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- 2021
- Working Paper
Time Dependence and Preference: Implications for Compensation Structure and Shift Scheduling
By: Doug J. Chung, Byungyeon Kim and Byoung G. Park
This study jointly examines agents’ time dependence—period effects within instantaneous utility—and time preference—behavior on discounting future utility. The study considers the start- and end-of-period effects for time dependence and exponential and hyperbolic...
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- 2021
- Working Paper
Diversity and Performance in Entrepreneurial Teams
By: Sophie Calder-Wang, Paul A. Gompers and Kevin Huang
We study the role of diversity and performance in the entrepreneurial teams. We exploit a unique dataset of MBA students who participated in a required course to propose and start a real micro-business that allows us to examine horizontal diversity (i.e., within the...
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- Article
Variety of Innovation in Global Value Chains
By: Giulio Buciuni and Gary P. Pisano
This article analyzes how the geography and organization of pre- and production stages in Global Value Chains (GVC) contribute to lead firms' innovation development. A novel approach in GVC studies is introduced based on transaction cost economics (TCE) and the...
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- January 2021
- Article
Commuting and Innovation: Are Closer Inventors More Productive?
By: Hongyu Xiao, Andy Wu and Jaeho Kim
We estimate the causal effect of workplace–home commuting distance on inventor productivity. We construct a novel panel of U.S. inventors with precisely measured workplace–home distances and inventor-level productivity. Our identification strategy exploits firm office...
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- Article
Soul and Machine (Learning)
By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to...
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- September 2020 (Revised April 2021)
- Case
Algramo
By: Michael Chu, Monica Silva and Mariana Cal
Founded in 2013 by José Manuel Moller in Chile, Algramo first became known for addressing the “poverty tax” (the surcharge paid by lower income families for staples sold in smaller sizes) through specially-designed dispensers in low-income neighborhood grocery stores...
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Keywords:
Packaging-as-a-wallet;
Plastic Waste;
Business At The Base Of The Pyramid;
Reusable Packaging;
Alliances With Fmcgs To Meet Esg Goals;
Social Entrepreneurship;
Environmental Sustainability;
Strategy;
Value Creation;
Goals and Objectives;
Business Model;
Consumer Products Industry;
Latin America;
South America;
Chile
- September 2020 (Revised December 2020)
- Case
Hot Wheels at Mattel: Reinventing the Wheel
By: Elie Ofek, Andres Terech and Nicole Tempest Keller
In 2017, Chris Down, Global Brand General Manager for Hot Wheels, and his team from the Advanced Play Group within Mattel, Inc., were considering which innovation path to pursue in order to "future proof" the Hot Wheels franchise going forward. Hot Wheels was the...
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- 2020
- Working Paper
Open Source Software and Global Entrepreneurship
Does more activity in open source lead to more entrepreneurial activity and, if so, how much, and in what direction? This study measures how participation on the GitHub open source platform affects the founding of new ventures globally. We estimate these effects using...
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- May 2020
- Article
How Quantitative Easing Works: Evidence on the Refinancing Channel
By: Marco Di Maggio, Amir Kermani and Christopher Palmer
We document the transmission of large-scale asset purchases by the Federal Reserve to the real economy using rich borrower-linked mortgage-market data and an identification strategy based on mortgage market segmentation. We find that central bank QE1 MBS purchases...
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Keywords:
Monetary Policy;
Mbs;
Quantitative Easing;
Lsap;
Refinancing;
Deleveraging;
Harp;
Gse;
Central Banking;
Global Range;
Financing and Loans;
Credit;
United States
- 2020
- Working Paper
A General Theory of Identification
By: Iavor Bojinov and Guillaume Basse
What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree
on a definition in the context of parametric statistical models — roughly, a parameter θ in a model
P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is injective....
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- 2020
- Chapter
Team Reflexivity
By: Michaéla Schippers, Amy C. Edmondson and Michael A. West
Many teams face the problem of process loss, or suboptimal functioning, with sometimes serious consequences, such as medical errors. Team reflexivity—a deliberate process of discussing team goals, processes, or outcomes—can aid in optimizing team performance. In the...
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- 2019
- Working Paper
Soul and Machine (Learning)
By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, improved medical diagnostics, and machine translation, but can it improve marketing decisions? It can. Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to rich media...
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- July 2019
- Supplement
Aadhaar: India's ‘Unique Identification’ System Video Supplement
By: Tarun Khanna
- 2019
- Working Paper
Identification Using Border Approaches and IVs
By: Xing Li, Wesley R. Hartmann and Tomomichi Amano
We document that recent quasi-experimental strategies for identifying advertising effects can be derived from a model in which ad decisions are made at a more aggregate level than conversion is measured. Next, we show that the identifying variation in one of these...
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- 2019
- Working Paper
Biometric Tracking, Healthcare Provision, and Data Quality: Experimental Evidence from Tuberculosis Control
By: Thomas Bossuroy, Clara Delavallade and Vincent Pons
Developing countries increasingly use biometric identification technology in hopes of improving the reliability of administrative information and delivering social services more efficiently. This paper exploits the random placement of biometric tracking devices in...
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- 2020
- Working Paper
Strict ID Laws Don't Stop Voters: Evidence from a U.S. Nationwide Panel, 2008–2018
By: Enrico Cantoni and Vincent Pons
U.S. states increasingly require identification to vote – an ostensive attempt to deter fraud that prompts complaints of selective disenfranchisement. Using a difference-in-differences design on a 1.6-billion-observations panel dataset, 2008–2018, we find that the laws...
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- February 2019
- Article
The Ethnic Migrant Inventor Effect: Codification and Recombination of Knowledge Across Borders
By: Prithwiraj Choudhury and Do Yoon Kim
Ethnic migrant inventors may differ from locals in terms of the knowledge they bring to host firms. We study the role of first-generation ethnic migrant inventors in cross-border transfer of knowledge previously locked within the cultural context of their home regions....
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Keywords:
Skilled Migration;
Ethnic Migration;
First-generation Migrant;
Cultural Context;
Knowledge Flows;
Knowledge Reuse;
Knowledge Recombination;
Recombinant Creation;
H1b Visas;
Knowledge Sharing;
Knowledge Use and Leverage;
Knowledge Dissemination;
Immigration;
Ethnicity;
Cross-Cultural and Cross-Border Issues
- 2018
- Working Paper
The Contribution of High-Skilled Immigrants to Innovation in the United States
By: Shai Benjamin Bernstein, Rebecca Diamond, Timothy McQuade and Beatriz Pousada
We characterize the contribution of immigrants to US innovation, both through their direct productivity as well as through their indirect spillover effects on their native collaborators. To do so, we link patent records to a database containing the first five digits of...
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- 2019
- Working Paper
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. As is well known, a supply-side instrument can resolve price endogeneity in demand estimation. We show that, under common assumptions, two other approaches also yield consistent estimates of the...
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