Seminario 20/11: Daniel Santín (Universidad Complutense de Madrid) Comparing the Evolution of Productivity and Performance Gaps in Education Systems through DEA: An Application to Latin American Countries
- Ponente: Daniel Santín, Universidad Complutense de Madrid.
- Fecha: 18/may/2020 - 12:00 horas
- Lugar: SEMINARIOS ONLINE CIO (UMH): http://cio.edu.umh.es/seminariosonline/ (Se grabará)
The main objective of this paper is to propose a tool for measuring the productivity and performance gaps across a set of Decision Making Units (DMUs)for monitoring their evolution and analyzing their components over time. To do this, we use the approach proposed by Aparicio and Santín (2018), which isgrounded on a base-group base-period productivity index and Data EnvelopmentAnalysis (DEA). Additionally, we propose a new index for measuring the performancegap between two or more groups of production units and its decomposition ineffectiveness gap and outcome possibility set gap. As an empirical illustration of the approach, we focus our attention onthe educational sector. In particular, we analyze six Latin American countriesover time. For this purpose, we rely on OECD-PISA data aggregated atschool level. Over the period 2006 to 2018, performance and productivityfollowed very different paths in each country showing that the correlationbetween school performance and productivity is very low. Therefore, we suggestthat the simultaneous analysis of performance and productivity gaps togetherwith their evolution over time is a must in order to benchmark countries andmonitor improvements and weaknesses in education systems. The information gathered could be used by policy makers to justify newprograms or new framework laws to boost results in either or both dimensions.This is especially important in the case of countries with federal systems ofgovernment, as it is the case of Spain, to assure that public services inequalities,mainly health and education, among states are tolerable or for making decisions on investment more in public or in stated-funded private production units.
Keywords: Data EnvelopmentAnalysis, performance, productivity, education.