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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...  View Details
Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning
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  • 2023
  • Article

Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations.
By: Edward McFowland III and Cosma Rohilla Shalizi
Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partners being informative about the node’s attributes and therefore its...  View Details
Keywords: Causal Inference; Homophily; Social Networks; Peer Influence; Social and Collaborative Networks; Power and Influence; Mathematical Methods
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  • 2023
  • Working Paper

Crowding in Private Quality: The Equilibrium Effects of Public Spending in Education
By: Tahir Andrabi, Natalie Bau, Jishnu Das, Asim Ijaz Khwaja and Naureen Karachiwalla
We estimate the equilibrium effects of a public-school grant program administered through school councils in Pakistani villages with multiple public and private schools and clearly defined catchment boundaries. The program was randomized at the village-level, allowing...  View Details
Keywords: Product Differentiation; Public Sector; Private Sector; Spending; Education; Competition
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  • 2023
  • Article

Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a...  View Details
Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
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  • January 2023
  • Article

Racial Diversity and Racial Policy Preferences: The Great Migration and Civil Rights
By: Alvaro Calderon, Vasiliki Fouka and Marco Tabellini
Between 1940 and 1970, more than 4 million African Americans moved from the South to the North of the United States, during the Second Great Migration. This same period witnessed the struggle and eventual success of the civil rights movement in ending institutionalized...  View Details
Keywords: Civil Rights; Great Migration; History; Race; Rights; Prejudice and Bias; Government Legislation
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  • December 2022
  • Article

Fostering Perceptions of Authenticity via Sensitive Self-Disclosure
By: Li Jiang, Leslie K. John, Reihane Boghrati and Maryam Kouchaki
Leaders’ perceived authenticity—the sense that leaders are acting in accordance with their “true self”—is associated with positive outcomes for both employees and organizations alike. How might leaders foster this impression? We show that sensitive self-disclosure, in...  View Details
Keywords: Authenticity; Weaknesses; Self-disclosure; Leaders; Impression Management; Leadership Style; Motivation and Incentives
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  • December 2022
  • Article

The Emotional Rewards of Prosocial Spending Are Robust and Replicable in Large Samples
By: Lara B. Aknin, Elizabeth W. Dunn and Ashley V. Whillans
Past studies show that spending money on other people—prosocial spending—increases a person’s happiness. However, foundational research on this topic was conducted prior to psychology’s credibility revolution (or “replication crisis”), so it is essential to ask...  View Details
Keywords: Happiness; Money
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  • November 2022
  • Article

My Boss' Passion Matters as Much as My Own: The Interpersonal Dynamics of Passion Are a Critical Driver of Performance Evaluations
By: Jon M. Jachimowicz, Andreas Wihler and Adam D. Galinsky
Companies often celebrate employees who successfully pursue their passion. Academic research suggests that these positive evaluations occur because of the passion percolating inside the employee. We propose that supervisors are also a key piece of this puzzle:...  View Details
Keywords: Passion; Job Performance; Motivation; Emotions; Performance Evaluation; Interpersonal Communication
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  • November 2022
  • Article

The Psychosocial Value of Employment: Evidence from a Refugee Camp
By: Reshmaan Hussam, Erin M. Kelley, Gregory Lane and Fatima Zahra
Employment may be important to wellbeing for reasons beyond its role as an income source. This paper presents a causal estimate of the psychosocial value of employment in refugee camps in Bangladesh. We involve 745 individuals in a field experiment with three arms: a...  View Details
Keywords: Psychosocial Wellbeing; Employment; Refugees; Well-being
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  • October–December 2022
  • Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed...  View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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  • September 16, 2022
  • Article

A Causal Test of the Strength of Weak Ties
By: Karthik Rajkumar, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson and Sinan Aral
The authors analyzed data from multiple large-scale randomized experiments on LinkedIn’s People You May Know algorithm, which recommends new connections to LinkedIn members, to test the extent to which weak ties increased job mobility in the world’s largest...  View Details
Keywords: Job Mobility; Social Networks; Social Ties; Networks; Personal Development and Career
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  • 2022
  • Working Paper

Human Capital and the Managerial Revolution in the United States
By: Tom Nicholas
This paper estimates the returns to human capital accumulation during the first era of megafirms in the United States by linking employees at General Electric—a canonical enterprise associated with the “visible hand” of managerial hierarchies—to data from the 1940...  View Details
Keywords: Returns To Education; Management Practices; Hierarchies; Human Capital; Management; Training; Higher Education; Government and Politics; United States
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  • 2022
  • Working Paper

Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments
By: Fanglin Chen, Xiao Liu, Davide Proserpio and Isamar Troncoso
We propose a method, Product2Vec, based on representation learning, that can automatically learn latent product attributes that drive consumer choices, to study product-level competition when the number of products is large. We demonstrate Product2Vec’s...  View Details
Keywords: Consumer Choice; Consumer Behavior; Competition; Product Marketing
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  • June 2022 (Revised July 2022)
  • Module Note

Causal Inference
By: Iavor I Bojinov, Michael Parzen and Paul Hamilton
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of...  View Details
Keywords: Causal Inference; Causality; Experiment; Experimental Design; Data Science; Analytics and Data Science
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  • June 2022
  • Article

Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation
By: Jacqueline N. Lane, Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan and Karim R. Lakhani
The evaluation and selection of novel projects lies at the heart of scientific and technological innovation, and yet there are persistent concerns about bias, such as conservatism. This paper investigates the role that the format of evaluation, specifically information...  View Details
Keywords: Project Evaluation; Innovation; Knowledge Frontier; Information Sharing; Negativity Bias; Projects; Innovation and Invention; Information; Knowledge Sharing
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  • May 2022
  • Article

Can Gambling Increase Savings? Empirical Evidence on Prize-Linked Savings Accounts
By: Shawn A. Cole, Benjamin Iverson and Peter Tufano
This paper studies the adoption and impact of prize-linked savings (PLS) accounts, which offer lottery-like payouts to individual account holders in lieu of interest. Using microlevel data from a bank in South Africa, we show that PLS is attractive to a broad group of...  View Details
Keywords: Household Finance; Banking; Savings; Prize-linked Savings; Lottery; Household; Personal Finance; Saving; Banks and Banking
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  • 2022
  • Working Paper

Causal Inference During A Pandemic: Evidence on the Effectiveness of Nebulized Ibuprofen as an Unproven Treatment for COVID-19 in Argentina
By: Sebastian Calonico, Rafael Di Tella and Juan Cruz Lopez Del Valle
Many medical decisions during the pandemic were made without the support of causal evidence obtained in clinical trials. We study the case of nebulized ibuprofen (NaIHS), a drug that was extensively used on COVID-19 patients in Argentina amidst wild claims about its...  View Details
Keywords: COVID-19; Drug Treatment; Health Pandemics; Health Care and Treatment; Decision Making; Outcome or Result; Argentina
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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...  View Details
Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
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  • April–June 2022
  • Other Article

Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'
By: Edward McFowland III
There has been a substantial discussion in various methodological and applied literatures around causal inference; especially in the use of machine learning and statistical models to understand heterogeneity in treatment effects and to make optimal decision...  View Details
Keywords: Causal Inference; Treatment Effect Estimation; Treatment Assignment Policy; Human-in-the-loop; Decision Making; Fairness
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  • 2022
  • Working Paper

Is Hybrid Work the Best of Both Worlds? Evidence from a Field Experiment
By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Kyle Schirmann
Hybrid work is emerging as a novel form of organizing work globally. This paper reports causal evidence on how the extent of hybrid work—the number of days worked from home relative to days worked from the office—affects work outcomes. Collaborating with an...  View Details
Keywords: Hybrid Work; Remote Work; Work-from-home; Field Experiment; Employees; Geographic Location; Performance; Work-Life Balance
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