Non-discretionary Variables Research Articles

Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies

In 2015 the Brazilian regulator presented a DEA benchmarking model to set the regulatory operational cost goals, to be reached in four years for 61 electricity distribution utilities. The DEA model uses: adjusted operational cost as the input variable, seven output variables and weight restrictions. Although non-discretionary variables or environmental variables are available in the dataset, the regulator argued that no statistically significant correlation was found between the DEA efficiency scores and the non-discretionary variables. This study evaluates the statistical correlation between the DEA efficiency scores and the available environmental variables. Spatial statistic methods are used to show that the efficiency scores are geographically correlated. Furthermore, due to Brazil's environmental diversity and large territory it is unlikely that only one environmental component is sufficient to adjust inefficiencies across the Brazilian territory. Thus, a new combined environmental variable is proposed. Finally, a second stage model using the proposed environmental variable and accounting for a spatial latent structure is presented. Results show major differences between original and corrected efficiency scores, mainly for utilities located in harsh environments and which originally achieved lower efficiency scores.

Assessment of efficiency in basic and secondary education in Tunisia: A regional analysis

To determine the factors enhancing the efficiency of basic and secondary education in 24 governorates of Tunisia in 1999, 2003, 2006 and 2008, we apply a non-parametric approach, Data Envelopment Analysis (DEA) to multi-inputs and multi-outputs. Physical resources used in the study are: the number of classes per 100 students and the number of schools per million inhabitants. Human and financial resources are described by the number of teacher per 100 students and education spending per student respectively. The output measures include the success rate of baccalaureate exam and the rate of non-doubling in the 9th year. Our results show the absence of significant relationship between school resources and student performance. The output variable, non-doubling rate in the 9th year is the only factor able to influence the efficiency level of governorates in terms of 2nd cycle of basic education and secondary education. By regressing efficiency scores on non-discretionary variables, we find that inefficiency in education is strongly related to poverty within governorates.

Measuring the performance of a dehydration plant of apples

Given the importance of the Chilean dried-fruit market and the characteristics of the industrial process of dehydration, it becomes imperative for companies to measure the efficiency of their production processes in order to identify critical areas and take the necessary actions to improve them. Hence, the present work performs an efficiency analysis for the production of dried apples in a plant of the Maule region, Chile. The methodology used is Data Envelopment Analysis, considering both discretionary and non-discretionary variables. The results indicate that the application of the model without non-discretionary variables shows higher efficiency indices than the model with non-discretionary variables. Additionally, the efficiency analysis results, segregated by variety, origin, and fruit type, indicate that the selection of these segregations could be used to increase the production or generate higher efficiencies. Finally, the technological change in the same plant is analyzed through the Malmquist index. The findings of this research could help improve the decision-making process of managers concerned with the efficient use of resources within the company.

A multiobjective approach for non-discretionary variables in data envelopment analysis

Data Envelopment Analysis is a non-parametrical approach for efficiency evaluation of so-called DMUs (Decision Making Units) and takes into account multiple inputs and outputs. For each inefficient DMU, a target is provided which is constituted by the inputs or outputs levels that are to be attained for the inefficient DMU to become efficient. However, multiobjective models, known as MORO (Multiobjective Model for Ratio Optimization) provide a set of targets for inefficient DMU, which provides alternatives among which the decision-maker can choose. In this paper, we proposed an extension of the MORO models to take into account non-discretionary variables, i.e., variables that cannot be controlled. We present a numerical example to illustrate the proposed multiobjective model. We also discuss the characteristics of this model, as well as the advantages of offering a set of targets for the inefficient DMUs when there are non-discretionary variables in the data set.

Os Determinantes da Eficiência dos Gastos Públicos com Segurança nos Municípios Mineiros: Uma Análise a partir da Metodologia DEA

Normal 0 21 false false false PT-BR X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:Tabela normal; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; text-align:center; mso-pagination:widow-orphan; font-size:11.0pt; font-family:Calibri,sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-fareast-language:EN-US;} In order to better manage scarce resources in the context of public policies, the requirement for indexes to evaluate the public spending efficiency in providing goods and services assumes increasing importance. However, non-discretionary variables may affect the environments where the public policies need to act and, thus, they have impacts over the efficiency and need to be taken in account. Thus, the present work aims to obtain efficiency indexes of the spending on the public safety in the cities of the state of Minas Gerais, by using the nonparametric methodology of Data Envelopment Analysis (DEA), and afterwards verify the relationships of these indexes with the environmental variables. The results were refined by outlier detection and a non-parametric test to split the sample among three groups of municipalities, according to their population. The results show that urbanization and the educational quality have important impacts on the efficiency for all the groups, so that the first have a positive relationship with the inefficiency, while the second has a negative one. For the smaller municipalities, the Gini Index and the per capita GDP are also important, having both a positive relation with the inefficiency.

Efficiency of municipal legislative chambers

Abstract A novel study of Brazilian city council efficiency using the non-parametric estimator FDH (free disposal hull) with bias correction is presented. In regional terms, study results show a concentration of efficient councils in the southern region. In turn, those in the northeastern and southeastern regions are among the most ineffective councils. In these latter two regions, most councils could at least double their outputs while maintaining the same volume of inputs. Regarding population size, for cities with up to 500,000 inhabitants, more than 60% of city councils could at least quadruple their output. Regarding inefficiencies revealed through non-discretionary variables (environmental variables), the study results show a correlation between councilor education levels and city council efficiency.

A data envelopment analysis approach for measuring the efficiency of Canadian acute care hospitals

Data envelopment analysis is a methodology particularly well-suited to measuring the efficiency of hospitals because it is able to accommodate multiple heterogeneous inputs and outputs in order to model the complex relationships that exist within them. This research uses data envelopment analysis to develop a model of Canadian hospital production efficiency in collaboration with the Canadian Institute for Health Information. The model is intended to illustrate the utility of data envelopment analysis as a hospital performance measurement tool for Canadian Institute for Health Information and to augment their current hospital performance indicators. The model measures the overall production efficiency of acute care hospitals using labour and capital inputs together with outputs measuring inpatient and outpatient activity. The model also includes non-discretionary variables adjusting for case-mix variations among the hospitals. The model is extensively validated and identifies a set of highly referenced, efficient hospitals ideal for the establishment of best practices.

Quality of Life and Efficiency in Italian Municipalities

The focus of our research is to assess the relationship between local government performance and urban quality of life (QoL), following the recent literature (Morais & Camanho, Omega, 2011). QoL is a multifaceted concept that is difficult to measure as it includes various aspects of well-being related to economic, environmental, and social dimensions of life. The perception of public service quality depends partially on inputs employed. Likewise, the concept of local government efficiency is not so easy to define, because potential inefficiencies in public service provision may create political and social frictions and the definition of government output may be controversial. We take into account these problems by explicitly considering not only traditional “desirable” outputs, like education, welfare, environment, urban transportation, local police and other relevant public services, but also “undesirable” outputs such as number of pollutants and number of accidents. The objective of our research is to analyze urban QoL using parametric and nonparametric procedures to evaluate the impact of both desirable and undesirable outputs and non-discretionary variables on the efficiency achieved by municipalities. We also include in the QoL measurement relevant variables such as budget constraints, social-economic conditions and political contexts. The empirical analysis uses a large dataset on municipalitý characteristics (main sources are the Association of Italian City Councils, ANCI, National Institute for Statistics, ISTAT and Legambiente, Italian environmental association) with detailed information on budgets, grants, taxation, structural variables related to QoL and social and environmental aspects. This procedure allows us to build a model of intervention to identify “best urban practices”. We employ data from 1997 to 2008 covering a wide span of time before the economic crisis, using as output indicators the Legambiente Survey and other environmental variables. As an input indicator we use the total cost of public services which also includes payments for capital and third parties services (Balaguer-Coll et al., European Economic Review, 2007). We proxy other inputs affecting administrators’ behavior with Int Adv Econ Res (2014) 20:347–348 DOI 10.1007/s11294-014-9473-0

An analysis of the efficiency of player performance at the 2011 Cricket World Cup

In limited overs cricket, efficiency plays a significant role in team success. Batsmen especially are under pressure to score quickly rather than in large quantities because only 50 overs are available per innings. This paper uses data envelopment analysis (DEA) and stochastic multicriteria acceptability analysis (SMAA) to assess the efficiency with which players at the 2011 Cricket World Cup converted inputs (balls faced or bowled) into performance outputs. The effect that non-discretionary variables like the cricketing resources available to a player have on his efficiency is controlled for, allowing for a fairer assessment across players from different countries.

Teaching hospitals in Brazil: Findings on determinants for efficiency

Hospital efficiency is an important dimension for health services evaluation and suffers the influence of different non-discretionary variables, not necessarily under the control of the hospital manager. These must be considered when establishing goals for efficient and socially committed health, which in many countries is now the primary goal. To test and further understand the context of non-controllable variables in healthcare delivery, this study examined 104 teaching hospitals in Brazil. The efficiency score was generated using weight restricted-output oriented data envelopment analysis model. A second-stage logistic regression analysis was deployed to examine the predictors of efficiency among the non-discretionary variables. The efficiency results indicate that, it requires reduction in labor and in bed capacity, while it increases necessary admissions and high complexity procedures. The main predictors of efficiency were the size of the hospital, high teaching intensity, and low teaching dedication. The model predicts no association between efficiency and ownership. Teaching load, as an important source of qualified human resources to society, although associated with higher health costs, when not considered in service delivery, may distort the analysis of efficiency for the teaching hospitals. These findings could have implications for any healthcare system that has teaching hospitals among its components.

Avoidable damage assessment of forest fires in European countries: an efficient frontier approach

The purpose of this research is to study the avoidable damage from forest fires in the most affected European Union (EU) Member States (MS) using a quantitative model based on a non-parametric efficient frontier technique, namely data envelopment analysis (DEA). The procedure allows the comparison of forest fire damage in EU countries by computing relative efficiency scores and quantifying improvement targets. The proposed DEA model evaluates a slacks-based measure of efficiency and considers two non-discretionary variables (the forest area of the countries and fire weather index). Data from the most affected EU countries over the period 2005–2010 have been used. An input-oriented model has been considered in order to take into account the number of fire events and total burned area as the fire management targets. The study finds evidence that there is a considerable excess of forest area affected by fire in most of the EU countries. The empirical results also suggest that the mean relative damage efficiency in Southern European MS and Other MS is not significantly different. From the efficiency scores, different clusters, with clear characteristic features, emerge. The next step is to extend the best practices of the efficient EU countries.

Measuring the performance of pharmacy stores using discretionary and non-discretionary variables

The purpose of this paper is to measure the performance of chain of 46 pharmacy retail stores located in Delhi and National Capital Region (NCR) and to analyze the impact of non-discretionary variables on the efficiency of the stores. A two stage procedure is used for benchmarking the retail stores. Firstly, data envelopment analysis is applied and in the second stage, Tobit regression model is applied to determine the drivers of efficiency. The results indicate that most of the retail stores are either average or below average in their performance and therefore needs improvement. Scale plays an important role in efficiency evaluation. Footfalls, sales, operating expenses and store size are identified as drivers of efficiency. The non-discretionary input variables, age and location of the store has insignificant impact on efficiency of retail stores. This shows that the current efficiency level is mainly attained through the controllable operations taking place at the store level. This study provides us with a framework for performance measures along with useful managerial insights. Also, assists in focusing upon the right areas of operations by identifying the efficiency drivers. This may help out the management in improving their overall performance.

Assessing health efficiency across countries with a two-step and bootstrap analysis

Regressing Data Envelopment Analysis (DEA) output efficiency scores on nondiscretionary variables, with a two-stage DEA/Tobit and bootstrap procedures, we show that health inefficiency in Organization for Economic Co-operation and Development (OECD) countries is related to Gross Domestic Product (GDP) per head, education level, obesity and smoking habits.

Categorical and continuous non-discretionary variables in data envelopment analysis: a comparison of two single-stage models

Non-discretionary or environmental variables are regarded as important in the evaluation of efficiency in Data Envelopment Analysis (DEA), but there is no consensus on the correct treatment of these variables. This paper compares the performance of the standard BCC model as a base case with two single-stage models: the Banker and Morey (1986a) model, which incorporates continuous environmental variables and the Banker and Morey (1986b) model, which incorporates categorical environmental variables. Simulation analyses are conducted using a shifted Cobb-Douglas function, with one output, one non-discretionary input, and two discretionary inputs. The production function is constructed to separate environmental impact from managerial inefficiency, while providing measures of both for comparative purposes. Tests are performed to evaluate the accuracy of each model. The distribution of the inputs, the sample size and the number of categories for the categorical model are varied in the simulations to determine their impact on the performance of each model. The results show that the Banker and Morey models should be used in preference to the standard BCC model when the environmental impact is moderate to high. Both the continuous and categorical models perform equally well but the latter may be better suited to some applications with larger sample sizes. Even when the environmental impact is slight, the use of a simple two-way split of the sample data can produce significantly better results under the Categorical model in comparison to the BCC model.

Managing Efficiency in International Tourist Hotels in Taipei using a DEA Model with Non-discretionary Inputs

In this paper, an input-oriented data envelopment analysis model with discretionary and non-discretionary variables is proposed for measuring the efficiency of international tourist hotels (ITHs). The model considers two outputs (total revenues and occupancy percentage), two discretionary inputs (total number of employees and total operating costs) and two non-discretionary inputs (total number of guest rooms and food and beverage capacity). Variable returns to scale are assumed. Both the proposed and the traditional input-oriented model are applied to measure the efficiency of 21 ITHs in Taipei during 2003–2007, and different efficiency measures and benchmarks are derived to help the management of these hotels adjust more effectively their discretionary inputs to achieve better efficiency. Implications are also discussed.

A NEW MALMQUIST PRODUCTIVITY INDEX BASED ON SEMI-DISCRETIONARY VARIABLES WITH AN APPLICATION TO COMMERCIAL BANKS OF CHINA

The Malmquist productivity index studies productivity change, that is, the technical progress or regress together with the efficiency changes over time. In a nonparametric framework, the index can be estimated by data envelopment analysis (DEA). In this paper, first all inputs are divided into three groups, namely, discretionary variables, nondiscretionary variables, and semi-discretionary variables, and then a mixed integer linear model is proposed to deal with semi-discretionary variables. The proposed models consider not only the properties of semi-discretionary inputs, but also the relationship between them and other inputs. By introducing such a relationship and the preferences of decision-makers (DMs), the models aid DMs in generating efficiency scores and finding proper benchmarking points. Finally, the Malmquist productivity index combining the proposed model is computed and illustrated by an empirical application to the evaluation of 17 branches of Bank of China in Anhui Province. The results show a slight decrease in productivity during the year 2007/2008, and the productivity change positively during 2008/2009 due largely to efficiency increase.

Influência de fatores ambientais na eficiência de hospitais de ensino

Summary Objective: to measure the performance of teaching hospitals by Data Envelopment Analysis (DEA) and to study the influence of environmental factors on the efficiency. Methodology: A hundred and four teaching hospitals were analyzed and the efficiency score was generated by DEA, VRS model, output oriented, with weight restrictions. The efficiency score criteria were then regressed on non-discretionary variables by logistic linear regression. Results: the efficiency score mean was 49% (SD=26%); five hospitals were efficient. In logistic regression, the main predictors of efficiency were the size of the hospital (p=0.001), high teaching intensity (p=0.027) and low teaching dedication (p=0.006). There was no association between efficiency and ownership form or HDI of the surrounding municipality. Conclusion: hospital efficiency suffers the influence of different environmental factors, not necessarily under the control of the manager, that should be considered when defining administrative goals and financing pacts.

Developing a stochastic DEA model for considering non-discretionary inputs

Formal statistical inference on efficiency measures is not possible. Stochastic DEA can deal effectively with noise in the non-parametric measurement of efficiency. In any realistic situation, however, there may be exogenously fixed or non-discretionary inputs or outputs that are beyond the control of a DMU’s management. The objective of this paper is to present a methodology for treating non-discretionary variables in stochastic formulation. Based on the proposed method, an effective performance measurement tool is developed to provide a basis for understanding the efficiency in stochastic situations. A numerical example is presented. In short, the main contributions of this work are as follows: an stochastic DEA model is extended to encompass non-discretionary variables and stochastic data, thus a typical model for efficiency analysis is developed as an effective performance measurement tool that is the contribution of the paper.

Performance and benchmarks of participating nations in Beijing Olympics using the DEA approach

In this paper, data envelopment analysis (DEA), a well known and effective tool for relative efficiency assessment, is used for measuring the performance of 86 participating nations that won at least one medal in Beijing Olympics. This approach considers two inputs (GDP and population) and three outputs (number of gold, silver and bronze medals won), and variable returns to scale are assumed. As both of the two inputs are non-discretionary variables which can not be controlled by decision makers, we choose an output-oriented DEA model for assessing the efficiency scores of participating countries. Performance indexes as well as benchmarks are analysed for each country. For the efficient participants, a performance index related to the benchmark is attained for expressing a complete ranking, while for the inefficient nations, a benchmarking result is provided for each of them to improve performance.

Stochastic DEA with ordinal data applied to a multi-attribute pricing problem

Multiple attribute pricing problems are highly challenging due to the dynamic and uncertain features in the associated market. In this paper, we address the condominium multiple attribute pricing problem using data envelopment analysis (DEA). In this study, we simultaneously consider stochastic variables, non-discretionary variables, and ordinal data, and present a new type of DEA model. Based on our proposed DEA, an effective performance measurement tool is developed to provide a basis for understanding the condominium pricing problem, to direct and monitor the implementation of pricing strategy, and to provide information regarding the results of pricing efforts for units sold as well as insights for future building design. A case study is executed on a leading Canadian condominium developer.