中国服务企业生产率异质性与资源再配置效应

本文采用世界银行提供的中国服务企业调查数据,运用半参数的LP方法测算了中国服务企业的全要素生产率（TFP）,并进一步将TFP分解考察了中国服务业TFP的增长源泉和市场资源的再配置效应。结果表明：管理、设计和通信等中间投入对服务企业产出的贡献率是最高的;中国服务企业TFP总体上呈现出上升态势;不同类型企业和行业的TFP水平及增长率存在较大差异。TFP分解后发现,中国服务业TFP的增长主要是靠外部市场需求和企业自身进步同时拉动的;但劳动力资源产生了误置,且国有化程度越高的技术密集型服务行业的资源再配置效应越差。与制造业企业的比较显示,中国服务企业的规模、TFP水平和增长率普遍偏低;总体上服务企业间的再配置效应优于制造业企业,但再配置效应在各服务行业上表现出更强的异质性。     

我国区域农业全要素生产率的演变趋势与影响因素

利用DEA-Malmquist指数法分析1992~2012年我国31个省份农业TFP的演变趋势及影响因素。研究显示,我国农业TFP的年均增长率为3.1%,对第一产业GDP年均增长率的贡献度为79.210%;技术进步是引致我国及各省份农业TFP变动的主要因素,东部、中部和西部的农业TFP依次下降,1993年以来各省份的农业TFP不存在σ收敛;人力资本含量、灌溉面积占比、工资性收入占比和农业财政支出占比对农业TFP有正面影响,而农业产值占比、粮食播种面积占比具有约束作用,这些因素的趋势性变化引致了区域农业TFP的发散格局。     

中国装备制造业全要素生产率增长的波动与异质性

研究目标：中国装备制造业及其细分行业TFP增长率的测定与分解。研究方法：构建超越对数形式的随机前沿生产函数模型,测算中国装备制造业及其细分行业TFP增长率,并对其进行分解。研究发现：中国装备制造业TFP增长率不但在区域和省份之间存在差异,而且存在明显的内部行业异质性;技术进步和配置效率变化分别是提高和阻碍装备制造业TFP增长率的主要原因和障碍;除技术进步均为正值外,技术效率变化、规模效率变化和配置效率变化在装备制造业各行业中异质性相当明显;装备制造业及其细分行业仍未从真正意义上实现由粗放型向集约型增长方式的转变。研究创新：中国装备制造业细分行业TFP增长率及其异质性。研究价值：为装备制造业转型与升级提供经验证据。     

中国全要素生产率变动的再测算:1978～2007年

中国经济在2003～2007年间年增长率都超过10%,这与前期文献对中国增长后劲乏力的悲观预测似不一致.本文使用并延展Holz(2006)的资本存量序列,通过要素收入份额可变的增长核算法,重新测算了我国改革开放以来的TFP增长率.研究发现,世纪之交前后的TFP增长率并不像其他文献所报告的那样接近于零甚至为负值,其原因在于前期的文献采用了不合适的投资流量指标,高估了资本存量的增长率,进而低估了TFP增长率.这一结果将有助于理解中国经济增长的可持续性.     

中国工业全要素生产率与结构演变：1990~2013年

本文测算了1989~2013年工业分行业的增加值、劳动投入、资本存量,利用随机前沿分析（SFA）计算1990~2013年分行业的全要素生产率（TFP）,进而估计工业所有制结构变化对工业TFP增长的效应。本文发现,在考察期内,只有技术进步基本保持了持续增长,配置效率改善在2000年以后明显放缓;工业所有制结构变化显著提高了工业TFP增长率,但对技术进步的作用不显著;将考察期划分为两个阶段后发现,后一阶段所有制结构变化对TFP的促进作用明显小于前一阶段。工业改革的重点在于促使资源合理、自由流动,创造公平的市场环境,为工业TFP增长释放更大的空间。     

全要素生产力对中国经济增长贡献的实证分析

在国内外学者研究的基础上,利用中国1978年到2005年的数据,研究了这27年劳动力投入、物质资本存量、TFP的平均增长率和对产出增长的贡献率,通过实证研究得到的结果可以看出物质资本存量对产出的贡献率已经达到一个顶峰,未来中国产出增长主要靠TFP的增长,并由此给出了相关建议。     

我国技术效率、技术进步与生产率区域差异的实证研究

本文用非参数Malmquist指数方法研究了我国全要素生产率的增长状况及其区域差异,并将其分解为技术进步和技术效率,同时采用增长回归法对我国地区之间TFP、技术效率、科技进步的差异进行了检验。研究表明:1994-2007年间我国全要素生产率年均增长率达到1%,主要得益于技术进步水平的提高,技术效率总体上呈现下滑趋势;我国各省市区的科技进步、技术效率、TFP变化呈现出较为明显的差异,其中TFP和科技进步变化差异最为明显,而技术效率变化差异不大。     

全要素生产率与资本、劳动投入的相关性研究——基于江苏省的实证分析

关于对全要素生产率（TFP）的内涵界定和计算,一般将其与技术进步等同起来,并采取“索洛余值”的方法进行计算。文章将以江苏省1990年～2008年统计数据为基础,对江苏省在次区间内的TFP和K、L、TFP对经济增长的贡献率进行分析。计量的结果表明,TFP对经济增长的贡献率一直较低,并在某些年份呈负值。通过分析,原因是由于TFP与K、L之间存在相关性,因此,TFP的计量数值应低于实际TFP对经济增长的贡献。因此,在TFP的计算中应该考虑K和L的影响。     

我国全要素生产率增长的区域差异

本文基于我国27省市人均人力资本存量、外贸依存度和R＆D投入增长率Panel Data的实证检验并结合其变化趋势，得出人均人力资本、R＆D投入的增长率下降是导致我国全要素生产率（以下简称TFP）增长缓慢的主要原因，而进出口量增长对TFP增长影响不显著，这也在一定程度上解释了进出口量增长迅速的一些地区TFP增长却不快。     

基于随机前沿面神经网络的TFP贡献率测度

针对全要素生产率(TFP)贡献率测度的问题,研究了用神经网络来测量TFP贡献率的方法和用随机前沿面来测量TFP贡献率的方法;指出了这两种方法在测算中存在的缺陷。并在此基础之上,提出了运用随机前沿面模型构造出随机前沿面神经网络来测量TFP贡献率,从而实现了利用随机前沿面神经网络模型进行TFP测度贡献率。全部计算过程都通过了编程计算,收进我们自己的软件系统DASC。     

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。     

中国农业生产率的变动与分解分析:1978～2004年--基于非参数的HMB生产率指数的实证研究

本文使用非参数的HMB生产率指数方法，考察了中国农村改革以来农业全要素生产率（TFP）的变动趋势，并把TFP的增长构成分解为技术进步、技术效率变化、规模效应和投入产出混合效应四个部分。结果表明，改革开放以来我国农业TFP的增长主要是由技术进步推动的，技术效率的下降对TFP的增长造成了不利影响，而规模效应和混合效应影响较弱。文章还指出中国农业的育种能力和生物技术的发展是农业技术进步的决定力量。     

The stationarity of British economic and productivity growth 1856–1913

Characterization of late nineteenth-century British economic performance rests heavily on identifying trends and turning points in GDP and productivity growth. Crafts, Leybourne and Mills (1989) provide the most sophisticated study in this genre, deploying a time-varying parameter model, to severely dent the notion of a climacteric. This paper argues the linear trend approach to assessing the climacteric may be otiose. Investigating the order of integration of the GDP series, and the cointegration of GDP and factor input growth, suggests both GDP and productivity growth tended to revert to a constant mean rate within the period 1856–1913, and undermines the notion of a climacteric.     

Regulation and Productivity

We investigate the impact of occupational safety and health (OSH) and environmental regulation on the rate of growth of total factor productivity (TFP) in the Quebec manufacturing sector during the 1985–88 period. Our results show that environmental regulation and OSH protective reassignments (a prevention policy with respect to OSH) have led to a reduction in productivity growth, while the presence of mandatory prevention programs and of fines for infractions to OSH rules have led to an increase in productivity growth. Interestingly, this is, to our knowledge, the first result showing that OSH regulation may have had a positive effect on productivity growth.     

经济增长、全要素生产率与GDP核算误差

全要素生产率是技术进步的一个替代性指标.从全要素生产率及其变化的角度,反观GDP及其增长率是否真实或可信这一逻辑是否成立,依赖于技术进步的性质.如果技术进步是一个相对稳定而且缓慢的演化过程,那么,作为技术进步替代性指标的全要素生产率,在正常情况下,即在没有面临重大自然灾害或天赐良机的情况下,就不会在短期内发生急剧的变化;如果没有非正常情况发生而全要素生产率却发生了急剧变化,一般而言,是产出测量或投入测量出现了问题.但如果恰好面临技术革命或根本性制度变迁时期,则全要素生产率会发生漂移性变化,即从这一时刻起全要素生产率会发生永久性水平的变化.本文利用DEA模型实证性地研究了中国X省经济增长、全要素生产率与GDP核算误差之间的关系,并对相关现象进行了理论分析.     

Market Imperfection and Productivity Growth—Alternative Estimates for Taiwan

This study first explores why the shares of factor inputs have not been measured correctly and concludes that the earlier findings are biased due to the miscalculation of factor shares which have produced low estimated total factor productivity (TFP) growth in the East Asian countries. Second, three approaches are proposed to empirically illustrate the impact of capital and labor shares on the estimates of TFP growth. It is suggested that TFP growth in the East Asian economies will be understated if net indirect taxes and imperfect competition profit are ignored. Finally, by taking the net indirect taxes and imperfect competition profits into account, the result of this paper indicates that Taiwan's economy has enjoyed an average annual TFP growth rate of 3.6% over the period 1980–1999.     

Total factor productivity growth in banking: The Israeli banking sector 1979–1982

The primary focus of this paper is the modeling and estimation of total factor productivity growth in banking. The measured total factor productivity growth is decomposed into its main components: 1) scale economy and output growth, 2) branching effect, and 3) technological change effect. Our findings indicate that total factor productivity grew at an annual average rate of 7.8% for the 1979–1982 period but this growth has slowed down to only 2.9% for the 1981–1982 period. Scale economy and output growth have contributed to about four-fifths of the growth, whereas branch growth and technical change have contributed to one-fifth of the growth. An important observation is the increasing importance of both branch growth and technical change throughout the period, especially for smaller banks.The refereeing process of this paper was handled by J. van den Broeck.     

The failure of effective technological transfer in Polish industry

Central planners in Poland have continuously emphasized the importance of increasing factor productivity as a major goal of Polish development policy and have included this goal as an integral part of every economic reform proposal of the last two decades. In the decade of the 1970s a new development strategy was initiated which counted heavily on the import of more technologically advanced machinery and equipment and the purchase of licenses and production processes from the West. This paper documents the tremendous increase in Western imports and the purchase of licenses which took place in the 1970s, and which would then be expected to generate an increase in joint factor productivity due to technological change. Empirical analysis, however, indicates that there was no effective transfer of the technology. Joint factor productivity for total industry calculated as a residual in estimated production functions, which include imported inputs, has a zero rate of growth from 1970 to 1978 (using quarterly data). Disaggregating and using annual data over a longer sample period yields estimates of the rate of growth of joint factor productivity which increase slightly for total industry in the 1973–1977 period. For the electrical and mechanical branch which received large numbers of license and joint production agreements the rate of growth of joint factor productivity remained unchanged. The results indicate that systemic factors such as central planning, managerial inhibitions and supply bottlenecks out-weighed any potential increase in factor productivity as a result of technology transfer.Wichita State University. I would like to thank Keith Crane, John Neufeld and two anonymous referees for useful comments on an earlier draft of this paper. Financial support for this research provided by the American Council of Learned Societies/Social Science Research Council (financed in part by the National Endowment for the Humanities and the Ford Foudation), the International Research and Exchanges Board and the UNCG Research Council is gratefully acknowledged. Responsibility for all errors remains with the author.     

全要素生产率中的加成定价与规模报酬效应

研究目标：考察经典方法估计全要素生产率时是否因加成定价或规模报酬效应而出现估计偏差。研究方法：基于放松完全竞争和规模报酬不变假设的增长核算框架估计全要素生产率,并在分别估计加成定价率和规模报酬率基础上对古典索洛余值进行分解。研究发现：加成定价效应是造成古典索洛余值与全要素生产率偏差的重要原因;富有弹性的劳动力市场可以降低全要素生产率受到经济冲击的影响。研究创新：基于扩展后的增长核算框架估计了中国、韩国、日本和美国的全要素生产率,分析古典索洛余值是否存在估计偏差以及偏差的主要来源。研究价值：分离新古典索洛余值中的加成定价和规模效应,可以有效降低经验研究中全要素生产率的估计偏差。     

Productivity accounting for separable technologies

This paper develops a method for decomposing total factor productivity growth in separable production technologies and uses it to examine the role of pest-damage prevention on agricultural productivity. The rate of technical change is decomposed into output-enhancing and damage-preventing components. Growth accounting cannot provide separate estimates of these two components of technical change, and instead a parametric model is developed based on the dual cost function. The proposed model captures both components of technical change, properly accounts for environmental effects, and also accommodates the presence of capacity utilization and scale biases. The empirical application of the model is to a sample of Cretan olive-oil producers, and the results show that output-enhancing technical change is more important than damage-preventing technical change in explaining observed total factor productivity (TFP) changes. The second largest source of TFP growth is due to the scale effect.