School closures and their implications for student outcomes: evidence from Lithuania

ABSTRACT

This paper studies the effect of school closures on student outcomes in the Lithuanian context. Using administrative student-level data from 2013–2017 and propensity score matching, we create a balanced sample of control and treatment groups. In contrast to other studies, we focus on students in the final years of high school, possibly eliciting the upper bar of the disruption effect. We also follow students after high school graduation, providing evidence on labour market outcomes. We find that school closure has a small, negative effect on only some exam outcomes and the probability of enrolling at a university, suggesting that the disruption effect is small even for students in the final years of high school.

KEYWORDS:

• School closure
• student displacement
• student outcomes
• labor market

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/13639080.2024.2335463

Notes

1. In Lithuania, there are two types of schools which provide 9th- to 12th-grade education: secondary schools and gymnasiums. Secondary schools provide all levels of education, or at least both lower secondary education and upper secondary education, whereas gymnasiums (with some minor exceptions) have only the 9th–12th grades. Although secondary schools were phased out until 2017 by transforming them into pre-gymnasiums or gymnasiums, during our sample period of 2013–2017, secondary schools still existed.

2. Students for whom Lithuanian is not a native language can also take exams on their native languages (Belorussian, Polish, Russian, German).

3. Different higher education programs can apply different weights to Matura exams, and might also add additional points for participation in national competitions, etc.

4. Even if their school closed in 2014, they were allowed to graduate in the same school.

5. Matching on the receiving school quality indicator would violate the assumption that all confounding variables should be measured before the treatment, i.e. the closure.

6. We would like to thank the anonymous referee for these suggestions.

Additional information

Notes on contributors

Eglė Jakučionytė

Eglé Jakučionyté holds a PhD from the University of Amsterdam and Tinbergen Institute. She is a junior research fellow at Vilnius University, and a principal research economist at the National Bank of Lithuania.

Indrė Pusevaitė

Indrė Pusevaitė is a Senior Researcher at Visionary Analytics with experience in coordinating and implementing national research and evaluation assignments. She holds an MA in Public Policy Analysis from Vilnius University.

Swapnil Singh

Swapnil Singh holds a PhD from the University of Amsterdam and Tinbergen Institute. He is a senior research fellow at the Kaunas University of Technology, and a rincipal research economist at the National Bank of Lithuania.