Gender Differences in Work Advice: A Laboratory Investigation

Last registered on June 10, 2019

Pre-Trial

Trial Information

General Information

Title
Gender Differences in Work Advice: A Laboratory Investigation
RCT ID
AEARCTR-0004244
Initial registration date
June 05, 2019

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
June 10, 2019, 9:48 PM EDT

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

Locations

Region
Region

Primary Investigator

Affiliation
Lund University

Other Primary Investigator(s)

PI Affiliation
University of Sydney

Additional Trial Information

Status
In development
Start date
2019-06-06
End date
2020-12-01
Secondary IDs
Abstract
We use a laboratory experiment to investigate whether men and women receive different work advice in a setting where the quality of the advisee is ambiguous. At a later stage, we also aim to test whether a potential gender difference in advice is removed when advisors are provided with more objective indicators of the advisee's performance, and when they are not made aware of the advisee's gender.
External Link(s)

Registration Citation

Citation
Silva Goncalves, Juliana and Roel van Veldhuizen. 2019. "Gender Differences in Work Advice: A Laboratory Investigation." AEA RCT Registry. June 10. https://doi.org/10.1257/rct.4244
Former Citation
Silva Goncalves, Juliana and Roel van Veldhuizen. 2019. "Gender Differences in Work Advice: A Laboratory Investigation." AEA RCT Registry. June 10. https://www.socialscienceregistry.org/trials/4244/history/47827
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2019-06-06
Intervention End Date
2019-12-02

Primary Outcomes

Primary Outcomes (end points)
See the pre-analysis plan
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
See the pre-analysis plan
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We develop a novel experimental design in which one group of participants ("the workers") are asked to choose between two different jobs. A second group of participants ("the advisors") are asked to give advice to workers to help them make their decision. Workers write a short motivation letter that advisors can use to help determine their advice.
Experimental Design Details
Participants are invited to the laboratory and split in two groups: the "workers" and the "advisors". The experiment consists of two parts. In part one, half the participants ("the workers") work on a real-effort task that consists of adding five two-digit numbers for five minutes and receive a piece-rate payment as well as a bonus if their performance meets a certain performance threshold. The advisors do not do anything in this part of the experiment.

In part two, we tell workers that they will have to work on some other real-effort task, and can choose either an “(A)dvanced” or a “(B)asic” task. Workers know nothing else about the task. Instead, we match them to an advisor who is given more detailed information on the two tasks and can therefore give valuable advice to the worker. This mimics real life situations, where “advisors” (teachers, supervisors) may have more information about different career paths than workers or students. To help the advisor give informed advice, we ask the worker to prepare a statement describing their prior experience with mathematics tasks, and indicate their confidence in their ability on such tasks on a scale from 0-10.

We then ask all worker-advisor pairs to, one by one, verbally confirm their presence in the laboratory. As part of this process, each advisor will get to hear the voice of his/her matched worker (and vice versa). We use this method (originally due to Bordalo, Coffman, Gennaioli and Shleifer; AER, forthcoming) to allow advisors to reliably identify their worker's gender, without making it salient to participants that we are interested in gender differences in advice.

We then send the statement and confidence (which jointly refer to as the "motivation letter") to the advisor along with the motivation letters of four other workers in the experimental session. We ask the advisor to recommend task A or task B for all five workers, though only the advisor's actual matched worker will receive the advice he/she sends. The advisor does not know which of the five worker is his/her matched worker. This implies that it is incentive compatible for each advisor to treat each letter as if it was written by his/her worker.

Workers receive advice from their advisor, choose between the two tasks and subsequently work on their chosen task for 10 minutes. The actual task is the same as in part 1; the only difference is that in the basic task (B) participants were paid $13 if they solved at least $13 math problems (and zero otherwise), whereas they were paid $26 if they solved at least $26 problems in task A (and zero otherwise). While workers are working on the task, we ask advisors to go through all five letters again and tell us how confident they are that each worker will reach the respective threshold in each task on a scale from 0 to 10. We also ask them to specify the threshold for a minimum score achieved in part 1 for which they'd recommend the advanced task to a hypothetical worker. The experiment concludes by giving workers and advisors feedback on their earnings, having them go through a brief questionnaire asking them for their gender, what gender they thought their matched worker/advisor had, as well as a number of questions related to how they came to their advice (advisors only) and their risk preferences and self-confidence. The final part of the questionnaire is an implicit association test aimed at testing gender stereotypes.

Our initial sessions will have only this single baseline treatment. In future sessions, we expect to run two additional treatments that either (a) eliminate the procedure that reveals the gender of their partner to each participant or (b) additionally present advisors with the worker's score in part 1 when they are deciding what advice to give.
Randomization Method
Roles are assigned randomly when participants enter the experimental laboratory.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
160 participants (80 workers and 80 advisors)
Sample size: planned number of observations
160 participants (80 workers and 80 advisors)
Sample size (or number of clusters) by treatment arms
160 participants (80 workers and 80 advisors)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We expect to be able to detect a 14 percentage point gender gap in the fraction of workers receiving advice A. More details are in the pre-analysis plan.
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Sydney Human Research Ethics Committee
IRB Approval Date
2019-04-23
IRB Approval Number
2019/257
Analysis Plan

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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