Health systems efficiency after the crisis in the OECD

This work evaluates the efficiency position of the health system of each OECD country. It identifies whether, or not, health systems changed in terms of quality and performance after the financial crisis. The health systems performance was calculated by fixed-effects estimator and by stochastic frontier analysis. The results suggest that many of those countries that the crisis affected the most are more efficient than the OECD average. In addition, some of those countries even managed to reach the top decile in the efficiency ranking. Finally, we analyze the stochastic frontier efficiency scores together with other health indicators to evaluate the health systems’ overall adjustments derived from the crisis.

Cobrança pelo uso da água e o setor de saneamento no Estado de São Paulo

A partir dos objetivos propostos pelas políticas nacionais de saúde, ambientais e de saneamento básico buscou-se analisar os efeitos da cobrança pelo uso da água no setor de saneamento básico, visando identificar possíveis variações causadas por este instrumento econômico no acesso à água, na qualidade do produto ofertado e na qualidade do serviço prestado. Ainda, por se tratar de um serviço público, analisamos a performance técnica das empresas paulistas do setor de saneamento básico na prestação deste serviço por meio da metodologia Data Envelopment Analysis. Esta ferramenta resulta em um indicador de desempenho, com base na melhor relação input/output, ao estabelecer um ranking de eficiência médio a partir das práticas mais eficientes de cada unidade produtiva.

Ranking efficiency units in DEA using bootstrapping an applied analysis for Slovenian farm data

This article explores how data envelopment analysis (DEA), along with a smoothed bootstrap method, can be used in applied analysis to obtain more reliable efficiency rankings for farms. The main focus is the smoothed homogeneous bootstrap procedure introduced by Simar and Wilson (1998) to implement statistical inference for the original efficiency point estimates. Two main model specifications, constant and variable returns to scale, are investigated along with various choices regarding data aggregation. The coefficient of separation (CoS), a statistic that indicates the degree of statistical differentiation within the sample, is used to demonstrate the findings. The CoS suggests a substantive dependency of the results on the methodology and assumptions employed. Accordingly, some observations are made on how to conduct DEA in order to get more reliable efficiency rankings, depending on the purpose for which they are to be used. In addition, attention is drawn to the ability of the SLICE MODEL, implemented in GAMS, to enable researchers to overcome the computational burdens of conducting DEA (with bootstrapping).

Application of multi-criteria decision making methods to compression ignition engine efficiency and gaseous, particulate and greenhouse gas emissions

Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.

Trainee-therapists are not all equal: Examination of therapeutic efficiency, effectiveness and early client dropout after 12 months of clinical training

Objective Contemporary research demonstrates the feasibility of assessing therapeutic performance of trainee-therapists through the use of objective measures of client treatment outcome. Further, significant variation between individual therapists based on their client treatment outcomes has been demonstrated. This study sets out to determine whether a reliable composite measure of therapeutic efficiency, effectiveness and early dropout can be developed and used to objectively compare trainee-therapists against each other. Design and methods Treatment outcomes of 611 clients receiving treatment from 58 trainee-therapists enrolled in a professional training programme were tracked with the OQ-45.2 over a 6-year period to assess therapeutic efficiency, therapeutic effectiveness and early client dropout. Results Significant variation between trainee-therapists was observed for each index. Findings of a moderately strong correlation between therapeutic efficiency and effectiveness enabled the ranking of trainee-therapists based upon a composite measure of these indexes. A non-significant correlation was found between early client dropout and measures of therapeutic effectiveness and efficiency. Conclusions The findings stress the importance of utilizing objective measures to track the treatment outcomes. Despite all trainee-therapists being enrolled in the same training programme, significant variation between trainee-therapists' therapeutic efficiency and effectiveness was found to exist. Practitioner points Developing of potential benchmarking tools that enable trainee-therapists, supervisors and educational institutions to quickly assess therapeutic performance can become part of a holistic assessment of a trainee-therapist's clinical development. Despite an inherent optimistic belief that therapists do not cause harm, there appears to be a small and significant proportion of trainee-therapists who consistently evidence little therapeutic change. Considerable variability in trainee-therapists' therapeutic efficiency and effectiveness can exist in the one training programme. Early client dropout may not be associated with therapists' therapeutic effectiveness and efficiency.

‘How to’ guide for measuring fan performance and efficiency in meat chicken sheds

This ‘how to’ guide provides readers with method to measure fan performance and energy efficiency of fans installed in meat chicken sheds. These methods are also useful for identifying fans that are under-performing or require maintenance. For more information about fan energy efficiency, a complementary report is available on the RIRDC website ‘Review of fan efficiency in meat chicken sheds’ (RIRDC Publication No. 15/018). A spreadsheet was also developed under this project for comparing and ranking fans against others in terms of energy efficiency, air flow and costs (‘Tunnel Ventilation Fan Comparison Spreadsheet’), and is available on the RIRDC website.

Carbon sequestration versus bioenergy: A case study from South India exploring the relative land-use efficiency of two options for climate change mitigation

This case study has been carried out as a comparison between two different land-use strategies for climate change mitigation, with possible application within the Clean Development Mechanisms. The benefits of afforestation for carbon sequestration versus for bioenergy production are compared in the context of development planning to meet increasing domestic and agricultural demand for electricity in Hosahalli village, Karnataka, India. One option is to increase the local biomass based electricity generation, requiring an increased biomass plantation area. This option is compared with fossil based electricity generation where the area is instead used for producing wood for non-energy purposes while also sequestering carbon in the soil and standing biomass. The different options have been assessed using the PRO-COMAP model. The ranking of the different options varies depending on the system boundaries and time period. Results indicate that, in the short term (30 years) perspective, the mitigation potential of the long rotation plantation is largest, followed by the short rotation plantation delivering wood for energy. The bioenergy option is however preferred if a long-term view is taken. Short rotation forests delivering wood for short-lived non-energy products have the smallest mitigation potential, unless a large share of the wood products are used for energy purposes (replacing fossil fuels) after having served their initial purpose. If managed in a sustainable manner all of these strategies can contribute to the improvement of the social and environmental situation of the local community. (C) 2009 Elsevier Ltd. All rights reserved.

Efficiency assessment of electricity power generation on Ireland’s Single Electricity Market by Data Envelopment Analysis

The efficiency of generation plants is an important measure for evaluating the operating performance. The objective of this paper is to evaluate electricity power generation by conducting an All-Island-Generator-Efficiency-Study (AIGES) for the Republic of Ireland and Northern Ireland by utilising a Data Envelopment Analysis (DEA) approach. An operational performance efficiency index is defined and pursued for the year 2008. The economic activities of electricity generation units/plants examined in this paper are characterized by numerous input and output indicators. Constant returns to scale (CRS) and variable returns to scale (VRS) type DEA models are employed in the analysis. Also a slacks based analysis indicates the level of inefficiency for each variable examined. The findings from this study provide a general ranking and evaluation but also facilitate various interesting efficiency comparisons between generators by fuel type.

Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

We present a mathematically rigorous Quality-of-Service (QoS) metric which relates the achievable quality of service metric (QoS) for a real-time analytics service to the server energy cost of offering the service. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

Bayesian ranking and selection of fishing boat efficiencies

The steadily accumulating literature on technical efficiency in fisheries attests to the importance of efficiency as an indicator of fleet condition and as an object of management concern. In this paper, we extend previous work by presenting a Bayesian hierarchical approach that yields both efficiency estimates and, as a byproduct of the estimation algorithm, probabilistic rankings of the relative technical efficiencies of fishing boats. The estimation algorithm is based on recent advances in Markov Chain Monte Carlo (MCMC) methods—Gibbs sampling, in particular—which have not been widely used in fisheries economics. We apply the method to a sample of 10,865 boat trips in the US Pacific hake (or whiting) fishery during 1987–2003. We uncover systematic differences between efficiency rankings based on sample mean efficiency estimates and those that exploit the full posterior distributions of boat efficiencies to estimate the probability that a given boat has the highest true mean efficiency.

Bayesian ranking and slection of fishing boat efficiencies

The steadily accumulating literature on technical efficiency in fisheries attests to the importance of efficiency as an indicator of fleet condition and as an object of management concern. In this paper, we extend previous work by presenting a Bayesian hierarchical approach that yields both efficiency estimates and, as a byproduct of the estimation algorithm, probabilistic rankings of the relative technical efficiencies of fishing boats. The estimation algorithm is based on recent advances in Markov Chain Monte Carlo (MCMC) methods— Gibbs sampling, in particular—which have not been widely used in fisheries economics. We apply the method to a sample of 10,865 boat trips in the US Pacific hake (or whiting) fishery during 1987–2003. We uncover systematic differences between efficiency rankings based on sample mean efficiency estimates and those that exploit the full posterior distributions of boat efficiencies to estimate the probability that a given boat has the highest true mean efficiency.

The effects of anxiety on visual search, movement kinematics, and performance in table tennis: A test of Eysenck and Calvo's processing efficiency theory

Processing efficiency theory predicts that anxiety reduces the processing capacity of working memory and has detrimental effects on performance. When tasks place little demand on working memory, the negative effects of anxiety can be avoided by increasing effort. Although performance efficiency decreases, there is no change in performance effectiveness. When tasks impose a heavy demand on working memory, however, anxiety leads to decrements in efficiency and effectiveness. These presumptions were tested using a modified table tennis task that placed low (LWM) and high (HWM) demands on working memory. Cognitive anxiety was manipulated through a competitive ranking structure and prize money. Participants' accuracy in hitting concentric circle targets in predetermined sequences was taken as a measure of performance effectiveness, while probe reaction time (PRT), perceived mental effort (RSME), visual search data, and arm kinematics were recorded as measures of efficiency. Anxiety had a negative effect on performance effectiveness in both LWM and HWM tasks. There was an increase in frequency of gaze and in PRT and RSME values in both tasks under high vs. low anxiety conditions, implying decrements in performance efficiency. However, participants spent more time tracking the ball in the HWM task and employed a shorter tau margin when anxious. Although anxiety impaired performance effectiveness and efficiency, decrements in efficiency were more pronounced in the HWM task than in the LWM task, providing support for processing efficiency theory.

A scalable re-ranking method for content-based image retrieval

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The Directional Distance Function and Measurement of Super-Efficiency: An Application to Airlines Data

Lovell and Rouse (LR) have recently proposed a modification of the standard DEA model that overcomes the infeasibility problem often encountered in computing super-efficiency. In the LR procedure one appropriately scales up the observed input vector (scale down the output vector) of the relevant super-efficient firm thereby usually creating its inefficient surrogate. An alternative procedure proposed in this paper uses the directional distance function introduced by Chambers, Chung, and Färe and the resulting Nerlove-Luenberger (NL) measure of super-efficiency. The fact that the directional distance function combines features of both an input-oriented and an output-oriented model, generally leads to a more complete ranking of the observations than either of the oriented models. An added advantage of this approach is that the NL super-efficiency measure is unique and does not depend on any arbitrary choice of a scaling parameter. A data set on international airlines from Coelli, Perelman, and Griffel-Tatje (2002) is utilized in an illustrative empirical application.

Dominance intensity methods for ranking of alternatives in mcdm with imprecise information

Los decisores cada vez se enfrentan a problemas más complejos en los que tomar una decisión implica tener que considerar simultáneamente muchos criterios que normalmente son conflictivos entre sí. En la mayoría de los problemas de decisión es necesario considerar criterios económicos, sociales y medioambientales. La Teoría de la Decisión proporciona el marco adecuado para poder ayudar a los decisores a resolver estos problemas de decisión complejos, al permitir considerar conjuntamente la incertidumbre existente sobre las consecuencias de cada alternativa en los diferentes atributos y la imprecisión sobre las preferencias de los decisores. En esta tesis doctoral nos centramos en la imprecisión de las preferencias de los decisores cuando éstas pueden ser representadas mediante una función de utilidad multiatributo aditiva. Por lo tanto, consideramos imprecisión tanto en los pesos como en las funciones de utilidad componentes de cada atributo. Se ha considerado el caso en que la imprecisión puede ser representada por intervalos de valores o bien mediante información ordinal, en lugar de proporcionar valores concretos. En este sentido, hemos propuesto métodos que permiten ordenar las diferentes alternativas basados en los conceptos de intensidad de dominación o intensidad de preferencia, los cuales intentan medir la fuerza con la que cada alternativa es preferida al resto. Para todos los métodos propuestos se ha analizado su comportamiento y se ha comparado con los más relevantes existentes en la literatura científica que pueden ser aplicados para resolver este tipo de problemas. Para ello, se ha realizado un estudio de simulación en el que se han usado dos medidas de eficiencia (hit ratio y coeficiente de correlación de Kendall) para comparar los diferentes métodos. ABSTRACT Decision makers increasingly face complex decision-making problems where they have to simultaneously consider many often conflicting criteria. In most decision-making problems it is necessary to consider economic, social and environmental criteria. Decision making theory provides an adequate framework for helping decision makers to make complex decisions where they can jointly consider the uncertainty about the performance of each alternative for each attribute, and the imprecision of the decision maker's preferences. In this PhD thesis we focus on the imprecision of the decision maker's preferences represented by an additive multiattribute utility function. Therefore, we consider the imprecision of weights, as well as of component utility functions for each attribute. We consider the case in which the imprecision is represented by ranges of values or by ordinal information rather than precise values. In this respect, we propose methods for ranking alternatives based on notions of dominance intensity, also known as preference intensity, which attempt to measure how much more preferred each alternative is to the others. The performance of the propose methods has been analyzed and compared against the leading existing methods that are applicable to this type of problem. For this purpose, we conducted a simulation study using two efficiency measures (hit ratio and Kendall correlation coefficient) to compare the different methods.