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- October 2023
- Case
KOKO Networks: Bridging Energy Transition and Affordability with Carbon Financing
By: George Serafeim, Siko Sikochi and Namrata Arora
The problem was massive: two million hectares of African forests were lost annually to charcoal production for cooking, an area equivalent to 13 times Greater London, resulting in one billion tons of carbon emissions yearly. At the same time, an estimated 700,000...
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- 2023
- Working Paper
Causal Interpretation of Structural IV Estimands
By: Isaiah Andrews, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan and Jesse M. Shapiro
We study the causal interpretation of instrumental variables (IV) estimands of nonlinear, multivariate structural models with respect to rich forms of model misspecification. We focus on guaranteeing that the researcher's estimator is sharp zero consistent, meaning...
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Keywords:
Mathematical Methods
Andrews, Isaiah, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan, and Jesse M. Shapiro. "Causal Interpretation of Structural IV Estimands." NBER Working Paper Series, No. 31799, October 2023.
- October, 2023
- Article
Cleaning Up the Great Lakes: Housing Market Impacts of Removing Legacy Pollutants
By: Alecia Cassidy, Robyn C. Meeks and Michale R. Moore
The Great Lakes and their tributaries make up the largest freshwater system on the planet, providing drinking water and recreational value to millions of people. Yet manufacturing plants left a legacy of toxic pollutants in the region, tarnishing it as part of the...
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Keywords:
Valuation Of Environmental Effects;
Housing Demand;
Water Pollution;
Water Quality;
Infrastructure;
Pollution;
Consumer Behavior
Cassidy, Alecia, Robyn C. Meeks, and Michale R. Moore. "Cleaning Up the Great Lakes: Housing Market Impacts of Removing Legacy Pollutants." Journal of Public Economics 226 (October, 2023).
- 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...
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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).)
- May–June 2023
- Article
Need for Speed: The Impact of In-Process Delays on Customer Behavior in Online Retail
By: Santiago Gallino, Nil Karacaoglu and Antonio Moreno
The impact of delays has been widely studied in various offline services. The focus of this study is online services, and we explore the impact of in-process delays—measured by website speed—on customer behavior. We leverage novel retail and website speed data to...
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Keywords:
Online Retail;
Quasi-experiments;
Abandonment;
Synthetic Control;
E-commerce;
Internet and the Web;
Consumer Behavior;
Policy;
Retail Industry
Gallino, Santiago, Nil Karacaoglu, and Antonio Moreno. "Need for Speed: The Impact of In-Process Delays on Customer Behavior in Online Retail." Operations Research 71, no. 3 (May–June 2023): 876–894.
- 2023
- Working Paper
Using GPT for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have quickly become popular as labor-augmenting tools
for programming, writing, and many other processes that benefit from quick text generation.
In this paper we explore the uses and benefits of LLMs for researchers and...
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Keywords:
Large Language Model;
Research;
AI and Machine Learning;
Analysis;
Customers;
Consumer Behavior;
Technology Industry;
Information Technology Industry
Brand, James, Ayelet Israeli, and Donald Ngwe. "Using GPT for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023. (Revised July 2023.)
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in...
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Keywords:
Price;
Demand and Consumers;
AI and Machine Learning;
Investment Return;
Entertainment and Recreation Industry;
Sports Industry
Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
- 2023
- Working Paper
A Welfare Analysis of Gambling in Video Games
By: Tomomichi Amano and Andrey Simonov
In 2020, gamers worldwide spent more than $15 billion on loot boxes, a lottery of virtual items built into video games. Loot boxes are contentious, as regulators worry that they constitute gambling. In contrast, video game companies maintain that loot boxes are...
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Keywords:
Consumer Behavior;
Policy;
Games, Gaming, and Gambling;
Product Design;
Video Game Industry
Amano, Tomomichi, and Andrey Simonov. "A Welfare Analysis of Gambling in Video Games." Harvard Business School Working Paper, No. 23-052, February 2023.
- 2023
- Working Paper
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to...
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Keywords:
Long-run Targeting;
Heterogeneous Treatment Effect;
Statistical Surrogacy;
Customer Churn;
Field Experiments;
Consumer Behavior;
Customer Focus and Relationships;
AI and Machine Learning;
Marketing
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Harvard Business School Working Paper, No. 23-023, October 2022. (Revised April 2023.)
- Article
Recovering Investor Expectations from Demand for Index Funds
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...
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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.
- August 2022
- Supplement
Zalora: Data-Driven Pricing Recommendations
By: Ayelet Israeli
This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the...
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Keywords:
Pricing;
Pricing Algorithms;
Dynamic Pricing;
Ecommerce;
Pricing Strategy;
Pricing And Revenue Management;
Apparel;
Singapore;
Startup;
Demand Estimation;
Data Analysis;
Data Analytics;
Exercise;
Price;
Internet and the Web;
Apparel and Accessories Industry;
Retail Industry;
Fashion Industry;
Singapore
Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
- 2022
- Working Paper
The Effect of Employee Lateness and Absenteeism on Store Performance
By: Caleb Kwon and Ananth Raman
We empirically analyze the effects of employee lateness and absenteeism on store performance by examining 25.5 million employee shift timecards covering more than 100,000 employees across more than 500 U.S. retail grocery store locations over a four year time period....
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Kwon, Caleb, and Ananth Raman. "The Effect of Employee Lateness and Absenteeism on Store Performance." Working Paper, August 2022.
- 2023
- Working Paper
Dynamic Pricing and Demand Volatility: Evidence from Restaurant Food Delivery
By: Alexander J. MacKay, Dennis Svartbäck and Anders G. Ekholm
Pricing technology that allows firms to rapidly adjust prices has two potential benefits. Prices can respond more rapidly to demand shocks, leading to higher revenues. On the other hand, time-varying prices can be used to smooth out demand across periods, reducing...
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MacKay, Alexander J., Dennis Svartbäck, and Anders G. Ekholm. "Dynamic Pricing and Demand Volatility: Evidence from Restaurant Food Delivery." Harvard Business School Working Paper, No. 23-007, July 2022. (Revised March 2023.)
- March 2022
- Article
Learning to Rank an Assortment of Products
By: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar
We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue...
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Keywords:
Online Learning;
Product Ranking;
Assortment Optimization;
Learning;
Internet and the Web;
Product Marketing;
Consumer Behavior;
E-commerce
Ferreira, Kris, Sunanda Parthasarathy, and Shreyas Sekar. "Learning to Rank an Assortment of Products." Management Science 68, no. 3 (March 2022): 1828–1848.
- 2022
- Working Paper
How Do Copayment Coupons Affect Branded Drug Prices and Quantities Purchased?
By: Leemore S. Dafny, Kate Ho and Edward Kong
Drug copayment coupons to reduce patient cost-sharing have become nearly ubiquitous for high-priced brand-name prescription drugs. Medicare bans such coupons on the grounds that they are kickbacks that induce utilization, but they are commonly used by...
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Keywords:
Prescription Drugs;
Coupons;
Impact;
Health Care and Treatment;
Markets;
Price;
Spending;
Pharmaceutical Industry;
United States
Dafny, Leemore S., Kate Ho, and Edward Kong. "How Do Copayment Coupons Affect Branded Drug Prices and Quantities Purchased?" NBER Working Paper Series, No. 29735, February 2022.
- 2023
- Working Paper
What Drives Variation in Investor Portfolios? Estimating the Roles of Beliefs and Risk Preferences
We present an empirical model of portfolio choice that allows for nonparametric estimation
of investors’ (subjective) expectations and risk preferences. Using a comprehensive
dataset of 401(k) plans from 2009 through 2019, we explore the heterogeneity in asset...
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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. (Revised April 2023. Direct download. NBER Working Paper Series, No. 29604, December 2021)
- 2021
- Working Paper
Who Benefits from Online Gig Economy Platforms?
By: Christopher Stanton and Catherine Thomas
This paper estimates the magnitude and distribution of surplus from the knowledge worker gig economy using data from an online labor market. Labor demand elasticities determine workers’ wages, and buyers’ past market experience shapes both their job posting frequency...
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Keywords:
Gig Economy;
Knowledge Workers;
Online Platforms;
Employment;
Internet and the Web;
Governing Rules, Regulations, and Reforms;
Wages;
Digital Platforms
Stanton, Christopher, and Catherine Thomas. "Who Benefits from Online Gig Economy Platforms?" NBER Working Paper Series, No. 29477, November 2021. (Revise and Resubmit at American Economic Review.)
- 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...
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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.)
- 2021
- Working Paper
Consumer Choice and Corporate Bankruptcy
By: Samuel Antill and Megan Hunter
Using an incentivized randomized experiment, we estimate the causal effect of a Chapter 11 bankruptcy filing on consumer demand for the bankrupt firm's products. Knowledge of Hertz's Chapter 11 bankruptcy reduces consumers' willingness-to-pay for Hertz by 35%. We show...
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Keywords:
Consumer Choice;
Bankruptcy;
Financial Distress;
Structural Estimation;
Experimental Economics;
Hertz;
Insolvency and Bankruptcy;
Consumer Behavior
Antill, Samuel, and Megan Hunter. "Consumer Choice and Corporate Bankruptcy." Working Paper, August 2021.
- 2021
- Working Paper
Dirty Money: How Banks Influence Financial Crime
By: Joseph Pacelli, Janet Gao, Jan Schneemeier and Yufeng Wu
On September 21st, 2020, a consortium of international journalists leaked nearly 2,500 suspicious activity reports (SAR) obtained from the U.S. Financial Crimes Enforcement Network, exposing nearly $2 trillion of money laundering activity. The event raises important...
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Pacelli, Joseph, Janet Gao, Jan Schneemeier, and Yufeng Wu. "Dirty Money: How Banks Influence Financial Crime." Working Paper, July 2021.