The operating efficiency of financial holding and nonfinancial holding banks—Epsilou‐based measure metafrontier data envelopment analysis model

Previous bank efficiency studies assumed that the same efficient frontier system exists in different types of banks, but the conventional radial data envelopment analysis (DEA) model slacks are not counted in efficiency scores, and nonradial DEA models do not consider radial features. This paper develops an Epsilou‐based measure meta‐DEA approach for measuring the efficiencies and technology gaps of different bank types. The results are as the follows: The average efficiency and technology gaps of nonfinancial holding banks are better than those of financial holding banks. The nonfinancial holding banks are more efficient than financial holding banks in investment and other income.     

A Quasi-Malmquist Productivity Index

The Malmquist productivity index is based on distance functions, which are reciprocals of radial Debreu-Farrell efficiency measures, and which have a number of desirable properties. Linear programming techniques are frequently employed to calculate the efficiency measures. However these techniques can leave slacks, which constitute a non-radial form of inefficiency which is not incorporated into the analysis. Thus a radial efficiency measure overstates true efficiency, the reciprocal distance function understates the distance to the relevant efficient subset, and the Malmquist productivity index is adversely affected, although in an analytically indeterminate direction. This has led us to consider a new definition of one-sided efficiency, and to develop a new nonradial efficiency measure which incorporates all slacks on the selected side. Replacing conventional radial efficiency measures with our new non-radial efficiency measures generates what we call a quasi-Malmquist productivity index. We illustrate our quasi-Malmquist productivity index with an application to productivity change in Spanish banking.     

Alternative efficiency measures for multiple-output production

This paper has two main purposes. Firstly, we develop various ways of defining efficiency in the case of multiple-output production. Our framework extends a previous model by allowing for nonseparability of inputs and outputs. We also specifically consider the case where some of the outputs are undesirable, such as pollutants. We investigate how these efficiency definitions relate to one another and to other approaches proposed in the literature. Secondly, we examine the behavior of these definitions in two examples of practically relevant size and complexity. One of these involves banking and the other agricultural data. Our main findings can be summarized as follows. For a given efficiency definition, efficiency rankings are found to be informative, despite the considerable uncertainty in the inference on efficiencies. It is, however, important for the researcher to select an efficiency concept appropriate to the particular issue under study, since different efficiency definitions can lead to quite different conclusions.     

Finding Closest Targets in Non-Oriented DEA Models: The Case of Convex and Non-Convex Technologies

This paper draws attention for the fact that traditional Data Envelopment Analysis (DEA) models do not provide the closest possible targets (or peers) to inefficient units, and presents a procedure to obtain such targets.It focuses on non-oriented efficiency measures (which assume that production units are able to control, and thus change, inputs and outputs simultaneously) both measured in relation to a Free Disposal Hull (FDH) technology and in relation to a convex technology. The approaches developed for finding close targets are applied to a sample of Portuguese bank branches.     

The measurement of human capital: a multivariate macro-approach

We examine the human capital status of 123 countries by employing factor analysis on various national human capital indicators for the period 2000–2008 to construct two new measures. The first measure is based on advanced human capital, while the second is based on basic human capital. Our measures differ substantially from indicators used in previous studies on human capital and also lead to different rankings of countries. As rankings are not that informative without further information, we analyzed the distance between each country and the sample mean. Differences between countries are much more pronounced for our measure on advanced human capital than for our measure on basic human capital. Using cluster analysis, we classified the countries in four homogenous groups.     

Statistical Inference in Nonparametric Frontier Models: The State of the Art

Efficiency scores of firms are measured by their distance to an estimated production frontier. The economic literature proposes several nonparametric frontier estimators based on the idea of enveloping the data (FDH and DEA-type estimators). Many have claimed that FDH and DEA techniques are non-statistical, as opposed to econometric approaches where particular parametric expressions are posited to model the frontier. We can now define a statistical model allowing determination of the statistical properties of the nonparametric estimators in the multi-output and multi-input case. New results provide the asymptotic sampling distribution of the FDH estimator in a multivariate setting and of the DEA estimator in the bivariate case. Sampling distributions may also be approximated by bootstrap distributions in very general situations. Consequently, statistical inference based on DEA/FDH-type estimators is now possible. These techniques allow correction for the bias of the efficiency estimators and estimation of confidence intervals for the efficiency measures. This paper summarizes the results which are now available, and provides a brief guide to the existing literature. Emphasizing the role of hypotheses and inference, we show how the results can be used or adapted for practical purposes.     

Accounting for Environmental Influences in Stochastic Frontier Models: With Application to International Airlines

The principal aim of this paper is to measure the efficiency of international airlines. We obtain measures of technical efficiency from stochastic frontier production functions which have been adjusted to account for environmental influences such as network conditions, geographical factors, etc. We observe that two alternative approaches to this problem have been proposed in the efficiency measurement literature. One assumes that the environmental factors influence the shape of the technology while the other assumes that they directly influence the degree of technical inefficiency. In this paper we compare the results obtained when using these two approaches. The two sets of results provide similar rankings of airlines but suggest differing degrees of technical inefficiency. Both sets of results also suggest that Asian/Oceanic airlines are technically more efficient than European and North American airlines but that the differences are essentially due to more favourable environmental conditions. Nevertheless, it is among Asian companies that the major improvements in managerial efficiency (technical efficiency with environmental factors netted out) took place over the sample period (1977–1990).     

The economic performance of Swiss drinking water utilities

This paper measures the performance in terms of costs of Swiss drinking water utilities accounting for environmental factors. We estimate a translog stochastic variable cost frontier using two different techniques on an unbalanced panel of 141 water distribution utilities over the years 2002–2009, for a total of 745 observations. Results show that exogenous factors have an impact on variable cost. More precisely, we find that the share of pumped over total extracted water, population density, altitude and meteorological factors (maximum 30 days temperature and extreme precipitation events) have a significant impact on variable cost. Likelihood ratio tests emphasize the importance to include observed heterogeneity in the estimations. Efficiency rankings provided by models accounting for exogenous factors and their counterparts without them are however relatively similar. On the contrary, the efficiency ranks differ strongly between alternative estimation techniques. In assessing the economic performance of utilities, the most important choice thus seems to be about the way unobserved heterogeneity is treated.     

Assessing the influence of external factors on agricultural production in Brazil

This article uses 2017 Brazilian agricultural census data (aggregated at county level) to evaluate the impact of external factors on agricultural efficiency in Brazil. The external factors are defined as access to credit, participation in cooperatives, proportion of literacy, technical assistance, and environmental production practices. All variables are transformed as the log of the municipal (county) rank. The response variable is defined as the free disposal hull (FDH) conditional ratio and a one-inflated beta regression is estimated. The results show that in counties where the FDH ratio is equal to 1, cooperatives have the biggest impact on efficiency, and where the FDH ratio is not equal to 1, environmental practices, which are most often associated with technology, have the largest effect on efficiency. Finally, the regions that are expected to see the largest gains in efficiency with increases in external factors are the Northeastern and the Northern regions of Brazil.     

Poverty Orderings

This paper reviews the literature of partial poverty orderings. Partial poverty orderings require unanimous poverty rankings for a class of poverty measures or a set of poverty lines. The need to consider multiple poverty measures and multiple poverty lines arises inevitably from the arbitrariness inherent in poverty comparisons. In the paper, we first survey the ordering conditions of various individual poverty measures for a range of poverty lines; for some measures necessary and sufficient conditions are identified while for others only some easily verifiable sufficient conditions are established. These ordering conditions are shown to have a close link with the stochastic dominance relations which are based on the comparisons of cumulative distribution functions. We then survey the ordering conditions for various classes of poverty measures with a single or a set of poverty lines; in all cases necessary and sufficient conditions are established. These conditions again rely on the stochastic dominance relations or their transformations. We also extend the relationship between poverty orderings and stochastic dominance to higher orders and explore the possibility and the conditions of increasing the power of poverty orderings beyond the second degree dominance condition.     

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

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.JEL Classification:C61, D24, E23, L23, L25, L92     

A new criterion for technical efficiency measures: non‐monotonicity across dimensions axioms

Based on non‐parametric deterministic production technologies radial and non‐radial measures of technical efficiency are evaluated using properties guaranteeing insensitivity to the dimensionality of technology. These new axioms are important in empirical research and may especially prevent manipulation of results when implementing these benchmark methodologies in private or public organizations. An empirical example illustrates to which extent a series of radial and non‐radial technical efficiency measures satisfies the proposed axioms. Copyright © 1999 John Wiley & Sons, Ltd.     

The closest strong efficient targets in the FDH technology: an enumeration method

This paper is concerned with the identification of the closest strong efficient target of a Decision Making Unit (DMU) in the Free Disposal Hull (FDH) technology in Data Envelopment Analysis (DEA). The paper uses the geometrical properties of the FDH Production Possibility Set (PPS) to design and test an enumeration algorithm to obtain the minimum distance from a DMU to the strong efficient frontier of the PPS, corresponding to each of the various returns to scale assumptions. The proposed method solves some simple optimization problems whose optimal solutions are obtained by calculating a limited number of ratios. Then, an attempt will be made to mitigate the problem of the lack of unit and translation invariance of the selected distances by considering weighted norms. Finally, the applicability of the presented method is illustrated by a numerical example using real data.

     

Rankings Methodology for International Comparisons of Institutions and Individuals: an Application to Economics in Australia and New Zealand

Abstract.  The objectives of this paper are threefold. First, we critically survey and analyse the different methodologies that have been adopted in the rankings literature. Second, using journal articles included in the ECONLIT database and on the basis of two criteria – one based on citations and the other on perceptions of journal quality, we rank economics teaching departments in Australia and New Zealand for 1988–2002 and 1996–2002 and for individual academic economists for the periods 1988–2002, 1988–1995 and 1996–2002. Furthermore, we identify individual star performers and recognize them in a designated 'Hall of Fame' for 1988–2002. Third, our methodology enables us to make international comparisons on total and per capita bases. Previous multi-country ranking studies in economics do not rank economics departments. They provide rankings based on total publications in economics in universities regardless of whether the economists are in the economics departments or in other departments. Thus, no rankings on per capita bases are provided. We correct this shortcoming by providing total and per capita rankings and analysing the correlations between total and per capita rankings. This is the first study to examine whether the size of the economics department matters with regard to productivity.     

Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach

The explanation of productivity differentials is very important to identify the economic conditions that create inefficiency and to improve managerial performance. In the literature two main approaches have been developed: one-stage approaches and two-stage approaches. Daraio and Simar (2005, J Prod Anal 24(1):93–121) propose a fully nonparametric methodology based on conditional FDH and conditional order-m frontiers without any convexity assumption on the technology. However, convexity has always been assumed in mainstream production theory and general equilibrium. In addition, in many empirical applications, the convexity assumption can be reasonable and sometimes natural. Lead by these considerations, in this paper we propose a unifying approach to introduce external-environmental variables in nonparametric frontier models for convex and nonconvex technologies. Extending earlier contributions by Daraio and Simar (2005, J Prod Anal 24(1):93–121) as well as Cazals et al. (2002, J Econometrics 106:1–25), we introduce a conditional DEA estimator, i.e., an estimator of production frontier of DEA type conditioned to some external-environmental variables which are neither inputs nor outputs under the control of the producer. A robust version of this conditional estimator is proposed too. These various measures of efficiency provide also indicators of convexity which we illustrate using simulated and real data. Cinzia Daraio received Research support from the Italian Ministry of Education Research on Innovation Systems Project (iRis) “The reorganization of the public system of research for the technological transfer: governance, tools and interventions” and from the Italian Ministry of Educational Research Project (MIUR 40% 2004) “System spillovers on the competitiveness of Italian economy: quantitative analysis for sectoral policies” which are acknowledged. Léopold Simar received Research support from the “Interuniversity Attraction Pole”, Phase V (No. P5/24) from the Belgian Government (Belgian Science Policy) is acknowledged.     

On FDH efficiency analysis: Some methodological issues and applications to retail banking,courts, and urban transit

The methodology of free disposal hull (FDH) measure of productive efficiency is defined and put in perspectivevis-à-vis other nonparametric techniques, in terms of the postulates on which they respectively rest. Computational issues are also considered, in relation to the linear programming techniques used in DEA. The first application bears on a comparison between a private and a public bank, in terms of the relative efficiency of their branches. Important characteristics of the data are revealed by FDH that are not by DEA, due to a better data fit. Next, efficiency estimates of judicial activities are used to evaluate what part of the existing backlog could be reduced by efficiency increases. Finally, with monthly data of an urban transit firm over 12 years, the FDH methodology is extended to a sequential treatment of time series, that supplements efficiency estimation with a measure of technical progress.     

Multiple Comparisons with the Best: Bayesian Precision Measures of Efficiency Rankings

A large literature measures the allocative and technical efficiency of a set of firms using econometric techniques to estimate stochastic production frontiers or distance functions. Typically, researchers compute only the precision of individual efficiency rankings. Recently, Horrace and Schmidt (Journal of Applied Economics 15, 1–26, 2000) have applied sampling theoretic statistical techniques known as multiple comparisons with a control (MCC) and multiple comparisons with the best (MCB) to make statistical comparisons of efficiency rankings. As an alternative, this paper offers a Bayesian multiple comparison procedure that we argue is simpler to implement, gives the researcher increased flexibility over the type of comparison, and provides greater, and more intuitive, information content. For these methods and a parametric bootstrap technique, we carry out multiple comparisons of technical efficiency rankings for a set of U.S. electric generating firms, estimated using a distance function framework. We find that the Bayesian method provides substantially more precise inferences than obtained using the MCB and MCC methods.Jel Classification: C11, C32, D24.     

Salience in Quality Disclosure: Evidence from the U.S. News College Rankings

This paper investigates the impact of college rankings, and the visibility of those rankings, on students’ application decisions. Using natural experiments from U.S. News and World Report College Rankings, we present two main findings. First, we identify a causal impact of rankings on application decisions. When explicit rankings of colleges are published in U.S. News, a one‐rank improvement leads to a 1‐percentage‐point increase in the number of applications to that college. Second, we show that the response to the information represented in rankings depends on the way in which that information is presented. Rankings have no effect on application decisions when colleges are listed alphabetically, even when readers are provided data on college quality and the methodology used to calculate rankings. This finding provides evidence that the salience of information is a central determinant of a firm's demand function, even for purchases as large as college attendance.     

Stochastic FDH/DEA estimators for frontier analysis

In this paper we extend the work of Simar (J Product Ananl 28:183–201, 2007) introducing noise in nonparametric frontier models. We develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specifically, our approach first allows for statistical noise, similar to Stochastic frontier analysis (even in a more flexible way), and second, it allows modelling multiple-inputs-multiple-outputs technologies without imposing parametric assumptions on production relationship, similar to what is done in non-parametric methods, like Data Envelopment Analysis (DEA), Free Disposal Hull (FDH), etc.... The methodology is based on the theory of local maximum likelihood estimation and extends recent works of Kumbhakar et al. (J Econom 137(1):1–27, 2007) and Park et al. (J Econom 146:185–198, 2008). Our method is suitable for modelling and estimation of the marginal effects onto inefficiency level jointly with estimation of marginal effects of input. The approach is robust to heteroskedastic cases and to various (unknown) distributions of statistical noise and inefficiency, despite assuming simple anchorage models. The method also improves DEA/FDH estimators, by allowing them to be quite robust to statistical noise and especially to outliers, which were the main problems of the original DEA/FDH estimators. The procedure shows great performance for various simulated cases and is also illustrated for some real data sets. Even in the single-output case, our simulated examples show that our stochastic DEA/FDH improves the Kumbhakar et al. (J Econom 137(1):1–27, 2007) method, by making the resulting frontier smoother, monotonic and, if we wish, concave.     

A comparative analysis of measures of social homogeneity

Social homogeneity refers to the degree to which the preferences of individuals in a society tend to be alike. A number of studies have been conducted to determine whether or not a relationship exists between various measures of social homogeneity and the probability that a Condorcet winner exists. In this study, it is shown that a strong general relationship of this type does not exist for measures of social homogeneity which account only for the proportions of individuals with various preference rankings. That is, for measures which account for these proportions but not for the preference rankings to which they are assigned. Profile specific measures of homogeneity do account for the preference rankings to which the proportions of voters are assigned. A much stronger relationship exists between profile specific measures of homogeneity and the probability that a Condorcet winner exists than for non-profile specific measures. In particular, Kendall's Coefficient of Condordance is shown to dominate twenty other measures of social homogeneity in terms of the strength of its relationship to the probability that a Condorcet winner exists.