Digital Skills: Socioeconomic Determinants and Social Inequality

Last registered on February 07, 2023


Trial Information

General Information

Digital Skills: Socioeconomic Determinants and Social Inequality
Initial registration date
January 31, 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
February 07, 2023, 11:24 AM EST

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



Primary Investigator

University of Hamburg

Other Primary Investigator(s)

PI Affiliation
LMU Munich
PI Affiliation
University of Würzburg & briq

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
With the digital transformation of labor, skills in connection with new technologies are becoming a key requirement for the future workforce. A recent literature demonstrates that economic returns to these skills are dramatically increasing, potentially affecting social mobility and inequality (Acemoglu & Restrepo 2021; Acemoglu et al. 2022; Alekseeva et al. 2021). In this study, we measure job-relevant digital skills of young adults in Germany using a novel and validated survey measure "youth Digital Skills Indicator" (Helsper et al. 2020). Drawing on longitudinal household survey data, we explore their socioeconomic determinants and compare skill levels of individuals from families with high socioeconomic status (SES) to those from low SES families. As a potential remedy to skills gaps, we study the causal impact of a randomized participation in a mentoring program during early childhood, which was designed to enrich the social environment of children from low SES families. Mentoring programs have not only been shown to have a positive long-term impact on learning capabilities and skills formation, but also to foster character traits, such as self-confidence, self-assessment, and attitudes (Deming 2009; Heckman & Mosso 2014; Kosse et al. 2020). Therefore, we also elicit individuals' confidence in own digital skills and their subjective beliefs about the implications of the digital transformation.
External Link(s)

Registration Citation

Kosse, Fabian, Tim Leffler and Arna Woemmel. 2023. "Digital Skills: Socioeconomic Determinants and Social Inequality." AEA RCT Registry. February 07.
Experimental Details


We exogenously enhanced the social environment of the treated low-SES families with the help of an existing and well-established non-profit mentoring program in Germany, ``Balu und Du''. In this program, elementary school children are provided with a mentor for up to one year. The mentors are predominantly university students (aged from 18 to 30) who volunteer to serve as a mentor for a child. The mentoring program is not targeted toward specific learning goals (such as improved school grades), but rather to enriching children’s everyday lives. A key component of the program is to introduce children to new activities, enable new experiences, and provide feedback; possibly exactly the inputs that are needed for them to develop an accurate sense of their abilities and that might be missing in low-SES families. In practical terms, a mentor typically spends one afternoon per week in one-to-one interactions with his/her mentee. During this time, they engage in joint activities such as cooking, sports, handicraft work, or visiting a zoo, museum, or playground.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
- Digital skills
Primary Outcomes (explanation)
We measure digital skills using the “youth Digital Skill Indicator” (yDSI), a novel and cross-nationally validated questionnaire covering five dimensions of digital skills relevant for young people in Europe (Helsper et al., 2021). We use three yDSI-dimensions, incl. 13 questionnaire items, that are essential for the labor market: (i) technical and operational dimension, (ii) the information navigation and processing dimension, and (iii) and programming. Items are measured using a Likert scale.

Secondary Outcomes

Secondary Outcomes (end points)
- Self-confidence in digital skills (i.e. self-perceived level of skills compared to the general population)
- Beliefs about the personal and society-wide chances and risks in connection with the digitalization
Secondary Outcomes (explanation)
Self-confidence in digital skills: We ask participants to give an estimate about the proportion of people in the general population and in their age cohort who have lower digital skills.
Beliefs: We ask individuals about their subjective beliefs on the personal and society-wide chances and risks in conneciton with the digitalization.

Experimental Design

Experimental Design
Sampling and data collection: We make use of the briq family panel (bfp), an annual longitudinal survey of families in Bonn and Cologne in Germany (Falk & Kosse 2020). The bfp was initiated in 2011 to study how the social environment of children influences their formation of personality, preferences and skills, as well as related life outcomes. In 2011, 95% of all families living in Bonn and Cologne with children born between September 2003 and August 2004 were invited to participate in a mentoring program, as well as one third of families with children born between September 2002 and August 2003 (N=14,451). Parents were truthfully informed that, due to capacity constraints, participation in the program was not guaranteed. Overall, 1,626 families indicated a willingness to participate and
answered a short questionnaire including questions on income, education and whether both parents lived in the same household. Children whose parents met at least one of the following three criteria were selected for the final sample: (i) Equivalence income of the household is lower than 1065 Euro, corresponding to the 30th percentile of the German income distribution. (ii) Neither parent has a school-leaving degree qualifying for university studies. (iii) Parents do not live in the same household. These children (N=700) and their parents were invited for a baseline interview conducted in September to October 2011. Overall, 590 children and their parents participated in the baseline interview and gave their written consent to allow the transmission of their address to the organization running the mentoring program. This is our main sample. Out of this sample, 212 families were randomly selected to be treated (“treatment group”), the remaining 378 families form the control group. About 480 children are expected to participate in the current survey wave.
Experimental Design Details
Randomization Method
Randomization was done in office by a computer.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
480 children
Sample size: planned number of observations
480 children
Sample size (or number of clusters) by treatment arms
140 children treatment group, 250 children in the low SES control group and 90 children in the high SES control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Ethikkomission VWL LMU München
IRB Approval Date
IRB Approval Number


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials