基于模糊神经网络我国仓储运输业上市公司企业规模实证研究

一个行业或企业的规模大小处于一种什么状态,是否合适,这是企业所关心的问题.在交易成本等规模经济理论及西方经济学生产函数理论的基础上,构建了企业规模函数指标,通过模糊神经网络对中国仓储运输业上市公司的企业规模的发展状态进行了实证研究.研究结果表明,我国仓储运输业上市公司的企业规模普遍偏小.     

基于DEA模型的中国家电上市公司效率实证分析

基于规模报酬可变的DEA模型和Malmquist指数方法,利用中国22家家电上市公司2006-2011年间的截面数据和面板数据,从静态视角和动态视角双维度考察了这一时期中国家电上市公司效率状况.研究发现,2006-2011年期间中国家电上市公司技术效率状况不佳,平均值为0.87,技术效率经历了下降后缓慢上升的趋势;中国家电上市公司动态效率较低,平均增长率为2.3%,且动态效率具有明显的波动性,缺乏持续的增长趋势,技术进步是中国家电上市公司动态效率增长主要动力,技术效率对其增长贡献较小.     

中国饲料业上市公司综合技术效率和全要素生产率分析

为了研究饲料业上市公司的综合技术效率和全要素生产率,运用数据包络分析法中的BCC模型和Malmquist指数法对12家饲料业上市公司2011-2016年的数据进行了测算,并从静态和动态两方面对其进行了分析.结果表明:只有5家上市公司实现了DEA有效,整体情况一般;从Malmquist指数法来看,在技术进步指标带领下,全要素生产率均值大于1,说明各公司经营管理效率不断上升.根据研究结论,并提出了饲料类上市公司在和种植业、养殖业协调发展的同时,应该提高农业创新力和公司经营管理效率,加快科技成果转化,领会新发展理念,加快新旧动能转换等建议.     

基于DEA模型的中国足球协会超级联赛俱乐部效率研究

基于2015-2017赛季中国足球协会超级联赛(以下简称"中超")俱乐部的面板数据,从"投入产出"角度建立俱乐部效率评价体系,运用数据包络分析(DEA)方法对中超俱乐部效率进行测度,并通过效率优化解决其投入冗余问题.研究表明:中超俱乐部2015-2017赛季整体效率均值各赛季都处于无效率水平,各赛季落入无效率区间的俱乐部数量均最多,而落入高效率区间的俱乐部数量则较少.高效率俱乐部当赛季的积分排名均不低于其投入排名.各赛季中超俱乐部均普遍处于规模收益递减状态,其中广州恒大、上海上港、上海申花和江苏苏宁俱乐部始终为规模收益递减.各赛季仅有少数俱乐部处于规模收益递增状态,其积分排名也均处于下游位置,其中辽宁开新俱乐部始终为规模收益递增.中超俱乐部不但普遍存在投入冗余情况,而且投入冗余度也较大,各赛季投入冗余度排名前三俱乐部的投入冗余度均超过50%.     

中国上市建筑企业规模经济和范围经济评价——一种随机边界成本函数方法

目前对于企业规模经济和范围经济的研究大多数是在不存在X无效的假设下进行的。即认为企业始终是在它们的有效边界内的,因此对企业规模经济和范围经济的实证研究也都是X有效的前提下的。本文试图采用一种成本非有效的随机边界成本函数,建立广义超越对数成本函数模型对企业规模经济和范围经济进行评价。数据来源于深沪两市建筑业板块25家上市公司2003-2007年的年度报告。研究结果表明:我国上市建筑企业中同时存在着规模不经济和范围不经济,而不存在X无效性假设条件下的估计结果使得规模经济值被提高。     

我国物流上市企业规模效率及影响因素研究

本文实证分析了1999-2009年间28家物流上市企业规模效率的动态变化和影响因素。结果表明:规模效率均值为0.784,尚有21.6%的改善空间,企业总资产不是规模效率的决定因素;稳定繁荣的宏观经济形势、资产的快速周转、可提供差异化的产品和服务都有助于规模效率的提升,而规模效率的改善与行业行政垄断是负向关系。研究显示提高资产的利用效率和差异化服务水平是利于规模效率进步的,政府应进一步提高交通运输部门的综合运管协调能力,提高企业规模效率。     

中国港口上市企业融资效率及影响因素研究

选取2015～2019年我国17家港口上市企业相关数据，采用DEA和Malmquist指数从静态和动态两个维度测度我国港口上市企业融资效率，构建Tobit回归模型研究其融资效率的影响因素及影响程度。实证研究结果表明：港口上市企业融资效率不高，多数企业未能达到DEA有效，技术效率较低的原因主要在于纯技术效率较低；港口上市企业全要素生产率呈现不稳定的上下波动状态，整体呈下降趋势；企业资金结构、股权集中程度和宏观经济发展状况与港口上市企业融资效率具有显著相关性。最后，从调整生产规模、优化融资结构和加大政策支持力度三个方面提出相关建议。     

基于KMV模型的我国上市公司信用风险研究

在KM V框架的基础上对股权价值计算方法进行了改进,通过改进后的方法,计算出1999年至2006年各年所有上市公司的违约距离、理论违约率、企业价值、股权价值等指标数据.从分析的结果来看,上市公司规模对信用风险有一定影响,上市公司规模越大,信用风险越小,公司规模越小,信用风险越大.从违约风险的变化情况看,2003—2006年上市公司的违约距离呈下降态势,说明近年来上市公司的违约风险加大.对比沪深300上市公司股改前和股改后信用状况,发现股改前后信用状况有显著不同,股改后上市公司的违约风险变大.通过违约距离的敏感性分析,认为股权价值波动率对违约距离最敏感.     

基于Translog生产函数的中国汽车工业规模经济与替代弹性及价格弹性研究

使用迭代似无关回归(ISUR)方法估计了以生产工人、非生产工人和资本为投入要素的中国汽车工业Translog生产函数及中国汽车工业规模报酬的阶数,利用获得的估计计算了投入要素之间的替代弹性并通过替代弹性计算了要素需求的价格弹性。在此基础上,对中国汽车工业规模经济的状况、投入要素之间的替代或互补关系和要素价格变化对要素需求的影响进行了分析.结果显示:在所研究的期间内,中国汽车工业处于规模报酬不变阶段;生产工人和资本之间以及非生产工人和资本之间是替代关系,而生产工人和非生产工人之间是互补关系;对中国汽车工业而言,三个要素需求缺乏弹性。     

基于协整理论和灰色系统的我国粗钢需求预测

运用协整理论和灰色系统对中国1979-2008年的粗钢消费量和GDP进行分析,并对中国2009-2020年粗钢需求量进行了预测和修正,得到中国2015年粗钢需求量在6.4-7.3亿吨之间,2020年在8.2-8.8亿吨之间的结论.     

Improving the identification of returns to scale in data envelopment analysis

In order to assess the efficiencies of a set of production units, it is necessary to identify the nature of returns to scale which characterise efficient production. Some methods have been developed to test the nature of the scale elasticity across the full range of scale sizes. However these tests are heavily weighted by the majority of the units and may not identify small ranges of scale size where different returns to scale hold. This paper develops a procedure based on a combination of Data Envelopment Analysis and regression analysis to identify the ranges of scale size where the returns to scale may differ from those in other ranges for the single-output, multi-input case. We also develop a measure of scale size across different input mixes.     

Efficiency decomposition for parallel production systems

For production systems composed of parallel processes, the system efficiency will more properly represent the aggregate performance of the component processes if the operation of each process is taken into consideration. Several approaches have been proposed for measuring the efficiency of parallel production systems. By requiring the same factor to have the same virtual multiplier, the proposed method is able to calculate the system and process efficiencies at the same time. Moreover, the former can be decomposed into a weighted average of the latter. A system is efficient only if all of its component processes are efficient. Chemistry departments in the UK are used as an example, where teaching and research are two major functions of the department. The relationship between the system and process efficiencies which holds for the case of constant returns to scale can be extended to the case of variable returns to scale.

     

Returns to scale pattern and efficient firm size in the public accounting industry: an empirical investigation

This paper employs Data Envelopment Analysis to investigate returns to scale patterns and efficient firm size in the public accounting industry in the USA post-Sarbanes–Oxley Act. Using contemporary survey data from Accounting Today's top-100 accounting firms for the years 2003 and 2004, our results indicate that the very largest accounting (first tier) firms display constant returns to scale, whereas approximately half of the smaller (second tier) firms exhibit increasing returns to scale. These findings suggest that while very large firms are optimally scaled, there still are economic efficiencies to be gained through expanding the size of nearly half of the second-tier accounting firms. Results for the remaining second-tier firms show either constant or decreasing returns to scale, indicating that they are either already optimally sized or that they should consider contraction. The results for the second-tier firms remain qualitatively unchanged when the first-tier firms are excluded from the estimation.     

Additive efficiency decomposition in two-stage DEA

Kao and Hwang (2008) [Kao, C., Hwang, S.-N., 2008. Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research 185 (1), 418–429] develop a data envelopment analysis (DEA) approach for measuring efficiency of decision processes which can be divided into two stages. The first stage uses inputs to generate outputs which become the inputs to the second stage. The first stage outputs are referred to as intermediate measures. The second stage then uses these intermediate measures to produce outputs. Kao and Huang represent the efficiency of the overall process as the product of the efficiencies of the two stages. A major limitation of this model is its applicability to only constant returns to scale (CRS) situations. The current paper develops an additive efficiency decomposition approach wherein the overall efficiency is expressed as a (weighted) sum of the efficiencies of the individual stages. This approach can be applied under both CRS and variable returns to scale (VRS) assumptions. The case of Taiwanese non-life insurance companies is revisited using this newly developed approach.     

Calculating scale elasticity in DEA models

In the data envelopment analysis (DEA) efficiency literature, qualitative characterizations of returns to scale (increasing, constant, or decreasing) are most common. In economics it is standard to use the scale elasticity as a quantification of scale properties for a production function representing efficient operations. Our contributions are to review DEA practices, apply the concept of scale elasticity from economic multi-output production theory to DEA piecewise linear frontier production functions, and develop formulas for scale elasticity for radial projections of inefficient observations in the relative interior of fully dimensional facets. The formulas are applied to both constructed and real data and show the differences between scale elasticities for the two valid projections (input and output orientations). Instead of getting qualitative measures of returns to scale only as was done earlier in the DEA literature, we now get a quantitative range of scale elasticity values providing more information to policy-makers.     

Listening to Students: How I Came to Love My Low-Residency Program

High-profile technology-transfer success stories are especially seductive to institutional leaders in today's economic climate, creating the impression that tomorrow's Gatorade, Taxol, and Google will occur on “my” campus. But longitudinal research of technology-transfer revenue and cost patterns, presented in the form of odds ratios for profitability (i.e., excess revenues available for reinvestment), provides new evidence that this belief is largely unsubstantiated. Universities that engage in less than about $200 million in research and development (R&;D) activity per year, develop fewer than 20 licenses per year, and/or employ fewer than five licensing professionals, confront substantially lower chances for financial success than do those above these output points. For those with a scale of operation above these levels, the marginal returns on higher R&;D investment, licensing, and staffing falls substantially, reaching an odds-for-financial-success maximum of 65 percent. Combined with data indicating that at least five years are required to realize financial success and that the odds for success fall substantially after that point, we argue that a shift in emphasis from revenue generation to the development of university/industry relationships and cost-containment efforts are both needed to meet higher education's social contract to contribute to the public good.     

Nonparametric estimation of returns to scale in the public sector with an application to the provision of educational services

Nonparametric programming models have been developed to measure technical efficiency and scale economies. The programming models used for public sector applications, however, are based on standard private sector production theory. In the public sector environmental variables have a significant impact on the provision of public services. Without controlling for these environmental factors point estimates of efficiency and returns to scale will be biased. This paper extends nonparametric methods to allow measurement of returns to scale in the provision of public services. The method is applied to the provision of educational services in New York State school districts for illustrative purposes.