Skip to content

Presentation

What role does the distance to the nearest educational institution play in educational choices? Drawing on detailed individual data tracing pupils’ pathways through secondary and higher education, this paper sheds new light on this question.

It analyses the impact of the creation of preparatory classes for the grandes écoles (CPGE) and higher technician sections (STS) known as ‘local’ programmes between 2006 and 2015. In France, where there are numerous barriers to student mobility, the uneven distribution of educational provision across the country contributes significantly to geographical disparities in access to selective courses.

Key Results

  • Although CPGE and STS programmes differ in terms of their social and academic profiles, their intake remains concentrated within a limited geographical area.
  • Access to selective courses varies greatly depending on the students’ secondary school of origin: in 2015, half of all general and technological secondary schools accounted for just 16 per cent of STS student numbers, whilst, conversely, 21 per cent of secondary schools accounted for half of these numbers. For CPGE programmes, these proportions were 14 per cent and 18 per cent respectively.
  • Pupils who take their baccalaureate at a secondary school offering a selective programme are more likely to apply for and be admitted to these courses than those from secondary schools without an equivalent programme. This gap can only be partially explained by differences in academic performance between these two groups of pupils.
  • The opening of a CPGE or an STS programme increases the probability of local pupils enrolling by around 8 per cent, whether they come from the school in question or from neighbouring schools. Pupils benefiting from the opening of a CPGE are more likely to gain entry to a ‘grande école’ within three years of taking their baccalaureate, with an effect of a similar magnitude to that observed for access to CPGE programmes.
  • The impact of new classes on access to these programmes stems mainly from pupils who, without this opportunity, would have opted for university rather than another selective pathway.
  • The effect of opening new CPGE and STS classes is more pronounced for pupils from small towns
    and, in the case of STS programmes, for those from the Vocational track/path.

Method and Data

The second part of the study aims to identify the causal effect of the introduction of CPGE or STS classes on pupils’ career choices after the baccalaureate. The empirical strategy used in the study exploits the temporal and spatial variation in the opening of these programmes between 2007 and 2015. This identification method, known as the staggered adoption design, has recently been the subject of numerous methodological developments.

In particular, it relies on the assumption of a constant treatment effect, both over time and across cohorts. To relax these assumptions, the study compares the results of the standard estimation method (two-way fixed effects) with three alternative estimators developed by De Chaisemartin and d’Haultfoeuille (2020), Callaway and Sant’Anna (2021) and Gardner (2021). The estimated effects are found to be very similar, regardless of the method used.

Data used

The study draws on annual censuses of pupils enrolled in secondary education (FAERE data from the SCOLARITÉ information system) and students enrolled in higher education (STS/CPGE data from SCOLARITÉ and SISE data) over the period 2006–2018.

These data were provided by the Directorate for Evaluation, Forecasting and Performance of the Ministry of National Education and Youth (MENJ-DEPP) and the Sub-Directorate for Information Systems and Statistical Studies of the Ministry of Higher Education and Research (MESR-SIES).

It provides detailed information on the socio-demographic characteristics of pupils and students (age, gender, nationality, municipality of residence, socio-professional category of legal guardians), as well as the institution attended and the course of study undertaken each year. These data are supplemented by A-level results, drawn from the OCEAN information system, as well as pre-enrolment choices for higher education, drawn from the Admission Post-Bac (APB) platform for the year 2015.

The national pupil identification number (INE), in encrypted form, enables these different sources to be linked in order to reconstruct pupils’ educational pathways, from their final year of secondary school until they leave the education system. Finally, geolocation data for secondary and higher education institutions, as well as information on the size and type of local authorities, are sourced from open data.

Partners

Chaire PEMSDirection de l’évaluation de la prospective et de la performance (DEPP)SIES

This study was carried out under a research agreement with the Directorate for Evaluation, Forward Planning and Performance of the Ministry of National Education and Youth (MENJ-DEPP) and the Sub-Directorate for Information Systems and Statistical Studies of the Ministry of Higher Education and Research (MESR-SIES). The author would like to thank the teams at the DEPP and the SIES for providing the data used in this research.

This paper also received support from the Chair in Educational Policy and Social Mobility. Established in 2021 as part of a partnership between the Ardian Foundation, the Directorate for Evaluation, Forecasting and Performance of the Ministry of National Education and Youth (MENJ-DEPP) and PSE-Paris School of Economics, this chair aims to promote high-level research and the dissemination of knowledge on education policies and social mobility.

Last modified: July 21, 2026