Issues in Assessing the Effect of Interindustry R&D Spillovers

This paper aims to clarify three issues concerning the weighting methodol ogy generally used to evaluate interindustry R&D spillovers. These issues concern the likely nature of the spillovers estimated through different types of supporting matrices; the similarity between input–output (IO), technology flows and technological proximity matrices; and the relevance of the assumption that a single matrix can be used for different countries. Data analyses of weighting components show that technology flows matrices are in an intermediate position between IO matrices and technological proximity matrices, but closer to the former. The various IO matrices, as well as the three technological proximity matrices, are very similar to each other. The panel data estimates of the effect of different types of interindustry R&D spillovers on industrial productivity growth in the G7 countries reject the hypotheses that a technology flows matrix can be approximated by an IO matrix and that a single IO matrix can be usedfor different countries. By transitivity, the procedure that comprises using a single technology flow for several countries is not reliable. The international comparison shows that each country benefits from different types of R&D externality. In Japan and, to a lesser extent, in the US, the rate of return to direct R&D is very high and is likely to compensate for relatively weak interindustry R&D spillover effects. In the five other industrialized countries, the reverse observation is true: strong social rates of return to R&D counterbal ance the poor performances of direct R&D.     

Technology Flows Between Industries: Identification and Productivity Effects

This paper investigates whether the Yale Technology Concordance (YTC) succeeds in identzbing technology flows between sectors. As a test, total factor productivity (TFP)-R&D regressions based on the YTC matrix are compared with regressions using technology flow data constructed fram input–output matrices and randomly created interindusty linkages. Because results based on the YTC do not dzffer markedly from the other estimates, one cannot easily infer @om the empirical evidence whether the YTC matrix appropriately captures interindusty technology flows or not.     

Certified and uncertified skills and productivity growth performance: Cross-country evidence at industry level

We analyse the relationship between human capital and productivity growth using a five-country multi-industry dataset together with a measure of human capital which accounts for both certified skills (educational qualifications) and uncertified skills acquired through on-the-job training and experience. We find evidence of positive human capital effects on growth in average labour productivity, particularly when using our composite human capital measure. We also find some tentative evidence that multi-factor productivity (MFP) growth is positively related to the use of high-skilled labour. However, externalities of this kind are largely confined to industries which make intensive use of university graduates.     

Impact of R&D and Technology Diffusion on Productivity Growth: Empirical Evidence for 10 OECD Countries

This paper examines the empirical evidence on the impact of performed R&D and of R&D embodied in intermediate and capital goods on productivity performance in 10 major OECD countries over the last two decades. To quantify intersectoral and international technology flows, industry-level embodied R&D variables were constructed from an input–output (IO) R&D embodiment model. The productivity variables used are discrete Divisia growth indexes of total factor productivity (TFP), which were estimated from an IO growth accounting model. The results from pooled regressions indicate that the rates of return of the R&D variables were positively significant and increasing in the 1980s. In particular, embodied R&D is an important source for TFP growth in services, indicating very high social returns of the flows of capital-embodied technology into this sector. Moreover, the information and communi-cation technology (ICT) cluster of industries played a major role in the generation and cquisition of new technologies at the international level.     

行业间生产率联动对中国工业生产率增长的影响——引入经济距离矩阵的空间GMM估计

本文把反映行业间生产率联动的购买距离矩阵和销售距离矩阵引入空间自回归模型,研究行业间生产率联动对我国工业生产率增长的影响。为了克服引入社会经济距离矩阵带来的异方差和矩阵的行标准化问题,本文采用空间GMM法进行模型的估计。结果表明,行业生产率联动对我国工业生产率增长具有显著的正影响,并且在资源密集型、劳动密集型和资本密集型工业行业中,行业间生产率联动对工业生产率增长的影响相对于其他因素的影响更为稳健。此外,由销售距离矩阵所体现的联动作用效果整体上大于购买距离矩阵体现的相关效果。     

Measuring the Impact of Direct and Indirect R&D on the Productivity Growth of Industries: Using the Yale Technology Concordance

This paper investigates the impact of direct and indirect R&D on the productivity growth of 30 French industries during the period 1978–92. The main aim of this paper is to assess the appropriateness of the Yale Technology Concordance (YTC) as a proxy for indirect R&D flows. We compare the effect on productivity growth of the Yale proxy with the traditional proxy based on goods input–output flows, and assess their suitability for different groups of industries. Results indicate that the indirect YTC proxy performs slightly better than the traditional proxy, as a result of superior performance in the high-tech and service sectors in particular.     

Productivity and Growth in UK Industries: An Intangible Investment Approach*

This article calculates some facts for the ‘knowledge economy’. Using new data, first we document UK intangible investment and find that (i) this is greater than tangible investment by £37bn in 2008; (ii) R&D is 11% of total intangible investment, software 15%, and training and organizational capital 22% each; (iii) the most intangible‐intensive industries are manufacturing and financial services. Next, we measure the contribution of intangible capital to growth for 2000–08. We find that intangible capital accounts for 23% of labour productivity growth and treating intangibles as investment lowers total factor productivity growth in the 2000s by 24% (R&D lowers it by 3%).     

中国经济增长的动力转换与政策选择

研究目标：探究经济增长动因结构及转换趋势。研究方法：基于中国1980～2014年三次产业的时间序列数据,构造结构指数生产函数,采取指数分析与对数分析相结合的方法进行实证研究。研究发现：2008年以来全要素生产率贡献缩减是经济增长大幅减速的最主要因素;要素规模增长率下降与产出弹性缩减的双重挤压导致资本和劳动力规模贡献下滑;资本和劳动生产率增长双减速是造成全要素生产率大幅下降的主导因素;全要素生产率增长动力从以产业要素生产率的提升为主转向以产业之间要素配置结构的优化为主。研究创新：从三次产业的要素规模和效率进行考察,三个层次层层推进,为经济增长动力及其变迁轨迹分析创造更加广阔的拓展空间。研究价值：揭示了中国经济增长变迁的动因结构以及最新转换趋势,为旨在推动国民经济又快又好发展的政策设计提供了新的科学决策参考。     

Inter-industry technology flows in the US food-processing industries

The study examines the origins of technology important to improving productivity in the food-processing industries. Technology flows were measured both by patents in patent classes closely identified with six food industries, and by a sample of significant food-processing innovations. These data are consistent with the hypothesis that interindustry technology flows are the most significant determinant of productivity improvements in the food industries. These findings solve the enigma that the food-processing industries have enjoyed rapid improvements in productivity despite making very modest investments in research and development.     

Information technology and U.S. productivity growth: evidence from a prototype industry production account

The rapid productivity growth in the US during the Information Age, prior to the dot-com bust in 2000, and the large contribution of the IT producing sector, is well known. Less known are the sources of the surprisingly rapid TFP growth during the slow growth period after 2000. We construct an account of US economic growth by aggregating over detailed industries using a new data set based on the NAICS classification. We find that, post 2000, TFP originating from the IT-Producing sector decelerated relative to the IT boom, but still accounted for 40% of aggregate productivity growth. This deceleration was counterbalanced by the contribution from IT-Using sectors, which buoyed aggregate TFP growth to almost the same rate as the 1995–2000 period. For aggregate GDP, the contributions to the growth rate of 2.8% during 2000–2007 were: capital input (1.7% points), labor input (0.4) and TFP (0.7).     

影响中国城市增长的因素:地级及以上城市的实证检验

论文以国内外相关城市增长理论为基础,构建了分析中国城市增长的系统模型,并利用206个城市1990年与2005年的社会经济统计数据进行了实证研究.研究结果表明:(1)中国城市的经济增长主要是由劳动生产率提高而非人口规模增长推动的;(2)政府财政支出和城市人力资本积累是目前中国城市经济增长的主要驱动力;(3)人力资本积累并没有在工资增长上得到体现;(4)城市公共设施和环境的改善引致了城市人口增长,但对城市经济发展却没有明显的作用.在以上研究结果基础上,论文提出了保持城市可持续发展的一些政策建议.     

Matrices with dominant diagonal blocks and economic theory

In this paper we shall define matrices with quasi-strictly-dominant diagonal blocks or quasi-dominant diagonal blocks on the basis of general matrix norms including the spectral norm. Several theorems on such matrices are derived and a simple numerical example and economic models are considered to apply our theorems.     

Interindustry R&D Spillovers for Electrical and Electronic Products: The Canadian Case

This paper estimates the effects of interindustry R&D spillovers on the cost and production structure for 10 Canadian manufacturing industries. Because of their high-tech nature and productivity performance, spillovers from electrical and electronic products are distinguished from other spillover sources. Generally, spillovers from electrical and electronic products generate cost reductions and render production processes for Canadian manufacturing industries more capital intensive (i.e. either more physical or R&D capital intensive). Social rates of return for R&D capital are calculated for all 10 industries. The social rates are 5–11 times greater than are the private rates. Indeed, the social rates are high for all the industries. This implies that the electrical and electronic products industry is an important interindustry spillover source but, like other industries, a major spillover-using industry.     

A Generalized Input-Output Multiplier Calculus for Australia

A static, generalized input-output framework for calculating simple multipliers is presented for Australian data. In this framework, capital investment and imports are internalized into domestic inter-industrial intermediate demand, non-square matrices are introduced in order to enable the inclusion of finer detail commodity data, and matrices in both monetary and physical units are employed. A range of labour and energy multipliers are calculated, referring to total output, final demand, final consumption, basic values, producers' prices, purchasers' prices, commodities and industries. Uncertainties of multipliers are assessed in detail, using Monte Carlo simulations.     

Intangible Flow Theory

The intangible flow theory explains that flows of economic material elements (such as physical goods; or cash) are consummated by human related intangible flows (such as work flows; service flows; information flows; or communicational flows) that cannot be precisely appraised at an actual or approximate value, and have properties precluding them from being classified as assets or capitals. Thus, although mathematical/quantitative research methodologies are very relevant for science, they are insufficient to study economy and society. Due to its prejudice against non‐mathematical/quantitative scientific reasoning, neoclassical economics could not be technologically prepared to reach the intangible flow dynamics of economic phenomena. Furthermore, the neoclassical solution to call people human capital or assets, besides being ethically very questionable, offers performative non‐scientific metaphors that intervene in the production of the reality they claim to represent; and sabotages the study of well delimited research questions by scientific approaches outside the realm of neoclassical economics.     

APPLYING SOCIAL NETWORK ANALYSIS TO INPUT–OUTPUT BASED INNOVATION MATRICES: AN ILLUSTRATIVE APPLICATION TO SIX OECD TECHNOLOGICAL SYSTEMS FOR THE MIDDLE 1990s

The paper discusses, illustrates and possibly contributes to overcoming two methodological problems that emerge in applying Social Network Analysis (SNA) to the study of IO-based innovation flows matrices. The first has to do with the scale-effects these matrices suffer from. The second refers to the need of dichotomising the matrices. Through an illustrative application to six OECD countries in the mid-1990s, the paper shows that, as for the former problem, different relativisation procedures can be, and have been, used, which either tend to alter the actual meaning of standard SNA indicators, or do not properly take into account the actual composition of countries' final demand. As for the latter problem, the paper shows that the choice of discrete cut-offs is extremely sensitive, as comparative results actually change along the continuum of the matrices values. In order to overcome the scale problem, a new relativisation procedure is put forward that measures innovation flows embodied in a unit value basket of final demand and thus properly retains all the information provided by the original matrix of intersectoral innovation (embodied) flows. In addressing the problem of dichotomisation, the paper suggests, as a second best, to work with density distributions that can make the choice of discrete cut-off values less arbitrary.     

The growth of information workers in the US economy, 1950–2000: the role of technological change,computerization, and structural change

Using data from the decennial US Censuses of 1950, 1960, 1970, 1980, 1990, and 2000, I construct matrices of employment by 267 occupations and 64 industries and then aggregate the occupations into four categories: (i) knowledge producers; (ii) data processors; (iii) service workers; and (iv) goods-processing workers. I find that information workers (the sum of the first two categories) increased from 37% of the workforce in 1950 to 59% in 2000. Then, using an input–output decomposition analysis, I find that the growth in information workers was driven not by a shift in tastes toward information-intensive goods and services (as measured by the composition of final demand) but rather by a roughly equal combination of the substitution of information workers for goods and service workers within the structure of production of industries and the unbalanced growth effect (from differential rates of industry productivity growth). Finally, on the basis of regression analysis, I find that R&D expenditures and computer investment are positively associated with the growth in knowledge workers but negatively associated with the growth of data workers.     

Productivity Growth,Human Capital and Technology Spillovers: Nonparametric Evidence for EU Regions

This paper assesses the strength of productivity spillovers nonparametrically in a data set of 12 industries and 231 NUTS2 regions in 17 European Union member countries between 1992 and 2006. It devotes particular attention to measuring the catching up through spillovers depending on the technology gap of a unit to the industry leader and the local human capital endowment. We find evidence of a nonlinear relationship between the technology gap to the leader as well as human capital and growth in logs. Spillovers are smallest for units with a medium‐high technology gap to the leader, especially for regions where human capital endowments are low.     

WHAT DRIVES CAPITAL FLOWS TO EMERGING MARKETS? A SURVEY OF THE EMPIRICAL LITERATURE

This paper reviews the rapidly growing empirical literature on the drivers of capital flows to emerging markets. The empirical evidence is structured based on the recognition that the drivers of capital flows vary over time and across different types of capital flows. The drivers are classified using the traditional distinction between ‘push’ and ‘pull’ drivers, which continues to serve as a useful framework. Push factors like global risk aversion and external interest rates are found to matter most for portfolio debt and equity flows, but somewhat less for banking flows. Pull factors such as domestic output growth, asset returns and country risk matter for all three capital flows components, but most for banking flows.     

Stock markets,banks and the sources of economic growth in low and high income countries

This paper studies the effects of stock markets and banks on the sources of economic growth, productivity and capital accumulation, using a large cross country panel that includes high- and low-income countries. Results show that, in low-income countries, banks have a sizable positive effect on capital accumulation. We find that stock markets, however, have not contributed to capital accumulation or productivity growth in these countries. Given the emphasis that has been placed in developing equity markets in developing countries, these findings are somewhat surprising. Conversely, in high-income countries, stock markets are found to have sizable positive effects on both productivity and capital growth, while banks only affect capital accumulation.