Be productive or face decline. On the sources and determinants of output growth in Italian manufacturing firms

This article investigates the sources and determinants of output growth of Italian manufacturing firms. Applying stochastic frontier techniques, we decompose output growth into factor accumulation and TFP growth for the period 1998–2003. TFP growth is further decomposed into technological change, efficiency change and scale effects. Two key results emerge from the analysis. After confirming that both input accumulation and TFP growth are important in explaining output growth, we show that efficiency change (technological catch-up) is the most significant component of TFP growth in explaining output growth distribution. Furthermore, using a specific model of the asymmetric error component, we find that R&D spillovers, banking efficiency and public infrastructures have statistically significant and economically relevant effects on technological catch-up.     

中国城市科技人才集聚促进了全要素生产率增长吗——来自285个地级市的经验研究

基于2005—2018年中国内地285个地级市数据，对城市科技人才集聚与全要素生产率（简称“TFP”）进行测度分析，实证考察科技人才集聚对TFP的影响。结果表明：①城市科技人才集聚与TFP空间分异特征显著，但二者具有较强的时空一致性，即科技人才集聚特征显著的城市，其TFP也相对稳定；②城市科技人才集聚对TFP的影响呈倒U型，但研究期内大多数城市仍处于集聚效应占主导阶段,科技人才集聚通过提升城市技术进步水平促进TFP增长，而科技人才集聚对技术效率的影响呈倒U型；③不同类型城市科技人才集聚对其TFP影响的异质性显著，且适宜集聚区间也存在差异。省会城市及一、二线城市等优势特征显著的城市所能承受的科技人才集聚规模上限更高，有利于通过释放集聚红利促进TFP增长，而非省会城市、三线及以下城市等则拐点值较低。     

GAUGING THE SOURCES OF GROWTH OF HIGH‐TECH AND LOW‐TECH INDUSTRIES: THE CASE OF KOREAN MANUFACTURING*

Literature argues that the source of growth for high‐tech industries emanates from technological progress, while that for low‐tech industries comes from technical efficiency improvement. Also, some empirical studies have shown that technological progress is often accompanied by deterioration in technical efficiency. The focus in this study is to discuss a methodology and test the above two hypotheses with regard to Korean manufacturing data from 1970 to 1997. The study found that the 2.5 per cent average annual rate of technological progress during this period was the major contributor to total factor productivity (TFP) growth in Korean manufacturing whereas technical efficiency grew by a modest 1.1 per cent per annum. The analysis also showed that technological progress was responsible for TFP growth in both high‐tech and low‐tech industries and that both technological progress and technical efficiency improvement co‐existed in the case of Korean manufacturing industries.     

Government subsidy and aggregate productivity dynamics: Evidence from China

Based on data for Chinese manufacturing firms from 1999 to 2007, this study explores the dynamic evolution of aggregate total factor productivity (TFP) from the perspective of firmsʼ entry and exit. It also quantifies how government subsidies influence the aggregate productivity growth. By decomposing aggregate productivity growth into components, including technological progress, reallocation, entry, and exit effects, we found that aggregate TFP growth in Chinese manufacturingfollows an upward trend during the sample period. This tendency originates from the contribution of technological progress, reallocation, and exit effects. Moreover, the effects of these four components on aggregate TFP growth of different industries, regions, and ownership types are different. Furthermore, technological progress, reallocation, and exit effects are important pathways for government subsidies to promote aggregate TFP growth in Chinese manufacturing.     

Why is TFP growth sectorally concentrated?

Research shows that total factor productivity (TFP) growth is weak in European countries. This is inter alia attributed to the fact that substantial TFP growth is limited to a few industries. Because TFP growth is typically understood as technological progress, it is concluded that technology diffusion between sectors in Europe is hampered. We use EU KLEMS data sets to decompose sectoral TFP for nine European countries by means of a Malmquist approach in order to identify potential sources besides technical progress. Applying Harberger diagrams, we describe the sectoral distribution of TFP growth, efficiency gains and losses, economies of scale and technological progress. The analysis reveals that technological progress is quite evenly distributed across sectors in most European countries. The wide scattering of TFP growth is explained by deviating efficiency developments and the unused economies of scale. We conclude that the technology transfer between sectors in most European countries seems to work. Therefore, Europe in general does not need a new technology policy, but a further integration of the markets and a reduction of national market entry barriers. This requires further unification of pan-European standards in fields like trade and crafts codes or consumer protection policies.     

中国服务业分行业生产率变迁及异质性考察

本文采用全国两次经济普查后的修订数据,引入"技术不会遗忘"假定,运用序列DEA-Malmquist生产率指数法测算了1990—2010年中国服务业细分行业的全要素生产率(TFP)、技术进步、纯技术效率与规模效率增长率。结果表明,中国服务业总体及细分行业的TFP均处于上升通道,在上世纪90年代,服务业TFP增长的主导因素是技术效率改进,进入21世纪后,则主要是技术进步提高,且技术效率改进已开始由以纯技术效率为主转向以规模效率为主,但服务业发展的粗放型特征仍然明显。同时,中国服务业TFP增长表现出了较大的行业异质性;与工业(制造业)行业对比,服务业TFP增长是滞后的。2010年与1991年相比,TFP及技术效率增长的行业间异质程度有所下降,而技术进步却有进一步拉大的迹象。可能的内在机制是现代信息技术对不同服务业企业资源配置的异质影响,以及中国服务业体制改革的渐进式道路。     

FDI和产业集聚对TFP增长影响的实证检验——基于上海制造业行业的数据

运用非参数的Malmquist生产率指数方法,测算了1998—2007年上海20个制造业行业的全要素生产率指数及其技术效率和技术进步的变化指数;用基于面板数据的计量回归模型对上海市制造业行业全要素生产率的影响因素进行了实证检验。得出以下结论:上海制造业行业全要素生产率的增长主要是由技术进步带来的,技术效率变化指数表现出负增长;外商直接投资对上海制造业企业没有明显的外溢效应,产业集聚对上海制造业行业的全要素生产率增长有显著的促进作用,出口贸易具有显著的阻碍作用,国有产权比重具有显著的反向作用。     

产业集聚、企业规模与全要素生产率增长——基于长三角制造业行业面板数据的分析

本文首先从理论上分析了产业集聚、企业规模对TFP增长的影响;其次,运用非参数的Malmquist生产率指数方法,测算了1998—2007年我国长三角地区两省一市(江苏、浙江、上海)20个制造业行业的全要素生产率增长及其技术效率和技术进步的变化;最后,用面板数据的计量回归模型对长三角两省一市制造业行业全要素生产率的影响因素进行了实证检验。得出以下结论:长三角地区两省一市制造业行业全要素生产率的增长主要是由技术进步带来的,而技术效率变化指数表现出负增长;产业集聚和企业规模对上海、江苏和浙江制造业行业TFP增长的作用显著,且产业集聚的作用大于企业规模的作用。     

Productivity growth patterns in US dairy products manufacturing plants

We analyse the productivity growth patterns in the US dairy products industry using the Census Bureau's plant-level data set. We decompose Total Factor Productivity (TFP) growth into the scale and technical change components and analyse variability of plants’ productivity by constructing transition matrices. We observe a cross-sectional dispersion in plant-level productivity growth in the industry. Even though the industry aggregate shows a small TFP growth rate ?0.3%, quartile rank analysis shows that while the lowest productivity quartile plants average 1.9% loss in productivity, the highest productivity quartile plants average 1.1% growth annually. Our results show considerable movements of plants in their productivity rank categories overall and across age groups, and we find that the scale effect contribution to TFP growth accounts for about 90% of TFP growth on average in the industry. These plants extract scale efficiencies over technological progress to fuel TFP growth. The youngest plants start with the lowest productivity growth at the initial time period, but they catch up older plants productivity, which present the highest average growth rate through years. This may indicate a ‘learning-by-doing’ process for the industry.     

金融发展与全要素生产率增长* ——基于中国省际面板数据的实证分析

本文以2000-2012年中国省际平衡面板数据为样本,从金融规模发展和金融效率发展两个维度衡量金融发展水平,实证检验金融发展与全要素生产率增长的联系以及中间渠道。研究结果发现,2000-2012年中国全要素生产率出现正增长且主要是由技术进步推动的;无论是从金融规模发展角度还是从金融效率发展角度去分析,都证实了金融发展显著地促进了全要素生产率的增长,金融效率发展的全要素生产率增长效应显著地高于金融发展规模的全要素生产率增长效应,且金融发展促进全要素生产率增长的中间渠道是技术进步效应而非技术效率增长效应;通过引入衡量金融发展缺陷程度指标（民间金融发展规模）,证实了中国金融发展体系效率低下。民间金融发展具有TFP增长效应,且民间金融发展TFP增长效应要显著地大于正规金融发展的TFP增长效应。     

Sources of output growth in Singapore's services sector

As services are an important engine of growth for Singapore, this paper attempts to empirically investigate the sources of output growth in this sector to shed light on the debate sparked off by Krugman (1994) on the miraculous or mythical growth of Singapore and the other newly industralizing Southeast Asian economies. This is done by using the stochastic production frontier model with panel data. Unlike existing studies which used the conventional growth accounting approach to decompose output growth into just input growth and total factor productivity (TFP) growth, this approach further decomposes TFP growth into technological progress and changes in technical efficiency.     

对外经济开放、区域市场整合与全要素生产率

本文在新增长理论的框架下,构建了一个对外经济开放和区域市场整合内生化全要素生产率的模型。在此基础上,利用中国1985—2008年的省际面板数据,采用工具变量两阶段最小二乘法(2SLS)实证检验了对外经济开放和区域市场整合对省际全要素生产率的影响。研究结果表明,对外经济开放和区域市场整合对中国省际全要素生产率都产生了显著的正向影响效应,而且二者存在替代关系。进一步的分析指出,在对外经济开放水平较高的沿海地区,区域市场整合对省际全要素生产率的影响效应较低,而在内陆地区则恰好相反。本文为理解中国省际全要素生产率的变化提供了新的视角,对后金融危机时代如何提升地区技术水平、转变经济增长方式也具有一定的启发意义。     

金融发展与全要素生产率增长:区域差异重要吗?——来自中国省级面板数据的经验证据

基于1997-2008年中国省级面板数据以及分全国层面、沿海地区与内陆地区三个样本对金融发展与全要素生产率增长的联系及其中间渠道重新进行检验,结果发现:中国金融发展的全要素生产率增长效应与区域因素有关;中国金融发展促进全要素生产率增长的中间渠道是技术进步效应而非技术效率增长效应。这意味着,加快中国金融体系改革,从而推动金融发展对于经济增长质量的提高是非常重要的。     

Embodiment, productivity, and the age distribution of capital

An important theme in modern research on productivity has been that technological progress may be embodied in capital in the sense that traditional measures of TFP growth reflect unmeasured improvements in the quality of capital inputs as well as pure disembodied technological progress. It is commonly believed that an implication of this embodiment hypothesis is that there should be a negative relationship between measured TFP and the age of the measured capital stock. This paper presents empirical evidence which suggests that an increase in the age of the capital stock is actually associated with higher TFP growth. This surprising result may be due to the presence of a mis-measurement normally overlooked in this literature: With mis-measured improvements in capital quality, the usual depreciation rates used to construct empirical capital stocks are incorrect for growth accounting. This effect dominates the usual average age effect.     

Financial deregulation and productivity growth in banking sector: empirical evidence from Bangladesh

This article examines the effects of regulatory reform on productivity growth in the Bangladesh banking industry. We use a unique balanced panel dataset comprising bank-level annual data from the early deregulation year (1984) to the most recent available period (2012) from major commercial banks in Bangladesh. Applying the Färe-Primont index, the paper provides estimates of productivity growth and identifies sources of total factor productivity (TFP) change. Empirical results show the sample banks have experienced positive TFP change after the financial deregulation. On average, TFP growth is higher in private banks than their public sector counterparts in the post-reform period. In addition, the decomposition analysis shows technological progress is the main driver of productivity change. Similar results are obtained by using the stochastic frontier analysis (SFA). Thus, empirical results remain robust irrespective of the methodology used. The regression analysis finds a positive technical change in the first stage of the reform program, i.e. during the transition period, as leading banks employ advanced technology to compete with potential new entrants. The result also shows that the banking industry still remains concentrated within the state-owned banks.     

On modeling the determinants of TFP growth

We investigate the determinants of TFP growth of Italian manufacturing firms. Using stochastic frontier techniques, we consider three approaches for taking into account the influence of external factors, i.e., the determinants or drivers of growth. First, in our novel approach external factors may influence the technological progress, that is the shift of the frontier. To model this possible unexplored effect, we extend the standard time trend model to make it a function of the external factors. Then, following more standard approaches, we model external factors as either influencing the distance from the frontier, i.e., inefficiency, or the shape of the technology. Using a sample of manufacturing firms in 1998–2003, we find that technological investments and spillovers, human capital and regional banking inefficiency all have a significant effect on TFP growth.     

我国西部地区经济增长中的技术因素分析

利用1978—2010年我国西部地区12省市的数据,测算了我国西部地区的资本、劳动力和TFP对经济增长的贡献率。结果显示:当期我国西部地区的经济增长主要源于资本投入;但是,由于资本对经济增长的贡献太大,因此TFP呈相对平稳下降趋势,TFP对经济增长的作用还不是很明显。指出:若2010—2020年西部地区TFP对经济增长的贡献率为37.1%,则西部地区能实现以技术进步带来可持续增长。最后提出西部地区实现经济可持续增长的政策建议。     

出口贸易、FDI与中国农产品加工业全要素生产率——基于行业面板数据的实证分析

通过利用中国农产品加工业12个子行业的面板数据,首先运用DEA的Malmquist方法测算了中国农产品加工业全要素生产率及其分解,之后重点考察了包括出口贸易和外商直接投资在内的各因素对全要素生产率的影响。研究结果发现:在2001-2011年期间,中国农产品加工业全要素生产率整体处于上升趋势,支持了中国农产品加工业全要素生产率平均增长率上升的动力主要来自于技术进步;出口贸易的发展对农产品加工业全要素生产率和技术效率的提高作用并不明显;外商直接投资所带来的技术溢出对于提高中国农产品加工业的全要素生产率有较好的促进作用。根据研究结论,文章得到的政策启示是:提升农产品加工业出口贸易对全要素生产率的正向作用;强化外商直接投资所带来的技术溢出效应;提高农产品加工业人力资本水平;改善农产品加工业RD投入结构和市场环境;改进农产品加工业的规模经济效应。     

Does productivity growth lower inflation in Korea?

We investigate Granger causality between productivity growth and inflation in Korea using quarterly data for the period 1985Q1–2002Q4. Our results indicate unidirectional Granger causality from productivity growth to inflation. In light of such causality, we estimate the effect of productivity and other variables on productivity. According to our regression results, a 1% increase in labour and Total Factor Productivity (TFP) reduces Consumer Price Index (CPI) inflation by 0.07–0.08% and 0.37–0.44%, respectively. Our results also suggest that the productivity-inflation nexus became stronger in Korea since the Asian financial crisis, and that this was largely due to structural reform and technological progress.     

Singapore's Manufacturing Sector's TFP Growth: A Decomposition Analysis

Singapore has been criticized recently for experiencing insignificant total factor productivity (TFP) growth. This paper examines whether this criticism is valid in the context of the manufacturing sector of Singapore. Using new data and the stochastic production frontier approach, TFP growth is decomposed into technological progress and changes in technical efficiency. While the results could not reject the hypothesis that Singapore's output growth is mostly input-driven, they show that, despite technological progress, technical inefficiency is the cause for the low and declining TFP growth in the manufacturing sector.J. Comp. Econom., December 2000, 28(4), pp. 828–839. The University of Queensland; Research School of Pacific and Asian Studies, The Australian National University.