Publications

Article

Optimality Bias in Moral Judgment

By: Julian De Freitas and Samuel G.B. Johnson

We often make decisions with incomplete knowledge of their consequences. Might people nonetheless expect others to make optimal choices, despite this ignorance? Here, we show that people are sensitive to moral optimality: that people hold moral agents accountable... View Details

Keywords: Moral Judgment; Lay Decision Theory; Theory Of Mind; Causal Attribution; Moral Sensibility; Decision Making

2023
Working Paper

Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection

By: Edward McFowland III, Sriram Somanchi and Daniel B. Neill

In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention’s effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides... View Details

Keywords: Causal Inference; Program Evaluation; Algorithms; Distributional Average Treatment Effect; Treatment Effect Subset Scan; Heterogeneous Treatment Effects

Article

Your Visual System Provides All the Information You Need to Make Moral Judgments about Generic Visual Events

By: Julian De Freitas and George A. Alvarez

To what extent are people's moral judgments susceptible to subtle factors of which they are unaware? Here we show that we can change people’s moral judgments outside of their awareness by subtly biasing perceived causality. Specifically, we used subtle visual... View Details

Keywords: Moral Judgment; Perceived Causality; Visual Illusions; Moral Sensibility; Judgments

December 2017
Article

Discordant vs. Harmonious Selves: The Effects of Identity Conflict and Enhancement on Sales Performance in Employee-Customer Interactions

By: Lakshmi Ramarajan, Nancy Rothbard and Steffanie Wilk

Across multiple studies, we examine how identity conflict and enhancement within people affect performance in tasks that involve interactions between people through two mechanisms: role-immersion, operationalized as intrinsic motivation, and role-taking,... View Details

Keywords: Identity; Interpersonal Communication; Sales; Performance

March 2016 (Revised March 2022)
Teaching Note

Evive Health and Workplace Influenza Vaccinations

By: John Beshears

Evive Health is a company that manages communication campaigns on behalf of health insurance plans and large employers. Using big data techniques and insights from behavioral economics, Evive deploys targeted and effective messages that improve individuals' health... View Details

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March 2016
Case

Evive Health and Workplace Influenza Vaccinations

By: John Beshears

Evive Health is a company that manages communication campaigns on behalf of health insurance plans and large employers. Using big data techniques and insights from behavioral economics, Evive deploys targeted and effective messages that improve individuals' health... View Details

Keywords: Vaccination; Influenza; Flu Shot; Preventive Care; Health Care; Behavioral Economics; Choice Architecture; Nudge; Experimental Design; Randomized Controlled Trial; RCT; Causal Inference; Consumer Behavior; Health Care and Treatment; Health Testing and Trials; Communication Strategy; Health Industry

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June 2012
Article

Consequence-Cause Matching: Looking to the Consequences of Events to Infer Their Causes

By: Robyn A. LeBoeuf and Michael I. Norton

We show that people non-normatively infer event causes from event consequences. For example, people inferred that a product failure (computer crash) had a large cause (widespread computer virus) if it had a large consequence (job loss), but that the identical failure... View Details

Keywords: Causal Inference; Product; Forecasting and Prediction; Motivation and Incentives; Failure

February 1994
Background Note

By: Arthur Schleifer Jr.

Discusses what causation is and what one can (and cannot) learn about causation from observational (nonexperimental) data. View Details

Keywords: Decision Making; Analytics and Data Science; Interests

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Research Summary

Overview

By: Eva Ascarza

Professor Ascarza’s research primarily focuses on providing researchers and marketers a better understanding of how to manage customer retention so as to reduce churn and increase firm’s profitability. She addresses these issues by building empirical models of customer... View Details

Keywords: Customer Retention; Churn; Field Experiments

Research Summary

Overview

By: Ashley V. Whillans

Engaged with field work in East Africa, South Asia, and in several large hybrid organizations in the United States, Professor Whillans places a focus on exploring questions with strong theoretical motivation in the social psychological literature and relevant... View Details

Forthcoming
Article

Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments

By: Kosuke Imai and Michael Lingzhi Li

Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details

Keywords: AI and Machine Learning; Mathematical Methods