Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/177071
Authors: 
Bennett, Magdalena
Bergman, Peter
Year of Publication: 
2018
Series/Report no.: 
IZA Discussion Papers 11267
Abstract: 
Truancy correlates with many risky behaviors and adverse outcomes. We use detailed administrative data on by-class absences to construct social networks based on students who miss class together. We simulate these networks and use permutation tests to show that certain students systematically coordinate their absences. Leveraging a parent-information intervention on student absences, we find spillover effects from treated students onto peers in their network. We show that an optimal-targeting algorithm that incorporates machine-learning techniques to identify heterogeneous effects, as well as the direct effects and spillover effects, could further improve the efficacy and cost-effectiveness of the intervention subject to a budget constraint.
Subjects: 
social networks
peer effects
education
JEL: 
I21
D85
Document Type: 
Working Paper

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