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- All HBS Web (992)
- Faculty Publications (348)
Show Results For
- All HBS Web (992)
- Faculty Publications (348)
- August 2018 (Revised April 2019)
- Supplement
Chateau Winery (B): Supervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
- 2018
- Working Paper
Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning
By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck
Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details
Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets
Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck. "Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning." Harvard Business School Working Paper, No. 19-040, October 2018.
- 09 Jun 2020
- Working Paper Summaries
Aggregate and Firm-Level Stock Returns During Pandemics, in Real Time
- Article
Financial Innovation and Endogenous Growth
By: Luc Laeven, Ross Levine and Stelios Michalopoulos
Is financial innovation necessary for sustaining economic growth? To address this question, we build a Schumpeterian model in which entrepreneurs earn profits by inventing better goods, and profit-maximizing financiers arise to screen entrepreneurs. The model has two... View Details
Laeven, Luc, Ross Levine, and Stelios Michalopoulos. "Financial Innovation and Endogenous Growth." Journal of Financial Intermediation 24, no. 1 (January 2015): 1–24.
- 09 Jun 2020
- News
Fed action, debt markets and stocks
- 2011
- Working Paper
The Flexible Substitution Logit: Uncovering Category Expansion and Share Impacts of Marketing Instruments
By: Qiang Liu, Thomas J. Steenburgh and Sachin Gupta
Different instruments are relevant for different marketing objectives (category demand expansion or market share stealing). To help brand managers make informed marketing mix decisions, it is essential that marketing mix models appropriately measure the different... View Details
Keywords: Decision Choices and Conditions; Forecasting and Prediction; Investment; Brands and Branding; Marketing Strategy; Demand and Consumers; Mathematical Methods
Liu, Qiang, Thomas J. Steenburgh, and Sachin Gupta. "The Flexible Substitution Logit: Uncovering Category Expansion and Share Impacts of Marketing Instruments." Harvard Business School Working Paper, No. 12-012, September 2011.
- 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.
- 06 Jun 2016
- News
Your Investment Tool Is Failing You
- Article
The Cross Section of Expected Holding Period Returns and Their Dynamics: A Present Value Approach
By: Matthew R. Lyle and Charles C.Y. Wang
We provide a tractable model of firm-level expected holding period returns using two firm fundamentals—book-to-market ratio and ROE—and study the cross-sectional properties of the model-implied expected returns. We find that 1) firm-level expected returns and expected... View Details
Keywords: Expected Returns; Discount Rates; Holding Period Returns; Fundamental Valuation; Present Value; Valuation; Investment Return
Lyle, Matthew R., and Charles C.Y. Wang. "The Cross Section of Expected Holding Period Returns and Their Dynamics: A Present Value Approach." Journal of Financial Economics 116, no. 3 (June 2015): 505–525.
- November–December 2018
- Article
Slack Time and Innovation
By: Ajay Agrawal, Christian Catalini, Avi Goldfarb and Hong Luo
Traditional innovation models assume that new ideas are developed up to the point where the benefit of the marginal project is just equal to the cost. Because labor is a key input to innovation when the opportunity cost of time is lower, such as during school breaks or... View Details
Agrawal, Ajay, Christian Catalini, Avi Goldfarb, and Hong Luo. "Slack Time and Innovation." Organization Science 29, no. 6 (November–December 2018): 1056–1073.
- October 2015
- Article
Agglomerative Forces and Cluster Shapes
By: William R. Kerr and Scott Duke Kominers
We model spatial clusters of similar firms. Our model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate. Overlapping firm interactions... View Details
Keywords: Agglomeration; Clusters; Industrial Organization; Silicon Valley; Technology Flows; Patents; Networks; Information Technology; Industry Clusters; Entrepreneurship; California
Kerr, William R., and Scott Duke Kominers. "Agglomerative Forces and Cluster Shapes." Review of Economics and Statistics 97, no. 4 (October 2015): 877–899.
- 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
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.
- 07 Jan 2019
- Research & Ideas
The Better Way to Forecast the Future
different fields,” says Grushka-Cockayne, whose research is on data science, forecasting, project management, and behavioral decision-making. “Our work is focused on using crowds for prediction and for forecasting something that is... View Details
- 2023
- Working Paper
How People Use Statistics
By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis... View Details
Bordalo, Pedro, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon, and Andrei Shleifer. "How People Use Statistics." NBER Working Paper Series, No. 31631, August 2023.
- October 2016 (Revised April 2018)
- Case
DataXu: Selling Ad Tech
By: Frank V. Cespedes, John Deighton, Lisa Cox and Olivia Hull
DataXu served marketers by buying digital advertising for brands using its demand-side platform. It sought a way to build a more predictable revenue stream in the very transactional media marketplace, and hoped that two new marketing analytics products would give it a... View Details
Keywords: Sales Management; Pricing; Programmatic Ad Buying; ＂Marketing Analytics＂; Advertising Technology; Sales; Digital Marketing; Marketing Strategy; Advertising Campaigns; Product Launch; Product Positioning; Media; Technology Industry; Advertising Industry; Boston; Massachusetts
Cespedes, Frank V., John Deighton, Lisa Cox, and Olivia Hull. "DataXu: Selling Ad Tech." Harvard Business School Case 817-012, October 2016. (Revised April 2018.)
- 2010
- Working Paper
Agglomerative Forces and Cluster Shapes
By: William R. Kerr and Scott Duke Kominers
We model spatial clusters of similar firms. Our model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate. Overlapping firm interactions... View Details
Keywords: Entrepreneurship; Geographic Location; Patents; Labor; Industry Clusters; Industry Structures; Relationships; Competitive Advantage; Technology Industry; California
Kerr, William R., and Scott Duke Kominers. "Agglomerative Forces and Cluster Shapes." Harvard Business School Working Paper, No. 11-061, December 2010.
- May 2023
- Article
Equilibrium Effects of Pay Transparency
By: Zoë B. Cullen and Bobak Pakzad-Hurson
The public discourse around pay transparency has focused on the direct effect: how workers seek
to rectify newly-disclosed pay inequities through renegotiations. The question of how wage-setting
and hiring practices of the firm respond in equilibrium has received... View Details
Keywords: Pay Transparency; Online Labor Market; Privacy; Wage Gap; Corporate Disclosure; Wages; Negotiation
Cullen, Zoë B., and Bobak Pakzad-Hurson. "Equilibrium Effects of Pay Transparency." Econometrica 91, no. 3 (May 2023): 765–802. (Lead Article.)
- 2022
- Working Paper
Values as Luxury Goods and Political Polarization
By: Benjamin Enke, Mattias Polborn and Alex A Wu
Motivated by novel survey evidence, this paper develops a theory of political
behavior in which values are a luxury good: the relative weight voters place
on values rather than material considerations increases in income. The model
predicts (i) voters who are... View Details
Keywords: Political Polarization; Government and Politics; Moral Sensibility; Luxury; Values and Beliefs; Voting
Enke, Benjamin, Mattias Polborn, and Alex A Wu. "Values as Luxury Goods and Political Polarization." Working Paper, April 2022. (Revised April 2023.)