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- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in...
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Keywords:
Empirical Methods;
Empirical Operations;
Statistical Methods And Machine Learning;
Statistical Interferences;
Research Analysts;
Analytics and Data Science;
Mathematical Methods
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
- 2024
- Article
Learning Under Random Distributional Shifts
By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler
Algorithmic assignment of refugees and asylum seekers to locations within host
countries has gained attention in recent years, with implementations in the U.S.
and Switzerland. These approaches use data on past arrivals to generate machine
learning models that can...
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Bansak, Kirk, Elisabeth Paulson, and Dominik Rothenhäusler. "Learning Under Random Distributional Shifts." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 27th (2024).
- 2024
- Working Paper
Modest Victims: Victims Who Decline to Broadcast Their Victimization Are Seen As Morally Virtuous
By: Nathan Dhaliwal, Jillian J. Jordan and Pat Barclay
What do people think of victims who conceal their victimhood? We propose that the decision to not broadcast that one has been victimized serves as a costly act of modesty—in doing so, one is potentially forgoing social support and compensation from one’s community. We...
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Dhaliwal, Nathan, Jillian J. Jordan, and Pat Barclay. "Modest Victims: Victims Who Decline to Broadcast Their Victimization Are Seen As Morally Virtuous." Working Paper, August 2024.
- 2024
- Working Paper
Digital Platforms 2.0: Learnings, Opportunities, and Challenges
By: Shrabastee Banerjee, Ishita Chakraborty, Hana Choi, Hannes Datta, Remi Daviet, Chiara Farronato, Minkyung Kim, Anja Lambrecht, Puneet Manchanda, Aniko Oery, Ananya Sen, Marshall W Van Alstyne, Prasad Vana, Kenneth C Wilbur, Xu Zhang and Bobby Zhou
Platform-based digital ecosystems form the backbone of our interactions with the Internet. Over the past decade, digital ecosystems have witnessed significant growth, both in terms of industry footprint and academic research. Yet, the challenges associated with their...
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Banerjee, Shrabastee, Ishita Chakraborty, Hana Choi, Hannes Datta, Remi Daviet, Chiara Farronato, Minkyung Kim, Anja Lambrecht, Puneet Manchanda, Aniko Oery, Ananya Sen, Marshall W Van Alstyne, Prasad Vana, Kenneth C Wilbur, Xu Zhang, and Bobby Zhou. "Digital Platforms 2.0: Learnings, Opportunities, and Challenges." Working Paper, June 2024.
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the...
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Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- February 2024
- Article
Conveying and Detecting Listening in Live Conversation
By: Hanne Collins, Julia A. Minson, Ariella S. Kristal and Alison Wood Brooks
Across all domains of human social life, positive perceptions of conversational listening (i.e., feeling heard) predict well-being, professional success, and interpersonal flourishing. But a fundamental question remains: Are perceptions of listening accurate? Prior...
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Collins, Hanne, Julia A. Minson, Ariella S. Kristal, and Alison Wood Brooks. "Conveying and Detecting Listening in Live Conversation." Journal of Experimental Psychology: General 153, no. 2 (February 2024): 473–494.
- 2024
- Chapter
Regulating Collective Emotions
By: Amit Goldenberg
When we think of emotion and emotion regulation, we typically think of them as processes occurring at the individual level. Even when emotions are experienced by multiple people who interact with each other, analysis is typically centered around individual-level...
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Goldenberg, Amit. "Regulating Collective Emotions." Chap. 22 in Handbook of Emotion Regulation. Third Edition edited by James J. Gross and Brett Q. Ford, 183–189. Guilford Press, 2024.
- 2024
- Working Paper
Bootstrap Diagnostics for Irregular Estimators
By: Isaiah Andrews and Jesse M. Shapiro
Empirical researchers frequently rely on normal approximations in order to summarize and communicate uncertainty about their findings to their scientific audience. When such approximations are unreliable, they can lead the audience to make misguided decisions. We...
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Andrews, Isaiah, and Jesse M. Shapiro. "Bootstrap Diagnostics for Irregular Estimators." NBER Working Paper Series, No. 32038, January 2024.
- January 2024
- Article
Population Interference in Panel Experiments
By: Kevin Wu Han, Guillaume Basse and Iavor Bojinov
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit’s outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in...
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Han, Kevin Wu, Guillaume Basse, and Iavor Bojinov. "Population Interference in Panel Experiments." Journal of Econometrics 238, no. 1 (January 2024).
- December 2023
- Supplement
Research In Motion: Launching and Scaling the World's First Smartphone Empire (B)
By: Tatiana Sandino and Samuel Grad
Sandino, Tatiana, and Samuel Grad. "Research In Motion: Launching and Scaling the World's First Smartphone Empire (B)." Harvard Business School Supplement 124-060, December 2023.
- December 2023
- Supplement
Research In Motion: Launching and Scaling the World's First Smartphone Empire (C)
By: Tatiana Sandino and Samuel Grad
Sandino, Tatiana, and Samuel Grad. "Research In Motion: Launching and Scaling the World's First Smartphone Empire (C)." Harvard Business School Supplement 124-061, December 2023.
- December 2023 (Revised December 2023)
- Case
Research In Motion: Launching and Scaling the World's First Smartphone Empire (A)
By: Tatiana Sandino and Samuel Grad
In 2005, Research In Motion’s (RIM) BlackBerry smartphone was a sensation. After its launch in 1999, the groundbreaking BlackBerry had captured the hearts and minds of corporate America through its secure wireless email service. The device was so addictive and...
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Keywords:
Business Growth and Maturation;
Decision Choices and Conditions;
Mobile and Wireless Technology;
Innovation and Management;
Technological Innovation;
Business or Company Management;
Management Style;
Product Development;
Managerial Roles;
Growth and Development Strategy;
Technology Industry;
United States;
Canada
Sandino, Tatiana, and Samuel Grad. "Research In Motion: Launching and Scaling the World's First Smartphone Empire (A)." Harvard Business School Case 124-023, December 2023. (Revised December 2023.)
- December 2023
- Article
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work
By: Mijeong Kwon, Julia Lee Cunningham and Jon M. Jachimowicz
Intrinsic motivation has received widespread attention as a predictor of positive work outcomes, including employees’ prosocial behavior. In the current research, we offer a more nuanced view by proposing that intrinsic motivation does not uniformly increase prosocial...
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Kwon, Mijeong, Julia Lee Cunningham, and Jon M. Jachimowicz. "Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work." Academy of Management Journal 66, no. 6 (December 2023): 1625–1650.
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance...
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Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause...
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Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- September 2023
- Article
A Pull versus Push Framework for Reputation
Reputation is a powerful driver of human behavior. Reputation systems incentivize 'actors' to take reputation-enhancing actions, and 'evaluators' to reward actors with positive reputations by preferentially cooperating with them. This article proposes a reputation...
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Jordan, Jillian J. "A Pull versus Push Framework for Reputation." Trends in Cognitive Sciences 27, no. 9 (September 2023): 852–866.
- 2023
- Article
On Minimizing the Impact of Dataset Shifts on Actionable Explanations
By: Anna P. Meyer, Dan Ley, Suraj Srinivas and Himabindu Lakkaraju
The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanations in practice. For instance, models...
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Meyer, Anna P., Dan Ley, Suraj Srinivas, and Himabindu Lakkaraju. "On Minimizing the Impact of Dataset Shifts on Actionable Explanations." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 39th (2023): 1434–1444.
- 2023
- Article
On the Impact of Actionable Explanations on Social Segregation
By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research...
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Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted...
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Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Management Science 69, no. 7 (July 2023): 3759–3777.
- June 2023
- Article
National Customer Orientation: An Empirical Test across 112 Countries
By: Ofer Mintz, Imran S. Currim and Rohit Deshpandé
Customer orientation is a central tenet of marketing. However, less is known about how customer orientation varies across countries and time. Mintz, Currim, and Deshpandé (Eur. J. Mark., 56: 1014–1041, 2022) propose a country-level construct, national customer...
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Mintz, Ofer, Imran S. Currim, and Rohit Deshpandé. "National Customer Orientation: An Empirical Test across 112 Countries." Marketing Letters 34, no. 2 (June 2023): 189–204.