The Determinants and Political Economy Consequences of Empathy

Last registered on May 21, 2025

View Trial History

Pre-Trial

Trial Information

General Information

Title

The Determinants and Political Economy Consequences of Empathy

RCT ID

AEARCTR-0015969

Initial registration date

May 13, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

May 21, 2025, 2:23 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

United States of America

Region

National

Primary Investigator

Name

Raeed Kabir

Affiliation

University of Alabama

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Reshmaan Hussam

PI Affiliation

Harvard Business School

Contact Investigator

Additional Trial Information

Status

In development

Start date

2024-04-16

End date

2025-05-25

Keywords

Behavior, Gender, Welfare

Additional Keywords

empathy, race, political economy

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

We use novel approaches to measure 'empathy' and show these are stable traits among decision-makers. We investigate sources of heterogeneity within these measures and how these correlate with policy preferences such as support for redistribution.

External Link(s)

Registration Citation

Citation

Hussam, Reshmaan and Raeed Kabir. 2025. "The Determinants and Political Economy Consequences of Empathy." AEA RCT Registry. May 21. https://doi.org/10.1257/rct.15969-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We use a survey experiment to measure key outcomes and test the stability of said outcomes.

Intervention (Hidden)

We measure several dimensions of empathy. We are primarily interested in whether information interventions and nudges can change average levels of empathy. We also are interested in whether these interventions impact policy support or interact with empathy to differentially predict policy support.

Intervention Start Date

2025-05-15

Intervention End Date

2025-05-25

Primary Outcomes

Primary Outcomes (end points)

empathy (several types including race, gender, wealth, physical attributes like weight, hair, vision), several likert-style questions on policy views on redistribution and fairness

Primary Outcomes (explanation)

We calculate empathy in a domain by asking people of various types (different races, for example) how they would feel if they became a different type. We assume that the other group's average answer to this symmetric question is the truth and calculate empathy to be how far you are from the "truth." We repeat across several types and domains of empathy. We use a very standard format of questions to elicit how much survey participants support various progressive policies.

Secondary Outcomes

Secondary Outcomes (end points)

Social desirability scale, Capital Adjustment Number survey questions, PHQ-8 (mental depression scale)

Secondary Outcomes (explanation)

Experimental Design

We employ a survey experiment in Qualtrics where we use built-in randomization software to assign various information treatments (text or video) to participants at various points in the survey. We ask several deep behavioral questions to see how these information treatments impact these behavioral parameters.

Experimental Design Details

There are several interventions. We block the first information treatment on race and gender (only on black and white respondents) where we inform them on several statistics on the wealth gap in the U.S. across gender and racial lines. After each of the treatments we describe in this study, the survey experience for all subjects (regardless of treatment assignment) converge, and the treatment assignment occurs on the full sample. Then, there is a video treatment that is intended to elicit emotions - one that elicits joy (happy video of transplant recipient meeting donor), one that elicits sadness (video of a news story about a Ukranian soldier who passed away in the recent war), and one that is a control. All subjects see one video, each with equal likelihood. Another treatment is blocked on white participants who each have a 50% chance of being informed of their racial empathy score. Then there are a series of policy questions, two of which have information treatment embedded. There is a question on policy support for Food stamps, and 50% of subjects are exposed to additional information about Food Stamps. We do the same for policy support for Universal Healthcare.

Randomization Method

randomization using Qualtrics software

Randomization Unit

subject level randomization

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

900 individuals (no clustering)

Sample size: planned number of observations

900

Sample size (or number of clusters) by treatment arms

We treat each intervention as distinct. Thus, for each intervention described above with 2 treatment arms, the sample split is expected to be 450 and 450. For the video treatment, we anticipate 300, 300, and 300 to be the sample sizes per arm.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB