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- October 2023
- Article
Coordination and Bandwagon Effects: How Past Rankings Shape the Behavior of Voters and Candidates
By: Riako Granzier, Vincent Pons and Clémence Tricaud
Candidates’ placements in polls or past elections can be powerful coordination devices for both parties and voters. Using a regression discontinuity design in French elections, we show that candidates who place first by only a small margin in the first round are more...
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- October 2023
- Article
Innovation on Wings: When Do Nonstop Flights Matter for Global Innovation?
By: Dany Bahar, Prithwiraj Choudhury, Do Yoon Kim and Wesley Koo
We study whether, when, and how better connectivity through nonstop flights leads to positive innovation outcomes for firms in the global context. Using unique data of all flights emanating from 5,015 airports around the globe from 2005 to 2015 and exploiting a...
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- August 2023
- Article
Formal Employment and Organized Crime: Regression Discontinuity Evidence from Colombia
By: Gaurav Khanna, Carlos Medina, Anant Nyshadham, Jorge Tamayo and Nicolas Torres
Safety net programs, common in settings with high informality like Latin America, often use a means test to establish eligibility. We ask: in settings in which organised crime provides lucrative opportunities in the informal market, will discouraging formal employment...
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- 2023
- Working Paper
Keep Your Enemies Closer: Strategic Platform Adjustments during U.S. and French Elections
By: Rafael Di Tella, Randy Kotti, Caroline Le Pennec and Vincent Pons
A key tenet of representative democracy is that politicians' discourse and policies should follow voters' preferences. In the median voter theorem, this outcome emerges as candidates strategically adjust their platform to get closer to their opponent. Despite its...
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- May 2023
- Case
CMA CGM: Reducing the Carbon Footprint of Container Shipping
By: Willy C. Shih and Emilie Billaud
Marine transport is the most cost-effective way to move large volumes over long distances, and container shipping is the backbone of international trade in goods. Yet shipping contributed 3% of worldwide greenhouse gas emissions, and the deep-sea segment, which...
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- 2023
- Article
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in...
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- 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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- March–April 2023
- Article
Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market...
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- 2023
- Working Paper
Advances in Power-to-Gas Technologies: Cost and Conversion Efficiency
By: Gunther Glenk, Philip Holler and Stefan Reichelstein
Widespread adoption of hydrogen as an energy carrier is widely believed to require continued advances in Power-to-Gas (PtG) technologies. Here we provide a comprehensive assessment of the dynamics of system prices and conversion efficiency for three currently prevalent...
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Keywords:
Clean Tech;
Decarbonization;
Carbon Emissions;
Learning By Doing;
Environment;
Energy;
Environmental Management;
Sustainable Cities;
Price;
Energy Industry;
Utilities Industry;
Industrial Products Industry;
Manufacturing Industry;
Transportation Industry;
Europe;
North America;
South America;
Africa;
Asia
- 2022
- Article
Becoming a Learning Organization While Enhancing Performance: The Case of LEGO
By: Thomas Borup Kristensen, Henrik Saabye and Amy Edmondson
Purpose - The purpose of this study is to empirically test how problem-solving lean practices, along with
leaders as learning facilitators in an action learning approach, can be transferred from a production context to a
knowledge work context for the purpose...
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- 2022
- Working Paper
Coordination and Incumbency Advantage in Multi-Party Systems: Evidence from French Elections
By: Kevin Dano, Francesco Ferlenga, Vincenzo Galasso, Caroline Le Pennec and Vincent Pons
In theory, free and fair elections can improve the selection of politicians and incentivize them to exert effort. In practice, incumbency advantage and coordination issues may lead to the (re)election of bad politicians. We ask whether these two forces compound each...
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- 2022
- Working Paper
Slowly Varying Regression under Sparsity
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami
We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem...
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Keywords:
Mathematical Methods
- September 2022
- Article
The Impact of Financial Assistance Programs on Health Care Utilization: Evidence from Kaiser Permanente
By: Alyce S. Adams, Raymond Kluender, Neale Mahoney, Jinglin Wang, Francis Wong and Wesley Yin
Most hospitals have financial assistance programs for low-income patients. We use administrative data from Kaiser Permanente to study the effects of financial assistance on health care utilization. Using a regression discontinuity design based on an income threshold...
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- 2022
- Article
Nonparametric Subset Scanning for Detection of Heteroscedasticity
By: Charles R. Doss and Edward McFowland III
We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning...
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- 2022
- Working Paper
Innovation on Wings: Nonstop Flights and Firm Innovation in the Global Context
By: Dany Bahar, Prithwiraj Choudhury, Do Yoon Kim and Wesley W. Koo
We study whether, when, and how better connectivity through nonstop flights leads to positive innovation outcomes for firms in the global context. Using unique data of all flights emanating from 5,015 airports around the globe from 2005 to 2015 and exploiting a...
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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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- May 2022
- Article
Complex Disclosure
By: Ginger Zhe Jin, Michael Luca and Daniel Martin
We present evidence that unnecessarily complex disclosure can result from strategic incentives to shroud information. In our lab experiment, senders are required to report their private information truthfully, but can choose how complex to make their reports. We find...
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- Article
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that...
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