Has Productivity Contributed to China's Growth?

This paper applies an extended Solow approach to examine the role of productivity in China's economic growth. The extended Solow approach allows the decomposition of output growth into factor contributions, technological progress and efficiency change. It is found that total factor productivity (TFP) has on average contributed to 13.5 percent of China's economic growth in the past two decades. This contribution is mainly due to technological progress which tends to accelerate over time. However, during 1982–97 efficiency change due to catch–up has been very volatile, reflecting the uncertainties associated with economic reforms and transition in China.     

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.     

Parametric Approaches to Productivity Measurement: A Comparison among Alternative Models

This paper deals with modeling total factor productivity (TFP) growth in a flexible manner using panel data. Several competing parametric models are used to explore whether there are any similarities in the estimates of TFP growth and technical change among these models. Using a primal approach, we decompose TFP growth into different components. The models are then used to measure productivity and technical change in the Swedish cement industry. In general, the results are found to be model dependent and often conflicting, although much less so for returns to scale and overall productivity growth.
JEL classification: O 30; C 33     

1978-2007年我国畜牧业全要素生产率及其影响因素研究

本文运用扩展的索洛模型和C-D生产函数测算了1978—2007年我国畜牧业全要素生产率(TFP)及其影响因素。分析结果表明,1978—2007年我国畜牧业TFP的年均增长率为4.71%;从总体上看,我国畜牧业生产处于规模报酬递增阶段,且畜牧业政策、劳动者质量、规模化程度和科技投入量是影响我国畜牧业TFP变动的主要因素。     

Productivity,technical efficiency and technological change in French agriculture during 2002-2015: a Färe-Primont index decomposition using group frontiers and meta-frontier

The objective of the article is to assess productivity change in French agriculture during 2002–2015; namely, total factor productivity (TFP) change and its components – technological change and efficiency change. For this, we use the Färe-Primont index which verifies the multiplicatively completeness property and is also transitive, allowing for multi-temporal and -lateral comparisons. We investigate the extent of heterogeneity within each type of farming sub-sample in terms of TFP change, with the help of the Herfindahl-Hirschman index (HHI). In addition, to compare the technologies among the five types of farming considered, we extend our analysis to the meta-frontier framework. Results indicate that during 2002–2015, all farms experienced TFP progress. The smallest average increase was experienced by the dairy farms and the largest by the field crop farms and the beef farms. The latter had the strongest technological progress but a deterioration in efficiency, while the opposite was found for field crop farms. The analysis of HHI reveals that sheep or goat farms are the most homogenous in terms of the direction of TFP change experienced over the period 2002–2015. The meta-frontier analysis shows that field crop farms’ technology is the most productive of all the types of farming.     

Technological progress and scientific indicators: a panel data analysis

Total factor productivity (TFP) is generally interpreted to be a proxy for technological advancement. In this paper, we use stochastic frontier analysis to decompose the growth in TFP into three components: technological progress, scale effect and change in technical efficiency. Then, we conduct a comprehensive panel data analysis using the technological progress component of the TFP growth and several scientific and technological indicators using data from 160 countries over the period from 1960 to 2009. Our results generally show that the technological progress component of the TFP growth properly reflects certain dimensions of actual scientific and technological progress. However, we also find that this result is somewhat sensitive to different econometric specifications and assumptions.     

中国商业银行全要素生产率分析——基于三阶段Malmquist指数模型

本文运用三阶段Malmquist指数对我国商业银行2004—2008年的全要素生产率变化情况进行研究。研究结果表明,环境变量对我国商业银行的投入变量有显著的影响,传统的Malmquist方法高估了我国商业银行全要素生产率变化指数、技术进步变化指数以及技术效率变化指数;我国银行业在2004—2008年间出现了全要素生产率的改进,这主要源于技术进步的作用;金融危机的爆发使得我国银行业整体生产率大幅度下降,但对国有商业银行的影响要小于对股份制商业银行的影响。     

TFP growth and its determinants: a model averaging approach

Total Factor Productivity (TFP) accounts for a sizable proportion of the income differences across countries. Two challenges remain to researchers aiming to explain these differences: on the one hand, TFP growth is hard to measure empirically; on the other hand, model uncertainty hampers consensus on its key determinants. This paper combines a non-parametric measure of TFP growth with Bayesian model averaging techniques in order to address both issues. Our empirical findings suggest that the most robust TFP growth determinants are time-invariant unobserved heterogeneity and trade openness. We also investigate the main determinants of two TFP components: efficiency change (i.e., catching up) and technological progress.     

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。     

科技金融发展能否促进R&D资本存量与主要素生产率

基于我国2005-2015年省级面板数据，利用固定效应、系统GMM和面板门槛回归模型,研究了各省科技金融发展水平对R&D资本存量和全要素生产率(TFP)的影响。实证结果显示：科技金融对R&D资本存量和TFP具有正向促进作用，且存在门槛效应，当科技金融指数高于门槛值时，科技金融对R&D资本存量和TFP的促进作用更强。基于《十三五国家科技创新规划》的政策指示，进一步研究发现：发展互联网金融有利于科技金融促进R&D资本存量和TFP；传统金融越发达，科技金融对R&D资本存量和TFP的促进作用越大；民间资本越发达，科技金融对R&D资本存量和TFP的促进作用越大；建设多层次资本市场，有利于科技金融促进R&D资本存量和TFP；加强专利保护，有利于科技金融促进R&D资本存量和TFP。     

人力资本与中国区域农业全要素生产率增长——基于DEA视角的实证分析

文章在考虑人力资本要素和技术非效率的前提下,使用非参数的DEA曼奎斯特生产率指数方法,对1988-2006年中国区域农业全要素生产率增长进行估计和测算,通过将其分解为技术进步、纯技术效率变化和规模效率变化三部分,来寻找农业TFP增长的源泉.实证表明,1988-2006年中国农业TFP增长较为显著,大致可以分为四个阶段,其对农业增长的贡献基本上是顺周期的,各个省区的TFP增长差异性则较为明显.从其内部构成来看,TFP增长主要由技术进步贡献,技术效率改善的作用则很有限.另外,是否考虑人力资本要素对农业增长的作用,会对TFP的估计产生较大影响.文章最终认为,应努力通过制度创新来消除农业技术扩散的各种制度性障碍,实现农业技术进步和技术效率增进共同推动农业TFP增长.     

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。     

Network technologies,communication externalities and total factor productivity

The main aim of this paper is to determine the factors which enhance or temper firms’ private incentives to use communications technologies that are characterised by network externalities and allow firms to influence their rate of technological change or total factor productivity (TFP). As regards the impact of the network effect on TFP, we find that when the externality parameter is low, a slightly negative effect appears, but this effect is reversed when the externality is higher. This relationship is valid regardless of the number of firms. Our result is particularly interesting because it offers a possible explanation for the Solow productivity paradox. We conclude that, in addition to the degree of network effects, market structure, consumer preferences and the number of users also have a very important influence on TFP and technological change.     

International trade,technological change and wage inequality in the UK economy

This paper examines the joint impact of international trade and technological change on UK wages across different skill groups. International trade is measured as changes in product prices and technological change as total factor productivity (TFP) growth. We take account of a multi-sector and multi-factor of production economy and use mandated wage methodology in order to create an well-balanced approach in terms of theoretical and empirical cohesion. We use data from the EU KLEMS database and analyse the impact of both product price changes and TFP changes of 11 UK manufacturing sectors on factor rewards of high-, medium- and low-skilled workers. Results show that real wages of skill groups are significantly driven by the sector bias of price change and TFP growth of several sectors of production. Furthermore, we estimate the share of the three different skill groups on added value for each year from 1970 to 2005. The shares indicate structural change in the UK economy. Results show a structural change owing to decreasing shares of low-skilled workers and increasing shares of medium-skilled and high-skilled workers over the years.     

Productivity growth in British manufacturing: spatial variation in the role of scale economies,technological growth and industrial structure

This paper investigates the role of scale economies, technological growth and industrial structure in creating spatial variation in manufacturing labour and Total Factor (TFP) productivity in Britain. Separate estimates of a translog specification are presented for British manufacturing firms located in defined areas of the country over the period 1994–1998. The results show that TFP change due to scale economies and technological growth has been of much less important in influencing the output growth of manufacturing firms than input growth or industrial structure. Regarding the components of TFP, technological growth has been the dominant force at play. The analysis of average labour productivity identifies shifts to other factors of production and industrial structure as being the main determinants of change, scale economies appear to have had a marginal role. The results identify spatial patterns indicating that more favourable locational effects arise for firms in areas adjacent to large urban centres, rather than for those located within cities, on the extreme periphery of the urban hinterland, or in rural areas and smaller towns.     

Spatial analysis of change trend and influencing factors of total factor productivity in China’s regional construction industry

Total factor productivity (TFP) is a measure of long-term economic growth and a comprehensive industry-level productivity measure. There are large gaps in China’s regional construction industry development due to unbalanced regional economy. Based on TFP measurement, this article puts forward a two-hierarchical analysis framework with coefficient of variation, Moran scatterplot and coefficient of convergence to analyse change trend of the construction industry TFP in three major regions in terms of spatial diversity, correlation and convergence. Then, the geographically weighted regression model is utilized to explore the influencing mechanism on the TFP. The results indicate the differences of the regional construction industry TFP are enlarging. There is obvious spatial correlation and heterogeneity in the regional TFP without a relatively stable space pattern. The TFP also exhibits convergence effects among three major regions. The construction industry productivity in all regions is significantly affected by economic environment, industrial organization structure and technological level. Industrial organization structure exerts the various influences on the productivity in different regions.     

Is utility additive? The case of alcohol

By using the quantile regressions of earnings equation, we find that the educational wage premium is higher in industries with rapid technological change than in industries with slower technological change at every decile in the distribution of wage residuals. The wage premium associated with the technological change is mostly explained by the returns to workers' unobserved heterogeneities, which are correlated with education, rather than the rents of high-tech industries.     

R&D, TECHNOLOGICAL PROGRESS AND EFFICIENCY CHANGE IN INDUSTRIAL ACTIVITIES

The objective of this paper is to estimate total factor productivity growth (TFP) in an international and sectoral setting using two alternative approaches based on the estimation of parametric stochastic frontiers and non-parametric production frontiers (DEA). The TFP is decomposed into two components, technological progress and efficiency change, that can also be interpreted as the results of the innovation and catching-up process, respectively. Finally their relationship is tested with a set of potential explanatory variables that includes R&D expenditures, international competition, and structural characteristics. It appears that the distinction between technological and efficiency performances does matter and must be taken into account in the design of industrial policy.     

AN ATTEMPT TO EXPLAIN DIFFERENCES IN ECONOMIC GROWTH: A STOCHASTIC FRONTIER APPROACH

Total factor productivity (TFP), factor accumulation, and growth are analysed for a panel of 40 countries in 2001–11. TFP growth and technical inefficiency are estimated using a stochastic frontier model. Environmental variables are found to have an important role in explaining differences in inefficiency across countries. Over 2001–11, the general improvement in technical efficiency of countries is almost outweighed by technological regress. Results indicate that differences in factor accumulation between OECD and emerging economies are more important than differences in TFP change to explain differences in economic growth. Results also indicate negative and significant random shocks for the OECD countries.     

THE IMPACT OF DOMESTIC AND FOREIGN COMPETITION ON SECTORAL GROWTH: A CROSS‐COUNTRY ANALYSIS

This paper examines the impact of competition on the total factor productivity (TFP) of 21 manufacturing sectors in eighteen OECD countries over the period of time 1990–2006. We assume that the source of TFP growth can be either domestic or foreign innovation or technology transfer from the technological frontier. Trade openness, R&D, and human capital can have two effects: a direct effect on TFP (e.g., through innovation) and an indirect effect depending on the productivity gap between a given country and the technological frontier. We find that tougher domestic competition is always associated with higher sectoral productivity. Both import and export penetrations are positively associated with an increase of TFP. However, the channels through which higher TFP is materialized are different: export penetration works through level effect, while import penetration acts mainly when conditional on the level of technological development. The economical magnitude of the effect is not trivial.