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ESG and Corporate Bailouts: September 2020 Survey

Last registered on September 29, 2020
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Pre-Trial

Trial Information

General Information

Title
ESG and Corporate Bailouts: September 2020 Survey
RCT ID
AEARCTR-0006542
Initial registration date
September 29, 2020

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
September 29, 2020, 7:31 AM 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

Primary Investigator

Name
Emanuele Colonnelli
Affiliation
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Niels Gormsen
PI Affiliation
University of Chicago, Booth School of Business
Contact Investigator

Additional Trial Information

Status
In development
Start date
2020-09-29
End date
2020-10-31
Keywords
Finance & Microfinance, Firms & Productivity, Governance
Additional Keywords
JEL code(s)
Secondary IDs
Abstract
This project aims to understand whether and how perceptions and salience about corporate ESG affect support for corporate bailouts and related policies.
External Link(s)

Registration Citation

Citation
Colonnelli, Emanuele and Niels Gormsen. 2020. "ESG and Corporate Bailouts: September 2020 Survey." AEA RCT Registry. September 29. https://doi.org/10.1257/rct.6542-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
This project aims to understand whether and how perceptions and salience about corporate ESG affect support for corporate bailouts and related policies. Compared to the May 2020 survey, this survey aims at (a) replicating the main results of our original study at a different point in time and (b) obtaining additional outcome measures, namely costly behavioral actions and open-ended questions.
Intervention Start Date
2020-09-29
Intervention End Date
2020-10-31

Primary Outcomes

Primary Outcomes (end points)
Our main outcomes are the questions on support for corporate bailouts. We ask the same self-reported question we asked in May 2020 (support for corporate bailouts from 0 to 10). Importantly, we added three more questions aimed at measuring “support for bailouts”, involving a real (costly) action from the respondent. First, we ask whether they would like to donate part of their winnings (via a lottery) to a non-profit organization (Business Roundtable) that represents executives of large American corporations (as a way to capture not just the support for a specific policy, like bailouts, but more broadly a change in attitude towards supporting large corporations). Second, we ask whether they would like to sign a petition that asks the House of Representatives and the Senate to provide additional bailout money to large corpo- rations. Third, we ask them to give us the OK to send a message to Senators of their choice, with their name in the signature, asking to support or oppose bailouts (we think our treatment will make it less likely to sign the support email, and more likely to sign the oppose email).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
We will analyze open-ended questions using primarily LDA machine learning algorithms. That is, we plan to classify profiles based on the responses, and see whether our treatment is more likely to lead to a specific profile (e.g. respondents who don't trust corporations or the government).
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This project aims to understand whether and how perceptions and salience about corporate ESG affect support for corporate bailouts and related policies.
Experimental Design Details
This project aims to understand whether and how perceptions and salience about corporate ESG affect support for corporate bailouts and related policies. We do so by means of an experimental survey where we randomly vary individual perceptions of ESG practices of large corporations through original short animated videos.
Randomization Method
The randomization is done by our research partner using a computer.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2000 individuals
Sample size: planned number of observations
2000 individuals
Sample size (or number of clusters) by treatment arms
1000 control, 1000 ESG-Neg
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
The University of Chicago Social and Behavioral Sciences Institutional Review Board
IRB Approval Date
2020-09-28
IRB Approval Number
IRB20-0543-AM003 (exempt)
Analysis Plan

Analysis Plan Documents

ColonnelliGormsen_PAP_SeptemberSurvey.pdf

MD5: d48796a64e6f8ddf42d02eed130d2f2a

SHA1: 1d2c57498353e79752a48828baf6e15d601ff32a

Uploaded At: September 29, 2020

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials