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.     

Enhancing the inclusion of non-discretionary inputs in DEA

The aim of this paper is to provide an alternative approach for estimating efficiency when a set of decision-making units uses non-discretionary inputs in the productive process. To test the influence of these variables, our proposal uses a multi-stage approach based on Tobit regressions. In order to avoid potential bias, a bootstrap procedure is used to estimate these regressions. This methodology allows enhancing other models previously proposed to introduce non-controllable inputs in data envelopment analysis (DEA) overcoming, thus, some of their main shortcomings. We illustrate our framework with an empirical application on Spanish high schools where non-controllable factors play a major role to explain educational achievements.     

Decomposing school and school-type efficiency

This paper puts forward a Data Envelopment Analysis (DEA) approach to decomposing a pupil’s under-attainment at school. Under-attainment is attributed to the pupil, the school and the type of funding regime under which the school operates. A pupil-level analysis is used firstly on a within school and secondly on a between school basis, grouping schools by type such as state-funded, independent and so on. Overall measures of each pupil’s efficiency are thus disentangled into pupil, school and school-type efficiencies. This approach provides schools with a set of efficiency measures, each one conveying different information.     

Chapter 12 New uses of DEA and statistical regressions for efficiency evaluation and estimation — with an illustrative application to public secondary schools in Texas

This paper examines new combinations of Data Envelopment Analysis (DEA) and statistical approaches that can be used to evaluate efficiency within a multiple-input multiple-output framework. Using data on five outputs and eight inputs for 638 public secondary schools in Texas, unsatisfactory results are obtained initially from both Ordinary Least Squares (OLS) and Stochastic Frontier (SF) regressions run separately using one output variable at-a-time. Canonical correlation analysis is then used to aggregate the multiple outputs into a single aggregate output, after which separate regressions are estimated for the subsets of schools identified as efficient and inefficient by DEA. Satisfactory results are finally obtained by a joint use of DEA and statistical regressions in the following manner. DEA is first used to identify the subset of DEA-efficient schools. The entire collection of schools is then comprehended in a single regression with dummy variables used to distinguish between DEA-efficient and DEA-inefficient schools. The input coefficients are positive for the efficient schools and negative and statistically significant for the inefficient schools. These results are consistent with what might be expected from economic theory and are informative for educational policy uses. They also extend the treatments of production functions usually found in the econometrics literature to obtain one regression relation that can be used to evaluate both efficient and inefficient behavior.     

Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools

In this paper we develop a Malmquist productivity index for public sector production characterized by the influence of environmental variables. We extend Johnson and Ruggiero (2011) to the more general case of variable returns to scale to further decompose the Malmquist productivity index into technical, efficiency, scale and environmental change. We apply our model to analyze productivity of Dutch schools using 2002–2007 data. The results indicate that the environment influences the productivity index as well as the technical, efficiency, scale and environmental change components. We see that schools with a moderate classification of environment have the highest productivity numbers. In line with expectations, schools with the worst environment also perform worse and would perform better with an improved environment.     

The role of innovations in secondary school performance – Evidence from a conditional efficiency model

This paper studies the influence of educational innovations on school performance. We apply a tailored, fully nonparametric conditional efficiency model to study secondary school efficiency in the Netherlands. The application uses official school data and a self-collected questionnaire on recent innovations in schools. In the nonparametric model, it is assumed that schools aim to maximize educational attainments of students under a budget constraint. The results suggest that innovations are positively related to efficiency. We find that profiling, pedagogic, process and education chain innovations are significantly related to school efficiency, whereas innovations in the professionalization of teachers are insignificantly related to school efficiency. Furthermore, the number of locations per school and the number of schools per governing body are negatively and significantly related to school efficiency. School type and region significantly influence school efficiency, whereas share of disadvantaged students, degree of urbanization and student/teacher ratio do not have significant influence.     

An extended slacks-based measure model for data envelopment analysis with negative data

Data envelopment analysis (DEA) is a non-parametric approach based on linear programming that has been widely applied for evaluating the relative efficiency of a set of homogeneous decision-making units (DMUs) with multiple inputs and outputs. The original DEA models use positive input and output variables that are measured on a ratio scale, but these models do not apply to the variables in which negative data can appear. However, with the widespread use of interval scale data and undesirable data, the emphasis has been directed towards the simultaneous consideration of the positive and negative data in DEA models. In this paper, using the slacks-based measure, we propose an extended model to evaluate the efficiency of DMUs, even if some variables are measured on an interval scale and some on a ratio scale. Moreover, the extended model allows for the presence of all interval-scale variables, which are capable of taking both negative and positive values.     

Monitoring managerial efficiency in the performing arts: A regional theatres network perspective

Managerial efficiency within the performing arts programming can be understood as the technical efficiency of transforming the resources cultural managers have available into a determined cultural output. Through this explanation different conceptions on the finished performance product it leads us to select two different output variables (number of performances, and number of attendances). In this way, three different models are considered regarding those conceptual points of view. Data on the Circuït Teatral Valencià, a Spanish regional theatres network, is used to develop empirically the concept of Managerial Efficiency and set up a framework to allow us to monitor it.     

Productivity change and innovation in Norwegian electricity distribution companies

Regulators of electricity distribution networks have typically applied Data Envelopment Analysis (DEA) to cross-section data for benchmarking purposes. However, the use of panel data to analyse the impact of regulatory policies on productivity change over time is less frequent. The main purpose of this paper is to construct a Malmquist productivity index to examine the recent productivity change experienced by Norwegian distribution companies between 2004 and 2007. The Malmquist index is decomposed in order to explore the sources of productivity change, and to identify the innovator companies that pushed the frontier forward each year. The input and output variables considered are those used by the Norwegian regulator. In order to reflect appropriately the exogenous conditions where the companies operate, the efficiency model used in this paper incorporates geography variables as outputs of the DEA model. Unlike the model used by the regulator, we included virtual weight restrictions in the DEA formulation to correct the biases in the DEA results that may be associated to a judicious choice of weights by some of the companies.     

Estimating technical and allocative efficiency in the public sector: A nonparametric analysis of Dutch schools

Public sector output provision is influenced not only by discretionary inputs but also by exogenous environmental factors. In this paper, we extended the literature by developing a conditional DEA estimator of allocative efficiency that allows a decomposition of overall cost efficiency into allocative and technical components while simultaneously controlling for the environment. We apply the model to analyze technical and allocative efficiency of Dutch secondary schools. The results reveal that allocative efficiency represents a significant 37 percent of overall cost efficiency on average, although technical inefficiency is still the dominant part. Furthermore, the results show that the impact of environment largely differs between schools and that having a more unfavorable environment is very expensive to schools. These results highlight the importance of including environmental variables in both technical and allocative efficiency analysis.     

A cognitive analytics management framework to select input and output variables for data envelopment analysis modeling of performance efficiency of banks using random forest and entropy of information

The efficiency of banks has a critical role in development of sound financial systems of countries. Data Envelopment Analysis (DEA) has witnessed an increase in popularity for modeling the performance efficiency of banks. Such efficiency depends on the appropriate selection of input and output variables. In literature, no agreement exists on the selection of relevant variables. The disagreement has been an on-going debate among academic experts, and no diagnostic tools exist to identify variable misspecifications. A cognitive analytics management framework is proposed using three processes to address misspecifications. The cognitive process conducts an extensive review to identify the most common set of variables. The analytics process integrates a random forest method; a simulation method with a DEA measurement feedback; and Shannon Entropy to select the best DEA model and its relevant variables. Finally, a management process discusses the managerial insights to manage performance and impacts. A sample of data is collected on 303 top-world banks for the periods 2013 to 2015 from 49 countries. The experimental simulation results identified the best DEA model along with its associated variables, and addressed the misclassification of the total deposits. The paper concludes with the limitations and future research directions.

     

Efficiency and equity in private and public education: A nonparametric comparison

We present a nonparametric approach for (1) efficiency and (2) equity evaluation in education. Firstly, we use a nonparametric (Data Envelopment Analysis) model that is specially tailored to assess educational efficiency at the pupil level. The model accounts for the fact that typically minimal prior structure is available for the behavior (objectives and feasibility set) under evaluation. It allows for uncertainty in the data, while it corrects for exogenous ‘environmental’ characteristics that are specific to each pupil. Secondly, we propose two multidimensional stochastic dominance criteria as naturally complementary aggregation criteria for comparing the performance of different school types (private and public schools). While the first criterion only accounts for efficiency, the second criterion also takes equity into consideration. The model is applied for comparing private (but publicly funded) and public primary schools in Flanders. Our application finds that no school type robustly dominates another type when controlling for the school environment and taking equity into account. More generally, it demonstrates the usefulness of our nonparametric approach, which includes environmental and equity considerations, for obtaining ‘fair’ performance comparisons in the public sector context.     

A DEA based procedure for the selection of subgroups

Data Envelopment Analysis (DEA) is a nonparametric technique originally conceived for efficiency analysis of a set of units. The main characteristic of DEA based procedures is endogenous determination of weighting vectors, i.e., the weighting vectors are determined as variables of the model. Nevertheless, DEA’s applications have vastly exceeded its original target. In this paper, a DEA based model for the selection of a subgroup of alternatives or units is proposed. Considering a set of alternatives, the procedure seeks to determine the group that maximizes overall efficiency. The proposed model is characterized by free selection of weights and allows the inclusion of additional information, such as agent’s preferences in terms of relative importance of the variables under consideration or interactions between alternatives. The solution is achieved by computing a mixed-integer linear programming model. Finally, the proposed model is applied to plan the deployment of filling stations in the province of Seville (Spain).     

Student teachers’ types of probing questions in inquiry-based mathematics teaching with and without GeoGebra

Previous studies have produced several typologies of teacher questions in mathematics. Probing questions that ask students to explain are often included in the types of questions. However, only rare studies have created subtypes for probing questions or investigated how questioning differs depending on whether technology is used or not. The aims of this study are to elaborate on different ways of asking students to give explanations in inquiry-based mathematics teaching and to investigate whether questioning in GeoGebra lessons differs from questioning in other lessons. Data was collected by video recording 29 Finnish mathematics student teachers’ lessons in secondary and upper secondary schools. The lesson videos were coded for the student teachers’ probing questions. After this, categories for the types of probing questions were created, which is elaborated in this paper. It was found that the student teachers who used GeoGebra emphasized conceptual probing questions during the explore phase of a lesson slightly more than the other student teachers.     

Private versus public high schools in Spain: disentangling managerial and programme efficiencies

The purpose of this paper is to compare the efficiency of a set of Spanish public and private high schools using data envelopment analysis (hereafter DEA). In view of the usual difficulties of obtaining reliable budget figures on private schools, we have used a restrictive efficiency notion which focuses on the relation between the academic results obtained by each school and the socio-economic background and academic profile of its pupils. In this study, special emphasis is placed upon decomposing the overall inefficiencies of each school into managerial (due to individual performance) and programme (due to structural differences between management models) components. Our results reveal that although, in general, private schools obtain better academic results than public schools in absolute terms, this is not the consequence of comparatively more effective management but rather of having pupils with a more favourable background for the educational process.     

A new approach for technical efficiency estimation in multiple output production

The nonparametric technique of Data Envelopment Analysis (DEA) has been used to measure technical efficiency. This approach has proven useful because, unlike regression analyses, it allows multiple outputs and does not require a priori functional form specification. DEA does, however, require correct model specification; inclusion of inappropriate variables or omission of relevant variables leads to distortions. The purpose of this paper is to develop an alternative methodology based on canonical correlation to measure technical efficiency for multiple output production correspondences. Using simulated data, the new methodology is compared with DEA. The results indicate that the canonical regression approach outperforms DEA in most cases.     

Convexity,quality and efficiency in education

While Data Envelopment Analysis (DEA) has many attractions as a technique for analysing the efficiency of educational organisations, such as schools and universities, care must be taken in its use whenever its assumption of convexity of the prevailing technology and associated production possibility set may not hold. In particular, if the convexity assumption does not hold, DEA may overstate the scope for improvements in technical efficiency through proportional increases in all educational outputs and understate the importance of improvements in allocative efficiency from changing the educational output mix. The paper therefore examines conditions under which the convexity assumption is not guaranteed, particularly when the performance evaluation includes measures related to the assessed quality of the educational outputs. Under such conditions, there is a need to deploy other educational efficiency assessment tools, including an alternative non-parametric output-orientated technique and a more explicit valuation function for educational outputs, in order to estimate the shape of the efficiency frontier and both technical and allocative efficiency.     

On centralized resource utilization and its reallocation by using DEA

The standard DEA model allows different DMU units to set their own priorities for the inputs and outputs that form part of the efficiency assessment. In the case of a centralized organization with many outlets, such as an education authority that is responsible for many schools, it may be more sensible to operate in the most efficient way, but under a common set of priorities for all DMUs. The algorithm that is used to do this, the centralized resource allocation model, does just this. We show that the centralized resource allocation model can be substantially simplified and we interpret the simplifications and show how the model works using real data of Spanish public schools. Apart from finding the best way to reallocate resource among the schools, it is shown that the most desirable operating unit is found to be a by-product of the estimation. This is useful information when planning new schools.     

The influence curve approach in data envelopment analysis

The behavior of efficiency in the stochastic DEA model is examined here in terms of the influence curve approach which quantifies the influence of observed data on the empirical fit of the production frontier. Data influence is analyzed here through robustness. Two types of robustness and sensitivity issues are analyzed here in terms of (a) a new class of minimax measures, and (b) a set nonlinear efficiency measures and it is shown through empirical applications that in suitable cases these measures outperform the conventional ones.This is a revised version of an invited paper presented at the 13th International Symposium on Mathematical Programming held in tokyo, Japan, 29 August 2 September 1988. Sincere thanks are due to Professors A. Charnes and J. Sojka for their valuable comments and suggestions. Thanks are also due to the Guest Editor S. Shinoda and the two anonymous referees for their comments.     

The impact of managerial and organizational aspects on hospital wards’ efficiency: Evidence from a case study

In spite of its acknowledged relevance, the impact of managerial and organizational aspects on hospital wards’ efficiency has been so far overlooked by the literature. In order to explore this issue, this paper presents a model of the relations between the decision making process of a hospital ward and its technical efficiency. In order to test the model, a two-step approach has been adopted. In the first step the technical efficiency of wards belonging to a large Italian Hospital Enterprise has been calculated using DEA. In the second step, efficiency scores have been regressed on a set of variables capturing managerial goals and actions internal to the ward, as well as re-organizations imposed by the hospital central management. Responses to a questionnaire administered to the heads of ward were used to build the independent variables. Results show that both decisions internal to the ward and exogenous re-organizations affect the ward’s efficiency, and suggest that these variables are more significant in explaining efficiency than environmental ones.