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- 2022
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of tools...
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Keywords:
Analytics and Data Science
- 2022
- Working Paper
Demand-and-Supply Imbalance Risk and Long-Term Swap Spreads
By: Samuel G. Hanson, Aytek Malkhozov and Gyuri Venter
We develop and test a model in which swap spreads are determined by end users' demand for and constrained intermediaries' supply of long-term interest rate swaps. Swap spreads reflect compensation both for using scarce intermediary capital and for bearing convergence...
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- Working Paper
Representation and Extrapolation: Evidence from Clinical Trials
By: Marcella Alsan, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein and Heidi L. Williams
This article examines the consequences and causes of low enrollment of Black patients in clinical
trials. We develop a simple model of similarity-based extrapolation that predicts that evidence is
more relevant for decision-making by physicians and patients when it...
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- 2022
- Working Paper
What's My Employee Worth? The Effects of Salary Benchmarking
By: Zoë B. Cullen, Shengwu Li and Ricardo Perez-Truglia
While U.S. legislation prohibits employers from sharing information about their employees’
compensation with each other, companies are still allowed to acquire and use more aggregated
data provided by third parties. Most medium and large firms report using this type...
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- 2022
- Working Paper
Perceptions about Monetary Policy
By: Michael D. Bauer, Carolin Pflueger and Adi Sunderam
We estimate perceptions about the Fed's monetary policy rule from micro data on professional forecasters. The perceived rule varies significantly over time, with important consequences for monetary policy and bond markets. Over the monetary policy cycle, easings are...
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- 2022
- Working Paper
Imagining the Future: Memory, Simulation and Beliefs about COVID
By: Pedro Bordalo, Giovanni Burro, Katherine B. Coffman, Nicola Gennaioli and Andrei Shleifer
How do people form beliefs about novel risks, with which they have little or no experience? A 2020 U.S. survey of beliefs about the lethality of COVID reveals that the elderly underestimate, and the young overestimate, their own risks, and that people with more health...
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- 2022
- Working Paper
Machine Learning Models for Prediction of Scope 3 Carbon Emissions
By: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15...
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- March 2022 (Revised July 2022)
- Module Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...
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- February 2022 (Revised September 2022)
- Case
Lilium: Preparing for Takeoff
By: Navid Mojir, Vincent Dessain, Mette Fuglsang Hjortshoej and Emer Moloney
Lilium is a German company focused on developing electric vertical takeoff and landing vehicles (eVTOLs) that can be used to offer air taxi services. The company went public in September 2021 through a special purpose acquisition company (SPAC) deal, raising more than...
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Keywords:
SPACs;
Business Model;
Forecasting and Prediction;
Green Technology;
Capital Markets;
Venture Capital;
Initial Public Offering;
Rural Scope;
Urban Scope;
City;
Disruptive Innovation;
Growth and Development Strategy;
Technological Innovation;
Demand and Consumers;
Market Timing;
Industry Growth;
Infrastructure;
Logistics;
Product Design;
Product Development;
Production;
Service Delivery;
Service Operations;
Strategic Planning;
Partners and Partnerships;
Risk and Uncertainty;
Urban Development;
Sustainable Cities;
Business Strategy;
Competitive Strategy;
Competitive Advantage;
Air Transportation;
Aerospace Industry;
Air Transportation Industry;
Green Technology Industry;
Transportation Industry;
Travel Industry;
Germany;
Munich;
Brazil;
United States;
Florida
- January 10, 2022
- Article
The Link Between Income, Income Inequality, and Prosocial Behavior Around the World: A Multiverse Approach
By: Lucia Macchia and Ashley V. Whillans
The questions of whether high-income individuals are more prosocial than low-income individuals and whether income inequality moderates this effect have received extensive attention. We shed new light on this topic by analyzing a large-scale dataset with a...
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- Article
Counterfactual Explanations Can Be Manipulated
By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate...
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- Article
Behavioral and Neural Representations en route to Intuitive Action Understanding
By: Leyla Tarhan, Julian De Freitas and Talia Konkle
When we observe another person’s actions, we process many kinds of information—from how their body moves to the intention behind their movements. What kinds of information underlie our intuitive understanding about how similar actions are to each other? To address this...
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- October 2021
- Article
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Nicolas Padilla and Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can...
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- September 2021
- Article
Learning from Deregulation: The Asymmetric Impact of Lockdown and Reopening on Risky Behavior During COVID-19
By: Edward L. Glaeser, Ginger Zhe Jin, Michael Luca and Benjamin T. Leyden
During the COVID-19 pandemic, states issued and then rescinded stay-at-home orders that restricted mobility. We develop a model of learning by deregulation, which predicts that lifting stay-at-home orders can signal that going out has become safer. Using restaurant...
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- 2021
- Working Paper
Salience
By: Pedro Bordalo, Nicola Gennaioli and Andrei Shleifer
We review the fast-growing work on salience and economic behavior. Psychological research shows that salient stimuli attract human attention “bottom up” due to their high contrast with surroundings, their surprising nature relative to recalled experiences, or their...
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- August 2021
- Supplement
Coats: Supply Chain Challenges: Spreadsheet Supplement
By: Willy C. Shih
Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour...
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- 2021
- Working Paper
Multiple Team Membership, Turnover, and On-Time Delivery: Evidence from Construction Services
By: Hise O. Gibson, Bradely R. Staats and Ananth Raman
Firms who want to compete in dynamic markets are finding that they must build more agile operations to ensure success. One way for a firm to increase organizational agility is to allocate employees to multiple project teams, simultaneously—a practice known as multiple...
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- 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...
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- June 2021
- Technical Note
Introduction to Linear Regression
By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical...
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- 2021
- Working Paper
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...
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