Quotas and the Labor Market

Last registered on December 03, 2021

Pre-Trial

Trial Information

General Information

Title
Quotas and the Labor Market
RCT ID
AEARCTR-0008604
Initial registration date
December 01, 2021

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
December 03, 2021, 7:12 PM EST

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

Locations

Primary Investigator

Affiliation
University of Cologne

Other Primary Investigator(s)

PI Affiliation
University of Cologne
PI Affiliation
University of Cologne
PI Affiliation
TU Braunschweig

Additional Trial Information

Status
In development
Start date
2021-12-03
End date
2022-04-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Quotas are often discussed as an engineering tool to combat discrimination in hiring decisions. Their effects within competitive labor markets, however, are not well understood yet. Indeed if quotas for promotions are enforced, a promotion can be a signal of lower ability
for those who are discriminated and can lead to lower wage offers on the labor market. On the one side this might harm those who have high ability and who would have received higher wage offers without quotas. On the other side this might also harm those with low ability, since not having been promoted even though the quota was in place is a very bad signal. We aim to investigate the behavioral effects of these mechanisms. We experimentally investigate the effect of quotas in a competitive labor market. Our setting is based on a model by Waldman (1984) which has been extended to explain discrimination and study quotas by Gürtler and Gürtler (2019). Three employers compete for six employees after promotion signals have been revealed to the market. In a baseline treatment employers and employees belong to the same group. In this setting no discrimination regarding promotions is expected. In a second treatment two groups are induced and endogenous statistical discrimination should occur, i.e., different equilibria should be selected. In a third treatment quotas are added.
External Link(s)

Registration Citation

Citation
Grundner, Stefan et al. 2021. "Quotas and the Labor Market." AEA RCT Registry. December 03. https://doi.org/10.1257/rct.8604
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-12-03
Intervention End Date
2022-04-30

Primary Outcomes

Primary Outcomes (end points)
The key outcome variables are the promotion decision of employers dependent on the treatments and the wage offers to employees. Since we ask employers and employees about their expectations of (other) employers' behavior, we can interpret wage offers dependent on ability/promotion decision and expectations of other employers' wage offers.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In our experiment, we introduce color groups. Each participant is assigned to one color group. Interacting participants might belong to the same or different color groups. Furthermore, participants are assigned a role. They either are employers or employees. Participants are sorted into labor markets such that each labor market includes 3 employers and 6 employees. Each employer is paired with two employees of her labor market. These employees are her current employees. Employees have a randomly assigned ability (high, low), which determines how valuable their work is for the employer. Depending on the employees' ability, employers decide which of their two current employees they want to promote. They have to promote one of them. They cannot promote both. The other employers in the labor market do not observe the ability of employees who they don't employ currently. The promotion decision on the other hand is visible. Also, employers can make a wage offer to their own employees and the other four employees in their labor market. For their own employees they can make the wage offer dependent on their abilities. For the other employees they can make their wage offer only dependent on whether or not the employee is promoted by her original employer. Subsequently, a set of rules decides for whom the employees will work. In the experimental treatments we vary the color group composition of employers and employees. We expect first, that employers are more likely to promote their employees from the same color group if they have the same ability as the current employee from a different color group and second, that employers expect other employers to act alike. Consequently, the expected ability of a promoted employee who belongs to the color group of her employer is lower than the expected ability of a promoted employee who does not belong to the the color group of her employer. We expect to see this difference reflected in wage offers to employees.
Experimental Design Details
For full transparency we note that we conducted an earlier version of this experiment in 2019. In both versions, employers' payoff is determined by the productivity of their employees minus the wage they pay to their employees. In the earlier version of the experiment we found that many employers paid their employees half of their productivity as wage. These observed wages were higher then the competitive wages predicted theoretically in all equilibria we expected to observe in different treatments. We concluded that we could not observe treatment differences in wages because of this unexpectedly "fair" behavior.
In the new design of the experiment, competition for employees should force employers to pay wages above half of the productivity of their employees and hence we expect treatment differences due to discriminatory behavior in our treatments.
Since from an ethical perspective no relevant changes have been made in the design we use the same IRB approval and notified the IRB about the updated design.
Randomization Method
Random assignment of participants to an experiment slot.
Randomization Unit
experimental session
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
We do not plan to use clusters in the data analysis
Sample size: planned number of observations
240 observational units (1 employer + 2 employees), 720 participants
Sample size (or number of clusters) by treatment arms
48 observations per treatment (5 treatments: Baseline, Color groups, Color group with quota rule 1, Color group with quota rule 2, Color group with quota rule 3) from the ORSEE pool of the Cologne Laboratory of Economic Research
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Comittee of the Wiso Faculty of the University of Cologne
IRB Approval Date
2019-07-24
IRB Approval Number
19021BI

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