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- Faculty Publications (148)
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- All HBS Web (382)
- Faculty Publications (148)
- 01 Mar 2017
- News
Students Forecast Climate Change’s Impact
this past fall with an open challenge: choose an organization whose operating model will be significantly affected by climate change, and tell us what it should be doing to address it. Students posted responses to the prompt on HBS’s Open... View Details
Keywords: Dan Morrell
- 2018
- Working Paper
Bayesian Ensembles of Binary-Event Forecasts: When Is It Appropriate to Extremize or Anti-Extremize?
By: Kenneth C. Lichtendahl Jr., Yael Grushka-Cockayne, Victor Richmond R. Jose and Robert L. Winkler
Many organizations face critical decisions that rely on forecasts of binary events. In these situations, organizations often gather forecasts from multiple experts or models and average those forecasts to produce a single aggregate forecast. Because the average... View Details
Keywords: Forecast Aggregation; Linear Opinion Pool; Generalized Additive Model; Generalized Linear Model; Stacking.; Forecasting and Prediction
Lichtendahl, Kenneth C., Jr., Yael Grushka-Cockayne, Victor Richmond R. Jose, and Robert L. Winkler. "Bayesian Ensembles of Binary-Event Forecasts: When Is It Appropriate to Extremize or Anti-Extremize?" Harvard Business School Working Paper, No. 19-041, October 2018.
- 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
Wang, Charles C.Y., and Albert Shin. "Residual Income Valuation Model." Harvard Business School Background Note 122-070, January 2022.
- September 2010
- Article
Do Inventory and Gross Margin Data Improve Sales Forecasts for U.S. Public Retailers?
By: Saravanan Kesavan, Vishal Gaur and Ananth Raman
Firm-level sales forecasts for retailers can be improved if we incorporate cost of goods sold, inventory, and gross margin (defined here as the ratio of sales to cost of goods sold) as three endogenous variables. We construct a simultaneous equations model, estimated... View Details
Keywords: Sales; Forecasting and Prediction; Distribution; Goods and Commodities; Cost; Public Sector; Profit; Mathematical Methods; Analytics and Data Science; Retail Industry; United States
Kesavan, Saravanan, Vishal Gaur, and Ananth Raman. "Do Inventory and Gross Margin Data Improve Sales Forecasts for U.S. Public Retailers?" Management Science 56, no. 9 (September 2010): 1519–1533.
- 13 Apr 2007
- Working Paper Summaries
Incorporating Price and Inventory Endogeneity in Firm-Level Sales Forecasting
- 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
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.)
- 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
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.
- 18 Sep 2019
- Working Paper Summaries
Using Models to Persuade
Keywords: by Joshua Schwartzstein and Adi Sunderam
- February 2007 (Revised January 2008)
- Supplement
Multifactor Models (CW)
By: Malcolm P. Baker
- Article
Scenario Generation for Long Run Interest Rate Risk Assessment
By: Robert F. Engle, Guillaume Roussellet and Emil N. Siriwardane
We propose a statistical model of the term structure of U.S. treasury yields tailored for long-term probability-based scenario generation and forecasts. Our model is easy to estimate and is able to simultaneously reproduce the positivity, persistence, and factor... View Details
Keywords: Forecasting; Stress Testing; Interest Rates; Forecasting and Prediction; Risk Management; United States
Engle, Robert F., Guillaume Roussellet, and Emil N. Siriwardane. "Scenario Generation for Long Run Interest Rate Risk Assessment." Special Issue on Theoretical and Financial Econometrics: Essays in Honor of C. Gourieroux. Journal of Econometrics 201, no. 2 (December 2017): 333–347.
- 26 Nov 2018
- Working Paper Summaries
Demand Estimation in Models of Imperfect Competition
Keywords: by Alexander MacKay and Nathan H. Miller
- July 2023
- Article
Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations
By: Dawson Beutler, Alex Billias, Sam Holt, Josh Lerner and TzuHwan Seet
In 2001, Dean Takahashi and Seth Alexander of the Yale University Investments Office developed a deterministic model for estimating future cash flows and valuations for the Yale endowment’s private equity portfolio. Their model, which is simple and intuitive, is still... View Details
Beutler, Dawson, Alex Billias, Sam Holt, Josh Lerner, and TzuHwan Seet. "Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations." Journal of Portfolio Management 49, no. 7 (July 2023): 144–158.
- 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
- October 2014 (Revised August 2018)
- Case
Caesars Entertainment
By: Janice H. Hammond and Aldo Sesia
This case describes the introduction of a regression analysis model for forecasting guest arrivals to Caesars Palace hotel in Las Vegas, Nevada. The company will use the forecast to staff the front desk in the hotel. The staff is unionized and the company has little... View Details
Keywords: Forecasting; Staffing; Gaming; Gaming Industry; Hotel Industry; Decision Making; Forecasting and Prediction; Human Resources; Selection and Staffing; Entertainment; Games, Gaming, and Gambling; Operations; Service Delivery; Service Operations; Accommodations Industry; Travel Industry; Tourism Industry; Food and Beverage Industry; Las Vegas
Hammond, Janice H., and Aldo Sesia. "Caesars Entertainment." Harvard Business School Case 615-031, October 2014. (Revised August 2018.)
- May 2018
- Article
Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing... View Details
Keywords: Forecasting Models; Simulation Methods; Regional Economic Activity: Growth, Development, Environmental Issues, And Changes; Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Economic Growth; Forecasting and Prediction
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings 108 (May 2018): 77–82.
- 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.)
- 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
Bordalo, Pedro, Nicola Gennaioli, Andrei Shleifer, and Stephen J. Terry. "Real Credit Cycles." NBER Working Paper Series, No. 28416, January 2021.
- 2010
- Working Paper
A New Model of Leadership (PDF File of Keynote Slides)
By: Michael C. Jensen and Allan L. Scherr
In this paper we provide a new definition of leadership that gives organizations and individuals access to new power, performance and accomplishment. In our model leadership consists of four critical elements The creation of a vision for the future that represents a... View Details
- 18 Jun 2024
- Research & Ideas
Central Banks Missed Inflation Red Flags. This Pricing Model Could Help.
environments.” If central banks had used economic models that account for variations in the speed of firm’s pricing decisions rather than their traditional forecasting tools, policymakers might have detected... View Details
- June 2020 (Revised May 2022)
- Case
Vanguard Retail Operations (A)
By: Willy C. Shih and Antonio Moreno
The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or... View Details
Keywords: Pooling; Generalist Model; Specialist Model; Operations; Service Operations; Management; Job Design and Levels; Financial Services Industry; United States
Shih, Willy C., and Antonio Moreno. "Vanguard Retail Operations (A)." Harvard Business School Case 620-104, June 2020. (Revised May 2022.)