2026-05-30T12:59:14Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/279892026-02-03T11:47:51Zcom_10630_2254col_10630_37959
Evaluating the efficiency of primary schools in Canary Islands: A Three-Stage SBM Approach.
Ladrón de Guevara Rodríguez, María
Oliveira Henriques, Carla
López-Agudo, Luis Alejandro
Marcenaro-Gutiérrez, Óscar David
Educación - Evaluación
Education, as a process of human capital accumulation, is essential for a society’s economic
growth. Given its relevance and bearing in mind that public spending is not exclusively devoted
to financing the education system, it is essential to analyse and identify the different obstacles
that hinder school efficiency. Throughout this paper we have carried out an efficiency analysis of
Canarian schools for the period 2018-2019 using data provided by the Canarian Agency for
University Quality and Educational Assessment. Specifically, a three-stage data envelopment
analysis (DEA) based on the slack measure (SBM) and combined with stochastic frontier analysis
(SFA) has been applied to find the benchmarks of inefficient schools, understand their
characteristics and explore the different opportunities for improvement. Using this non-
parametric methodology, we can overcome one of the drawbacks of the DEA approach by
enabling us to consider the influence of contextual variables and random errors in the assessment
of efficiency. In particular, using mathematics and reading scores as outputs, teacher-student ratio
and an index of the quality of schools’ educational resources and some contextual variables such
as socio-economic status, we have tried to find out how efficiency varies when contextual
variables are introduced, and which contextual variables have the greatest influence on schools’
inefficiency.
2023-11-10T08:27:42Z
2023-11-10T08:27:42Z
2023-11-10T08:27:42Z
2023
conference output
https://hdl.handle.net/10630/27989
eng
9th International Workshop on Efficiency in Education, Health and other Public Services
Madrid
19 y 20 de Octubre de 2023
open access