基于Global Malmquist-Luenberger(GML)指数模型的物流业绿色全要素生产率测算分析——以2010—2020年京津冀13个城市为例

构建Global Malmquist-Luenberger (GML)指数模型对2010—2020年京津冀区域13个城市的物流业绿色全要素生产率(GTFP)进行测度,并对生产率变化、指数分解、区域差异、收敛性情况展开一系列分析。主要结论有:(1)整体来看,京津冀区域的物流业GTFP主要源于绿色技术进步(GBPG)驱动,GBPG累积提升约10.63%,绿色技术效率(GEC)下降明显;“十二五”时期的GML指数波动较大,“十三五”时期趋于平稳提升。(2)观测期内京津冀三地物流业绿色全要素生产率发展成效差异明显,仅河北实现了物流业GTFP提升,GBPG增长率高达25.18%,特别是张家口、邢台、衡水和秦皇岛四市在“十三五”时期已实现了GEC和GBPG双驱动发展;北京近年来物流业GTFP反弹提升明显,但GEC指数仍处于较低水平;天津的GBPG指数和GEC指数均有不同程度降低。(3)京津冀、津冀和河北城市组的物流业GTFP均通过了绝对β和条件β收敛检验,行政壁垒效应的存在导致三地收敛速度有所差异,河北城市组收敛速度最快,京津冀城市组最慢。

Radiative dryness index and potential productivity of vegetation in China

The Chikugo Model is used to estimate radiative dryness indexes (RDI) and net primary productivity (NPP) of vegetation zones in China by calculating cli-matic parameters. That provides the water-heat equilibrium condition, potential primary production for natural vegetation in various vegetation zones, and their geographical distribution pattern. That could be used as the basis for study the effect of global climate change on ecosystems.

Measuring Scientific Productivity in China Using Malmquist Productivity Index

Purpose: This paper aims to investigate the scientific productivity of China's science system. Design/methodology/approach: This paper employs the Malmquist productivity index(MPI) based on Data Envelopment Analysis(DEA).Findings: The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities.Research limitations: As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research.Practical implications: The results indicate that Chinese education administrative departments should take actions to guide and promote the teaching activities and formulate reasonable resource allocation regulations to reach the balanced development in Chinese universities.Originality/value: This paper selects 58 Chinese universities and conducts a quantified measurement during the period 2009–2016. Three main functional activities of universities(i.e. teaching, researching, and application) are innovatively categorized into different schemes, and we calculate their performance, respectively.

The Correlation between the Power Quality Indicators and Entropy Production Characteristics of Wind Power+Energy Storage Systems

Power quality improvements help guide and solve the problems of inefficient energy production and unstable power output in wind power systems.The purpose of this paper is mainly to explore the influence of different energy storage batteries on various power quality indicators by adding different energy storage devices to the simulated wind power system,and to explore the correlation between systementropy generation and various indicators,so as to provide a theoretical basis for directly improving power quality by reducing loss.A steady-state experiment was performed by replacing the wind wheel with an electric motor,and the output power qualities of the wind power systemwith andwithout energy storagewere compared and analyzed.Moreover,the improvement effect of different energy storage devices on various indicatorswas obtained.Then,based on the entropy theory,the loss of the internal components of the wind power system generator is simulated and explored by Ansys software.Through the analysis of power quality evaluation indicators,such as current harmonic distortion rate,frequency deviation rate,and voltage fluctuation,the correlation between entropy production and each evaluation indicator was explored to investigate effective methods to improve power quality by reducing entropy production.The results showed that the current harmonic distortion rate,voltage fluctuation,voltage deviation,and system entropy production are positively correlated in the tests and that the power factor is negatively correlated with system entropy production.In the frequency range,the frequency deviationwas not significantly correlated with the systementropy production.

Production Chain Length and PPI-CPI Divergence:Analysis Based on the Global Input-output Price Model

Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.

Assessing Total Factor Productivity for Soybean Production in China Based on DEA-Malmquist Index: 2005-2017

The low and slowly increasing soybean yield restricts the development of soybean production. Accurate measures of total factor productivity (TFP) for soybean production can be helpful in identifying conditions, institutions or policies that promote soybean production development in China. In this paper, TFP growth for soybean production was estimated for a panel data of 10 major soybean producing provinces from 2005 to 2017. Results reveal that TFP grew at an average rate of 1.3% over the whole period, with technical progress contributing 2.3% and efficiency change providing the other -1.0%. The change of TFP for soybean production over that time, whether increase or decline, was mainly derived by technical change except in three years (2005-2007). Positive TFP growth in the provinces of Liaoning and Inner Mongolia, and negative TFP growth in Hebei and Anhui were mainly driven by efficiency change, specifically scale efficiency change except pure technical efficiency in Liaoning.

Productivity Growth in the Transportation Industries in the United States: An Application of the DEA Malmquist Productivity Index

This study reviews productivity growth in the five major transportation industries in the United States (airline, truck, rail, pipeline, and water) and the pooled transportation industry from 2004 to 2011. We measure the average productivity for these eight years by state in each transportation industry and the annual average productivity by transportation industry. The major findings are that the U.S. transportation industry shows strong and positive productivity growth except that in the years of the global financial crisis in 2007, 2008, and 2010, and among the five transportation industries, the rail and water sectors show the highest productivity growth in 2011.

Assessing economic performance of the three major urban agglomerations in China by using Malmquist productivity index

Forty years of reform and opening up,China has become to the world’s second-largest economy with great success.However,it is an undoubted actuality that the economic mode of Chinese development is still at the extensive stage.China’s economy has shifted from a high-speed growth phase to a high-quality development phase.In this study,we analyzed three major urban agglomerations’total factor productivity index dynamically by means of Malmquist productivity i?ndex method.The results showed that MPI of Beijing-Tianjin-Hebei urban agglomeration was the highest,as the reasons of the effectiveness of dual-wheel driving both the technology progress and the cluster scale.The mean of MPI of Yangtze River Delta urban agglomeration was fallen into decline by an average of 1.3%annually due to the rate of increase of the size of the cluster towards to optimal frontier was inferior to the relative risk reduction of technology progress.Pearl River Delta urban agglomeration MPI declined by an average of 2.2%annually as a result of the contribution of technology progress reducing.The study of the economic performance of three major urban agglomerations provides a theoretical basis and important practical value for urban development of high quality optimization.

A comparative analysis of Japanese firm productivity： Solow residual and Malmquist productivity index

For some time, two major kinds of Total Factor Productivity （TFP） have existed independently of each other： the Solow residual and the Malmquist Productivity Index （MPI）. The Solow residual was introduced in macro economic growth models, and the MPI has been used in micro economics and management studies. As both indices were developed independently, few studies utilize both together and compare the results. This paper uses the same data to compare the two productivity indices by setting to determine the economic implications of combining the two indices. We discovered that we could decompose TFP with each aspect of the Soiow residual and MPI. We could then interpret their relationship in the business cycle. Our results indicated that the frontier shift in MPI of Japanese firms often occurred when the Solow residual increased, meaning that improving oroductivitv with the Solow residual could be generated by a firm that could shift new production frontiers.

Overall profit Malmquist productivity index under data uncertainty

The calculation of the overall profit Malmquist productivity index(MPI)requires precise and accurate information on the input,output,input-output prices of each decision making unit(DMU).However,in many situations,some inputs and/or outputs and input-output prices are imprecise.As such,we consider the overall profit MPI problem when the input,output,and input-output prices are imprecise and vary over intervals,showing that method(MCM 54:2827–2838,2011)has some shortfalls.To remedy these shortfalls,we propose another method for measuring the overall profit MPI when the inputs,outputs,and price vectors vary over intervals.That is,to calculate the overall profit efficiency intervals,cone-ratio data envelopment analysis models can be applied to the incorporated information as weight restrictions.Further,we provide a new approach to calculating the upper bound of the overall profit efficiency of each DMU.A numerical example is provided for illustrating the proposed method.

Estimating the Three-Stage Cost Malmquist Productivity Index in the Taiwan Biotech and Biopharmaceutical Industry

This paper estimates and decomposes the output-oriented three-stage cost Malmquist productivity index of the Taiwan Residents biotech and biopharmaceutical （B＆BP） industry in 2004-2007 periods. The empirical estimations proceed in three stages. Following the methodology of Yang and Huang （2009） with the assumption of variable return to scale （VRS） in the first stage, the original cost Malmquist productivity index （CM） is decomposed into five sources of productivity change： pure technical efficiency change, technical change, allocative efficiency change （AEC）, input-price effect, and cost scale efficiency change. The method of Yang and Huang （2009） is an excellent contribution, but it did not deal with the exogenous environmental variables and noises. In the second stage, the original input variables are adjusted by the exogenous environmental variables. Finally, adjusted input variables produced by the second stage are reused for obtaining the reality of CM in the third stage.

Effects of SPAD Decline Value of Mid-season Hybrid Rice Leaves after Full-heading Stage on Productivity of Rice Fertilized with Nitrogen

[Objective] The aim was to research relationship between SPAD decline index after full-heading stage （SDIFHS） and productivity of rice. fertilized with nitro- gen in order to provide theoretical and practical references for selection and breed- ing of rice varieties. [Method] From 2008 to 2010, 18 mid-season hybrid rice vari- eties were researched every year to explore relationship＇ between SDIFHS and pro- ductivity of rice fertilized with nitrogen. [Result] The productivity of rice fertilized with nitrogen was of extremely significant positive corretation with SDIFHS, because the higher SPAD decline index is, the higher LAI decline index and the transformation ratio of dry matter to spikes in overground plant would be. [Conclusion] The re- search established a new method to predict productivity of rice fertilized with nitro- gen based on SPAD decline index.

中国农业绿色生产效率的动态变迁与空间分异——基于DDF-Global Malmquist-Luenberger指数方法的分析

基于资源环境约束角度,运用DDF模型测算2004—2018年中国30个省(自治区、直辖市)农业绿色生产中投入要素集约利用潜力、期望产出扩张潜力和非期望产出减排潜力,将30个省(自治区、直辖市)分为农业绿色生产高效区、集约区、粗放区、低效区和无效区五类区域。通过GML指数分析,得到五类区域在资源环境约束下农业绿色生产效率及影响因素变动情况。结果表明:从全国整体来看,各要素集约利用潜力、非期望产出减排潜力逐年下降,期望产出扩张潜力逐年减小,趋于饱和;中国农业绿色生产效率整体呈上升趋势,技术进步对农业绿色生产效率提升产生累积正效应,技术效率下降则产生累积负效应;无效区GML累积增长幅度最高,粗放区、低效区、集约区依次降低,高效区GML累积增长幅度最低;高效区和无效区的农业绿色生产效率增长源于技术效率提高和技术进步协同效应,技术进步是集约区、粗放区和低效区农业绿色生产效率增长的主要动力。

环境约束下的工业全要素生产率增长——基于Malmquist-Luenberger指数的行业面板数据分析

目前,关于工业全要素生产率的研究多数只考虑如增加值之类的"好"产出,从而忽略了环境污染"坏"产出,故对工业发展效率的评价出现失真。鉴此,通过Malmquist-Luenberger指数重新测算考虑环境污染约束的工业全要素生产率增长,并寻找行业"创新者",同时与不考虑环境污染约束的情况进行对比分析。实证研究发现:虽然忽略环境约束会低估技术效率水平和技术效率指数,但会高估技术进步指数和全要素生产率指数;行业"创新者"主要集中于制造业,尤其是环境污染较低的行业。

考虑非期望产出的中国海水养殖业全要素生产率研究——基于Global Malmquist-Luenberger指数

本文运用Global Malmquist-Luenberger指数方法,将海水养殖过程中的非期望产出纳入评价体系,在环境约束下对我国海水养殖业的全要素生产率进行综合评价。选取我国沿海9省份2003-2014年的数据为研究对象进行分析,发现样本期内我国海水养殖业全要素生产率自2008年起稳步提升;环渤海经济圈涨幅最大,南海经济圈的增长则略显微弱;山东省全要素生产率的增速最快,广东省生产率的提升最为缓慢,整体发展不平衡;生产率的提高主要来源于技术的进步,相对技术效率的提升作用未显现。海水养殖业的进一步发展需要在继续提高技术的同时注重效率的改进。

Malmquist指数与Malmquist-Luenberger指数的比较研究

提出了基于减少有害产出同时增加有益产出的Malmquist-Luenberger生产力指数评价方法.分析了该指数与Malmquist指数联系与差异,并通过美国电力产业的数据(19962000)对两种指数进行了实证对比.与Malmquist生产效率评价方法相比较,本文中所提出的方法可用于企业面对环境约束下的生产效率评价,并且在评价中不需要有关投入和产出的价格信息,评价指数也可以通过求解一个简单的线性规划模型来计算.

低碳约束下中国全要素生产率的时空演变——基于Sequential Malmquist-Luenberger生产率指数分解方法

在全要素框架下运用基于连续前沿的Malmquist-Luenberger生产率增长指数方法,估算了1987—2009年中国28个省(自治区、直辖市)的低碳全要素生产率、技术进步和效率改善,对中国低碳全要素生产率的总体发展、区域差异进行实证分析。然后,利用核密度估计,对累积相对低碳全要素生产率增长、累积相对技术进步和累积相对效率改善做分布动态演进分析。结果表明:考察期内中国整体的低碳全要素生产率趋于上升,但上升幅度逐渐减小;东、中、西三大区域的低碳全要素生产率存在显著差异,呈东高西低的增长格局;东、中部地区的低碳全要素生产率提升是技术进步和效率改善共同推进的结果;西部地区的低碳全要素生产率提升仅靠技术进步驱动,效率改善存在退步迹象;省际间的低碳全要素生产率呈一定程度的"俱乐部收敛"特征,技术进步有明显的"追赶效应"。

收入差距约束下西南边境地区全要素生产率测度分析——基于Malmquist-Luenberger指数

将收入差距因素引入全要素生产率体系,运用Malmquist-Luenberger生产指数估算西南边境11个州(市)2003-2014年的全要素生产率,并与传统不考虑收入差距的Malmquist生产率指数对比,结果表明:样本期内西南边境地区不考虑收入差距的平均全要素生产率大于1,考虑收入差距时平均全要素生产率则小于1,而且全要素生产率增长很不稳定,全要素生产率增长的主要来源是技术进步;考虑收入差距的全要素生产率、技术效率以及技术进步均有不同程度的下降,即不考虑收入差距大大高估了西南地区的全要素生产率。采用面板数据模型对影响西南边境地区收入差距约束下全要素生产率增长的因素进行回归分析,结果显示:城镇化率与TFP的增长呈负相关关系,地区经济开放程度、产业结构和城乡收入差距缩小与TFP的增长呈正相关关系。

中国交通运输业碳排放全要素生产率研究——基于Global Malmquist-Luenberger指数

运用Global Malmquist-Luenberger指数评价2009—2016年全国30个省级行政区交通运输业碳排放全要素生产率的变化情况,基于泰尔指数和变异系数分析其区域差异及形成原因,并结合GML指数的分解指数探讨影响全要素生产率变化的因素。结果表明,研究期间中部与西部地区交通运输业碳排放全要素生产率呈现下降趋势,并导致全国全要素生产率总体水平降低;全国全要素生产率变化的区域差异主要来源于四大经济区域内部差异,且西部和东北地区内部差异的贡献率较大;虽然影响全要素生产率变化的主要因素存在差异,但各地区全要素生产率的进步均受到技术发展的限制。

Dynamic Prediction Method of Production Logistics Bottleneck Based on Bottleneck Index

In modern manufacturing pattern, there are many uncertain factors in the modern manufacturing process, such as changes of product attribute, changes of manufacturing resources＇ state, and so on, which cause production logistics bottleneck frequently shift, and make decisions of production planning and control based on formed bottleneck deviated from practical production process. Considering these factors, present researches mainly apply afterwards control to optimize production process to passively adapt to bottleneck changes If the direction of bottleneck shifting can be accurately forecasted, the transition from afterwards control of chasing bottleneck to beforehand control can be realized. Therefore, aiming at the phenomenon of production logistics bottleneck shifting under uncertain manufacturing circumstances, this paper starts off with dynamic property of capability and requirement and then builds the concepts of bottleneck degree and bottleneck index to describe dynamic bottleneck characteristic of production unit; taken production capability, production load and quality assurance capability into consideration, mathematical model of bottleneck index is established to measure bottleneck degree accurately, consequently, quantitative research on mechanism of production logistics shifting is achieved. Based on bottleneck index, the prediction model of production logistics bottleneck is founded to predict dynamic change of bottleneck accurately. Finally, an example of forecasting and monitoring the production logistics bottleneck in one manufacturing shop is given to testify the validation and practicability of the prediction method.