Non-discretionary Inputs Research Articles

The analysis of the efficiency of primary schools in Morocco: modelling using TIMSS database (2011)

ABSTRACTThis article aims to analyze the efficiency of primary education schools in Morocco using the database ‘Trends in International Mathematics and Science Study’ (TIMSS) in the fourth year of primary education compiled 2011 by the International Association for the Evaluation of Educational Achievement (IEA). The methodology of Data Envelopment Analysis ‘DEA’ is used to define the efficiency scores for each school. To participate in the debate on the inclusion or exclusion of non-discretionary inputs in the DEA, efficiency scores were also determined taking into account the socio-economic environment of the school. Also, the analysis of external factors that impact the efficiency scores is carried out using the ordered probit econometric model. Particular attention is paid to the characteristics of the student and parents. The results confirm the hypothesis that the socio-economic environment of the student has a significant impact on the efficiency of primary schools in Morocco.

Economic efficiency of public secondary education expenditure: How different are developed and developing countries?

This study measures the efficiency of public secondary education expenditure in 37 developing and developed countries using a two-step semi-parametric DEA (Data Envelopment Analysis) methodology. We first implement two cross-country frontier models for the 2012-2015 period: one using a physical input (i.e., teacher-pupil ratio) and one using monetary inputs (i.e., government and private expenditure per secondary student as a percentage of GDP). These results are corrected by the effects of GDP per capita and adult educational attainment as non-discretionary inputs. We obtain five important results: 1) developed and developing countries are similar in terms of the education production process due to the peers used in the non-parametric Este articulo fue recibido el 4 de mayo del 2017, evaluado el 15 de septiembre del 2017 y finalmente aceptado el 30 de noviembre del 2017.estimation of relative efficiency; 2) developing countries could increase their enrolment rates and PISA scores by approximately 22% and ...

Do dropout and environmental factors matter? A directional distance function assessment of tunisian education efficiency

The purpose of this paper is to investigate the education efficiency in Tunisia based on a sample of secondary schools. We place some special focus on schools resources and corresponding dropout levels. We use the Directional Distance Function (DDF) methodology to simultaneously deal with bad outputs and non-discretionary inputs. Our assessment is based on Data Envelopment Analysis (DEA) method. The data is extracted from the Program for International Student Assessment (PISA) 2012 survey. We generate four models through various inputs and outputs specifications while considering dropout levels and education environment. Our empirical study reveals strong influence between education performance and both school infrastructure and educational resources. In particular, the financial constraints seem to have real effect on the dropout levels.

Economic Efficiency of Public Secondary Education Expenditure: How Different are Developed and Developing Countries?

This study measures the efficiency of public secondary education expenditure in 35 developing and developed countries using a two-step semi-parametric DEA (data envelopment analysis) methodology. First, we implement two cross-country frontier models for the 2009-2012 period: one using a physical input (i.e., teacher-pupil ratio) and one using a monetary input (i.e., government expenditure per secondary student). These results are corrected by the effects of GDP per capita and adult educational attainment as non-discretionary inputs. We obtain four important results: (i) developed and developing countries have the same education production processes when they are compared using physical inputs but not when compared using monetary inputs; (ii) developing countries could increase their enrollment rates and PISA scores by approximately 9% and 5%, respectively, by maintaining the same teacher-pupil ratios and public spending levels as developed countries; (iii) Ireland, Japan and Korea are efficient countries in the two frontier models (Colombia is also included in this category when the teacher-pupil ratio is used as input); and (iv) robust empirical evidence indicates that both income and parental educational attainment positively affect the efficiency of public education in both models.

Resource scheduling in a private cloud environment: an efficiency priority perspective

Purpose Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at the problem of resource scheduling in the private cloud environment, the purpose of this paper is to propose a resource scheduling approach from an efficiency priority point of view. Design/methodology/approach To measure the computational efficiencies for the resource nodes in a private cloud environment, the data envelopment analysis (DEA) approach is incorporated and a suitable DEA model is proposed. Then, based on the efficiency scores calculated by the proposed DEA model for the resource nodes, the 0-1 programming technique is introduced to build a simple resource scheduling model. Findings The proposed DEA model not only has the ability of ranking all the decision-making units into different positions but also can handle non-discretionary inputs and undesirable outputs when evaluating the resource nodes. Furthermore, the resource scheduling model can generate for the calculation tasks an optimal resource scheduling scheme that has the highest total computational efficiency. Research limitations/implications The proposed method may also be used in studies of resource scheduling studies in the environments of public clouds and hybrid clouds. Practical implications The proposed approach can achieve the goal of resource scheduling in private cloud computing platforms by attaining the highest total computational efficiency, which is very significant in practice. Originality/value This paper uses an efficiency priority point of view to solve the problem of resource scheduling in private cloud environments.

Efficiency assessment and output maximization possibilities of European small and medium sized airports

The aim of this research is to investigate the operational efficiency and potential output increase scenarios of 21 small and medium sized airports (SMA) located in 10 different European countries. A key feature of the proposed Data Envelopment Analysis (DEA) models is the consideration of two novel inputs related to the number of airlines and scheduled routes operating at each airport, in addition to the more common capital non-discretionary inputs (runways, boarding gates and apron). These novel inputs are a way of considering the effects of the air transport market on airports' performance and growth prospects. In particular, a model to estimate the growth in passenger numbers, aircraft movements and cargo that can be achieved by an airport through increasing its number of airlines and routes, and assuming an efficient operation, is presented. Also, a multi-objective DEA model is proposed to explore the possible trade-offs in the output Pareto efficient frontier of a given airport. In addition, a second stage fractional regression model specific for explaining DEA efficiency scores is conducted and the results suggest that ownership structure and hub airport status are significant factors for explaining variations in the operational efficiency of European SMA.

Developing imprecise dual-role hybrid measure of efficiency for international market selection using ternary variable

By choosing the best international market from a set of potential countries, firms plan to start new or expand existing international activities. In marketing literature, this process is known as international market selection or target market selection. In realistic situations, some of data of international markets cannot be provided accurately since they are imprecise. Some other criteria of international market analysis are dual-role, i.e., they may be classified either as an input or as an output, simultaneously. The quantity of such factors may influence relative attractiveness of international markets. Moreover, in international market selection, some factors are beyond control of decision-maker(s) and cannot be modified at discretion of management. These factors may affect final decision. As a non-parametric technique, data envelopment analysis (DEA) provides adequate ability for decision makers to select a set of international markets. In this paper, using ternary variable, a new DEA-based model is proposed for international market selection in the presence of imprecise data, dual-role factors, and non-discretionary inputs. The proposed model is able to take into account radial and non-radial measures, as well. A case study illustrates the application of the proposed model.

Measuring the Relative Efficiencies of Statistics Departments in Turkey Using Data Envelopment Analysis

Determinants of success of an education system can be the facilities offered during an educational process and the qualifications obtained afterwards. However, conversion of the offered facilities into outputs efficiently in the performance evaluation plays an important role for an educational system. On the contrary, comparison of Turkish university performances can be generally performed according to only output based performance indicators like academician performances and nationwide exam results of their graduates publicly. Aim of this study is to calculate the relative efficiencies of 18 statistics departments in Turkey, which are considered as decision making units, using data envelopment analysis. Reasons for inefficiencies of departments arise from pure technical efficiency component. Furthermore, a second stage analysis is implemented to observe the effects of external factors called non-discretionary inputs on efficiency results. Finally, efficiency differences between two types of departments are tested according to their education programs with a Mann - Whiney U Test.

Computation of scale elasticity in presence of exogenously fixed inputs

In this paper, the notion of scale elasticity is initially developed for models with non-discretionary inputs. A new unified formulation, resembling those for classic developments is proposed for computation of scale elasticity in presence of exogenously fixed inputs in the framework of date envelopment analysis.In order to remove the harshness of fixed inputs, we invoke regression of fixed inputs over efficiency measures and therefore units with more favorable environment indices are discounted for pioneers set. This naturally implies that different production possibility sets are induced according to environmental affect. Scale elasticity is then computed using indirect approach for both differentiable and non-differentiable cases.Also, the approach is illustrated with numerical examples and proved its benefit over selective approach, proposed by Podinovski and Førsund, by comparing and contrasting with numerical data. Moreover, the geometry and rationale behind the notion are described.

PRM36 - Non-Discretionary Inputs Are Important Factors In Hospital Efficiency Studies And Policy Evaluation

PRM36 - Non-Discretionary Inputs Are Important Factors In Hospital Efficiency Studies And Policy Evaluation

Data Envelopment Analysis and non-discretionary inputs: How to select the most suitable model using multi-criteria decision analysis

Within Data Envelopment Analysis, several alternative models allow for an environmental adjustment. The majority of them deliver divergent results. Decision makers face the difficult task of selecting the most suitable model. This study is performed to overcome this difficulty. By doing so, it fills a research gap. First, a two-step web-based survey is conducted. It aims (1) to identify the selection criteria, (2) to prioritize and weight the selection criteria with respect to the goal of selecting the most suitable model and (3) to collect the preferences about which model is preferable to fulfil each selection criterion. Second, Analytic Hierarchy Process is used to quantify the preferences expressed in the survey. Results show that the understandability, the applicability and the acceptability of the alternative models are valid selection criteria. The selection of the most suitable model depends on the preferences of the decision makers with regards to these criteria.

Directional distances and their robust versions: Computational and testing issues

Directional distance functions provide very flexible tools for investigating the performance of Decision Making Units (DMUs). Their flexibility relies on their ability to handle undesirable outputs and to account for non-discretionary inputs and/or outputs by fixing zero values in some elements of the directional vector. Simar and Vanhems (2012) and Simar, Vanhems, and Wilson (2012) indicate how the statistical properties of Farrell–Debreu type of radial efficiency measures can be transferred to directional distances. Moreover, robust versions of these distances are also available, for conditional and unconditional measures. Bădin, Daraio, and Simar (2012) have shown how conditional radial distances are useful to investigate the effect of environmental factors on the production process. In this paper we develop the operational aspects for computing conditional and unconditional directional distances and their robust versions, in particular when some of the elements of the directional vector are fixed at zero. After that, we show how the approach of Bădin et al. (2012) can be adapted in a directional distance framework, including bandwidth selection and two-stage regression of conditional efficiency scores. Finally, we suggest a procedure, based on bootstrap techniques, for testing the significance of environmental factors on directional efficiency scores. The procedure is illustrated through simulated and real data.

Introducing a new DEA methodology for environmental inputs

Data envelopment analysis or DEA is a standard methodology for assessing technical efficiency. In many DEA applications, e.g. in the case of schools or hospitals, the issue arises of calculating efficiency in the presence of nondiscretionary/environmental inputs. We propose a three-stage DEA model to address the environmental input issue, and we provide a simulation analysis that illustrates the implementation and potential advantages of our approach relative to the leading existing multi-stage model of nondiscretionary inputs.

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.

Eficiência na provisão de educação pública municipal: uma análise em três estágios dos municípios brasileiros

O artigo busca analisar as características municipais que afetam a eficiência dos municípios brasileiros na gestão educacional, consequência do processo de descentralização educacional na década de 90. As informações foram extraídas da Prova Brasil, Censo Escolar, Finbra e STN para 2005. Empregamos um procedimento em três estágios, cujo primeiro consiste no uso de modelos SBM (slacks based measure) no cálculo da eficiência no uso de insumos discricionários. Em seguida, controlamos pelos insumos não discricionários, resultando em um novo índice de eficiência. Finalmente, aplicamos as misturas finitas para analisar a heterogeneidade existente entre os diversos municípios em relação aos níveis de eficiência da gestão municipal. Os resultados mostram a não uniformidade de impactos demográficos, políticos e de recursos sobre a eficiência da gestão educacional entre os diversos grupos de municípios brasileiros. O aumento de democracia e recursos como o decorrente do Fundef, em geral, aumenta a eficiência da administração escolar municipal.

Developing Common Set of Weights with Considering Nondiscretionary Inputs and Using Ideal Point Method

Data envelopment analysis (DEA) is used to evaluate the performance of decision making units (DMUs) with multiple inputs and outputs in a homogeneous group. In this way, the acquired relative efficiency score for each decision making unit lies between zero and one where a number of them may have an equal efficiency score of one. DEA successfully divides them into two categories of efficient DMUs and inefficient DMUs. A ranking for inefficient DMUs is given but DEA does not provide further information about the efficient DMUs. One of the popular methods for evaluating and ranking DMUs is the common set of weights (CSW) method. We generate a CSW model with considering nondiscretionary inputs that are beyond the control of DMUs and using ideal point method. The main idea of this approach is to minimize the distance between the evaluated decision making unit and the ideal decision making unit (ideal point). Using an empirical example we put our proposed model to test by applying it to the data of some 20 bank branches and rank their efficient units.

Using DEA cross-efficiency evaluation for suppliers ranking in the presence of non-discretionary inputs

Supply chain includes all activities associated with the flow and transformation of goods from the raw material stage through to the end user. Supplier selection is one of the most important parts of supply chain management (SCM). For selecting suppliers, data envelopment analysis (DEA), as a multiple criteria decision making tool, has been applied for several times. However, sometimes in supplier selection problem, there may exist some criteria that are beyond the control of a management. These criteria are called non-discretionary or exogenously fixed factors. Since in traditional treatment of non-discretionary inputs in DEA, free reign is given when deciding for each decision making unit (DMU) which outputs and inputs to emphasise, many different avenues are present by which a DMU can appear efficient. Therefore, it is common to have many DMUs that are relatively efficient. In addition, since each DMU has its own set of weights, all of its weight might be put on a single output and input. As a result, the objective of this paper is to propose a cross-efficiency model which is able to consider non-discretionary inputs. A numerical example demonstrates the application of the proposed model in supplier selection context.

Relative efficiency of police directorates in Slovenia: A non-parametric analysis

The main purpose of the paper is to apply a non-parametric methodology for measuring public police performance in Slovenia. The paper considers how previous studies have modeled the role of policing in their specifications of inputs and output. In particular, the multiple-stage Data Envelopment Analysis (DEA) technique is presented and then applied to measure the relative efficiency of police-work-related data for eleven Police Directorates (PDs) in 2010 and also compared with the efficiency scores in 2005. The data obtained from the police databases is analyzed through the Frontier Analyst 4.0 and SPSS 19.0 statistical package software. The results show that the technical efficiency varies significantly across the police directorates and across the selected years, even when we allow for environmental factors and control for these non-discretionary inputs. Most police directorates in Slovenia could attain a higher output if they were fully efficient. Indeed, all of the inefficient police directorates can learn how to ensure a “good” performance from the efficient ones (i.e. the Maribor PD and the Novo mesto PD) by observing how they are processing their inputs and outputs. Finally, the empirical results of the paper are important indicators of the relative efficiency (or inefficiency) of police directorates that can serve as a guide to the General Police Directorate when further investigating how to enhance the performance efficiency of the various units.

Local Government Efficiency: Evidence from the Czech Municipalities

We measure cost efficiency of 202 Czech municipalities of extended scope in period 2003-2008. The study is the first application of overall efficiency measurement of the local governments in the new EU member states, and the second in post-communist countries. We measure government efficiency through established quantitative and qualitative indicators of the provision of education, cultural facilities, infrastructure and other local services. First, we employ non-parametric approach of the data envelopment analysis and adjust the efficiency scores by bootstrapping. Second, we employ the stochastic frontier analysis and control for effects of various demographic, economic, and political variables. We compare scores under our preferred specification, i.e. pseudo-translog time-variant stochastic-frontier analysis with determinants, with alternative scores. The determinants that robustly increase inefficiency are population size, distance to the regional center, share of university-educated citizens, capital expenditures, subsidies per capita, and the share of self-generated revenues. Concerning political variables, increase in party concentration and the voters' involvement increases efficiency, and local council with a lower share of left-wing representatives also tend to be more efficient. We interpret determinants both as indicators of slack, non-discretionary inputs, and unobservable outputs. The analysis is conducted also for the period 1994-1996, where political variables appear to influence inefficiency in a structurally different way. From comparison of the two periods, we obtain that small municipalities improve efficiency significantly more that large municipalities.

A data envelopment analysis model for selecting suppliers in the presence of both dual-role factors and non-discretionary inputs

Supplier selection is the strategy adopted by the manufacturer, to evaluate and select suppliers, which can fulfil the requirements of the manufacturer. To this end, data envelopment analysis (DEA), as a multiple criteria decision-making tool, has been applied for several times. However, conventional DEA models cannot simultaneously consider dual-role and non-discretionary factors. The objective of this paper is to propose a DEA model for ranking suppliers in the presence of both dual-role factors and non-discretionary inputs. A numerical example demonstrates the application of the proposed model.