Publications
Publications
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- All HBS Web
(408)
- Faculty Publications (94)
- July 2023
- Article
So, Who Likes You? Evidence from a Randomized Field Experiment
By: Ravi Bapna, Edward McFowland III, Probal Mojumder, Jui Ramaprasad and Akhmed Umyarov
With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by... View Details
- 2023
- Working Paper
Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation
By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov
Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to... View Details
- February 2023
- Article
Increasing the Demand for Workers with a Criminal Record
By: Zoë Cullen, Will Dobbie and Mitchell Hoffman
State and local policies increasingly restrict employers’ access to criminal records, but without
addressing the underlying reasons that employers may conduct criminal background checks.
Employers may thus still want to ask about a job applicant’s criminal record... View Details
- 2023
- Working Paper
Life After Death: A Field Experiment with Small Businesses on Information Frictions, Stigma, and Bankruptcy
By: Shai Benjamin Bernstein, Emanuele Colonnelli, Mitchell Hoffman and Benjamin Iverson
In a randomized control trial (RCT) with U.S. small businesses, we document that a large share of firms are not well-informed about bankruptcy. Many assume that bankruptcy necessarily entails the death of a business and do not know about Chapter 11 bankruptcy, where... View Details
- December 2022
- Article
Social Skills Improve Business Performance: Evidence from a Randomized Control Trial with Entrepreneurs in Togo
By: Stefan Dimitriadis and Rembrand Koning
Recent field experiments demonstrate that advice, mentorship, and feedback from randomly assigned peers improve entrepreneurial performance. These results raise a natural question: what is preventing entrepreneurs and managers from forming these peer connections... View Details
- 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
- 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
- June 2022 (Revised January 2025)
- Technical Note
Causal Inference
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
- 2022
- Working Paper
Is Hybrid Work the Best of Both Worlds? Evidence from a Field Experiment
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
- 2022
- Working Paper
Do Startups Benefit from Their Investors' Reputation? Evidence from a Randomized Field Experiment
By: Shai Benjamin Bernstein, Kunal Mehta, Richard Townsend and Ting Xu
We analyze a field experiment conducted on AngelList Talent, a large online search platform for startup jobs. In the experiment, AngelList randomly informed job seekers of whether a startup was funded by a top-tier investor and/or was funded recently. We find that the... View Details
- Article
Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)
By: Eva Ascarza and Ayelet Israeli
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details
- March 2022
- Article
Sensitivity Analysis of Agent-based Models: A New Protocol
By: Emanuele Borgonovo, Marco Pangallo, Jan Rivkin, Leonardo Rizzo and Nicolaj Siggelkow
Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such... View Details
- February 15, 2022
- Article
How Managers Can Build a Culture of Experimentation
By: Frank V. Cespedes and Neil Hoyne
Testing in business presents qualitatively different challenges than those in clinical trials and most scientific research. There are very few opportunities for randomized control experiments in a changing, competitive market. Yet, change and competition make testing a... View Details
- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
- November 2021
- Article
Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective
By: Iavor Bojinov, Ashesh Rambachan and Neil Shephard
In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative... View Details
- Article
Using Fresh Starts to Nudge Increased Retirement Savings
By: John Beshears, Hengchen Dai, Katherine L. Milkman and Shlomo Benartzi
We conducted a field experiment to study the effect of framing future moments in time as new beginnings (or “fresh starts”). University employees (N=6,082) received mailings with an opportunity to choose between increasing their contributions to a savings plan... View Details
- October 2021
- Article
Changing Gambling Behavior through Experiential Learning
By: Shawn A. Cole, Martin Abel and Bilal Zia
This paper tests experiential learning as a debiasing tool to reduce gambling in South Africa, through a randomized field experiment. The study implements a simple, interactive game that simulates the odds of winning the national lottery through dice rolling.... View Details
- Article
Measuring the Scientific Effectiveness of Contact Tracing: Evidence from a Natural Experiment
By: Thiemo Fetzer and Thomas Graeber
Contact tracing has for decades been a cornerstone of the public health approach to epidemics, including Ebola, severe acute respiratory syndrome, and now COVID-19. It has not yet been possible, however, to causally assess the method’s effectiveness using a randomized... View Details
- 2023
- Working Paper
Should Human Capital Development Programs Be Voluntary or Mandatory? Evidence from a Field Experiment
By: Jason Sandvik, Richard Saouma, Nathan Seegert and Christopher Stanton
In a field experiment, we find large differences in productivity treatment effects between voluntary and mandatory workplace mentorship programs. A significant portion of this difference is due to the best employees opting into the program when it is voluntary and... View Details
- July 2021
- Article
Invisible Inequality Leads to Punishing the Poor and Rewarding the Rich
By: Oliver P. Hauser, Gordon T. Kraft-Todd, David Rand, Martin A. Nowak and Michael I. Norton
Four experiments examine how the lack of awareness of inequality affects behaviour towards the rich and poor. In Experiment 1, participants who became aware that wealthy individuals donated a smaller percentage of their income switched from rewarding the wealthy to... View Details
Keywords: Income Transparency; Income; Wealth; Equality and Inequality; Knowledge; Behavior; Outcome or Result; Society; Policy