Beliefs about Labor Market Discrimination Against Female Job Applicants with a Migration Background

Last registered on November 21, 2023

Pre-Trial

Trial Information

General Information

Title
Beliefs about Labor Market Discrimination Against Female Job Applicants with a Migration Background
RCT ID
AEARCTR-0012471
Initial registration date
November 08, 2023

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
November 17, 2023, 7:53 AM EST

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

Last updated
November 21, 2023, 4:53 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
Institute for Employment Research

Other Primary Investigator(s)

PI Affiliation
Institute for Employment Research (IAB)

Additional Trial Information

Status
On going
Start date
2023-11-13
End date
2023-12-15
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We conduct a survey experiment in two waves in Germany to assess people’s beliefs about the extent of labor market discrimination and to examine to what extent these beliefs drive support for anti-discrimination policies. In the first wave, we elicit beliefs about discrimination by asking how likely a female candidate with Turkish-sounding names is to receive a callback for an interview relative to an identical female candidates with a German-sounding name. To isolate the role of religious signals, We assess beliefs about the callback rate for candidates with the same Turkish-sounding name with and without headscarf. We then provide a random subset of our respondents with information about the results from a correspondence study that found evidence of discrimination in the labor market. We design the experiment to differentiate the effect of two sources of information, namely academic versus newspaper. Subsequently, we assess belief updates immediately after the information treatment and measure self-reported support for anti-discrimination policies. Two weeks after the first wave, we verify the stability of belief updates and stated preferences in a follow-up survey. Exogenous variation in the beliefs induced by the treatment enables us to assess how beliefs affect the support for anti-discrimination policies that target helping migrants in the labor market.
External Link(s)

Registration Citation

Citation
Ehab, Maye and Sekou Keita. 2023. "Beliefs about Labor Market Discrimination Against Female Job Applicants with a Migration Background." AEA RCT Registry. November 21. https://doi.org/10.1257/rct.12471-2.1
Experimental Details

Interventions

Intervention(s)
The intervention is an information treatment. Respondents in treatment groups receive information about the results from a correspondence study conducted in Germany. The study finds evidence of hiring discrimination against women with a migration background signaled by their name.
Intervention Start Date
2023-11-13
Intervention End Date
2023-12-15

Primary Outcomes

Primary Outcomes (end points)
Beliefs about hiring discrimination against women with a migration background.
Support for antidiscrimination policies.
Primary Outcomes (explanation)
See pre-analysis plan.

Secondary Outcomes

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

Experimental Design

Experimental Design
We collect survey data on people’s beliefs about the extent of labor market discrimination against women with a Turkish background in Germany using an online panel. We first investigate to what extent beliefs respond to information from different sources. In a second step, we examine to what extent these beliefs drive support for anti-discrimination policies.

The experiment hast two waves separated by two weeks. In the first wave, we elicit prior beliefs from all respondents about the extent of discrimination against female applicants with a Turkish background in the German labor market. We also elicit post-treatment beliefs about hiring discrimination using qualitative scales as well as beliefs about discrimination in another market, namely, the carpooling market. This enables us to check if there are short-term belief updates based on the information provision. Furthermore, we ask questions about support for anti-discrimination policies. In the second wave, we ask again the same questions about beliefs about hiring discrimination in the labor market and the policy support questions.

In the first wave, we elicit prior beliefs distinguishing between beliefs attributed to the Turkish background and beliefs attributed to presumed religious affiliation. We present respondents with the same profiles used in the correspondence study by Weichselbaumer (2020), which we use as a benchmark for objectively measured callback discrimination. The Turkish background is signaled through the name of the applicant (Meryem Öztürk instead of Sandra Bauer) while all other characteristics that are part of the job application are held constant (including qualifications, age, German nationality, and photograph).

We present respondents with hypothetical job applicants who are identical in all dimensions except either their name or their profile picture (see main part in the appendix). We inform them about the callback rate for the reference scenario of a female applicant aged 27 named Sandra Bauer (candidate A), which is considered a German-sounding name. Respondents are asked to estimate the callback rate for another candidate for whom a Turkish background is signaled through the name (Meryem Öztürk instead of Sandra Bauer, candidate B) while all other characteristics are held constant (including qualifications, age, German nationality, and photograph). Using the same procedure, we isolate the specific role of religion by assessing beliefs about the callback rate for a third candidate with the same Turkish-sounding name (Meryem Öztürk) with photographs showing the same candidate with headscarf (candidate C). She is again compared to Sandra Bauer, i.e., the same candidate with a German-sounding name and without headscarf.

After eliciting the prior beliefs, respondents are allocated to one of three groups using computer-assisted randomization. The first two subsets of respondents (the treatment groups) receive information about the results from the correspondence study by Weichselbaumer (2020). In her study, the author tested for labor market discrimination by randomly varying (i) whether names on fictitious resumes were Turkish- or German-sounding or (ii) whether the photograph of candidates with a Turkish-sounding name were with or without headscarf. We present the first treatment group with information on the study results using a summary we wrote ourselves. We include a link to a YouTube video where the author presents the study results herself. We refer to this treatment as the academic treatment. We offer the second treatment group an excerpt from a newspaper article reporting on the same study results. We refer to this treatment as the newspaper treatment. The remaining respondents constitute the control group and do not receive any information from the research article. Instead, they receive a general article about gender differences in the labor market.

Following the information treatment, we measure post-treatment belief updates using explicit questions on beliefs about discrimination as well as results from a different correspondence study and assess preferences for anti-discrimination policies.

To reduce concerns regarding anchoring, we elicit post-treatment beliefs in the first wave in another market, namely, carpooling. This question uses a smaller range of possible answers (0-10 instead of 0-100) and success rates are much higher than in the job application study. These differences should make anchoring more difficult for respondents. Two weeks after the first wave, we measure again beliefs about hiring discrimination in the labor market and we elicit our respondents’ views regarding anti-discrimination policies. This second wave allows us to verify the stability of belief updates in response to the information provision in the first wave and to mitigate concerns about pure experimenter-demand effects.
Experimental Design Details
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Wave 1: 3.500 individual respondents from an online panel.
Wave 2: 2450 individual respondents after 70% attrition
Sample size: planned number of observations
Wave 1: 3.500 respondents from an online panel. Wave 2: 2450 respondents after 70% attrition
Sample size (or number of clusters) by treatment arms
1.166 individual respondents per treatment arm in the first wave.
816 individual respondents per treatment arm in the second wave after 70% attrition
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable effect size for the main outcomes is 0.15 of a standard deviation with 80% power.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics comittee of the Institute for Employment Research (IAB)
IRB Approval Date
2022-12-21
IRB Approval Number
N/A
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