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Schoolverzuim in het Brussels Hoofdstedelijk Gewest
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Theory and evidence indicate that, if family size grows, the younger children will get less parental involvement than the older children. These differences in parental involvement through birth order may impact academic achievement if, and only if, parental involvement is an important determinant of children’s educational attainment. The oldest child then benefits the most in terms of educational outcomes. Estimates for the Netherlands show a robust negative relationship between birth order and parental involvement, and significant positive medium to large effects of parental involvement through birth order on various measures of academic achievement. Furthermore, our findings indicate that academic achievement is rooted in a school-supportive home climate, and often created by the mother. However, when it comes to math performance and grade retention, it is better that both parents unduly interfere with school. We also find that parents with low socio economic status and from immigrant families are as much involved in the education of their children as the average Dutch family, but their involvement is less effective in terms of children’s learning outcomes.
This paper contributes to the growing literature on school dropout by proposing and empirically testing a theoretical framework on the enrollment decision of youngsters in secondary education. The model relates school dropout to time preferences, motivation, opportunity costs and policy measures. It is empirically tested on longitudinal data of about 4000 Dutch vocational students. We evaluate the enrollment decision of students for (i) different intensity levels of dropout prevention policy, and for (ii) different levels of economic development. The results indicate that the model can accurately predict actual enrollment rates over the period 2000–2013. Copyright
School absenteeism (or truancy) may be a signal of an ongoing process of student attrition that eventually leads to early school leaving. This article estimates how unauthorized school absenteeism accelerates the dropout decision. In particular, the timing of the dropout decision of truants is compared with the timing of regular school attendees using administrative data with insights into wrongly specified truancy spells. We correct in a Bayesian duration model for issues on data uncertainty and show that only a Bayesian structure on the data yields insightful and consistent results. The results indicate that the risk of truants to leave school early before the end of the compulsory education age increases with as much as 37.4%.
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 percentage points in the school year 2009-10 compared to the control schools and the school year 2008-09. The highest impact (-1.4 percentage points) of the intervention was estimated for the least able students.
Naming and shaming is a frequently applied incentive by supra-national organizations. Although common practice, a mere comparison between the outcome variable is meaningless. The observed outcome variable consists of two parts: (1) a part which is due to the general economic climate and where the policy maker does not have an influence on; (2) a ‘net’ part which is the direct result of policy interventions. This paper suggests a regression model to estimate the net policy outcome. The proposed linear panel data model accounts for short and long term economic influences, as well as time and country fixed effects. This yields an indication on the effect attributed to policy making. It is applied to early school leaving outcomes, which increasingly attract attention since recent policy actions stipulated in, e.g., the Lisbon Agenda or the No Child Left Behind Act. Despite Portugals’ best performance in the traditional naming and shaming model, once controlled for non direct policy influences, the results indicate that Luxembourg and the Netherlands can be named, while Portugal and Spain should be shamed.
School absenteeism and particularly unauthorized absenteeism or truancy has been the focus of a number of, so far largely unsuccessful, recent policy initiatives. The paper draws upon two sources of data, the British Household Panel Survey and detailed interviews with a group of persistent truants, to consider the extent, consequences and explanations for truancy from secondary schools. Truancy increases steadily across the years of secondary school and, especially in the later years of compulsory schooling there is evidence that patterns of truancy established in one year carry on into the next. Truancy is strongly associated with negative outcomes in terms of not staying in education post‐16, GCSE results and becoming unemployed. Coming from families of low socio‐economic status, parents not monitoring homework, negative attitudes towards teachers and the value of education are all associated with higher levels of truancy. However, the majority of young people in these situations do not truant and there are many truants who do not have these characteristics. A major explanation given by young people themselves for their non‐attendance is poor relationships with teachers, including teachers failing to match their expectations. Other factors mentioned by young people include bullying but also a more general dislike of the atmosphere of the school, sometimes associated with a change of school. There was little evidence of negative responses to the curriculum leading to truancy. It is suggested that we can distinguish between socio‐economic and attitudinal factors which make young people vulnerable to truancy and precipitating events or processes which result in truanting behaviour.
The difference-in-differences (DID) estimator is one of the most popular tools for applied research in economics to evaluate
the effects of public interventions and other treatments of interest on some relevant outcome variables. However, it is well
known that the DID estimator is based on strong identifying assumptions. In particular, the conventional DID estimator requires
that, in the absence of the treatment, the average outcomes for the treated and control groups would have followed parallel
paths over time. This assumption may be implausible if pre-treatment characteristics that are thought to be associated with
the dynamics of the outcome variable are unbalanced between the treated and the untreated. That would be the case, for example,
if selection for treatment is influenced by individual-transitory shocks on past outcomes (Ashenfelter's dip). This article
considers the case in which differences in observed characteristics create non-parallel outcome dynamics between treated and
controls. It is shown that, in such a case, a simple two-step strategy can be used to estimate the average effect of the treatment
for the treated. In addition, the estimation framework proposed in this article allows the use of covariates to describe how
the average effect of the treatment varies with changes in observed characteristics.
20 jaar socio-economische evolutie in Brussel. Dossier van de conjunctuurbarometer
BISA (2009). 20 jaar socio-economische evolutie in Brussel. Dossier van de conjunctuurbarometer,
nummer 12.