Patterns of corporate governance and technical efficiency in Italian manufacturing

The purpose of this paper is to analyse the relationship between the corporate governance system and technical efficiency in Italian manufacturing. We use a non-parametric frontier technique (DEA) to derive technical efficiency measures for a sample of Italian firms taken from nine manufacturing industries. These measures are then related to the characteristics of the corporate governance system. Two of these characteristics turn out to have a positive impact on technical efficiency: the percentage of the company shares owned by the largest shareholder and the fact that a firm belongs to a pyramidal group. Interestingly, a trade-off emerges between these influences, in the sense that one is stronger in industries where the other is weaker. Copyright © 2007 John Wiley & Sons, Ltd.

A cautionary note on methods of comparing programmatic efficiency between two or more groups of DMUs in data envelopment analysis

In some applications of data envelopment analysis (DEA) there may be doubt as to whether all the DMUs form a single group with a common efficiency distribution. The Mann-Whitney rank statistic has been used to evaluate if two groups of DMUs come from a common efficiency distribution under the assumption of them sharing a common frontier and to test if the two groups have a common frontier. These procedures have subsequently been extended using the Kruskal-Wallis rank statistic to consider more than two groups. This technical note identifies problems with the second of these applications of both the Mann-Whitney and Kruskal-Wallis rank statistics. It also considers possible alternative methods of testing if groups have a common frontier, and the difficulties of disaggregating managerial and programmatic efficiency within a non-parametric framework. © 2007 Springer Science+Business Media, LLC.

Programmatic efficiency comparisons between unequally sized groups of DMUs in DEA

Data envelopment analysis (DEA) is a popular non-parametric technique for determining the efficiency of a homogeneous set of decision-making units (DMUs). In many practical cases, there is some doubt if the all the DMUs form a single group with a common efficiency distribution. The Mann-Whitney rank statistic has been used in DEA both to test if two groups of DMUs come from a common efficiency distribution and also to test if the two groups have a common frontier, each of which are likely to have important but different policy implications for the management of the groups. In this paper it is demonstrated that where the Mann-Whitney rank statistic is used for the second of these it is likely to overestimate programmatic inefficiency, particularly of the smaller group. A new non-parametric statistic is proposed for the case of comparing the efficient frontiers of two groups, which overcomes the problems we identify in the use of the Mann-Whitney rank statistic for this purpose. © 2005 Operational Research Society Ltd. All rights reserved.

Measurement of productivity index with dynamic DEA

Fare, Grosskopf, Norris and Zhang developed a non-parametric productivity index, Malmquist index, using data envelopment analysis (DEA). The Malmquist index is a measure of productivity progress (regress) and it can be decomposed to different components such as 'efficiency catch-up' and 'technology change'. However, Malmquist index and its components are based on two period of time which can capture only a part of the impact of investment in long-lived assets. The effects of lags in the investment process on the capital stock have been ignored in the current model of Malmquist index. This paper extends the recent dynamic DEA model introduced by Emrouznejad and Thanassoulis and Emrouznejad for dynamic Malmquist index. This paper shows that the dynamic productivity results for Organisation for Economic Cooperation and Development countries should reflect reality better than those based on conventional model.

Profitability of a sample of Portuguese bank branches and its decomposition into technical and allocative components

The efficiency literature, both using parametric and non-parametric methods, has been focusing mainly on cost efficiency analysis rather than on profit efficiency. In for-profit organisations, however, the measurement of profit efficiency and its decomposition into technical and allocative efficiency is particularly relevant. In this paper a newly developed method is used to measure profit efficiency and to identify the sources of any shortfall in profitability (technical and/or allocative inefficiency). The method is applied to a set of Portuguese bank branches first assuming long run and then a short run profit maximisation objective. In the long run most of the scope for profit improvement of bank branches is by becoming more allocatively efficient. In the short run most of profit gain can be realised through higher technical efficiency. © 2003 Elsevier B.V. All rights reserved.

Exchanging uncertainty: interoperable geostatistics?

Traditionally, geostatistical algorithms are contained within specialist GIS and spatial statistics software. Such packages are often expensive, with relatively complex user interfaces and steep learning curves, and cannot be easily integrated into more complex process chains. In contrast, Service Oriented Architectures (SOAs) promote interoperability and loose coupling within distributed systems, typically using XML (eXtensible Markup Language) and Web services. Web services provide a mechanism for a user to discover and consume a particular process, often as part of a larger process chain, with minimal knowledge of how it works. Wrapping current geostatistical algorithms with a Web service layer would thus increase their accessibility, but raises several complex issues. This paper discusses a solution to providing interoperable, automatic geostatistical processing through the use of Web services, developed in the INTAMAP project (INTeroperability and Automated MAPping). The project builds upon Open Geospatial Consortium standards for describing observations, typically used within sensor webs, and employs Geography Markup Language (GML) to describe the spatial aspect of the problem domain. Thus the interpolation service is extremely flexible, being able to support a range of observation types, and can cope with issues such as change of support and differing error characteristics of sensors (by utilising descriptions of the observation process provided by SensorML). XML is accepted as the de facto standard for describing Web services, due to its expressive capabilities which allow automatic discovery and consumption by ‘naive’ users. Any XML schema employed must therefore be capable of describing every aspect of a service and its processes. However, no schema currently exists that can define the complex uncertainties and modelling choices that are often present within geostatistical analysis. We show a solution to this problem, developing a family of XML schemata to enable the description of a full range of uncertainty types. These types will range from simple statistics, such as the kriging mean and variances, through to a range of probability distributions and non-parametric models, such as realisations from a conditional simulation. By employing these schemata within a Web Processing Service (WPS) we show a prototype moving towards a truly interoperable geostatistical software architecture.

A cost Malmquist productivity index

This paper develops a productivity index applicable when producers are cost minimisers and input prices are known. The index is inspired by the Malmquist index as extended to productivity measurement. The index developed here is defined in terms of input cost rather than input quantity distance functions. Hence, productivity change is decomposed into overall efficiency and cost technical change. Furthermore, overall efficiency change is decomposed into technical and allocative efficiency change and cost technical change into a part capturing shifts of input quantities and shifts of relative input prices. These decompositions provide a clearer picture of the root sources of productivity change. They are illustrated here in a sample of hospitals; results are computed using non-parametric mathematical programming. © 2003 Elsevier B.V. All rights reserved.

Statnote 14: the correlation of two variables (Pearson's 'r')

Pearson's correlation coefficient (‘r’) is one of the most widely used of all statistics. Nevertheless, care needs to be used in interpreting the results because with large numbers of observations, quite small values of ‘r’ become significant and the X variable may only account for a small proportion of the variance in Y. Hence, ‘r squared’ should always be calculated and included in a discussion of the significance of ‘r’. The use of ‘r’ also assumes that the data follow a bivariate normal distribution (see Statnote 17) and this assumption should be examined prior to the study. If the data do not conform to such a distribution, the use of a non-parametric correlation coefficient should be considered. A significant correlation should not be interpreted as indicating ‘causation’ especially in observational studies, in which the two variables may be correlated because of their mutual correlations with other confounding variables.

Statistical analysis in microbiology:statnotes

This book is aimed primarily at microbiologists who are undertaking research and who require a basic knowledge of statistics to analyse their experimental data. Computer software employing a wide range of data analysis methods is widely available to experimental scientists. The availability of this software, however, makes it essential that investigators understand the basic principles of statistics. Statistical analysis of data can be complex with many different methods of approach, each of which applies in a particular experimental circumstance. Hence, it is possible to apply an incorrect statistical method to data and to draw the wrong conclusions from an experiment. The purpose of this book, which has its origin in a series of articles published in the Society for Applied Microbiology journal ‘The Microbiologist’, is an attempt to present the basic logic of statistics as clearly as possible and therefore, to dispel some of the myths that often surround the subject. The 28 ‘Statnotes’ deal with various topics that are likely to be encountered, including the nature of variables, the comparison of means of two or more groups, non-parametric statistics, analysis of variance, correlating variables, and more complex methods such as multiple linear regression and principal components analysis. In each case, the relevant statistical method is illustrated with examples drawn from experiments in microbiological research. The text incorporates a glossary of the most commonly used statistical terms and there are two appendices designed to aid the investigator in the selection of the most appropriate test.

The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

Statistical guidelines for clinical studies of human vision

Citation information: Armstrong RA, Davies LN, Dunne MCM & Gilmartin B. Statistical guidelines for clinical studies of human vision. Ophthalmic Physiol Opt 2011, 31, 123-136. doi: 10.1111/j.1475-1313.2010.00815.x ABSTRACT: Statistical analysis of data can be complex and different statisticians may disagree as to the correct approach leading to conflict between authors, editors, and reviewers. The objective of this article is to provide some statistical advice for contributors to optometric and ophthalmic journals, to provide advice specifically relevant to clinical studies of human vision, and to recommend statistical analyses that could be used in a variety of circumstances. In submitting an article, in which quantitative data are reported, authors should describe clearly the statistical procedures that they have used and to justify each stage of the analysis. This is especially important if more complex or 'non-standard' analyses have been carried out. The article begins with some general comments relating to data analysis concerning sample size and 'power', hypothesis testing, parametric and non-parametric variables, 'bootstrap methods', one and two-tail testing, and the Bonferroni correction. More specific advice is then given with reference to particular statistical procedures that can be used on a variety of types of data. Where relevant, examples of correct statistical practice are given with reference to recently published articles in the optometric and ophthalmic literature.

Environmental quality in residential areas : a social survey approach to improvement priorities

The research is concerned with the measurement of residents' evaluations of the environmental quality of residential areas. The research reflects the increased attention being given to residents' values in planning decisions affecting the residential environment. The work was undertaken in co-operation with a local authority which was in the process of revising its housing strategy, and in particular the priorities for improvement action. The study critically examines the existing evidence on environmental values and their relationship to the environment and points to a number of methodological and conceptual deficiencies. The research strategy developed on the basis of the research review was constrained by the need to keep any survey methods simple so that they could easily be repeated, when necessary, by the sponsoring authority. A basic perception model was assumed, and a social survey carried out to measure residents' responses to different environmental conditions. The data was only assumed to have ordinal properties, necessitating the extensive use of non-parametric statistics. Residents' expressions of satisfaction with the component elements of the environment (ranging from convenience to upkeep and privacy) were successfully related to 'objective' measures of the environment. However the survey evidence did not justify the use of the 'objective' variables as environmental standards. A method of using the social survey data directly as an aid to decision-making is discussed. Alternative models of the derivation of overall satisfaction with the environment are tested, and the values implied by the additive model compared with residents' preferences as measured directly in the survey. Residents' overall satisfactions with the residential environment were most closely related to their satisfactions with the "Appearance" and the "Reputation" of their areas. By contrast the most important directly measured preference was "Friendliness of area". The differences point to the need to define concepts used in social research clearly in operational terms, and to take care in the use of values 'measured' by different methods.

Absorptive capacity and the benefits from global reservoirs of knowledge:evidence from a linked China-OECD dataset

This paper investigates the role of absorptive capacity in the diffusion of global technology with sector and firm heterogeneity. We construct the FDI-intensity weighted global R&D stock for each industry and link it to Chinese firm-level panel data relating to 53,981 firms over the period 2001-2005. Non-parametric frontier analysis is employed to explore how absorptive capacity affects technical change and catch-up in the presence of global knowledge spillovers. We find that R&D activities and training at individual firms serve as an effective source of absorptive capability. The contribution of absorptive capacity varies according to the type of FDI and the extent of openness.

Is a little sunshine all we need? On the impact of sunshine regulation on profits, productivity and prices in the Dutch drinking water sector

This paper analyzes the performance of Dutch drinking water utilities before and after the introduction of sunshine regulation, which involves publication of the performance of utilities but no formal price regulation. By decomposing profit change into its economic drivers, our results suggest that, in the Dutch political and institutional context, sunshine regulation was effective in improving the productivity of publicly organised services. Nevertheless, while sunshine regulation did bring about a moderate reduction in water prices, sustained and substantial economic profits suggest that it may not have the potential to fully align output prices with economic costs in the long run. In methodological terms, the DEA based profit decomposition is extended to robust and conditional non-parametric efficiency measures, so as to account better for both uncertainty and differences in operating environment between utilities.

Statnote 34 : the Kolmogorov-Smirnov (KS) test

The Kolmogorov-Smirnov (KS) test is a non-parametric test which can be used in two different circumstances. First, it can be used as an alternative to chi-square (?2) as a ‘goodness-of-fit’ test to compare whether a given ‘observed’ sample of observations conforms to an ‘expected’ distribution of results (KS, one-sample test). An example of the use of the one-sample test to determine whether a sample of observations was normally distributed was described previously. Second, it can be used as an alternative to the Mann-Whitney test to compare two independent samples of observations (KS, two-sample test). Hence, this statnote describes the use of the KS test with reference to two scenarios: (1) to compare the observed frequency (Fo) of soil samples containing cysts of the protozoan Naegleria collected each month for a year with an expected equal frequency (Fe) across months (one-sample test), and (2) to compare the abundance of bacteria on cloths and sponges sampled in a domestic kitchen environment (two-sample test).