science; Sports Industry; San Francisco; United States
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      Bojinov, Iavor I., and Michael Parzen. "Data Science at the Warriors." Harvard Business School Case 622-048, August 2021. (Revised February 2024.)
      • August 2021 (Revised November 2023)
      • Supplement

      Coats: Supply Chain Challenges

      By: Willy C. Shih
      Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour... View Details
      Keywords: Inventory Management; Supply Chain; Inventory; Supply Chain Management; Operations; Apparel and Accessories Industry; Asia
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      Shih, Willy C. "Coats: Supply Chain Challenges." Harvard Business School PowerPoint Supplement 622-041, August 2021. (Revised November 2023.)
      • August 2021
      • Supplement

      Coats: Supply Chain Challenges: Spreadsheet Supplement

      By: Willy C. Shih
      Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour... View Details
      Keywords: Inventory Management; Supply Chain; Inventory; Supply Chain Management; Operations; Growth and Development Strategy; Forecasting and Prediction; Demand and Consumers; Consolidation; Apparel and Accessories Industry; Asia
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      Shih, Willy C. "Coats: Supply Chain Challenges: Spreadsheet Supplement." Harvard Business School Spreadsheet Supplement 622-702, August 2021.
      • May 2021 (Revised July 2021)
      • Case

      Coats: Supply Chain Challenges

      By: Willy C. Shih and Adina Wong
      Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour... View Details
      Keywords: Inventory Management; Supply Chains; Digital; Operations; Supply Chain Management; Apparel and Accessories Industry; Asia
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      Shih, Willy C., and Adina Wong. "Coats: Supply Chain Challenges." Harvard Business School Case 621-115, May 2021. (Revised July 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; Analytics and Data Science
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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.
      • 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: Statistics; Experiments; Forecasting and Prediction; Performance Evaluation; AI and Machine Learning
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      Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021. (Click here to access this tutorial.)
      • June 2021
      • Article

      From Predictions to Prescriptions: A Data-driven Response to COVID-19

      By: Dimitris Bertsimas, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg and Cynthia Zeng
      The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at... View Details
      Keywords: COVID-19; Health Pandemics; AI and Machine Learning; Forecasting and Prediction; Analytics and Data Science
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      Bertsimas, Dimitris, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg, and Cynthia Zeng. "From Predictions to Prescriptions: A Data-driven Response to COVID-19." Health Care Management Science 24, no. 2 (June 2021): 253–272.
      • 2021
      • Working Paper

      Real Credit Cycles

      By: Pedro Bordalo, Nicola Gennaioli, Andrei Shleifer and Stephen J. Terry
      We incorporate diagnostic expectations, a psychologically founded model of overreaction to news, into a workhorse business cycle model with heterogeneous firms and risky debt. A realistic degree of diagnosticity, estimated from the forecast errors of managers of U.S.... View Details
      Keywords: Econometric Models; Business Cycles; Credit
      Citation
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      Bordalo, Pedro, Nicola Gennaioli, Andrei Shleifer, and Stephen J. Terry. "Real Credit Cycles." NBER Working Paper Series, No. 28416, January 2021.
      • Article

      Towards Robust and Reliable Algorithmic Recourse

      By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
      As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan approvals), there has been growing interest in post-hoc techniques which provide recourse to affected individuals. These techniques generate recourses under the assumption... View Details
      Keywords: Machine Learning Models; Algorithmic Recourse; Decision Making; Forecasting and Prediction
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      Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. "Towards Robust and Reliable Algorithmic Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • 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
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      Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." American Economic Review 111, no. 1 (January 2021): 276–323.
      • October 2020 (Revised March 2021)
      • Supplement

      Migros Turkey: Scaling Online Operations During COVID-19 (C)

      By: Antonio Moreno and Gamze Yucaoglu
      The case opens in August 2020 as Ozgur Tort and Mustafa Bartin, CEO and chief large-format and online retail officer of Migros Ticaret A.S. (Migros), Turkey’s oldest and one of its largest supermarket chains, are navigating Migros through COVID-19 and the unprecedented... View Details
      Keywords: Business Model; Strategy; Digital Platforms; Information Technology; Technology Adoption; Value Creation; Globalization; Competition; Expansion; Logistics; Profit; Resource Allocation; Diversification; Corporate Strategy; Crisis Management; Health Pandemics; Strategic Planning; Food and Beverage Industry; Turkey
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      Moreno, Antonio, and Gamze Yucaoglu. "Migros Turkey: Scaling Online Operations During COVID-19 (C)." Harvard Business School Supplement 621-062, October 2020. (Revised March 2021.)
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