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Labor Market Information and Education Decisions

Last registered on September 01, 2018

Pre-Trial

Trial Information

General Information

Title
The Role of Labor Market Information in Education Decisions
RCT ID
AEARCTR-0003220
Initial registration date
August 31, 2018

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
September 01, 2018, 6:52 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
Maastricht University

Other Primary Investigator(s)

PI Affiliation
Erasmus University Rotterdam
PI Affiliation
Maastricht University

Additional Trial Information

Status
In development
Start date
2018-09-03
End date
2020-09-01
Secondary IDs
Abstract
Education is known to affect the labor market prospects of individuals. The experimental literature shows that beliefs about how education influences labor market prospects plays a role in decisions on whether, where and in what study program to enroll. However, the effects are not always large and differ strongly by subpopulation. Moreover, a number of potentially influential factors have not been studied yet. While many studies provide different types of information, none has looked at the potentially detrimental effect of information overload. Furthermore, while information is often provided by an individual, the effect of the individual on the use of information has not been studied yet. With this paper, we hope to provide more evidence on the effect of labor market information in education decisions and fill in some of the existing gaps in the literature.
External Link(s)

Registration Citation

Citation
de Koning, Bart, Robert Dur and Didier Fouarge. 2018. "The Role of Labor Market Information in Education Decisions." AEA RCT Registry. September 01. https://doi.org/10.1257/rct.3220-1.0
Former Citation
de Koning, Bart, Robert Dur and Didier Fouarge. 2018. "The Role of Labor Market Information in Education Decisions." AEA RCT Registry. September 01. https://www.socialscienceregistry.org/trials/3220/history/33777
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Experimental Details

Interventions

Intervention(s)
See experimental design.
Intervention Start Date
2018-09-03
Intervention End Date
2019-07-20

Primary Outcomes

Primary Outcomes (end points)
Rankings of occupations; Elicited beliefs about occupations' labor market prospects; (Intended) study profile choice;
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In this experiment, we aim to investigate the role of labor market information in education decisions. Dutch preparatory vocational education students select five occupations that fit their preferences and aptitudes according to a test. They are then asked to rank these occupations on the basis of how much they would like to pursue that occupation and state their beliefs about the labor market prospects of the occupations. Subsequently, we provide a number of treatment groups with information about the actual labor market prospects of the different occupations and observe how this changes the students' attitudes towards the occupations, their beliefs about the labor market prospects of the occupations and their study profile choice. Moreover, we estimate whether the use of information is influenced by who provides it and whether more information influences students' sensitivity to the information.

The proposed experiment takes place within the online career counseling platform of Qompas. The platform provides preparatory vocational education students with computer assignments and tests to do in class. One of the tests is the so-called occupation test. In this test, students answer a number of questions about themselves and potential occupations. Based on the answers given, Qompas calculates a score for each of the 353 occupations in their system. This score represents how well the occupation fits the student's preferences and aptitudes. After the test, the students are shown their scores. They are subsequently asked what study profile they intend to choose. In the Netherlands, students choose a profile after the first two years in preparatory vocational education. This profile dictates the courses students take and therefore what study programs they will be eligible for. Once this question has been answered, the students select the five occupations they are most interested in pursuing out of the twenty occupations they scored highest on. After picking the occupations, the students are shown information about the work content of these occupations. Subsequently, they are asked to rank the five occupations on the basis of how much they would like to pursue that occupation. When making the ranking, the study profiles associated with the different occupations are shown. The experiment starts after the first ranking.

After the ranking, the students are asked about their beliefs about the labor market prospects of the different occupations. They are asked to estimate both the opportunities of finding a job in six years and the current hourly wage of intermediate vocational education graduates for the selected occupations. The opportunities of finding a job can be either very good, good, reasonable, bad or very bad. The options for the hourly wage range between 10 and 26 Euros, with 1 Euro intervals. These beliefs are elicited so that we know in what direction the provided information influences the beliefs of the student.

Once the beliefs are elicited, students are shown a number of screens, depending on the treatment group they belong to. On the school level, students are randomized into five groups: one control group and four treatment groups.

The control group is shown no information about the labor market prospects of different occupations and is therefore shown no sender either. Treatment 1 is given information about just the job opportunities and shown a human information sender. Treatment 2 gets information on just job opportunities as well, but is not shown a human information sender. Instead, students are told the research center for education and the labor market provides them with the information. Treatment 3 and 4 are shown the same senders as treatments 1 and 2, respectively. However, in treatments 3 and 4, students are provided with information about both the opportunities of finding a job and hourly wages.

The information about job opportunities is taken from the research center for education and the labor market’s biannual labor market forecasts. These forecasts predict the job opportunities for 113 different occupational groups in six years. The Qompas occupations are divided over these occupational groups. The information about the gross hourly wage is taken from administrative data. It is the median hourly wage for individuals who graduated from an intermediate vocational education program and work in the occupational group associated with the Qompas occupation.

The human ‘information senders’ are employees of the research center for education and the labor market. Senders are divided into four groups: inexperienced male researchers, experienced male researchers, inexperienced female researchers and experienced female researchers. A researcher that does not have a Ph.D. (yet) is considered inexperienced, whereas a researcher with a Ph.D. is considered experienced. For each sender, the name and experience are shown. Gender is not explicitly mentioned, but the names of all senders are indicative of their gender and the word ‘researcher’ is different for men and women in Dutch. No pictures of the sender are shown either, so as to avoid bias caused by appearance unrelated to status or gender.

To ensure that all groups have some time to think about their ranking based on being asked about their beliefs and potentially the information presented to them, all groups are shown a video about work in general after the first ranking (control group) or information provision (treatment groups). The video does not mention the relation between education and job opportunities or wages.

After the video, the students are asked to rank the five selected occupations a second time. They are shown their first ranking and asked whether they want to change anything. To estimate how strongly beliefs change, beliefs are elicited again after the second ranking. Eliciting beliefs a second time allows us to see how beliefs are updated and is especially important to analyze the effect of information overload.

It is possible that students select occupations with very bad labor market prospects only. In this case, providing information is not very useful. To counteract this, students who selected only occupations that have very bad, bad or reasonable job opportunities are shown a number of alternative occupations. Based on a sample of historical data, approximately 20% of students is expected to select only such occupations. The occupations suggested are those with the best labor market prospects out of the twenty occupations they selected, ranked first on job opportunities and then on hourly wages. The difference between the control group and treatment groups lies in the information provided. The control group gets no information about why these occupations are suggested. Treatments 1 and 2 only get information about the job opportunities and treatments 3 and 4 get information about both the job opportunities and the hourly wages. After the alternative occupations are suggested, the students are asked whether they want to change their ranking one last time. In this ranking, they are allowed to include the alternative occupations. If students were not shown alternative occupations, they are not asked to rank the occupations a third time.

The ranking is subsequently included in their student file. The students are supposed to periodically review this file.

Before the end of the school year, the students have to choose a study profile. Unfortunately, it is not possible to match individual data from the experiment to administrative data. We therefore observe the choice of profile through a survey in the Qompas system. Historically, the response rate of this survey is low. Therefore, we also include a question about the intended profile choice at the end of the experiment.
Experimental Design Details
Randomization Method
Stratified randomization done on a computer.
Randomization Unit
School
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
286 schools
Sample size: planned number of observations
Approximately 35,000 students
Sample size (or number of clusters) by treatment arms
96 schools control, 47 schools treatment 1, 47 schools treatment 2, 48 schools treatment 3, 48 schools treatment 4
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

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