How CEO Gender Shapes Interpretation of Financial Information: Evidence from an Experimental Study

Last registered on February 04, 2026
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Pre-Trial

Trial Information

General Information

Title
How CEO Gender Shapes Interpretation of Financial Information: Evidence from an Experimental Study
RCT ID
AEARCTR-0017595
Initial registration date
January 29, 2026

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
February 04, 2026, 9:56 AM EST

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

Locations

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Primary Investigator

Name
Beatrice Ferrario
Affiliation
Harvard University
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Other Primary Investigator(s)

PI Name
Marcela Carvalho
PI Affiliation
London Business School
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Additional Trial Information

Status
In development
Start date
2026-01-26
End date
2026-02-27
Keywords
Behavior, Finance & Microfinance, Firms & Productivity, Gender
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study is a second wave of a previously conducted experiment in which we surveyed three sections of MFA students at LBS. The design and randomization procedures are unchanged; the second wave is slightly streamlined to reduce completion time.
In the first wave, we anticipated that a sample of roughly 300 students might provide limited statistical power. The results were directionally consistent with our hypotheses but only weakly significant (typically at the 10% level). We are therefore re-running the same experiment in a very similar population—MBA students at LBS—to increase the sample size and improve statistical precision.
Below is the abstract for the second wave of the experiment.

Participants complete two rounds of a forecasting task. Each round begins with a short case about a retail firm that is presented to students as fictional but adapted from a real public company: the financial statements and EPS history are real, while the firm’s name and any identifying details are withheld. After reading the case, participants report a prior EPS forecast and two relative-rank judgments—managerial talent of the CEO and the firm’s fundamentals—on a 0–100 scale relative to retail peers of similar size. The case embeds two independent manipulations: (i) CEO gender, randomized via first name and pronouns while all other text is held constant, and (ii) an information display consisting of noisy signals of the true EPS realization labeled as “experts’ forecasts,” accompanied by a single paragraph that contextualizes those signals; the signals are randomized to be optimistic or pessimistic in each round. Participants then provide posterior values for the same three outcomes.
External Link(s)

Registration Citation

Citation
Carvalho, Marcela and Beatrice Ferrario. 2026. "How CEO Gender Shapes Interpretation of Financial Information: Evidence from an Experimental Study." AEA RCT Registry. February 04. https://doi.org/10.1257/rct.17595-1.0
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Experimental Details

Interventions

Intervention(s)
Participants complete two rounds of a forecasting task. In each round, they read a short, standardized case about a retail firm and make an initial EPS forecast. The intervention embeds two orthogonal manipulations: (1) CEO gender randomization and (2) information signal randomization (optimistic vs. pessimistic).
CEO gender randomization: In each round, the perceived gender of the CEO is randomized by swapping only the CEO’s first name and corresponding pronouns from a pre-specified list of gender-diagnostic names. All other case content (firm facts, financials, layout, length, tone) is held constant, and no additional gender cues are introduced. Each participant is exposed to one female-named CEO and one male-named CEO across the two rounds.
Information signal randomization (optimistic vs. pessimistic): After the initial forecast, participants see three noisy signals of the true EPS realization labeled as “experts’ forecasts.” In each round, this set is randomized to be either optimistic (all signals above the true EPS realization known to the researchers) or pessimistic (all below), with equal probability. The three experts’ forecasts are paired with a brief text that contextualizes the signals; these texts are generated by a large language model trained on analysts’ reports to emulate sell-side language and framing.
The two manipulations—CEO gender and the sign of the experts’ signals—are randomized independently in each of the two rounds at the participant × round level.
Intervention Start Date
2026-01-26
Intervention End Date
2026-02-27

Primary Outcomes

Primary Outcomes (end points)
In each of the two rounds, our primary outcomes are the participant’s prior and posterior beliefs for three items: (i) a point EPS forecast for the focal firm, (ii) the CEO’s managerial talent, and (iii) the firm’s fundamentals. For talent and fundamentals, participants place the CEO/firm on a 0–100 relative-rank scale among retail firms of similar size (higher = better). Prior measures are elicited immediately after reading the case; posterior measures are re-elicited after the information display labeled as experts’ forecasts.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Participants complete two rounds of a forecasting task. Each round begins with a short case about a retail firm that is presented to students as fictional but adapted from a real public company: the financial statements and EPS history are real, while the firm’s name and any identifying details are withheld. After reading the case, participants report a prior EPS forecast (incentivized) and two relative-rank judgments—managerial talent of the CEO and the firm’s fundamentals—on a 0–100 scale relative to retail peers of similar size (not incentivized). Each participant is shown one male-named CEO and one female-named CEO across the two rounds. The case embeds two independent manipulations: (i) CEO gender, randomized via first name and pronouns while all other text is held constant, and (ii) an information display consisting of noisy signals of the true EPS realization labeled as “experts’ forecasts,” accompanied by a single paragraph that contextualizes those signals; the signals are randomized to be optimistic or pessimistic in each round. Participants then provide posterior values for the same three outcomes. Randomizations occur independently in every round.
Experimental Design Details
Not available
Randomization Method
Done by computer.
Randomization Unit
Both the ceo-gender and the news signal randomization are implemented at student round
level and they are independent between each other.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
The experiment is conducted on a voluntary participation basis. Participants will be recruited by distributing the survey link through mailing lists of MBA and MiM students. Data collection will stop once 200 completed responses are reached. We target 200 participants as an optimistic upper bound on feasible recruitment.
Sample size: planned number of observations
Each participants completes two exercises for a total of 400 participant x firm sample
Sample size (or number of clusters) by treatment arms
CEO gender is perfectly balanced at the individual level: each participant is exposed to exactly one male-led firm and one female-led firm. The gender of the first CEO is randomly assigned; conditional on this assignment, the gender of the second CEO is deterministically set to ensure balance within participant.
The news treatment is balanced in expectation at the sample level but not within participant. That is, participants are not constrained to observe both positive and negative news; instead, news realizations are randomly assigned such that positive and negative news occur with equal probability in the full sample.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Research Ethics Committee at London Business School
IRB Approval Date
2026-01-26
IRB Approval Number
REC1090
Analysis Plan