全球价值链嵌入能否提升中国工业的低碳全要素生产率?

中国的全球分工参与对本国的经济与环境都产生了巨大的影响。文章基于2000～2015年中国33个工业行业的面板数据,采用投入产出模型和动态EBM-Malmquist指数分别测算了33个行业的全球价值链(GVC)嵌入程度和低碳全要素生产率(TFP),然后采用固定效应模型回归分析了GVC嵌入对中国工业低碳TFP的内在传导机制及其影响因素。结果表明:中国工业低碳全要素生产率整体呈现增长趋势,而全球价值链嵌入程度整体略有下降;全球价值链嵌入显著促进了中国工业低碳全要素生产率的增长,其内在传导路径为规模效率、环境改善效率与技术进步,而非技术效率;产业结构调整、环境规制及外商直接投资促进了低碳TFP增长,而能源结构、所有制结构对低碳TFP增长表现为阻碍作用,研发投入对低碳TFP未产生显著影响。     

高新技术产业各行业全要素生产率及其贡献率的比较研究

本文应用C-D生产函数和索洛经济增长模型测算的北京高新技术产业不同行业的全要素生产率(TFP)及其贡献率的结果表明:五大行业的TFP及其增长率并不均衡,其中TFP最高的是新能源,最低的是生物医药行业;增长率最快和最慢的行业则反之;而由技术进步贡献率指标反映的经济增长方式显示电子信息和新材料两个行业依然是粗放型增长.不同行业应依据不同的技术发展状态采取不同的策略,从而全面提高新技术产业的经济增长质量.     

中国区域物流产业技术进步及其影响因素研究

本文应用SFA模型评价我国区域物流业整体技术效率和全要素生产率,得出以下结论:我国物流产业TFP增长呈现震荡上升的趋势,其中东部地区TFP增长率相对较高,物流产业全要素生产率增长出现了一定的收敛趋势。引起全要素生产率增长率变化的主要因素是技术进步率和技术效率变化率。区域的经济发展水平、区域的市场化程度以及港口物流有助于提高我国区域物流的全要素生产率。     

资源环境约束下的城市经济效率测度与差异研究——基于中部与长江经济带14市的比较

将资源和环境因素同时纳入效率研究框架中,运用SBM模型以及Malmquist指数方法测度了2006—2013年14个城市的经济效率、全要素生产率（TFP）,并将全要素生产率变动分解为技术效率和技术进步,实现了TFP增长的动态分解。研究结果表明,大多数城市存在效率改进空间;当考虑资源环境约束时,城市绿色TFP较低,技术进步是推动绿色TFP增长的主要源泉,而技术效率的作用并不明显。在生产效率的核算中,如果忽略资源环境因素的刚性约束,有可能导致经济增长效率被高估,由此得出的政策建议会带有一定的误导性。     

跨越中等收入陷阱中全要素生产率的作用及比较

文章探讨了全要素生产率在经济体跨越中等收入陷阱过程中的作用,实证研究了不同经济发展阶段下经济体实现TFP增长的路径差异。首先,借助面板有序Logit模型,证实了在经济体跨越中等收入陷阱的过程中TFP起到了关键性作用;其次,构建技术边界收敛模型,进一步探讨了处于不同收入阶段的经济体提升TFP的路径选择。实证研究发现:在低收入、中等收入发展阶段,经济体主要通过效率提升带来的赶超效应和技术进步效应提升TFP,而高收入经济体主要通过自主创新实现TFP增长;技术进步效应的差异将对中等收入经济体提升全要素生产率,进而跨越中等收入陷阱发挥关键作用;中等收入阶段是全要素生产率提升路径的转型阶段,亟需实现由外界驱动向自主创新驱动的转型,方能保证经济体真正进入高收入发展阶段。     

跨越中等收入陷阱中全要素生产率的作用及比较北大核心CSSCISSCI

文章探讨了全要素生产率在经济体跨越中等收入陷阱过程中的作用,实证研究了不同经济发展阶段下经济体实现TFP增长的路径差异。首先,借助面板有序Logit模型,证实了在经济体跨越中等收入陷阱的过程中TFP起到了关键性作用;其次,构建技术边界收敛模型,进一步探讨了处于不同收入阶段的经济体提升TFP的路径选择。实证研究发现:在低收入、中等收入发展阶段,经济体主要通过效率提升带来的赶超效应和技术进步效应提升TFP,而高收入经济体主要通过自主创新实现TFP增长;技术进步效应的差异将对中等收入经济体提升全要素生产率,进而跨越中等收入陷阱发挥关键作用;中等收入阶段是全要素生产率提升路径的转型阶段,亟需实现由外界驱动向自主创新驱动的转型,方能保证经济体真正进入高收入发展阶段。     

中国经济的高增长能否持续:基于企业生产率动态变化的分析

经济持续增长的基础是生产效率的提高。本文运用增长核算法(growth accounting)系统地研究了中国大中型工业企业1995—2002年37个两位数工业行业的全要素生产率(TFP)的增长趋势。研究发现:(1)1996～2002年工业增加值增长率平均为11.5％,而 TFP 的行业加权年均增长率为6.8%,且呈逐年上升的趋势,全要素生产率的增长逐渐成为经济增长的主要源泉,显示大中型工业的增长可以持续;(2)全要素生产率的提高与资本深化分不开,工业产出高速增长的同时,伴随着资本增长放缓及从业人数的绝对减少;(3)从行业分布来看,开放程度高、竞争程度高的行业的全要素生产率增长快,而高垄断、开放程度低的行业生产率增长慢,甚至出现下降的局面。     

中国工业的全要素生产率:1952-2005

本文利用柯布-道格拉斯(C-D)模型和加总的年度数据对1952-2005年中国工业的生产率表现进行了估算,分别从理论和方法上对C-D函数进行改进以回应学界之前对它的批评:首先,相应的经济假定使我们放松了新古典增长理论框架下一些严格的限制条件,例如竞争性市场行为、固定规模效应和希克斯中性技术进步;其次,本文中的TFP增长率还针对经济周期进行了调整;同时,本文还对大多数相关文献中存在的自相关问题进行了处理.文章的主要发现包括:(1)资本积累是1952-2005年中国工业经济快速发展的主要原因;(2)改革开放之后,全要素生产率对于经济增长有十分显著的作用;(3)20世纪80年代后期,随着中国日益融入世界经济体系的进程不断加快,TFP又开始大幅增长.     

我国总量生产函数的贝叶斯估计——基于动态随机一般均衡的视角

本文把生产要素利用率的微观行为引入企业生产,在动态随机一般均衡的框架下,利用贝叶斯方法估计了我国的总量生产函数,并研究了1978-2007年间的全要素生产率(TFP).结果表明:第一,在规模报酬不变假设下,劳动的产出弹性约为0.55,高于传统文献中的估计值;第二,通过将TFP分解为长期增长和短期波动两部分,我们发现:(1)资本积累和TFP是1978-2007年中国经济增长的主要动因,两者地位相同,总共解释了平均增长的87%;(2)忽略要素利用率的内生行为,会导致传统定义的TFP明显高估中性技术冲击对于经济波动的贡献.     

新疆经济增长因素的实证分析

本文运用索洛经济增长核算模型，对新疆经济增长因素进行了测算，以探索影响新疆经济增长的主导因素，得出以下结论：(1)新疆经济增长属于资本推动型，但是，综合要素生产率(TFP)已成为新疆经济增长的重要动因。(2)技术进步、经济结构变动、宏观制度变迁等是TFP提高的重要原因。并提出了推动新疆国民经济持续健康发展的几点对策。     

Total factor productivity growth for 12 Asian economies: The past and the future

This study examines the importance of TFP growth in the long-term past and future economic growth of 12 Asian economies. We analyze the pattern of past growth based on a calculation of TFP growth, investigate the TFP dynamics by estimations of a TFP growth model, decompose the factors affecting TFP growth, and offer long-term projections of TFP growth. The main findings are as follows. First, results suggest that the growth accounting paradigm has shifted in the recent decade toward a productivity-based growth paradigm. Second, the catch-up effect is the major source of TFP growth in past decades, and the human capital contribution to TFP growth is gradually rising in Hong Kong, Korea, Singapore, and Taiwan in the most recent decade but is stagnated or weakened for other Asian economies. Third, the results project strong TFP growth for the two subperiods of 2010–2020 and 2020–2030 and thus suggest that the productivity-based growth will continue in the future long-term growth of the Asian economies.     

Does the productivity J-curve exist in Japan?-Empirical studies based on the multiple q theory

Brynjolfsson, Rock, and Syverson (2021) argued that the standard TFP growth is low during an investment boom for new technology such as the IT revolution. As the new capital is operated and productivity improves, the shape of the movements in the standard productivity growth resembles a J-curve. However, when costs associated with investment for new technology are recognized as intangible investment - which is not counted in the conventional value added –, the revised TFP growth including these unmeasured intangibles show different movements from the standard TFP growth. Following Brynjolfsson, Rock, and Syverson (2021), we examine the gap between the standard TFP growth and the revised TFP growth. According to their theory, unmeasured intangibles are estimated by the gap between the shadow value and the price of investment goods. We obtain this shadow value of investment through an estimated parameter in each asset using listed firm-level data and revise the standard TFP growth rate. In the case of all industries, the standard TFP growth is overestimated in most years in the late 1990s and the 2000s, because the growth in intangible investment associated with measured investment is lower than measured capital accumulation rate. When we focus on the IT-intensive industries, we find the productivity J-curve in the late 1990s, at the early stage of the IT revolution, as indicated by Brynjolfsson, Rock and Syverson (2021).     

Total Factor Productivity of the Japanese Rice Industry

We calculate partial factor productivity and total factor productivity (TFP) indices for rice production using panel data across 42 Japanese prefectures from 1996 to 2006, and perform panel unit root tests of TFP convergence across prefectures. We find that during this period, the partial factor productivity growth rates for capital, land and materials stagnated at the aggregate national level, as did the TFP growth rate, despite a large increase in labor productivity. We also identify evidence of a convergence in TFP across Japanese prefectures.     

Process Versus Product Innovation: Do Consumption Data Contain Any Information?

In a model of endogenous growth in which product and process innovations are the joint outputs of an unspecified research program, we show that if quality growth is not captured by official price indices the usual isomorphism of product and process innovations breaks down. We derive and estimate a Euler equation for a representative consumer under the assumption of measurement error. Unobserved quality improvements account for at least half of growth, and real productivity growth in postwar United States was two to five times greater than measured total factor productivity (TFP) growth. We also find that at least 15% of the measured slowdown in TFP growth can be attributed to unobserved increases in the relative importance of product innovations.     

The effects of demographic changes on the real interest rate in Japan

What are the effects of demographic changes on the real interest rate in Japan? We present a dynamic general equilibrium model in which demographic changes are captured by exogenous changes in the ratio of workers to the total population. Our model predicts that a decline in this ratio in the process of population aging lowers the real interest rate; and the demographic impact on the real interest rate is amplified by a fall in land prices in the presence of collateral constraints. The model is simulated with the realized and forecasted changes in the working-age population ratio, the TFP growth, and government spending in Japan. Our results indicate that the TFP growth is the main source of variations in the real interest rate, but the demographic factor is also quantitatively important especially for its long-term movements.     

Call For Papers: The Eighth International Convention of the East Asian Economic Association

This paper provides empirical estimates of total factor productivity (TFP) trends in a sample of 17 APEC countries over the period 1975 to 1996. TFP growth is an important measure of an economy's performance and if measured correctly it can provide valuable guidance on issues related to the assessment of sustainable growth trends. We use the Malmquist index to measure TFP growth and decompose it into an efficiency change and a technical change component. This decomposition provides extra insight on assessing sustainable growth trends. The measurement technique itself is regarded as a significant improvement over previous conventional measures of TFP growth. The results are very interesting. Japan, Thailand and primarily Indonesia and Malaysia are identified as countries exhibiting on average negative TFP growth rates in the 1975-1990 period. In all these countries as well as in South Korea and Taiwan the main cause of low TFP growth is a poor (negative) efficiency record. The average TFP growth rate for Japan and Malaysia is positive in the 1975-1996 period but the efficiency change component remains negative. In all these countries the main contributor to labour productivity growth is capital accumulation. Unlike previous studies we find no evidence of a poor TFP growth performance for Singapore. Furthermore, we estimate that most of Singapore's labour productivity growth is driven by efficiency change. Estimates of rates of convergence towards the frontier economy that is estimated (not assumed as in other studies) to be the US, are also reported.     

An Application of the Extended Glass and McKillop Procedure for Computing TFP Growth to the Malaysian Rice Sector

The objective of the present study is three-fold: to employ an aggregated data to investigate the total factor productivity (TFP) growth of the Malaysian rice sector; to investigate the sources of the TFP growth; and, to examine and extend the Glass and McKillop procedure for computing TFP growth. To this end, we establish several procedures which make it possible for us to: (i) link the TFP analysis with the theory of production; (ii) disentangle the sources of TFP growth into scale and technological change effects; and (iii) apply, compute, examine and extend the Glass and McKillop procedure for computing TFP growth.The finding of the study is as follows. (i) Using the standard procedure forcomputing TFP growth it was found that the average TFP growth for Malaysian rice farming was 1.37%, of which the scale effect contributed 0.29% and the remaining 1.08% was due to the technological change effect. (ii) Using the extended Glass and McKillop procedure, however, it was found that the average TFP growth, the technological change effect and the scale effect were 3.48%, 3.19% and 0.29%, respectively. (iii) Comparing these two results, derived from two different procedures, we concluded that the difference in magnitude of the TFP growth was due to the two distinct procedures for computing the technological change effect per se.     

环境约束下地区工业生产率增长的异质性研究

采用SML指数法测算1998—2008年全国各地区环境约束下的工业TFP指数,进而采用PSTR模型探索工业TFP变化及地区差异的原因。实证分析表明,TFP增长已成为我国工业增长的重要驱动力,技术进步是工业TFP增长的源泉,相对效率的改善十分微弱,而近年来我国的环保努力和国际金融危机分别对工业TFP增长率形成了正向和反向的冲击。PSTR回归分析显示各地区环境约束下的工业TFP增长具有明确的异质性,多个解释变量对工业TFP增长的影响在模型的高、低体制下具有显著的差异。     

中国省域全要素生产率增长的空间邻居效应

区域TFP增长是区域经济研究的一个重要课题。以往的研究主要关注对外开放度、人力资本存量和制度变量对区域TFP增长的影响,很少有人关注空间邻居效应,即地理位置相邻的地区TFP增长对一个地区TFP增长的影响。本文基于中国28个省市1996—2005年间的面板数据,通过构造空间邻居变量,实证分析了中国地区间TFP增长的空间邻居效应。结果显示:一个地区TFP增长的21.3%可归因于相邻地区TFP增长的正向影响,即空间邻居效应十分显著。此结果对于地区之间有关经济政策的协同制定或建立经济联盟,均提供了可靠的依据和合理的建议。     

环境约束下长江流域主要城市全要素生产率研究

文章采用方向性距离函数和Malmquist-Luenberger生产率指数,对我国长江流域2003-2012年24个城市考虑环境因素和不考虑环境因素两种情形下的全要素生产率进行了测度。研究结果表明,考虑非期望产出时,技术无效率是长江流域主要城市的普遍现象,各城市之间投入产出效率差异大,但这种差异在逐渐缩小;长江流域城市全要素生产率不断增长,技术进步是其增长的主要源泉;多数城市技术效率明显恶化,成为阻碍长江流域城市绿色全要素生产率提高的主要原因;长江上游城市全要素生产率明显高于中下游城市;当考虑环境因素时,长江上、中游城市TFP增长幅度明显降低,下游城市开始出现"波特双赢"局面。