基于等效益面生产函数的全要素生产率与技术进步贡献率

一个评价单元的等效益面生产函数是这个单元的技术效率与前沿面生产函数之积。在这一定义之下，本文证明了全要素生产率的改变就是等效益面生产函数的相对垂直移动。由此，在假设规模效益不变的情况下，可将一个评价单元的经济增长量分解为三个要素的代数和。这三个要素分别是：技术进步、技术效率的改善和投入量增加的贡献。在此时间离散型分解式的基础上，根据这些要素的不同变化情况，进一步给出了技术进步贡献率的测算方法。这种测算方法既可以评价各生产单元的单期技术进步贡献率，也可以测算它们在一个周期上的技术进步贡献率。基于等效益面生产函数上的关于经济增长的代数分解式与技术进步贡献率的定义均具有明显的几何意义。     

山西煤炭工业全要素生产率变动实证研究

山西煤炭工业在全国煤炭工业中占有重要地位,文中应用基于DEA的非参数Malmquist指数法,对2001～2008年中国27省区煤炭工业的全要素生产率进行了测算,并将其分解为技术进步指数和技术效率指数,重点研究了山西煤炭工业的全要素生产率的变动趋势及原因,结果表明:山西煤炭工业的全要素生产率平均增长了5.7%,主要原因在于技术效率水平的提高,而技术进步水平有所下降;进一步分解,在技术效率的提高中,基本上是规模效率在起作用,而纯技术效率没有得到改善。接着对山西煤炭工业的技术进步、纯技术效率、规模效率作了详尽的分析,最后给出提高全要素生产率的建议。     

中国保险业全要素生产率增长分解与分析

研究1999年至2003年我国保险业全要素生产率增长趋势，并将其分解为前沿技术进步、纯技术效率的变化、规模效率的变化三大因素。研究发现，保险业的全要素增长率呈现逐年上升的趋势；前沿技术进步已成为我国保险业全要素生产率增长的最主要动力；保险公司相对前沿的技术效率差距拉大，已出现阻碍全要素生产率增长的趋势，但这种技术效率的差距不是因纯技术效率的差异影响而是受规模效率的影响。     

人力资本、配置效率及全要素生产率变化

考虑到人力资本的异质性,本文将劳动分为低技能劳动和人力资本,利用随机前沿超越对数生产函数模型测算了中国1997—2012年30个省市全要素生产率的变化。在引入要素价格的基础上,借助 Kumbhakar 模型对全要素生产率变化进行分解后发现：（1）配置效率不高制约了全要素生产率的增长;（2）配置效率表现出物质资本和劳动低配,人力资本高配;（3）报酬结构调整对配置效率改进模拟结果表明改善人力资本配置效率最有利于全要素生产率的增长;（4）发挥人力资本配置效率优势,还需进一步扩大教育规模。     

我国商业银行效率分析(2005～2010)——基于Malmqusit指数

本文基于Malmquist指数研究我国13家商业银行6年间的效率及其动态变化,将Malmquist指数分解为技术进步、纯技术效率和规模效率。利用DEA程序以产出为主导型,考虑规模报酬的变动,得出结论:我国商业银行全要素生产率整体上呈增长趋势,国有商业银行技术进步率较高,但技术效率低于股份制商业银行,并根据银行现状,提出改进建议。     

新疆经济增长的全要素生产率的实证研究

本文根据C-D生产函数和索罗余值法,建立了新疆的总量生产函数模型,并利用新疆1991～2010年相关指标数据进行了测算。研究发现,新疆总量生产函数是一个规模报酬递减的生产函数,新疆的经济增长模式为粗放型经济增长模式,代表技术进步的全要素生产率对新疆经济增长的贡献率平均保持在57.13%左右,但其与发达国家的80%～90%还是有一定的差距的。因此,要保持新疆经济长期持续增长,还需要大力提高新疆全要素生产率的增长率。     

效率增进、技术进步与全要素生产率增长——制造业内外资企业生产率比较

运用随机前沿生产函数和1999～2006年产业面板数据,本文研究了制造业内外资企业全要素生产率和技术效率的动态变化特征。实证结果表明,内外资企业全要素生产率均不断提高,由于内资企业增速更快,二者之间的差距开始缩小。进一步的分解表明,前沿技术进步已成为全要素生产率增长的核心动力,1999～2006年前沿技术进步对内外资企业生产率增长的贡献平均约为80%和90%。     

战略性新兴产业高端化了吗？

战略性新兴产业的高端化发展关系到经济发展方式的转变,是推动产业转型与升级的主导力量。采用DEA非参数Malmquist指数方法,利用战略性新兴产业上市公司数据,测度并分析全要素生产率变化率及其分解指标的变动趋势。结果表明,产业整体和分产业层面的全要素生产率变化率,政策后均呈现下滑态势,这主要由技术进步率和纯技术效率的降低造成的,呈现“轻技术创新,重规模扩张”的产业低端化发展趋势。通过产业整体和分产业层面的回归分析,实证检验了全要素生产率变化率及其分解的变动趋势和影响因素,验证了产业发展的低端化趋势。     

中国碳排放效率与全要素生产率研究

基于各要素调整比例不同的Russell方向性距离函数数据包络分析模型,对中国各省份考虑能源环境情况下总的非效率和碳排放非效率进行测算,并计算了碳排放的非效率占整个非效率项的大小。结果表明,各省份总的非效率存在较大的差异,北京、上海、广东这三个省份各年都处在前沿面上,碳排放的非效率不是各省份非效率的主要原因。此外,计算了全要素生产率指数的增长情况,并进行分解,得到碳排放的全要素生产率指数,研究发现碳排放的全要素生产率指数占总的指数部分较大,且碳排放的全要素生产率指数多数是正的,对总的全要素生产率指数的上升起到积极的作用。对碳排放的全要素生产率进行分解发现,碳排放的全要素生产率指数上升的贡献主要来自技术进步,技术效率有待提高。     

纯要素生产率对要素投入及其成本的影响

本文首先将具有希克斯中性技术进步的线性齐次生产函数扩展到n要素非线性齐次情形,明确指出在非规模报酬不变时,技术进步因子其实不能确切体现技术进步的作用。进而在文献[1],[2]的基础上,讨论了纯要素生产率对要素投入及其成本的影响,给出了一组简明的数学表示式,揭示了纯要素生产率在微观经济活动中的机理和作用。     

Parametric Decomposition of a Generalized Malmquist Productivity Index

This paper provides a parametric decomposition of a generalized Malmquist productivity index which takes into account scale economies. Unlike Balk (2001), the contribution of scale economies to productivity change is evaluated without recourse to scale efficiency measures, which are neither bounded for globally increasing, decreasing, or constant returns to scale technologies nor for ray-homogeneous technologies. An empirical application using panel data from Spanish savings banks is included. This application shows the advantages of the suggested method compared to Balk's approach. The results show an increase of total factor productivity which can be mainly attributed to technical progress and the positive effect of returns to scale.     

Decomposing TFP growth in the presence of cost inefficiency,nonconstant returns to scale,and technological progress

A thorough understanding of changes in productivity measures is important to economists and policymakers, because productivity growth is a major source of economic growth. This article explores the relationship between changes in total factor productivity (TFP) growth, defined using an index number approach, and changes in returns to scale, cost efficiency, and technology. Several decompositions are developed, using alternatively production and cost frontiers. The last decomposition developed also allows for multiple outputs.The refereeing process of this paper was handled through W.H. Greene.     

资本市场扭曲对城市全要素生产率的影响研究——基于规模和技术视角

在创新驱动发展的背景下,资本市场化改革有助于提高资本配置效率,进而对全要素生产率产生影响。基于中国城市相关数据,利用生产函数法和随机前沿估计法测算资本市场扭曲,并利用DEA-Malmquist指数法对城市全要素生产率进行分解,从规模和技术视角切入,实证分析了资本市场扭曲对城市规模效率、技术效率和全要素生产率的影响。研究发现,资本市场扭曲增加对规模效率具有正向影响,对技术效率和全要生产率具有负向影响。反事实分析结果显示,当消除资本市场扭曲后,从全国层面看,规模效率平均下降0.54%,技术效率平均上升4.25%,全要素生产率平均上升1.54%。     

Decompositions of profitability change using cost functions

The paper presents a decomposition of a production unit’s cost ratio over two periods into explanatory factors. The explanatory factors are growth in the unit’s cost efficiency, output growth, changes in input prices and technical progress. In order to implement the decomposition, an estimate of the industry’s best practice cost function for the two periods under consideration is required. Profitability at a period of time is defined as the value of outputs produced by a production unit divided by the corresponding cost. Using the earlier work by Balk and O’Donnell, the paper provides a decomposition of profitability growth over two periods into various explanatory factors that are similar to the cost ratio decomposition except that change in outputs explanatory factor is replaced by two separate factors: an index of output price growth and a measure of returns to scale.     

Public support for performing arts. Efficiency and productivity gains in eleven European countries

This paper investigates the importance of public cultural expenditure for the efficiency and productivity of the performing arts (PA) firms. To this aim, we estimate a translog production function using the stochastic frontier approach (SFA), and we obtain the estimates of both technical efficiency and its determinants for the PA firms in EU-11 countries over the period 2009–2017. The large panel data set enables the application of robust true random-effects SFA techniques, which control for noise, unobserved firms' heterogeneity and endogeneity of the inputs. Moreover, by estimating a production function, the characteristics of the production technology in the PA sector is also derived. The empirical results demonstrate that PA firms are technically inefficient, implying that the investigated firms could increase their artistic output between 32 and 42% and that decreasing returns to scale are prevalent, due to the presence of too many micro and large-scale firms in the European PA sector. In contrast to the seminal Baumol and Bowen's [5] paper, we also demonstrate that the total factor productivity (TFP) increased in the EU PA firms over the examined period. Technical efficiency, although relatively low, was the main driver of this productivity growth, as opposed to scale efficiency change or technological change, which display very small or no increases. We also find that, contrary to the common wisdom on its negative effects on firm efficiency, public spending on culture increases the efficiency of PA firms. Within this context some policy implications are discussed.     

Externalities, efficiency, regulation, and productivity growth in the U.S. electric utility industry

This paper examines the decomposition of total factor productivity growth for firms subject to regulation, given the production of a bad output. The production of good and bad outputs provides benefits and costs to society. Corporate socially responsible firms recognize the cost to society of producing the bad output. The paper separates the production technology and regulation effects from both the scale and technical change components. The paper also examines the measurement and decomposition of productivity growth when not accounting for production of the bad output. Using a 1992–2000 panel of 34 U.S. investor-owned electric utilities, results indicate that improvements in the scale, efficiency change, and technical change components contributed to positive growth. Not accounting for production of the bad output led to, on average, an overestimation of both the rate of productivity growth, and the contributions of scale economies and technical change to changes in productivity growth.

基于环境负产出的能效动态Malmquist模型研究

本文旨在研究环境效率—能源效率—经济效率的"三位一体动态全要素生产率"。首先基于数据包络分析建立了环境约束下的能效动态Malmquist模型,定义了能效效率改变指数、污效效率改变指数和动态进步指数。通过对中国18个行业2000～2007年的数据分析,指出未考虑环境效应、动态效应的Malmquist模型会带来误判,进而揭示出在中国能效全要素生产率改变过程中,能源环境效应起到了不可忽略的作用,而动态效应则是最大的瓶颈,却没得到应有的重视。     

Efficiency, productivity, and scale economies in the U.S. property-liability insurance industry

The paper examines efficiency, productivity and scale economies in the U.S. property-liability insurance industry. Productivity change is analyzed using Malmquist indices, and efficiency is estimated using data envelopment analysis. The results indicate that the majority of firms below median size in the industry are operating with increasing returns to scale, and the majority of firms above median size are operating with decreasing returns to scale. However, a significant number of firms in each size decile have achieved constant returns to scale. Over the sample period, the industry experienced significant gains in total factor productivity, and there is an upward trend in scale and allocative efficiency. More diversified firms and insurance groups were more likely to achieve efficiency and productivity gains. Higher technology investment is positively related to efficiency and productivity improvements.     

Hicks-Moorsteen versus Malmquist: a connection by means of a radial productivity index

A primal index of productivity change is introduced which decomposes exactly into three components: technical change, technical efficiency change and average scale economies (radial scale change). The productivity index is defined using variations of the distance function along pre-assigned input–output rays and, for this reason, it is deemed a radial productivity index (RPI). It is proven that: first, the RPI index collapses to the Malmquist productivity index when the technology is constant returns to scale (CRS); second the RPI index equals the Hicks-Moorsteen productivity index under homotheticity of technology (and non-CRS). The key to these results is a new definition and measure of the contribution of scale economies to productivity change.     

时变弹性生产函数生产率分解公式及其政策含义

本文基于时变弹性生产函数,推导出经济增长来源于资本、劳动力、中性技术进步和偏向性技术进步贡献度之和;索洛余值在数值上等于中性技术进步贡献度与偏向性技术进步贡献度之和,也等于资本生产增长率与劳动生产增长率的加权和,其权数分别为资本和劳动时变产出弹性。研究认为,提高劳动收入份额,有利于促进经济向集约型发展方式转变。