Knowledge about Child Care in Germany and Policy Preferences

Last registered on November 30, 2022

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Pre-Trial

Trial Information

General Information

Title

Knowledge about Child Care in Germany and Policy Preferences

RCT ID

AEARCTR-0010455

Initial registration date

November 22, 2022

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 30, 2022, 2:56 PM EST

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

Locations

Country

Germany

Region

Primary Investigator

Name

Fabian Mierisch

Affiliation

Catholic University Eichstaett-Ingolstadt

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Henning Hermes

PI Affiliation

Düsseldorf Institute for Competition Economics

PI Name

Philipp Lergetporer

PI Affiliation

Technical University Munich

PI Name

Guido Schwerdt

PI Affiliation

University of Konstanz

PI Name

Simon Wiederhold

PI Affiliation

Catholic University Eichstaett-Ingolstadt

Additional Trial Information

Status

On going

Start date

2022-08-01

End date

2023-03-31

Keywords

Education

Additional Keywords

Child Care, Discrimination, Experiment

JEL code(s)

J13, I24, C93, J15

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

There is a persistent enrollment gap in early child care by migration background in Germany. This raises the question why policy interventions to mitigate this gap are not implemented. By means of a representative Germany-wide survey and randomized survey experiments, we investigate the causal effect of information about the early child care system on participants’ support for various policies that aim at closing the enrollment gap between migrants and natives.

External Link(s)

Registration Citation

Citation

Hermes, Henning et al. 2022. "Knowledge about Child Care in Germany and Policy Preferences." AEA RCT Registry. November 30. https://doi.org/10.1257/rct.10455-1.0

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

We use a Germany-wide representative survey to conduct our experiment. In the survey, we randomly provide information about the early child care system in Germany to participants. We organize this information in four different treatment groups and one control group, which does not receive additional information. We then investigate whether the information provided had an effect on preferences for four different policies that aim at closing the existing enrollment gap between migrants and natives in the German early child care system.

Intervention Start Date

2022-11-14

Intervention End Date

2022-12-09

Primary Outcomes

Primary Outcomes (end points)

• Policy Preferences:
First, we assess preferences for four policies that have the potential to close the enrollment gap between native and migrant children in early child care in Germany. We measure preferences on a five point Likert scale from "1 – I completely disagree" to "5 – I completely agree".

• Discrimination Source:
Second, we ask participants how they would explain existing discrimination in the admission process against migrants, using a multiple choice list design.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We will conduct heterogeneity analyses by respondents’ migration background, political affiliation, parent status, stated priors, and education background.

Secondary Outcomes (explanation)

Experimental Design

We conduct a survey experiment to investigate respondents’ support of policy measures to mitigate enrollment gaps in German early child care. To do so, we randomly inform respondents about various existing inequalities in the German early child care system. We then measure the causal effect of this information provision on policy preferences

Experimental Design Details

Randomization Method

Randomization by survey software

Randomization Unit

Participant level

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Sample size: planned number of observations

6'000 survey participants.

Sample size (or number of clusters) by treatment arms

We have five treatment arms (including the control group) at planned 6'000 survey participants, which results in ~1'250 observations per treatment arm dependent on the randomization.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

With a sample of 6’000 respondents, five treatment arms and 80% power at the 5% significance level, the minimum detectable effect size is at around 0.04 of a difference in the mean scale points between two treatment conditions. Similarly, assuming a mean of 50% and a sample of 6’000 respondents, the minimum detectable effect size is at around a 4% difference in the mean of selected reasons for discrimination.

Supporting Documents and Materials

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