Pursuing efficiency: a data envelopment analysis of MFIs in Latin America

This article analyses the overall profitability efficiency (PE) of Microfinance Institutions (MFIs) in Latin America. The PE of each MFI in the study is broken down into two components: pure technical efficiency and scale efficiency. One data envelopment model is used to analyse each component. Each MFI was labelled as either a bank, cooperative and credit union, nonbanking financial institution or non-governmental organization, and then the analysis was performed on each separate group. The results suggest that, on average, banks are the most efficient MFIs; while NGOs are, on average, the least efficient MFIs. On average, all 4 groups are more pure technically efficient than scale efficient. Banks, nongovernmental organizations, nonbanking financial institutions, cooperatives and credit unions all seem to have problems with scale efficiency. Many MFIs seem to be operating on the increasing returns to scale frontier and are in a more favourable position for expansion.     

Measuring the efficiency of search engines: an application of data envelopment analysis

This paper adopted the data envelopment analysis (DEA) method to investigate the efficiency of several search engines. A query search on a search engine is modelled as a production process. The input and output vectors are defined and measured accordingly. We studied seven engines, Alta Vista, Excite, Hotbot, Lycos, Infoseek, Open Text, and WebCrawler and found that Alta Vista, Excite, Infoseek, and WebCrawler are efficient but the other three are not. Possible efficiency improvements are calculated.     

Cost efficiency of the Chinese banking sector: A comparison of stochastic frontier analysis and data envelopment analysis

This paper investigates the consistency of efficiency scores obtained from the stochastic frontier analysis and data envelopment analysis methods. We estimate cost efficiency and economies of scale based on an unbalanced panel data set of Chinese banks over the period 1994 to 2007. The results suggest moderate consistency between parametric and non-parametric frontier methods in efficiency scores rankings, identification of best and worst practise banks, the stability of efficiency scores over time and correlation between frontier efficiency and accounting based performance measures. Based on the findings, we conclude that the use of multiple frontier techniques for efficiency analysis is to be strongly recommended and that this methodological cross-checking analysis will result in more robust and convincing assessments of bank performance.     

Contract farmer and poultry farm efficiency in Bangladesh: a data envelopment analysis

The objective of this article is to determine the efficiency of the poultry farm in Bangladesh and to assess the influence of contract farming system, using a data envelopment analysis. Seventy-five commercial poultry farms (25 and 50 independent and contract farms, respectively) were randomly selected. The results reveal that efficiency scores vary across sample farms. To explain some of these variations, the efficiency scores were regressed on some human capital variables and farming system using a Tobit model. The study also estimates elasticities to provide the information on the magnitude of the influence of variables on Technical Efficiency (TE), Allocative Efficiency (AE) and Economic Efficiency (EE). The results show that the contracting system is positively and significantly related to the farm's TE, AE and EE. This is expected because under contractual agreement, in order to obtain sufficient supplies of the right quality of poultry meat at the right time, the company provides technical know how assistance through company's recruited supervisor, production inputs and services, and production credit along with intensive supervision, which in turn improves farm efficiency. Thus, by receiving technical know how contract farmers have gained more knowledge on their resource and practices, which enables them to use resources more efficiently. Empirical results can provide crucial information to policy makers that improve poultry farm efficiency.     

Measuring the efficiency of health systems of OECD countries by data envelopment analysis

This study aims to assess the efficiency of health sectors of 34 OECD countries by employing input-oriented data envelopment analysis (DEA) method both under constant and variable returns to scale assumptions. In the analysis, the number of doctors, number of patient beds and health expenditure per capita were used as input variables and life expectancy at birth and infant mortality rate were used as outputs. At the first stage, DEA analysis was performed for 34 countries, and at the second stage outlier 8 countries were eliminated to form a more homogeneous group and to achieve more accurate results. 11 of the 26 countries were found to have efficient health systems, and there is room for efficiency improvements in health sector in the remaining 15 countries.     

The relative efficiency of schizophrenia health care systems: an international comparison using data envelopment analysis

Abstract

Aim

To compare the health economic efficiency of health care systems across nations, within the area of schizophrenia, using a data envelopment analysis (DEA) approach.     

An economic efficiency study on different regions of Ghana via Slack-based data envelopment analysis and regression analysis

In this article, we evaluate the efficiency of the 10 different regions of Ghana using slack-based data envelopment analysis, a nonparametric linear programming technique. Furthermore, we analyse the variable effects on the efficiency of the regions by various regression models using bootstrap sampling technique. The data come from the 1991/1992 and 1998/1999 Ghana Living Standards Survey. Our results show that wealth is not strongly related to efficiency. For example, the study indicates that the Brong–Ahafo region is the most efficient region but not the most wealthy in Ghana. Generally, urban regions are not found to be among the most efficient regions due to the high expenditures. The regression analysis shows that female heads of household have an overall positive effect on efficiency. In addition, any form of education obtained is also found to have a significant positive effect on efficiency.     

Environmental cost-benefit analysis of alternative timing strategies in greenhouse gas abatement: A data envelopment analysis approach

Assessing the benefits of climate policies is complicated due to ancillary benefits: abatement of greenhouse gases also reduces local air pollution. The timing of the abatement measures influences both the economic costs and ancillary benefits. This paper conducts efficiency analysis of ten alternative timing strategies, taking into account the ancillary benefits. We apply the approach by Kuosmanen and Kortelainen [Valuing Environmental Factors in Cost-Benefit Analysis Using Data Envelopment Analysis, Ecological Economics 62 (2007), 56-65], which does not require prior valuation of the environmental impacts. The assessment is based on synthetic data from a dynamic applied general equilibrium model calibrated to The Netherlands. Our assessment shows that if one is only interested in GHG abatement at the lowest economic cost, then equal reduction of GHGs over time is preferred. If society is willing to pay a premium for higher ancillary benefits, an early mid-intensive reduction strategy is optimal.     

Valuing environmental factors in cost-benefit analysis using data envelopment analysis

Environmental cost-benefit analysis (ECBA) is used for the social evaluation of investment projects and policies that involve significant environmental impacts. Economic valuation of environmental impacts forms one of the critical steps of ECBA. We develop a new method for this purpose, which does not require price estimation for environmental impacts using stated or revealed preference methods. Our approach is based on data envelopment analysis (DEA), which is modified to ECBA by using absolute shadow prices instead of relative prices. We also discuss how the method can be used for sensitive analysis in ECBA. We illustrate the method by means of a hypothetical numerical example.     

Using data envelopment analysis to assess macroeconomic policy performance

It is common practice to summarize the macroeconomic performance of countries in terms of the four well-known dimensions captured by the magic diamond of the OECD. This study provides a comparison of several synthetic indicators that merge the four separate indicators into one single statistic. These indicators are inspired by Data Envelopment Analysis (DEA)-based models, which allow for unequal weighting of the different economic objectives. The calculated weights then act as proxies for the true policy priorities. Comparison of the models focuses on the underlying assumptions as well as on the empirical results they generate.     

Efficiency and credit rating in Taiwan banking: data envelopment analysis estimation

In this article, we use the data envelopment analysis to measure the efficiency of banks before and after credit rating is taken into consideration and we also employ the Malmquist Productivity Index to measure the total factor productivity changes from 2001 to 2003. The results are as follows: (1) There is a positive relationship between the efficiency scores and credit rating, and thus, the credit rating can be a representative to evaluate the performance and quality of a bank; (2) We use the Wilconxon two-sample test of nonparametric statistic to test the influences of credit rating. The empirical result shows that the credit rating is proven to influence the efficiency of banks; (3) The efficiency scores improve in both investment grade (above tw BBB?) and speculation grade (under tw BBB?), when credit rating is taken into consideration. The empirical results show that the efficiency scores of banks with a high credit rating improved relatively more when compared to banks with a lower credit rating; (4) In this research we also adopt the Malmquist index to observe the productivity and efficiency changes from year to year. We obtain results whereby the improvement of efficiency may be influenced greatly both from pure technical and scale efficiency changes.     

Estimating most productive scale size with stochastic data in data envelopment analysis

This article estimates most productive scale size in stochastic data envelopment analysis (DEA). Jahanshahloo and Khodabakhshi [Jahanshahloo, G.R. and Khodabakhshi, M., Using input–output orientation model for determining most productive scale size in DEA. Applied Mathematics and Computation 2003, 146(2–3), 849–855.] studied most productive scale size in classic data envelopment analysis. The classic data envelopment analysis requires that the values for all inputs and outputs be known exactly. However, this assumption may not be true, because data in many real applications cannot be precisely measured. One of the important methods to deal with imprecise data is considering stochastic data in DEA. Therefore, this research studies most productive scale size with considering stochastic data in DEA. To that end, input–output orientation model introduced in Jahanshahloo and Khodabakhshi [Jahanshahloo, G.R. and Khodabakhshi, M., Using input–output orientation model for determining most productive scale size in DEA. Applied Mathematics and Computation 2003, 146(2–3), 849–855.] is extended in stochastic data envelopment analysis. To solve the stochastic model, a deterministic equivalent is obtained. Although the deterministic equivalent is non-linear, it can be converted to a quadratic program. Furthermore, data of software companies is used to apply the proposed approach. Performance of software companies are evaluated based on their scale sizes in classic and stochastic data envelopment analysis.     

Local resource reallocation considering practical feasibility: a centralized data envelopment analysis approach

Many studies have addressed resource allocation issues by using centralized data envelopment analysis models. However, few of them provided a local resource reallocation plan which may be carried out more easily. This article proposes two models to get such plans. The first one considers an acceptable percentage of changes in resources to ensure practical feasibility. The second one further considers a situation where resources can only be allowed to shift within specific units. The proposed models are applied to an empirical study based on a hospital system in Taiwan. To demonstrate the practical feasibility of the suggested plans, we compare our reallocation suggestions to a plan that can make the whole system be perfectly efficient. The main conclusion is that the plans derived from our models are more practically feasible than that with perfect efficiency.     

Estimating most productive scale size with double frontiers data envelopment analysis

In this paper, most productive scale size (MPSS) for input and output mixes is measured from pessimistic point of view by using pessimistic data envelopment analysis (DEA). It is proved that the decision making unit (DMU) with the maximum pessimistic efficiency represents MPSS. However, the optimistic and the pessimistic measurements may identify different DMU as MPSS. To find the optimal DMU that represents MPSS, a double frontiers approach is developed by using the Hurwicz criterion to integrate both the information on the optimistic and the pessimistic frontiers. Numerical examples are provided to show the applications of the proposed methods in estimating MPSS.     

Performance evaluation of the English Premier Football League with data envelopment analysis

This paper uses data envelopment analysis (DEA) to evaluate the performance of English Premier League football clubs from 1998/99 to 2002/03 combining sport and financial variables. The paper evaluates how close the clubs are relative to the frontier of best practices, analysing how they manage sport as well as financial results. Managerial implications of the research are devised.     

Impact of input substitution and output transformation on data envelopment analysis decisions

Data envelopment analysis (DEA) can aid managerial decision-making because it offers an opportunity to measure organizational performance in a holistic manner, aggregating data from partial indicators into a single comprehensive measure. However, there are some methodological hazards associated with the use of DEA that are especially relevant to managerial decisions, but which have been largely ignored in the literature. Herein, we identify and show the impact of a ubiquitous methodological hazard in DEA modelling – the economic assumptions regarding input substitutions and output transformations.     

Economies of scale in the US computer industry: An empirical investigation using data envelopment analysis

Up to recently, economists have had no good tools to measure the returns to scale of individual corporations in an industry. Data envelopment analysis (DEA) is a linear programming technique for determining the efficiency frontier (the envelope) to the inputs and outputs of a collection of individual corporations or other productive units. While DEA offers an avenue for calculating the returns to scale of individual corporations, the approach has been riddled by mathematical complications arising from the possibility of alternate optima. The present paper develops theory for calculating the entire range of these alternate optima. Furthermore, in a quite ambitions empirical application, DEA is employed to determine the time path of returns to scale of all publicly held U.S. computer companies over the time period 1980–1991. For the great majority of companies, a unique time path is obtained; only in less than 4 percent of the linear programming calculations is an entire range of alternate optima obtained. The results indicate that the computer industry was polarized into two camps: large aging corporations with decreasing returns to scale, and swarms of small upstart companies with advanced technology exhibiting increasing returns to scale.     

A panel data analysis of productive efficiency in freestanding health clinics

By using a panel data on a number of freestanding health clinics in New York State over 1984–1987, we have estimated the production function for ambulatory care after controlling for unmeasured clinic-specific managerial efficiency. We found significant differences in management efficiency, which peaks around 50500 visits per year. The optimal staffing ratio between doctors, extenders and nurses was found to be around 1∶1/3∶1, in order for a clinic to be on the efficiency frontier.