Abstract
Unauthorized truancy is considered as one of the earliest signals of a prospective school dropout decision. This paper evaluates the effectiveness of an active school attendance intervention tackling school dropout in Dutch secondary education. The intervention consists of increased care for, and interaction with, at-risk students by, for example, visits at home. It relies on professional mentors, teachers, case managers, social workers, and compulsory education age consultants. We analyze the effect of the intervention by a difference-in-differences analysis in combination with matching estimation techniques. The results indicate that the intervention schools significantly reduced school dropout with \(-0.54\) % points in the school year 2009–2010 compared to the control schools and the school year 2008–2009. The highest impact (\(-1.4\) % points) of the intervention was estimated for the least able students.
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Notes
‘School dropout‘, ‘early school leaving’, and ‘leaving education early’ are used as synonyms throughout this paper.
In-line with the European Commission, we define a school dropout as a youngster below the age of 24 without a higher secondary certificate and who is not enrolled in education or training.
Since the year 2007, students have to obtain a higher secondary certificate (i.e., vocational education of at least level-2, general secondary or pre-university education) due to the regulation of the qualification law in the compulsory education age law of 1969.
If a student lives in a poverty area, then the area may be denoted by the total number of inhabitants with low income or benefits, or unemployment status.
It should be noted that a matching at school level is less meaningful in the application at hand because of two reasons. First, in a proper school-level matching scenario, the matching could potentially grasp the effect of school-level policies (such as the active truancy policy we are evaluating in this paper). As such, school-level characteristics are “confounding” and then should not be used in matching (Rosenbaum and Rubin 1983; Lechner 2001). Second, it would result in an analysis with a very weak power as there are only few schools.”
Note that including these variables in the matching analysis does not suffice to properly control for similar heterogeneity. Owing to the matching analysis, we can construct a proper control group. And owing to the covariates in the DiD analysis, we can estimate the effect of the intervention more efficiently and consistently.
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Acknowledgments
We are grateful to LVO-group Limburg, Wiel Cals, Wim Groot, Henriëtte Maassen van den Brink, and TIER seminar participants, the two anonymous referees and the managing editor. The authors acknowledge financial support of Platform31. The usual caveat applies.
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Cabus, S.J., De Witte, K. The effectiveness of active school attendance interventions to tackle dropout in secondary schools: a Dutch pilot case. Empir Econ 49, 65–80 (2015). https://doi.org/10.1007/s00181-014-0865-z
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DOI: https://doi.org/10.1007/s00181-014-0865-z