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.     

Introduction: Invention Input–Output Analysis

The papers in this issue are directed towards the development of invention input–output (I(IO)) coefficients. They discuss the procedures for creating I(IO) coefficients using the Yale Technology Concordance, which assigns patented inventions to the industry of manufacture and sector of use, utilizing the International Patent Class system. Tests of reliability of the I(Io) coefficients and their use in economic studies are reported.     

Interindustry Technology Flows and Productivity in Finnish Manufacturing

The paper examines the importance of interindustry technology flows in finnish manufacturing in the 1980s and early 1990s. An attempt is made to distinguish between embodied technology flows and spillovers, so clarifying the spillover concept.Embodied technology covers intermediate goods and capital equipment. The embodied technology data that have been used are partly based on input—output analysis, while the spillover estimates presented are based on measures of technological distance based on the industry-specific distributions of R&D expenditures. Econometric analysis of the effects of the various technology inputs on total factor productivity implies that technology embodied in foreign machinery, domestic spillovers and, to some extent, the firms' own R&D have been the most important technology sources on average.     

Industrial Productivity Growth Linkages Between OECD Countries, 1970–90

Technology ‘spillovers’ are increasingly being recognized as sources of productivity growth. International ‘convergence’ in productivity levels has also been noted in recent studies. This paper reports a study of international total factor productivity (TFP) growth for 11 industrial sectors in seven OECD countries. Spillover variables are defined based on interindusty and international invention input–output (I(IO)) weights. These variables are tested against import-weighted variables. The study concludes that I(IO)-weighted R&D ‘spill-ins’ are important determinants of TFP growth and that convergence is dependent on domestic RBD.     

Innovation and Invention in Canada

This paper compares innovation survey data with invention data as recorded by patents (and, therefore, the basis of the Yale Technology Concordance), presenting input–output tables for both data sets. We describe and compare the intersec-toral flows of technology from the industry of manufacture (IOM) to the sector of use (SOU); compare patent-to-innovation ratios by industry; and present correlations between innovation, invention and R&D by industy. One significant conclusion is that, while innovation and invention data are highly correlated in the IOM, they diverge on the SOU, especially in certain key industries that we identify.     

Application of the Yale Technology Concordance to the Construction of International Spillover Variables for India

Although there is increased interest in the role of international technology spillovers, empirical studies have been hampered by a host of measurement problems. This paper reviews recent attempts to address two of these problems. First, there are differing degrees of transferability of technology from one region to another. Second, both embodied and disembodied technology are transferred, and these different modes of transfer have distinct implications for both behavior and policy. To deal with the first measurement problem, the Yale Technology Concordance (YTC)—a matrix that maps patents into industries of manufacture and sectors of use—was used to construct indices of relevance of foreign technology to India. To deal with the second measurement problem, the YTC was again used to construct pools of embodied and disembodied international technology. After describing the variable construction, the paper highlights the performance of these variables in equations that predict Indian firms' R&D, technology purchases and output.     

Estimating Regional Variations of R&D Effects on Productivity Growth by Entropy Econometrics

Abstract

In this paper we adopt an entropy econometrics-based estimator to study regional variations in regression coefficients and apply it to analyse productivity growths generated by R&D activities at a regional level. Considering the possible effects of the region's own R&D stock as well as the spillovers produced in other regions, the paper proposes the use of an entropy-based technique to estimate these effects for a specific location. Depending on the degree of heterogeneity of the set of regions analysed, it is possible that some of these regions present characteristics that enable them to more easily convert R&D efforts (generated in the region itself or obtained from other regions by R&D spillovers) into productivity gains, whereas in other regions the effect of (direct or spillover generated) R&D activities may be irrelevant. We illustrate this idea with an empirical application for Spanish regions.

RÉSUMÉ Dans la présente communication, nous adoptons un estimateur d'entropie à base économétrique pour l’étude de variations régionales des coefficients de régression et leur application pour l'analyse de d'augmentations de la productivité produites par des activités de recherche et développement à l’échelon régional. En se penchant sur les effets possibles du stock de recherches et développement propre à la région, ainsi que les retombées produites dans d'autres régions, la communication propose l'emploi d'une technique à base d'entropie pour effectuer une évaluation de ces effets pour un lieu spécifique. En fonction du degré d'hétérogénéité du groupe de régions analysé, il est possible que ces régions présentent des caractéristiques leur permettant de convertir plus facilement des interventions de recherche et développement (R&D) (générées dans cette même région, ou obtenues d'autres régions par retombées de R&D) en gains de productivité, alors que dans d'autres régions, l'effet (direct ou par retombée) d'activités de R&D pourra n'avoir aucune pertinence. Nous illustrons cette idée avec une application empirique pour des régions d'Espagne.

EXTRACTO En este estudio adoptamos un estimador basado en máxima entropía para estudiar las variaciones regionales en coeficientes de regresión, y lo aplicamos al análisis de los crecimientos de productividad generados por actividades de I+D a nivel regional. Considerando los posibles efectos del stock de I+D propio de la región, así como los spillovers producidos en otras regiones, el estudio propone el uso de una técnica basada en entropía para estimar estos efectos en relación con una ubicación específica. Dependiendo del grado de heterogeneidad del conjunto de regiones analizadas, es posible que algunas de estas regiones presenten características que les permitan convertir más fácilmente los esfuerzos de I+D (generados en la región misma u obtenidos de otras regiones a través de spillovers de I+D) en ganancias de productividad, mientras que en otras regiones el efecto de las actividades de I+D (directas o generadas de spillovers) podrían ser irrelevantes. Ilustramos esta idea con una aplicación empírica para regiones españolas.

摘要:

本文中, 我们采用基于熵计量经济学的估计器研究回归系数的区域变化, 并用它分析地域级R&D活动带来的生产率增长。考虑到区域自身R&D储备和其他区域的人才流入可能带来影响, 本文提出一种熵方法估计这些因素对某个特定区域的影响。根据所分析区域集的异质程度, 其中有些区域可能会表现出一些特征, 使其更容易将R&D能力 (该区域自己产生或者从其他区域流入)转化为生产收益, 而另外一些区域R&D活动的影响 (直接或者流入)与生产收益无关。我们以对西班牙地区的实验应用为例证明了这一论点。     

Measuring Intersectoral Technology Spillovers: Estimates from the European and US Patent Office Databases

This paper presents several new methods for measuring intersectoral knowledge spillovers, and applies these methods in an analysis of productivity growth in manufacturing for a cross-country, cross-sectional sample for the 1980s. It is argued that existing methods of measuring such intersectoral knowledge spillovers are mostly aimed at measuring so-called crent spillovers'. The methods developed here are aimed at measuring knowledge spillovers—an additional aspect of the spillover process. The empirical analysis shows that there are indeed differences between these two types of spillover measure.     

Assigning Patents to Industries: Tests of the Yale Technology Concordance

We describe a method to predict patent counts disaggregated by industry, using available data on patenting by technology field. This method—the Yale Technology Concordance (YTC)—exploits a data set of patents that have been individually assigned by the Canadian Patent Office to both an industry and a technology field. The procedure for predicting patents by industry is developed as a statistical model so that the standard errors of the predictions can be estimated. The YTC is tested on several subsets of Canadian patents by comparing out-of-sample predictions with industry assignments made by the Canadian Patent Office. We find that the predictions of patents by industry are quite accurate for the subset of patents form US inventors. The prediction errors are much greater for the subset of patents granted or published after 1989. This suggests that the relationship between the technology fields and industries has shifted in a way that the procedure does not capture. Nonetheless, predictions from the YTC do appear to give a reasonably accurate picture of the pattern of patenting by industry.     

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.     

Contributions and Channels of Interindustry R&D Spillovers: An Estimation for Japanese High-tech Industries

This paper estimates the contributions of R&D spillovers to four high-tech industries in Japan—general machinery, electrical machinery, transportation machinery and chemicals—by estimating the trans-log cost and share functions that include the R&D stock variables of own and spillover-source industries. The candidates for spillover- source industries are selected on the basis of large R&D flow or R&D proximity. The R&D flow measures the spillover embodied in purchased intermediate goods using input–output coefficients. The R&D proximity measures the extent of similarity between a pair of industries of the distribution of R&D expenditures across research fields, and is expected to show the likelihood of spillover at the R&D stage. The results suggest that electrical machinery benefited from R&D in the chemical industry, through the purchase of intermediate goods, whereas general machinery and transportation machinery benefited from R&D in the metal products industry, through R&D proximity. There was no evidence of the chemical industry benefiting from R&D spillovers. These results clearly imply that the contributions and the channels of R&D spillovers are diverse, casting doubt on earlier studies that used weighted sums of R&D expenditures (or their stocks) of other industries as aggregate spillover variables.     

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.     

Spillovers,Linkages and Technical Change

Using US input–output data for the period 1958–87, I find strong evidence that industry total factor productivity (TFP) growth is significantly related to the TFP performance of the supplying sectors, with an elasticity of almost 60%. R&D intensity is also found to be a significant determinant of industry TFP growth, with an estimated return of about 10–13% and the return to embodied R&D is estimated at 43%. Direct productivity spillovers, from the technological progress made by supplying sectors, appear to be more important than spillovers from the R&D performed by suppliers. They also play a key role in explaining changes in manufacturing TFP growth over time. Changes in the contribution made by direct productivity spillovers to TFP growth account for almost half of the slowdown in TFP growth in manufacturing from 1958–67 to 1967–77, and for 20% of the TFP growth recovery in this sector from 1967–77 to 1977–87. Changes in R&D intensity and embodied R&D are relatively unimportant in explaining movements in manufacturing TFP growth over these three periods.     

Measuring Intersectoral Spillovers: French Evidence

In this paper, we measure the effect of internal R&D and various spillover concepts on productivity growth, using a database for France that covers the period 1978–92. Three spillover concepts are distinguished: rent spillovers related to investment goods; rent spillovers related to intermediate goods; pure knowledge spillovers. When production is measured by gross output, all three spillover concepts yield positive and statistically significant coefficients. Each concept has a measurable effect on technological progress at the sectoral level.     

MEASURING INTERSECTORAL KNOWLEDGE SPILLOVERS: AN APPLICATION OF SENSITIVITY ANALYSIS TO ITALY

R&D spillovers are unanimously considered as one of the main driving forces of technical change, innovation and economic growth. This paper aims at measuring interindustry R&D spillovers. We apply an ‘uncertainty-sensitivity analysis’ to the Italian input–output table of intermediate goods split into 31 economic sectors for the year 2000. The value added of using this methodology is the opportunity of distinguishing between spillover effects induced by productive linkages (the Leontief forward multipliers) and those activated by R&D investments, capturing the uncertain and non-linear nature of the relations between spillovers and factors affecting them.     

Technological Opportunity and Productivity of R&D Activities

Economists have managed to find a positive impact of R&D efforts on productivity. However, the empirical results of their studies have not explained the observed sectoral differences in this important impact. With due reference to three global industries, namely, chemical, computer, and electrical/electronic, the objective of this study is to evaluate the impact of technological opportunity on the productivity of R&D activities. Technological opportunity refers to the ease of achievement of innovations and technical improvements, which could be jointly represented by the intensities of knowledge spillovers, inter-firm research overlap and scope of research. In this study, the degree of technological opportunity is quantified by patent statistics. The empirical findings confirm a positive relationship between technological opportunity and the productivity of R&D effort, and the estimated rate of return falls within the range as reported by past studies.     

Government Consumption and Industrial Productivity: Scale and Compositional Effects

Within a production function framework in which government spending produces public goods which enter firms production functions, empirical tests using time series data spanning eleven countries and thirty industries find both the scale and the composition of government consumption spending to affect the level and the rate of growth of total factor productivity at the industry level.Jel Classification: H50, D24     

中国高技术产业的全要素生产率及产业比较

基于2001～2007年中国5个高技术产业的细分行业的面板数据,运用Malmquist指数构建一个三投入三产出的模型,分别测算了高技术产业及其细分行业的全要素生产率。结果显示,5个细分行业全要素生产率的增长率差异较大,而且整个高技术产业的全要素生产率的增长率不稳定,主要原因是技术进步因素发生波动。     

Knowledge Flows,Patent Citations and the Impact of Science on Technology

Technological innovation depends on knowledge developed by scientific research. The number of citations made in patents to the scientific literature has been suggested as an indicator of this process of transfer of knowledge from science to technology. We provide an intersectoral insight into this indicator, by breaking down patent citations into a sector-to-sector matrix of knowledge flows. We then propose a method to analyze this matrix and construct various indicators of science intensity of sectors, and the pervasiveness of knowledge flows. Our results indicate that the traditional measure of the number of citations to science literature per patent captures important aspects of intersectoral knowledge flows, but that other aspects are not captured. In particular, we show that high science intensity implies that sectors are net suppliers of knowledge in the economic sector, but that science intensity does not say much about pervasiveness of either knowledge use or knowledge supply by sectors. We argue that these results are related to the specific and specialized nature of knowledge.     

Trade and product innovations as sources for productivity increases: an empirical analysis

Increases in total factor productivity (TFP) are commonly associated with technological innovations measured by the stock of R&D. Empirical evidence seems to corroborate this relationship. However, in trading countries like The Netherlands, productivity increases, even in industry, can also be the result of innovations in the way transactions are managed. These innovations reduce transaction costs and exploit the welfare gains from (further) international division of labour. Such innovations are only partly included in R&D data. Consequently there is not much attention for these ‘trade innovations’—as we label them—in policy. In an empirical analysis this paper compares the influence of trade innovations with the influence of the stock of R&D on TFP in The Netherlands. The regression results show that in this country trade innovations are as important for TFP as technological innovations which directly affect the efficiency of production, which we label ‘product innovations’.