Cross redundancy and sensitivity in DEA models

Data envelopment analysis (DEA) measures the efficiency of each decision making unit (DMU) by maximizing the ratio of virtual output to virtual input with the constraint that the ratio does not exceed one for each DMU. In the case that one output variable has a linear dependence (conic dependence, to be precise) with the other output variables, it can be hypothesized that the addition or deletion of such an output variable would not change the efficiency estimates. This is also the case for input variables. However, in the case that a certain set of input and output variables is linearly dependent, the effect of such a dependency on DEA is not clear. In this paper, we call such a dependency a cross redundancy and examine the effect of a cross redundancy on DEA. We prove that the addition or deletion of a cross-redundant variable does not affect the efficiency estimates yielded by the CCR or BCC models. Furthermore, we present a sensitivity analysis to examine the effect of an imperfect cross redundancy on DEA by using accounting data obtained from United States exchange-listed companies.     

Efficiency and Technical Change in Intertemporal Intersectoral DEA

A new procedure for the measurement of efficiency and technical change is presented, using DEA with three-dimension data (box data), pooling over sectors, regions and time. Until now, when pooling the data in panel applications it has been assumed that technology remained unchanged, so productivity change was entirely attributed to technical efficiency change. However, patterns of technology change and the decomposition into efficiency and technical change elements can be accomplished by means of restrictions on the general structure of the technology indexes. Under the assumption of non-regressive technical change, upper and lower bounds for efficiency and technical change are obtained. The new methodology is illustrated in an analysis of productivity growth in 13 manufacturing sectors in the Spanish regions from 1980 to 1992.     

Optimal solutions of multiplier DEA models

Journal of Productivity Analysis - Conventional models of data envelopment analysis (DEA) are based on the constant and variable returns-to-scale production technologies. Any optimal input and...     

银行效率DEA分析的可信度检验

近年来涌现出大量基于DEA方法的银行效率这一热点问题的研究成果,但是由于DEA方法自身的局限性,诸如对效率值的估计偏低且离散程度较大,以及不能方便地检验结果的显著性等等问题,使其研究的结果受到影响;而Bootstrap技术是基于对经验数据及其相关估计的重复抽样来提高估计置信区间和临界值精度的统计技术,可有效地克服DEA方法结果可信度的这种内在依赖性。本文给出了基于Boot-strap技术的DEA方法来计量银行效率的手段,提高了效率分析结果的可信度,并对我国四大国有商业银行的效率进行了对比性实证分析。     

基于DEA的安徽省广告效率评价

在广告界一直流传着这样一句名言:"我知道在广告上的投资有一半是无用的,但我不知道是哪一半."广告作为一种重要的营销手段,其效率评价一直是营销界关注的热点.本文在了解安徽省广告业发展现状及广告效率相关研究后,用DEA方法分析安徽省2000-2017年广告效率.结果表明:安徽省广告业发展水平整体效率不高;一半的年份广告业纯技术效率为1,能充分利用现有资源实现最优资源配置和输出的最大化;有6年规模效率有效,投入规模达到最优.本文研究结果可以为提高广告活动效率、改进广告决策提供建议.     

基于DEA评价城市管理市场有效性模型

采用DEA方法建立了评价城市管理市场有效性的模型,对中国主要城市的劳动力市场、房地产市场、公共物品市场进行了评价.从一个新的角度为评价城市管理现代化提供了辅助手段.     

基于DEA模型的河南省物流产业效率评价

以物流业投资的固定资产、物流业从业人数作为投入指标,以物流业的增加值、货物周转量作为产出指标,构建了河南省物流产业效率评价指标体系,运用DEA效率评价模型对河南2004-2012年物流系统的相对有效性、技术有效性、规模效益有效性和超效率进行分析,结果显示,河南物流投入、产出总体有效性为44%,在此结果基础上分析了物流产业效率制约因素,并提出了物流产业效率提升要点及提升策略。     

On the calculation of the scale elasticity in DEA models

An issue in the multiple-output case within the literature on piecewise linear frontier production functions has been how to determine the nature of the scale properties. It is shown that knowledge of scale efficiency does not permit calculation of scale elasticity or vice versa. For inefficient units there is a relationship between input-saving and output-increasing efficiency measures through the average value of the scale elasticity between the two different reference points on the frontier. A direct approach to determine the scale properties is to calculate the scale elasticity from the dual problem to the calculation of Farrell efficiency measures.     

基于DEA的安徽省物流效率研究

随着我国经济的不断发展,物流行业作为重要的服务业,发展势头十分迅猛。文章运用DEA模型中的两个经典模型:CCR(判断决策单元是否同时为技术有效和规模有效)模型和BCC(判断决策单元是否为技术有效)模型,根据中华人民共和国国家统计局网站和《安徽省统计年鉴》数据,对安徽省2003~2012年的物流投入、产出情况进行实证分析,测算安徽省的物流效率,并对安徽省的物流行业持续健康发展提出建议。     

基于DEA模型的安徽省城市效率分析

基于安徽省16个地级市2015-2017年的城市经济面板数据,运用DEA模型进行城市效率的静态分析.结果表明:安徽省各城市的效率普遍偏高,然而大部分地级市的资源配置水平仍处于低效状态.因此,在促进城市发展的进程中,安徽省需着重提高生产要素配置的合理性,以进一步提升城市效率.本文的研究为安徽省的相关政策调整与制定提供了一定的依据.     

New Approaches to Measures of Efficiency in DEA: An Introduction

Journal of Productivity Analysis -     

基于DEA模型的安徽省城市效率分析

基于安徽省16个地级市2015-2017年的城市经济面板数据,运用DEA模型进行城市效率的静态分析.结果表明:安徽省各城市的效率普遍偏高,然而大部分地级市的资源配置水平仍处于低效状态.因此,在促进城市发展的进程中,安徽省需着重提高生产要素配置的合理性,以进一步提升城市效率.本文的研究为安徽省的相关政策调整与制定提供了一定的依据.     

Stochastic leader–follower DEA models for two-stage systems

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). In recent years, it has been widely used to evaluate two-stage systems under different organization mechanisms. This study modifies the conventional leader–follower DEA models for two-stage systems by considering the uncertainty of data. The dual deterministic linear models are first constructed from the stochastic CCR models under the assumption that all components of inputs, outputs, and intermediate products are related only with some basic stochastic factors, which follow continuous and symmetric distributions with nonnegative compact supports. The stochastic leader–follower DEA models are then developed for measuring the efficiencies of the two stages. The stochastic efficiency of the whole system can be uniquely decomposed into the product of the efficiencies of the two stages. Relationships between stochastic efficiencies from stochastic CCR and stochastic leader–follower DEA models are also discussed. An example of the commercial banks in China is considered using the proposed models under different risk levels.     

基于两阶段DEA的跨境电商物流系统效率

从系统的角度分析跨境电子商务物流系统的构成和影响其效率的主要因素,构建跨境电子商务物流系统的两阶段DEA模型,将其分为境内物流和境外物流两个阶段,对其指标进行前沿面分析,通过对相应指标进行调整,使其整体达到有效,并且提出了提升跨境电子商务物流系统效率的策略。     

基于DEA数据包络分析的建筑业企业效率评价

追求高效率是经济活动的重要因素,作为大投入大产出的建筑业生产更应该如此,但如今我国建筑业企业更多的是专注于提高业绩却很少注意到生产资料是否被合理利用。文章将DEA数据包络分析方法及其模型应用到建筑业企业的效率评价中来,为建筑业企业的效率评价提供新的思路。     

Developing foreign bank efficiency models for DEA grounded in finance theory

We develop foreign bank technical, cost and profit efficiency models for particular application with data envelopment analysis (DEA). Key motivations for the paper are (a) the often-observed practice of choosing inputs and outputs where the selection process is poorly explained and linkages to theory are unclear, and (b) foreign bank productivity analysis, which has been neglected in DEA banking literature. The main aim is to demonstrate a process grounded in finance and banking theories for developing bank efficiency models, which can bring comparability and direction to empirical productivity studies. We expect this paper to foster empirical bank productivity studies.     

Some characterizations of distributions by regression models for ordinal response data

Summary Let a random variableX be classified intok classes. By doing so, a new random variable is obtained, measured on ordinal scale. If this variable is a response variable in certain regression models for ordinal response data, the distribution ofX is characterized by the models. In this paper, characterizations of the distribution ofX by the proportional odds model and the proportional hazards model are given.     

基于DEA模型的城市科技活动效率评价

将DEA理论应用于广东21城市科技活动的分析中，建立评价城市科技活动效率的数据包络分析模型，谊模型评价了各城市的总体效率和技术效率的状况，进而对非DEA有效的城市提出达到DEA有效的可行措施，并分析了城市科技活动效率和资源配置之间的关系。