Showing papers on "Data envelopment analysis published in 2005"

Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References

Abstract: General Discussion.- The Basic CCR Model.- The CCR Model and Production Correspondence.- Alternative Dea Models.- Returns To Scale.- Models with Restricted Multipliers.- Discretionary, non-Discretionary and Categorical Variables.- Allocation Models.- Data Variations.- Super-Efficiency Models.

Measuring Eco-efficiency of Production with Data Envelopment Analysis

Abstract: Summary Aggregation of environmental pressures into a single environmental damage index is a major challenge of eco-efficiency measurement. This article examines how the data envelopment analysis (DEA) method can be adapted for this purpose. DEA accounts for substitution possibilities between different natural resources and emissions and does not require subjective judgment about the weights. Although DEA does not require subjective or normative judgment, soft weight restrictions can be incorporated into the framework. The proposed approach is illustrated by an application to assessing ecoefficiency of road transportation in the three largest towns of eastern Finland.

The Impact of Macroeconomic and Regulatory Factors on Bank Efficiency: A Non-Parametric Analysis of Hong Kong's Banking System

Abstract: This paper assesses the relative technical efficiency of institutions operating in a market that has been significantly affected by environmental and market factors in recent years, the Hong Kong banking system. These environmental factors are specifically incorporated into the efficiency analysis using the innovative slacks-based, second stage Tobit regression approach advocated by Fried et al (1999). A further innovation is that we also employ Tone's (2001) slacks-based model (SBM) to conduct the Data Envelopment Analysis (DEA), in addition to the more traditional approach attributable to Banker, Charnes and Cooper (BCC) (1984). The results indicate: high levels of technical inefficiency for many institutions; considerable variations in efficiency levels and trends across size groups and banking sectors; and also differential impacts of environmental factors on different size groups and financial sectors. Surprisingly, the accession of Hong Kong to the People's Republic of China, episodes of financial deregulation, and the 1997/98 South East Asian crisis do not seem to have had a significant independent impact on relative efficiency. However, the results suggest that the impact of the last mentioned may have come via the adverse developments in the macro economy and in the housing market.

A reassessment of the human development index via data envelopment analysis

Abstract: To consider different aspects of life when measuring human development, the United Nations Development Program introduced the Human Development Index (HDI). The HDI is a composite index of socioeconomic indicators that reflect three major dimensions of human development: longevity, knowledge and standard of living. In this paper, the assessment of the HDI is reconsidered in the light of data envelopment analysis (DEA). Instead of a simple rank of the countries, human development is benchmarked on the basis of empirical observations of best practice countries. First, on the same line as HDI, we develop a DEA-like model to assess the relative performance of the countries in human development. Then we extend our calculations with a post-DEA model to derive global estimates of a new development index by using common weights for the socioeconomic indicators. Finally, we introduce the transformation paradigm in the assessment of human development. We develop a DEA model to estimate the relative efficiency of the countries in converting income to knowledge and life opportunities.

Cross-Country Efficiency of Secondary Education Provision: A Semi-Parametric Analysis with Non-Discretionary Inputs

Abstract: We address the efficiency of expenditure in education provision by comparing the output (PISA results) from the educational system of 25, mostly OECD, countries with resources employed (teachers per student, time spent at school). We estimate a semi-parametric model of the education production process using a two-stage procedure. By regressing data envelopment analysis output scores on nondiscretionary variables, both using Tobit and a single and double bootstrap procedure, we show that inefficiency is strongly related to GDP per head and adult educational attainment.

Nonparametric frontier estimation: a conditional quantile-based approach

Abstract: In frontier analysis, most of the nonparametric approaches (free disposal hull [FDH], data envelopment analysis [DEA]) are based on envelopment ideas, and their statistical theory is now mostly available. However, by construction, they are very sensitive to outliers. Recently, a robust nonparametric estimator has been suggested by Cazals, Florens, and Simar (2002, Journal of Econometrics 1, 1–25). In place of estimating the full frontier, they propose rather to estimate an expected frontier of order m. Similarly, we construct a new nonparametric estimator of the efficient frontier. It is based on conditional quantiles of an appropriate distribution associated with the production process. We show how these quantiles are interesting in efficiency analysis. We provide the statistical theory of the obtained estimators. We illustrate with some simulated examples and a frontier analysis of French post offices, showing the advantage of our estimators compared with the estimators of the expected maximal output frontiers of order m.We thank J.P. Florens for helpful discussions and C. Cazals for providing the post office data set. We also are very grateful to the referees for useful suggestions.

Efficiency of public spending in developing countries : an efficiency frontier approach

Abstract: Government spending in developing countries typically account for between 15 and 30 percent of GDP. Hence, small changes in the efficiency of public spending could have a major impact on GDP and on the attainment of the government's objectives. The first challenge that stakeholders face is measuring efficiency. This paper attempts such quantification and has two major parts. The first part estimates efficiency as the distance between observed input-output combinations and an efficiency frontier (defined as the maximum attainable output for a given level of inputs). This frontier is estimated for several health and education output indicators by means of the Free Disposable Hull (FDH) and Data Envelopment Analysis (DEA) techniques. Both input-inefficiency (excess input consumption to achieve a level of output) and output-inefficiency (output shortfall for a given level of inputs) are scored in a sample of 140 countries using data from 1996 to 2002. The second part of the paper seeks to verify empirical regularities of the cross-country variation in efficiency. Results show that countries with higher expenditure levels register lower efficiency scores, as well as countries where the wage bill is a larger share of the government's budget. Similarly, countries with higher ratios of public to private financing of the service provision score lower efficiency, as do countries plagued by the HIV/AIDS epidemic and those with higher income inequality. Countries with higher aid-dependency ratios also tend to score lower in efficiency, probably due to the volatility of this type of funding that impedes medium term planning and budgeting. Though no causality may be inferred from this exercise, it points at different factors to understand why some countries might need more resources than others to achieve similar educational and health outcomes.

Data envelopment analysis with common weights: the compromise solution approach

Abstract: A characteristic of data envelopment analysis (DEA) is to allow individual decision-making units (DMUs) to select the factor weights that are the most advantageous for them in calculating their efficiency scores. This flexibility in selecting the weights, on the other hand, deters the comparison among DMUs on a common base. In order to rank all the DMUs on the same scale, this paper proposes a compromise solution approach for generating common weights under the DEA framework. The efficiency scores calculated from the standard DEA model are regarded as the ideal solution for the DMUs to achieve. A common set of weights which produces the vector of efficiency scores for the DMUs closest to the ideal solution is sought. Based on the generalized measure of distance, a family of efficiency scores called ‘compromise solutions’ can be derived. The compromise solutions have the properties of unique solution and Pareto optimality not enjoyed by the solutions derived from the existing methods of common weights. An example of forest management illustrates that the compromise solution approach is able to generate a common set of weights, which not only differentiates efficient DMUs but also detects abnormal efficiency scores on a common base.

Measuring human development via data envelopment analysis: the case of Asia and the Pacific

Abstract: The United Nations Development Program introduced in 1990 the Human Development Index (HDI), which ever since is published annually in the Human Development Report. In this paper, the assessment of the HDI is reconsidered in the light of data envelopment analysis (DEA). The new approach is applied to the countries of the regional aggregate of Asia and the Pacific. Human development is benchmarked on the basis of empirical observations of best practice countries. First, on the same line with HDI, we develop a DEA-like linear programming model to assess the relative performance of the countries in terms of human development. Then we extend our calculations with a post-DEA goal-programming model to derive estimates of a new development index by using optimal weights for the socioeconomic indicators. Finally, we estimate the relative efficiency of the countries in converting income to human development. We develop and solve for this purpose a pure DEA model with variable returns to scale.

The application of mathematical programming approaches to estimating container port production.

Abstract: Container terminal production is both an important and complicated element in the contemporary global economy. This paper aims to evaluate the efficiency of the world’s most important container ports and terminals using the two alternative techniques of Data Envelopment Analysis (DEA) and the Free Disposal Hull (FDH) model. The results give an insight into the current efficiency ranking of the world’s major container ports and terminals. They also confirm expectations that the available mathematical programming methodologies lead to different results and that appropriate variable definition of input and output factors is a crucial element in meaningful applications of DEA and FDH. It is also concluded that the availability of panel data, rather than cross-sectional data would greatly improve the validity of the efficiency estimates derived from all the mathematical programming techniques applied.

Measuring DEA efficiency in internet companies

Abstract: This paper uses Data Envelopment Analysis (DEA), a non-parametric approach to the estimation of production functions, in order to assess efficiency in dot corn firms. These firms have two objectives: to make an impact in the Internet and to obtain revenues from their activities. For this reason, the outputs have been two: unique visitors--a web metric--and revenues. DEA efficiencies have been obtained under various input/output combinations. A ranking of dot com firms in terms of relative efficiency has been obtained. A method based on multivariate analysis has been proven to be successful at showing the strengths and weaknesses of individual dot com firms. It is shown that there is a relationship between the type of e-business (e-tailers, search/portal, content/communities), and the way in which efficiency is obtained. The paper suggests a new approach to the problem of deciding which inputs and outputs the model should contain.

The Application of Mathematical Programming Approaches to Estimating Container Port Production Efficiency

Abstract: Container terminal production is both an important and complicated element in the contemporary global economy. This paper aims to evaluate the efficiency of the world’s most important container ports and terminals using the two alternative techniques of Data Envelopment Analysis (DEA) and the Free Disposal Hull (FDH) model. The results give an insight into the current efficiency ranking of the world’s major container ports and terminals. They also confirm expectations that the available mathematical programming methodologies lead to different results and that appropriate variable definition of input and output factors is a crucial element in meaningful applications of DEA and FDH. It is also concluded that the availability of panel data, rather than cross-sectional data would greatly improve the validity of the efficiency estimates derived from all the mathematical programming techniques applied.

Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Measurements for Outliers

Abstract: In this paper we estimate the DEA technical efficiency for 4796 Brazilian municipalities, by applying a recently proposed “Jackstrap” method, which combines Bootstrap and Jackknife resampling techniques, to reduce the effect of outliers and possible errors in the data set. We perform calculations to identify and eliminate high leverage municipalities, using different variants of Data Envelopment Analysis (DEA), as well as Free Disposal Hull (FDH). Corroborating previous results, efficiency results for the Brazilian municipalities show a clear relationship between the size of the municipality and its efficiency scores. Indeed, under both DEA variants, smaller cities tend to be less efficient than larger ones hence indicating that the quality of the frontier adjustment improves significantly as the size of the municipality increases. We present arguments that may explain to some extent these findings, such as economies of scale and the excess spending due to revenue from royalties. However, such effects require further, more careful examination.

Measuring the efficiency of public services: the limits of analysis

Abstract: Summary. Policy makers are increasingly seeking to develop overall measures of the efficiency of public service organizations. For that, the use of 'off-the-shelf' statistical tools such as data envelopment analysis and stochastic frontier analysis have been advocated as tools to measure organizational efficiency. The analytical sophistication of such methods has reached an advanced stage of development. We discuss the context within which such models are deployed, their underlying assumptions and their usefulness for a regulator of public services. Four specific model building issues are discussed: the weights that are attached to public service outputs; the specification of the statistical model; the treatment of environmental influences on performance; the treatment of dynamic effects. The paper concludes with recommendations for policy makers and researchers on the development and use of efficiency measurement techniques.

Estimating the Potential Gains from Mergers

Abstract: We introduce simple production economic models to estimate the potential gains from mergers. We decompose the gains into technical efficiency, size (scale) and harmony (mix) gains, and we discuss alternative ways to capture these gains. We propose to approximate the production processes using the non-parametric Data Envelopment Analysis (DEA) approach, and we use the resulting operational approach to estimate the potential gains from merging agricultural extension offices in Denmark.

Evaluating the efficiency of a small hotel chain with a Malmquist productivity index

Abstract: By applying data envelopment analysis (DEA) a two-stage procedure is followed to evaluate the determinants of efficiency of a Portuguese public-owned hotel chain, Enatur for the period 1999 to 2001. In the first stage the paper estimates the Malmquist index and breaks it down into technical efficiency and technological change. In the second stage, a Tobit econometric model, designed to relate efficiency scores, along with other managerial and contextual variables, is used to identify the efficiency drivers. The implications of this study for managerial purposes are then discussed. Copyright © 2005 John Wiley & Sons, Ltd.

An International Comparison of R&D Efficiency : DEA Approach

Abstract: Summary A prerequisite for making R&D more productive is to be able to measure its productivity. Most of the previous studies on this topic have attempted to measure R&D productivity at the firm or industry levels. In this study, however, R&D productivity is measured at the national level to provide R&D policy implications, particularly for Asian countries. Contrary to the previous studies where total factor productivity was adopted, this study employs the data envelopment analysis (DEA) approach to measure R&D productivity. DEA is a multi‐factor productivity analysis model for measuring the relative efficiency of each Decision Making Unit (DMU). In addition to the basic DEA model that includes all inputs and outputs, five additional models are constructed by combining single input with all outputs and single output with all inputs in order to measure specialized R&D efficiency. In this study, the twenty‐seven countries are classified into four clusters based on the output‐specialized R&D efficiency: inve...