Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/254238 
Year of Publication: 
2022
Series/Report no.: 
MAGKS Joint Discussion Paper Series in Economics No. 02-2022
Publisher: 
Philipps-University Marburg, School of Business and Economics, Marburg
Abstract: 
An important role is ascribed to students' social networks in explaining both social and ethnic differentials in educational achievement and attainment. For example, students' social networks are assumed to influence their probability of success by providing educationally-relevant resources and by promoting effort and educational investments. The direction and strength of the network's effect on students' educational success is assumed to depend on the network's precise characteristics, such as educational and migration background. As track selection by school performance (as is the case in Germany) goes hand in hand with a segregation of students by characteristics like social and migration background, it can be assumed that educational success itself has an influence on the social resources students have access to at later stages of their educational careers. Given the complexity of instruments commonly applied in self-administered questionnaires to assess students' social resources, the quality of data on measures of network characteristics is likely to depend on the respondents' abilities. As regards the estimation of the association between network characteristics and educational success, biased measurement of social network characteristics apparently constitutes a challenge as spurious correlation may be observed between measures of educational achievement and network characteristics if the bias systematically correlates with education. We report empirical findings on a complex instrument used in a self-administered questionnaire applied in the National Educational Panel Study (NEPS) to 9th-graders in the classroom, which was designed to measure the social resources young people have at their disposal at the point of transition from general into vocational education. The data allows identifying population subgroups who face particularly strong difficulties in completing the relevant set of questions in a consistent way. Specifically, this selection can be shown to be significantly correlated with different measures of educational achievement as well as with the respondents' migration background. As the network characteristics we investigate, i.e., the network members' educational and migration background, have been found to correlate with students' educational success, ignoring this selection can be shown to heavily bias estimates of the association between educational achievement and social network characteristics.
Subjects: 
Social networks
network characteristics
network composition
social resources
answering behavior
cognitive skills
measurement bias
migration background
educational success
educational attainment
Document Type: 
Working Paper

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