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- Faculty Publications (230)
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- Article
Overhead Allocation via Mathematical Programming Models
By: Robert S. Kaplan and Gerald Thompson
Keywords: Mathematical Methods
Kaplan, Robert S., and Gerald Thompson. "Overhead Allocation via Mathematical Programming Models." Accounting Review 46, no. 2 (April 1971): 352–364.
- June 1994
- Article
Influence of Mathematical Models in Finance on Practice: Past, Present and Future
By: Robert C. Merton
Merton, Robert C. "Influence of Mathematical Models in Finance on Practice: Past, Present and Future." Series A. Philosophical Transactions of the Royal Society of London, Series A, Physical Sciences and Engineering 347 (June 1994): 451–463. (Reprinted in Financial Practice and Education, spring 1995.)
- 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.
- Article
Active World Model Learning with Progress Curiosity
By: Kuno Kim, Megumi Sano, Julian De Freitas, Nick Haber and Daniel Yamins
World models are self-supervised predictive models of how the world evolves. Humans learn world models by curiously exploring their environment, in the process acquiring compact abstractions of high bandwidth sensory inputs, the ability to plan across long temporal... View Details
Kim, Kuno, Megumi Sano, Julian De Freitas, Nick Haber, and Daniel Yamins. "Active World Model Learning with Progress Curiosity." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020).
- Article
Learning Models for Actionable Recourse
By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely... View Details
Ross, Alexis, Himabindu Lakkaraju, and Osbert Bastani. "Learning Models for Actionable Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 2022
- Working Paper
A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure
By: Jesse M. Shapiro and Liyang Sun
Linear panel models featuring unit and time fixed effects appear in many areas of empirical economics. An active literature studies the interpretation of the ordinary least squares estimator of the model, commonly called the two-way fixed effects (TWFE) estimator, in... View Details
Shapiro, Jesse M., and Liyang Sun. "A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure." NBER Working Paper Series, No. 29976, April 2022.
- March 2022 (Revised July 2022)
- Technical Note
Linear Regression
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to... View Details
Keywords: Data Science; Linear Regression; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Linear Regression." Harvard Business School Technical Note 622-100, March 2022. (Revised July 2022.)
- March 2022 (Revised July 2022)
- Technical Note
Statistical Inference
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 Modeling; Mathematical Methods; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Statistical Inference." Harvard Business School Technical Note 622-099, March 2022. (Revised July 2022.)
- January 2006
- Tutorial
Cost-Volume Profit Models
By: David F. Hawkins, V.G. Narayanan, Jacob Cohen and Michele Jurgens
Covers fixed, variable, and semivariable costs and their role in building and interpreting cost-volume-profit models. Introduces the cost-volume and contribution-volume-profit models and identifies some of their uses and limitations. Teaches how to use the... View Details
- April 2021
- Article
A Model of Multi-Pass Search: Price Search Across Stores and Time
By: Navid Mojir and K. Sudhir
In retail settings with price promotions, consumers often search across stores and time. However, the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using scanner data has modeled search across... View Details
Keywords: Consumer Search; Multi-pass Search; Price Search; Store Search; Spatial Search; Temporal Search; Spatiotemporal Search; Dynamic Structural Models; MPEC; Price Promotions; Store Loyalty; Consumer Behavior; Price; Spending; Marketing; Mathematical Methods
Mojir, Navid, and K. Sudhir. "A Model of Multi-Pass Search: Price Search Across Stores and Time." Management Science 67, no. 4 (April 2021): 2126–2150.
- June 2007
- Tutorial
Congruence Model Tutorial
By: Christopher Marquis and Alison Comings
Utilizes Beer & Tushman's SMA: Microelectronic Products Division (A) case to explore O'Reilly and Tushman's congruence model. Participants learn about the model through a series of video presentations and become familar with the problems facing SMA through an... View Details
- February 2007 (Revised January 2008)
- Supplement
Multifactor Models (CW)
By: Malcolm P. Baker
- 18 Sep 2019
- Working Paper Summaries
Using Models to Persuade
Keywords: by Joshua Schwartzstein and Adi Sunderam
- July 2006
- Article
Dynamic Mixed Duopoly: A Model Motivated by Linux vs. Windows
By: Ramon Casadesus-Masanell and Pankaj Ghemawat
This paper analyzes a dynamic mixed duopoly in which a profit-maximizing competitor interacts with a competitor that prices at zero (or marginal cost), with the cumulation of output affecting their relative positions over time. The modeling effort is motivated by... View Details
Keywords: Open Source Software; Demand-side Learning; Network Effects; Linux; Mixed Duopoly; Competitive Dynamics; Business Models; Duopoly and Oligopoly; Information Technology; Applications and Software; Business Model; Mathematical Methods; Digital Platforms; Profit; Balance and Stability; Management Analysis, Tools, and Techniques; SWOT Analysis; Competition; Price; Information Technology Industry
Casadesus-Masanell, Ramon, and Pankaj Ghemawat. "Dynamic Mixed Duopoly: A Model Motivated by Linux vs. Windows." Management Science 52, no. 7 (July 2006): 1072–1084.
- 1987
- Chapter
Continuous-Time Stochastic Models
By: Robert C. Merton
Keywords: Mathematical Methods
Merton, Robert C. "Continuous-Time Stochastic Models." In The New Palgrave: A Dictionary of Economic Theory and Doctrine, edited by John Eatwell, Murray Milgate, and Peter Newman. London: Macmillan Press, 1987. (Revised in The New Palgrave Dictionary of Money and Finance, London: MacMillan Press, Ltd., 1992.)
- February 2006
- Teaching Note
Cost-Volume-Profit Models (TN)
By: David F. Hawkins, V.G. Narayanan, Michele Jurgens and Jacob Cohen
Keywords: Mathematical Methods
- 2006
- Chapter
Advanced Regression Models
By: Raghuram Iyengar and Sunil Gupta
Keywords: Mathematical Methods
- 2004
- Chapter
The Harrod-Domar Model
By: Diego Comin
Comin, Diego. "The Harrod-Domar Model." In An Eponymous Dictionary of Economics, edited by C. R. Braun and Julio Segura. Edward Elgar Publishing, 2004.
- December 2008
- Article
Behavioral Frontiers in Choice Modeling
We review the discussion at a workshop whose goal was to achieve a better integration among behavioral, economic, and statistical approaches to choice modeling. The workshop explored how current approaches to the specification, estimation, and application of choice... View Details
Keywords: Mathematical Methods; Integration; Goals and Objectives; Decision Choices and Conditions; Problems and Challenges; Business Processes; Customers; Behavior; Economics
Adamowicz, Wiktor, David Bunch, Trudy Ann Cameron, Benedict G.C. Dellaert, Michael Hanneman, Michael Keane, Jordan Louviere, Robert Meyer, Thomas J. Steenburgh, and Joffre Swait. "Behavioral Frontiers in Choice Modeling." Marketing Letters 19, nos. 3/4 (December 2008): 215–219.