Productivity drivers of infrastructure companies: Network industries utilizing economies of scale in the digital era

What drives the productivity dynamics of infrastructure companies? Using a panel of firms in 14 countries, we study total factor productivity (TFP) enhancers of utility and network services companies. We find that moving TFP closer to the technological frontier drives productivity growth at higher speeds in Asian countries than in European countries. We also find that financial leverage exerts a positive effect on TFP growth for larger infrastructure firms and that more financially developed countries utilize economies of scale through better use of financial resources. Large utility and transportation companies display a higher rate of TFP growth, indicating that a competition policy to encourage M&As would be prudent for the utility/transportation sectors to maximize economies of scale. In contrast, we find diseconomies of scale for energy companies in some countries. Moreover, young network firms improve TFP growth faster than their peers in countries with fewer product market regulations. Therefore, policies should remove entry barriers while facilitating the departure of old and low-productivity firms from network markets. Finally, policymakers should offer well-targeted fiscal incentives for intangible investments to boost TFP because the accumulation of intangible assets such as digital technology promotes more scale economies through network effects.     

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.     

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.     

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.     

Productivity effects of environmental performance: evidence from TFP analysis on marketing cooperatives

The object of the present article is to offer a decomposition of productivity indices incorporating environmental changes. The model followed is an input oriented approach related to undesirable output (environmental performance attribute) in horticultural marketing cooperatives. This study is motivated by both the lack of analysis of environmental performance's effects on agribusiness productivity and the relevance of cooperative firms in the European agricultural model for attaining sustainability. For this purpose, bootstrapped envelopment analysis is applied and the best practice frontier obtained corresponds to decision making units showing the best environmental behaviour. The Malmquist total factor productivity (TFP) is decomposed into technological change, efficiency and environmental change. In the second stage, the correlations of these changes with other management variables of cooperatives are analysed. The indicators obtained, on one hand, advice about the nonseparable distance function estimations when the environmental factor is introduced. On the other hand, the results display a relevant increase in efficiency and environmental components for the period under study showing a high influence from labour qualification, environmental effort and spillover effect in the sector.     

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.     

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.     

Firms' Innovation,Public Financial Support,and Total Factor Productivity: The Case of Manufactures in Peru

Based upon an adjusted Crepon–Duguet–Mairesse (CDM) model, this paper analyzes the relationship between investment intensity, public financial support, innovation, and total factor productivity (TFP) for a sample of manufacturing firms of Peru with data obtained from the 2004 survey of science, technology, and innovation (STI) activities. The estimation of the model indicates that large firms are more likely to invest in STI activities and firms' size increases the probability of producing technological inovation (TI) and non‐technological innovation (NTI). STI firms' investment intensity and public financial support have also helped manufacturing firms to increase the probability of producing TI outcomes. Further, such support may have increased firms' investment on STI activities. The innovation effects on TFP, however, were statistically not clear or robust. Thus, whereas investment intensity did increase firms' TPF in low‐tech manufacturing firms, this is not the case for high‐tech firms. For this group of firms, relatively high capital–labor ratio and the availability of a high level of human capital seem to promote higher levels of TFP.     

What determines the productivity growth? Evidence from Chinese renewable energy firms by using Bayesian stochastic frontier approach

This paper examines the determinants of the total factor productivity (TFP) growth of Chinese renewable energy firms from 2011 to 2016, using a Bayesian stochastic frontier approach. Employing the “Bauer–Kumbhakar” decomposition method, the TFP growth is decomposed into the technology part and the market part. The empirical results reveal that the TFP improvement of Chinese renewable energy firms is mainly due to technical progress, followed by technical efficiency change. With regard to the market part, the misallocation of production factors has hindered the TFP growth. Our findings also indicate that only for large firms, the TFP growth can benefit from the scale economy effect. Compared with non‐state‐owned firms, state‐owned firms suffer much lower allocative efficiency.     

Services liberalization and productivity of manufacturing firms

Employing a unique database of Ukrainian firms in 2001–07, we use the external push for liberalization in the services sector as a source of exogenous variation to identify the effect of services liberalization on total factor productivity (TFP) of manufacturing firms. The results indicate that a standard deviation increase in services liberalization within a firm is associated with a 9.2 percent increase in TFP. The effect is stronger for firms with high productivity, bringing about a reallocation of resources within an industry. Industry‐level results show that the effect of reallocation on industry productivity is almost as strong as the within‐firm effect. The dynamic interaction of services liberalization and TFP through the investment channel reinforces the effect. The effect is robust to different estimation methods and to different sub‐samples of the data. In particular, it is more pronounced for domestic and small firms.     

E-commerce,R&D,and productivity: Firm-level evidence from Taiwan

This study investigates the impact of e-commerce and R&D on productivity, using a unique panel dataset obtained from Taiwanese manufacturing firms for the period from 1999 to 2002. We specifically consider the network externalities of e-commerce and employ the system generalized method of moment (GMM) technique to deal with the endogenous problem of e-commerce adoption. The empirical results show that both e-commerce and R&D capital have a positive influence on productivity, while R&D exhibits a larger productivity-enhancing effect. We also find a complementary relationship between e-commerce and R&D on enhancing productivity. Crucially, the inter-industry network externality of e-commerce significantly contributes to productivity.     

Use Of Information Network And Organizational Productivity: Firm-Level Evidence In Korea

This paper studies the relationship between the use of various information networks and organizational productivity in Korean firms. To this end, first. the current firm-level usage panems of information networks are explained in the following network categories: (1) LAN (Local Area Network). (2) inter- and intra-firm networks, (3) various types of inter-firm networks, and (4) the Internet and intranet, Second, by deriving TFP (Total Factor Roductivity) from the baseline production function, which augments lT stock into otherwise standard one, the impact of various information networks is investigated. The results show that LAN, the Intemet and intranet have significant impacts on fm-level TFP, while inter-firm network does not. Also, the productivity of firm using the Internet is 8.5 percent higher than the firms using only LAN, and the productivity of firms using intranet is 43.6 percent higher than the firms using just the Internet.     

中国商业银行业的全要素 生产率增长及其分解——基于24家银行面板数据的实证分析

本文收集了2003-2010年24家商业银行的非平衡面板数据,首先通过构建随机前沿生产模型,对中国银行业的技术效率进行测算,然后利用TFP分解模型对商业银行TFP增长的驱动因素及其演变过程进行了系统分析。研究发现,整体来说,中国银行业的全要素生产率在所有年份均实现了明显的增长。相对而言,国有大型商业银行在研究初期并没有显示出明显的优势,但随着时间的推移,其TFP增长率开始不断上升,并逐渐赶超中小型银行。通过对TFP增长率的分解计算,技术效率变化和要素配置效率变化对中国银行业TFP增长具有较强的拉动作用,技术进步的影响并不明显,而规模效率变化的负面作用最为显著。     

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。     

融资约束视角下的运营资本对中国企业全要素生产率的贡献*

金融危机后中国经济增长缓慢，产业和总需求分析框架失灵。本文从供给侧动力和非正规金融入手，研究中国企业全要素生产率与运营资本的关系。本文利用1999—2013年非上市企业的动态面板数据，采用系统GMM的方法进行回归分析，研究发现运营资本对中国企业的全要素生产率有显著的影响，而且这种影响是非线性的。但是，这种关系只在民营企业和外资企业中成立，对国有企业并不成立。本文进一步引入融资约束机制，论证了运营资本是中国非国有企业突破融资困境、促进企业全要素生产率提高的重要金融中介。       

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。     

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。     

THE IMPACT OF MANUFACTURING FIRMS’ USE OF ACADEMIC WORKERS ON THEIR PRODUCTIVITY LEVEL

We examine how firms’ productivity level, measured by the total factor productivity (TFP), is affected by their use of academic workers. A panel dataset of Norwegian manufacturing firms is used. Firms’ production level is shown to be negatively affected by their share of academic workers, but we find no clear relationship between this share and the TFP. If we account for the fact that there is an interaction between the share of academic workers and the capital stock, we find that this share has a non‐significant effect on the production level.     

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.     

Biofuels and Climate Change Mitigation: A CGE Analysis Incorporating Land-Use Change

We examine the impact of a “green network effect” in a market characterized by consumers’ environmental awareness and competition between firms in terms of both environmental quality and product prices. The unique aspect of this model comes from the assumption that an increase in the number of consumers of green (brown) product increases the satisfaction of each green (brown) consumer. We show that, paradoxically, when the network effect of a green product is higher than that of a brown product, this externality reduces product environmental quality and raises consumption of the green product. Conversely, when the network effect of the brown product is higher, the externality improves product environmental quality and raises consumption of the brown product. In both cases, the network effect does not affect the overall pollution level. The externality correction requires the use of three optimal fiscal policies: an ad valorem tax on products, an emission tax, and a subsidy or a tax on the green purchase. A second-best optimum can also be reached through the green taxation.