How to deal with S-shaped curve in DEA

経済学 / EconomicsIn DEA we are often puzzled by the big difference in CRS and VRS scores, and by the convex production possibility set syndrome in spite of the S-shaped curve often observed in many real data. In this paper we perform a challenge to these subjects.http://www.grips.ac.jp/list/facultyinfo/tone_kaoru

Methodological Advances in Dea

We survey the methodological advances in DEA over the last 25 years and discuss the necessary conditions for a sound empirical application. We hope this survey will contribute to the further dissemination of DEA, the knowledge of its relative strengths and weaknesses, and the tools currently available for exploiting its full potential. Our main points are illustrated by the case of the DEA study used by the regulatory office of the Dutch electricity sector (Dienst Toezicht Elektriciteitswet; Dte) for setting price caps

Nonparametric production technologies with weakly disposable inputs

In models of production theory and efficiency analysis, the inputs and outputs are assumed to satisfy some form of disposability. In this paper, we consider the assumption of weak input disposability. It states that any activity remains feasible if its inputs are simultaneously scaled up in the same proportion. As suggested in the literature, the Shephard technology incorporating weak input disposability could be used to evaluate the effect of input congestion. We show that the Shephard technology is not convex and therefore introduces bias in evaluation of congestion. To address this, we develop an alternative convex technology whose use in the evaluation of congestion removes the noted bias. We undertake a further axiomatic investigation and obtain a range of production technologies, all of which exhibit weak input disposability but are based on different, progressively relaxed, convexity assumptions. Apart from the evaluation of input congestion, such technologies should also be useful in applications in which some inputs are closely related or are overlapping, and therefore satisfy only the weak input disposability assumption incorporated in the new models

Stochastic non-smooth envelopment of data : semi-parametric frontier estimation subject to shape constraints

The field of productive efficiency analysis is currently divided between two main paradigms: the deterministic, nonparametric Data Envelopment Analysis (DEA) and the parametric Stochastic Frontier Analysis (SFA). This paper examines an encompassing semiparametric frontier model that combines the DEA-type nonparametric frontier, which satisfies monotonicity and concavity, with the SFA-style stochastic homoskedastic composite error term. To estimate this model, a new two-stage method is proposed, referred to as Stochastic Non-smooth Envelopment of Data (StoNED). The first stage of the StoNED method applies convex nonparametric least squares (CNLS) to estimate the shape of the frontier without any assumptions about its functional form or smoothness. In the second stage, the conditional expectations of inefficiency are estimated based on the CNLS residuals, using the method of moments or pseudolikelihood techniques. Although in a cross-sectional setting distinguishing inefficiency from noise in general requires distributional assumptions, we also show how these can be relaxed in our approach if panel data are available. Performance of the StoNED method is examined using Monte Carlo simulations.v2012o

Can Omitted Carbon Abatement Explain Productivity Stagnation? Quantile Shadow-Price Fisher Index Applied to OECD Countries

Explaining the secular stagnation of productivity growth is a widely recognized challenge to economists and policymakers. One potentially important explanation without much attention concerns the ongoing low-carbon transition. This paper explores whether considering greenhouse gas emissions can explain productivity stagnation in OECD countries. We propose a quantile shadow-price Fisher index to gauge green total factor productivity (TFP) based on the newly developed penalized convex quantile regression approach. The quantile shadow-price Fisher index requires neither the real price data nor an ad hoc choice of quantiles and allows the quantiles to move in the inter-period sample. An empirical application to 38 OECD countries during 1990--2019 demonstrates that the measured productivity growth is considerably higher when the GHG emissions are accounted for. For countries that have reduced GHG emissions most actively, the average green TFP growth rate could double the conventional TFP growth. The impacts of ignoring human capital and different representations of fixed capital on green TFP growth are also discussed explicitly

Using DEA to profile in-hospital surgeon services: A South African funder perspective

Includes bibliographical references.The comparative assessment of physician performance, also known as ‘physician profiling’ is frequently used by healthcare funders. It aims to identify and improve the resource efficiency and quality of physician care. South African private healthcare funders use a wide range of profiling techniques; however, currently the use of frontier analysis is absent. This study explores the use of the non - parametric frontier analysis technique called Data Envelopment Analysis (DEA) for the profiling of physicians in South Africa. This is investigated by following a DEA profiling approach to evaluate the performance of 403 general/ paediatric surgeons in providing in - hospital services in 2012. A 7 - input 1 - output VRS DEA model is used to determine the efficiency of the surgeons. The profiling results are then analysed to determine their usefulness. It results reveal that 58 surgeons are efficient, representing only 14.4% of surgeons profiled. Therefore, the DEA approach reveals a large potential for efficiency improvements. The average efficiency score of inefficient surgeons is found to be 0.68. This means that, on average, inefficient surgeons have to decrease resource utilisation by 32% to achieve efficiency. The DEA approach is also found to be proficient at identifying the physicians presenting the most severe levels of inefficiency. 37 surgeons are found to be significantly inefficient. The approach also allows for the identification of peers against which inefficient surgeons are able to directly compare their practices. These results are determined to be of significant potential use to South African private healthcare funders. It is, however, noted that the analysis and results obtained was solely of a statistical nature. Closer consideration of the clinical appropriateness of the results is essential. In any case, this study concludes that a DEA profiling approach can be considered a useful technique in the comparison of physician performance in South Africa

Análise envoltória de dados na avaliaçăo de empréstimos financeiros realizados pelo Banco Social /

Orientador: Volmir Eugęnio WilhelmDissertaçăo (mestrado) - Universidade Federal do Paraná, Setores de Tecnologia e Cięncias Exatas, Programa de Pós-Graduaçăo em Métodos Numéricos em Engenharia. Defesa: Curitiba, 2005Inclui bibliografia e anexosÁrea de concentraçăo: Programaçăo matemátic

Performance Evaluation of Wind Power Systems Based on Production Economics Theory

The research in this dissertation addresses the issues in the performance evaluation of wind power systems under commercially operating circumstances. Such an evaluation is critical to a wide range of decisions including operations and maintenance planning, reliability assessment, asset procurement, and system designs. However, accurate evaluation is excessively challenging due to the unknown causal relationship between wind input and power output, the dependency of power output on numerous uncontrollable factors, and the high level of uncertainty observed in power output. While addressing these challenges, we develop a new performance measure based on production economics theories and propose effective methodologies for evaluating the performance of wind power systems. By doing so, this dissertation study aims to improve the practice of performance evaluation in the wind industry. We define an efficiency metric analogous to productive efficiency, which requires estimating a performance benchmark, i.e., the performance referring to 100% efficiency. For the performance benchmark, we develop a stochastic nonparametric estimator maintaining S-shape, the typical shape observed in the wind input-power output relationship. When applying the efficiency metric for comparing performance under different scenarios, other environmental factors need to be controlled for, as their difference could produce a difference in power output. We devise a covariate density matching method that selects subsets of data for which probability densities of the environmental factors are comparable; evaluating only these subsets, then, ensures a fair comparison. We further investigate wake situations in which the operation of a turbine could cause a significant power deficit on its neighboring turbines. In the presence of the performance benchmark introduced earlier, ii we can model the power deficit as a non-negative term subtracted from the benchmark. Based on this model setup, we develop a spline model with a non-negativity constraint imposed for characterizing such a wake effect. When each of the proposed methods is applied to operational wind data, the respective results demonstrate that each of the methods outperforms its competitive alternatives in terms of estimation and/or prediction accuracy. This suggests that the methods can reduce the unaccounted uncertainty in power output and thus provide better insight into the performance of wind power systems