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- 2019
- Working Paper
Large-Scale Demand Estimation with Search Data
By: Tomomichi Amano, Andrew Rhodes and Stephan Seiler
In many online markets, traditional methods of demand estimation are difficult to implement because assortments are very large and individual products are sold infrequently. At the same time, data on consumer search (i.e., browsing) behavior are often available and are... View Details
Amano, Tomomichi, Andrew Rhodes, and Stephan Seiler. "Large-Scale Demand Estimation with Search Data." Harvard Business School Working Paper, No. 19-022, September 2018. (Revised June 2019. Stanford University Research Paper, No. 18-36, 8-20 2018.)
- Research Summary
Estimating Demand Uncertainty Using Judgmental Forecasts
Measuring demand uncertainty is a key activity in supply chain planning, but is difficult when demand history is unavailable such as for new products. One method that can be applied in such cases uses dispersion among forecasting experts as a measure of demand... View Details
- July–August 2023
- Article
Demand Learning and Pricing for Varying Assortments
By: Kris Ferreira and Emily Mower
Problem Definition: We consider the problem of demand learning and pricing for retailers who offer assortments of substitutable products that change frequently, e.g., due to limited inventory, perishable or time-sensitive products, or the retailer’s desire to... View Details
Keywords: Experiments; Pricing And Revenue Management; Retailing; Demand Estimation; Pricing Algorithm; Marketing; Price; Demand and Consumers; Mathematical Methods
Ferreira, Kris, and Emily Mower. "Demand Learning and Pricing for Varying Assortments." Manufacturing & Service Operations Management 25, no. 4 (July–August 2023): 1227–1244. (Finalist, Practice-Based Research Competition, MSOM (2021) and Finalist, Revenue Management & Pricing Section Practice Award, INFORMS (2019).)
- Research Summary
Dynamic Demand Estimation in Platform and Two-Sided Markets
This
paper develops techniques to structurally estimate consumer demand
in general platform-intermediated and two-sided markets. By
estimating both sides of the market simultaneously, the methodology
presented here is able to (1) endogenize the utility of a platform
as... View Details
- Article
Recovering Investor Expectations from Demand for Index Funds
By: Mark Egan, Alexander J. MacKay and Hanbin Yang
We use a revealed-preference approach to estimate investor expectations of stock market returns. Using data on demand for index funds that follow the S&P 500, we develop and estimate a model of investor choice to flexibly recover the time-varying distribution of... View Details
Keywords: Stock Market Expectations; Demand Estimation; Exchange-traded Funds (ETFs); Demand and Consumers; Investment
Egan, Mark, Alexander J. MacKay, and Hanbin Yang. "Recovering Investor Expectations from Demand for Index Funds." Review of Economic Studies 89, no. 5 (October 2022): 2559–2599.
- 2021
- Working Paper
Recovering Investor Expectations from Demand for Index Funds
By: Mark Egan, Alexander J. MacKay and Hanbin Yang
We use a revealed-preference approach to estimate investor expectations of stock market returns. Using data on demand for index funds that follow the S&P 500, we develop and estimate a model of investor choice to flexibly recover the time-varying distribution of... View Details
Keywords: Stock Market Expectations; Demand Estimation; Exchange-traded Funds (ETFs); Demand and Consumers; Investment; United States
Egan, Mark, Alexander J. MacKay, and Hanbin Yang. "Recovering Investor Expectations from Demand for Index Funds." NBER Working Paper Series, No. 26608, January 2020. (Accepted at the Review of Economic Studies. Harvard Business School Working Paper, No. 20-122, May 2020. Direct download. Revised July 2021.)
- 27 Sep 2018
- Working Paper Summaries
Large-Scale Demand Estimation with Search Data
- fall 2007
- Article
Estimating Demand Uncertainty Using Judgmental Forecasts
By: Vishal Gaur, Saravanan Kesavan, Ananth Raman and Marshall L. Fisher
Gaur, Vishal, Saravanan Kesavan, Ananth Raman, and Marshall L. Fisher. "Estimating Demand Uncertainty Using Judgmental Forecasts." Manufacturing & Service Operations Management 9, no. 4 (fall 2007).
- 2024
- Working Paper
Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP
We delineate a general framework for incorporating many types of micro data from summary statistics to full surveys of selected consumers into Berry, Levinsohn, and Pakes (1995) style estimates of differentiated products demand systems. We extend recommended practices... View Details
Conlon, Chris, and Jeff Gortmaker. "Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP." Working Paper, September 2024.
- 26 Nov 2018
- Working Paper Summaries
Demand Estimation in Models of Imperfect Competition
Keywords: by Alexander MacKay and Nathan H. Miller
- Article
Best Practices for Differentiated Products Demand Estimation with PyBLP
Differentiated products demand systems are a workhorse for understanding the price effects of mergers, the value of new goods, and the contribution of products to seller networks. Berry, Levinsohn, and Pakes (1995) provide a flexible random coefficients logit model... View Details
Conlon, Chris, and Jeff Gortmaker. "Best Practices for Differentiated Products Demand Estimation with PyBLP." RAND Journal of Economics 51, no. 4 (2020): 1108–1161.
- February 2025
- Article
Estimating Models of Supply and Demand: Instruments and Covariance Restrictions
By: Alexander MacKay and Nathan H. Miller
We consider the identification of empirical models of supply and demand with imperfect competition. We show that a restriction on the covariance between unobserved demand and cost shocks can resolve endogeneity and identify the price parameter. We demonstrate how to... View Details
Keywords: Demand Estimation; Identification; Endogeneity Bias; Covariance Restrictions; Ordinary Least Squares; Instrumental Variables; Price; Demand and Consumers; Competition
MacKay, Alexander, and Nathan H. Miller. "Estimating Models of Supply and Demand: Instruments and Covariance Restrictions." American Economic Journal: Microeconomics 71, no. 1 (February 2025): 238–281. (Direct download.)
- Other Unpublished Work
A Technique to Estimate Retail Demand and Lost Sales
By: A. Raman and Giulio Zotteri
- 2024
- Working Paper
What Drives Variation in Investor Portfolios? Estimating the Roles of Beliefs and Risk Preferences
By: Mark Egan, Alexander MacKay and Hanbin Yang
We present an empirical model of portfolio choice that allows for the nonparametric estimation of investors' (subjective) expectations and risk preferences. Utilizing a comprehensive dataset of 401(k) plans from 2009 through 2019, we explore heterogeneity in asset... View Details
Keywords: Stock Market Expectations; Demand Estimation; Retirement Planning; Defined Contribution Retirement Plan; 401 (K); Finance; Investment Portfolio; Investment; Retirement; Behavioral Finance; Financial Services Industry; United States
Egan, Mark, Alexander MacKay, and Hanbin Yang. "What Drives Variation in Investor Portfolios? Estimating the Roles of Beliefs and Risk Preferences." Harvard Business School Working Paper, No. 22-044, December 2021. (Revisions Requested at the Review of Financial Studies. Revised April 2024. Direct download. NBER Working Paper Series, No. 29604, December 2021)
- 2021
- Working Paper
Diagnosing Quality: Learning, Amenities, and the Demand for Health Care
By: Achyuta Adhvaryu, Emilio Gutierrez, Anant Nyshadham and Jorge Tamayo
We study the role of amenities in increasing demand for underutilized healthcare services. We evaluate the offer of a high-amenity diagnostic consultation for cataracts with a randomized price and find that a lower price for the high-amenity consultation increases... View Details
Keywords: Health Care Demand; Amenities; Health Care Quality; Cataracts; Surgery; Health Care and Treatment; Demand and Consumers; Quality; Learning; Mexico
Adhvaryu, Achyuta, Emilio Gutierrez, Anant Nyshadham, and Jorge Tamayo. "Diagnosing Quality: Learning, Amenities, and the Demand for Health Care." Harvard Business School Working Paper, No. 21-110, March 2021.
- 2021
- Working Paper
Consuming Contests: Outcome Uncertainty and Spectator Demand for Contest-based Entertainment
By: Patrick J. Ferguson and Karim R. Lakhani
Contests that are designed to be consumed for entertainment by non-contestants are a fixture of economic, cultural and political life. In this paper, we examine whether individuals prefer to consume contests that have more uncertain outcomes. We look to... View Details
Keywords: Contest Design; Information Preferences; Consumer Demand; Sports; Entertainment; Games, Gaming, and Gambling; Demand and Consumers; Outcome or Result
Ferguson, Patrick J., and Karim R. Lakhani. "Consuming Contests: Outcome Uncertainty and Spectator Demand for Contest-based Entertainment." Harvard Business School Working Paper, No. 21-087, February 2021.
- March 2011 (Revised December 2012)
- Case
Demand Media
By: John Deighton and Leora Kornfeld
Google search had helped Demand Media grow to be a $1.9 billion online publisher. Then, social media and smartphone apps began to change the way people navigated the Internet. How should Demand Media respond? The business ran on a radically new model in which a stable... View Details
Keywords: Business Model; Information Publishing; Consumer Behavior; Customization and Personalization; Internet and the Web; Publishing Industry
Deighton, John, and Leora Kornfeld. "Demand Media." Harvard Business School Case 511-043, March 2011. (Revised December 2012.) (request a courtesy copy.)
- 2022
- Working Paper
On the Estimation of Demand-Based Asset Pricing Models
A growing literature uses portfolio holdings data to quantify the impact of investor demand on equilibrium prices via counterfactual experiments. The key parameter in relating demand and equilibrium prices is investors’ elasticity of demand with respect to the price.... View Details
van der Beck, Philippe. "On the Estimation of Demand-Based Asset Pricing Models." Swiss Finance Institute Research Paper Series, No. 22-67, May 2022.
- 2023
- Working Paper
Rising Markups and the Role of Consumer Preferences
By: Hendrik Döpper, Alexander MacKay, Nathan H. Miller and Joel Stiebale
We characterize the evolution of markups for consumer products in the United States
from 2006 to 2019. We use detailed data on prices and quantities for products in more
than 100 distinct product categories to estimate demand systems with flexible... View Details
Keywords: Market Power; Markups; Demand Estimation; Consumer Products; Retailers; Product; Price; Demand and Consumers; Consumer Behavior
Döpper, Hendrik, Alexander MacKay, Nathan H. Miller, and Joel Stiebale. "Rising Markups and the Role of Consumer Preferences." Harvard Business School Working Paper, No. 22-025, October 2021. (Revised March 2023. Direct download.)