The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia

Most applications of data envelopment analysis (DEA) employ standard constant or variable returns-to-scale (CRS or VRS) models. In this paper we suggest that these models may sometimes underutilize our knowledge of the underlying production process. For example, in the context of higher education considered in the reported application, individual universities often maintain a certain student-to-staff ratio which points that there should be an approximately proportional relationship between students and staff, at least in the medium to long run. A different example is an observation that the teaching of postgraduate students generally requires more resources than the teaching of the same number of undergraduate students. In order to incorporate such information in a DEA model, we propose a novel approach that combines the recently developed hybrid returns-to-scale DEA model with the use of production trade-offs. The suggested approach leads to a better-informed model of production technology than the conventional DEA models. We illustrate this methodology by an application to Malaysian public universities. This approach results in a tangibly better efficiency discrimination than would be possible with the standard DEA models

Efficiency in education. A review of literature and a way forward

This paper provides an extensive and comprehensive overview of the literature on efficiency in education. It summarizes the earlier applied inputs, outputs and contextual variables, as well as the used data sources of papers in the field of efficiency in education. Moreover, it reviews the papers on education that applied methodologies as Data Envelopment Analysis, Malmquist index, Bootstrapping, robust frontiers, metafrontier, or Stochastic Frontier Analysis. Based on the insights of the literature review, a second part of the paper provides some ways forward. It attempts to establish a link between the parametric 'economics of education' literature and the (semi-parametric) 'efficiency in education literature'. We point to the similarities between matching and conditional efficiency; difference-in-differences and metafrontiers; and quantile regressions and partial frontiers. The paper concludes with some operative directions for prospective researchers in the field

Assessing European primary school performance through a conditional nonparametric model

This paper uses a fully nonparametric framework to assess the efficiency of primary schools using data about schools in 16 European countries participating in PIRLS 2011. This study represents an original enterprise since most of the empirical research in the field is restricted to evaluations at regional or national level and focused on secondary education. For our purpose, we adapt the metafrontier framework to compare and decompose the technical efficiency of primary schools operating in heterogeneous contexts, which in our case is represented by different educational systems or countries. Similarly, we use an extension of the conditional nonparametric robust approach to test the potential influence of a mixed set of environmental school factors and variables representing cultural values of each country. Our results indicate that the intergenerational transmission of non-cognitive skills such as responsibility or perseverance are significantly related to school efficiency, whereas most school factors do not seem to have a significant influence on school performance

Medida de eficiencia técnica en la educación media de América Latina: Pruebas PISA

Vol. 27, No. 1 (2019)En el presente estudio se evalúa la eficiencia técnica de estudiantes de 8 países de América Latina que participaron en las pruebas PISA 2015. El estudio se desarrolló bajo una metodología no paramétrica. Para ello, se empleó un modelo FDH con orientación al producto con un enfoque de estimaciones robustas y una descomposición de Metafrontera, esto último permite descomponer la eficiencia total de los estudiantes, entre la atribuible al estudiante y la atribuible al país. Los datos utilizados en el estudio provienen de las pruebas PISA 2015. Los datos utilizados corresponden 35,880 observaciones de igual número de estudiantes que presentaron la prueba mencionada. Los resultados revelan que la mayor parte de la ineficiencia se debe a los propios estudiantes. Identificando a Uruguay y Brasil como los países donde se presenta el menor puntaje de ineficiencia. Y a México y República Dominicana como los que presentan un mayor puntaje de ineficiencia.This study evaluates the technical efficiency of students from 8 Latin American countries that participated in the PISA 2015 tests. The study was developed under a non-parametric methodology. For this, a product-oriented FDH model was used with a robust estimations approach and a Meta-frontier decomposition. The latter allows decomposing the total efficiency of the students, between that attributable to the student and that attributable to the country. The data used in the study comes from the PISA 2015 tests. The data used correspond to 35,880 observations from the same number of students who presented the aforementioned test. The results reveal that most of the inefficiency is due to the students themselves. Identifying Uruguay and Brazil as the countries with the lowest inefficiency score. And to Mexico and the Dominican Republic as those with the highest inefficiency score

Assessment of TFP in European and American higher education institutions – application of Malmquist indices

In this study we apply Malmquist methodology, based on the estimation of distance measures through Data Envelopment Analysis (DEA), to a sample of 500 universities (in 10 European countries and the U.S.) over the period 2000 to 2010 in order to assess and compare their productivity. On average, a rise in TFP is registered for the whole European sample (strongest for Dutch and Italian HEIs), while the productivity of American HEIs suffered a slight decline. Additionally, we show that productivity growth is negatively associated with size of the institution and revenues from government, and positively with regional development in the case of the European sample, while American HEI productivity growth is characterised by a negative association with GDP and a positive one with the share of government resources out of total revenue. First published online: 24 Nov 201

Can better governance increase university efficiency?

This paper links governance reforms with potential improvements in efficiency in Spanish universities. Taking the classic DEA model as our starting-point, we focus on the study of efficient units to identify the ones that present atypical behaviour (outliers) and should be removed from the analysis, and then to order the remaining institutions in terms of what is known as robust efficiency. Moreover, we use a second stage regression analysis and a threestage adjusted values non-parametric model to analyse the influence of environmental factors on the efficiency scores obtained. Once environmental factors are taken into account, the remaining unexplained inefficiency is attributed to governance failures. Our results indicate that the observed inefficiency in Spanish public universities is mainly determined by deficient governance. Thus, there is scope for improvements in efficiency through governance reform

Explaining (in)efficiency in higher education: a comparison of parametric and non-parametric analyses to rank universities

In recent years more and more numerous are the rankings published in the newspapers or technical reports available, covering many aspects of higher education, but in many cases with very conflicting results between them, due to the fact that universities’ performances depend on the set of variables considered and on the methods of analysis employed. The aim of this study is to rank higher education institutions (HEIs) in Italy, comparing parametric and non-parametric approaches: we firstly apply a so-called double bootstrap Data Envelopment Analysis (DEA) to generate unbiased coefficients (Simar and Wilson, 2007) and then a Stochastic Frontier Analysis (SFA), modelling the production set through an output distance function, applying a within transformation to data as developed by Wang and Ho (2010), to evaluate which determinants have an impact on universities’ efficiencies. The findings reveal that, on average and among the macro-areas of the country, the level of efficiency does not change significantly among estimation methods which, instead, generate different rankings. This may guide universities’ managers and policymakers as rankings have a strong impact on academic decision-making and behaviour, on the structure of the institutions and also on students and graduates recruiters. Variables describing institution, market place and environment have an important role in explaining (in)efficiency

Explaining (in)efficiency in higher education: a comparison of parametric and non-parametric analyses to rank universities

In recent years more and more numerous are the rankings published in the newspapers or technical reports available, covering many aspects of higher education, but in many cases with very conflicting results between them, due to the fact that universities’ performances depend on the set of variables considered and on the methods of analysis employed. The aim of this study is to rank higher education institutions (HEIs) in Italy, comparing parametric and non-parametric approaches: we firstly apply a so-called double bootstrap Data Envelopment Analysis (DEA) to generate unbiased coefficients (Simar and Wilson, 2007) and then a Stochastic Frontier Analysis (SFA), modelling the production set through an output distance function, applying a within transformation to data as developed by Wang and Ho (2010), to evaluate which determinants have an impact on universities’ efficiencies. The findings reveal that, on average and among the macro-areas of the country, the level of efficiency does not change significantly among estimation methods which, instead, generate different rankings. This may guide universities’ managers and policymakers as rankings have a strong impact on academic decision-making and behaviour, on the structure of the institutions and also on students and graduates recruiters. Variables describing institution, market place and environment have an important role in explaining (in)efficiency

An analysis of the efficiency of public expenditure on education in the Municipalities of the State of Amazonas from 2013 to 2017

Purpose:  This article aimed to evaluate the efficiency of public expenditure in the municipalities of the State of Amazonas with primary education in the years 2013 to 2017 by building a ranking of the efficiency of the municipalities relating the results obtained in IDEB by each city in the period, under the counterpart of the values of expenses paid for primary education, the average number of students enrolled in the period, average expenditure per student and GDP per capita of each municipality. Methodology: We used Data Envelopment Analysis (DEA) technique to evaluate the 37 Amazonian municipalities' efficiency in the sample. The variables analyzed include municipal data on the Gross Domestic Product (GDP), number of inhabitants, number of students enrolled, spending on education, and IDEB notes for the period. Results:  The results showed that only eight municipalities (21.6%) were classified as efficient and that these municipalities were those with the worst starting conditions, in terms of average wealth and educational performance, and that made the lowest expenses per enrolled student, which reaffirms the finding of diminishing returns to scale in education. On the other hand, the least efficient municipalities were those with the best starting condition in terms of GDP per capita and which presented high expenditures per student, but which reached the worst performances in the 2017 IDEB. Contributions of the Study:  Considering the amounts spent by Amazonian municipalities on primary education, taking into account the size and performance in the IDEB of each city in the period under analysis, the research seeks to demonstrate the efficiency in the application of spending on primary education, providing useful and information for a more qualified and efficient allocation of public resources in education, providing improvements in the social aspects of the population aspects