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.     

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.     

创新补贴、研发投入与技术突破:机制与路径

关键核心技术缺失是当前中国实现经济高质量发展的紧要问题,而关键核心技术突破始于企业研发投入环节。本文基于对中国科技发展相关特征事实的梳理,以研发投入有效性不足为问题切入点,针对生产过程技术构建研发决策博弈模型,探讨激励企业研发投入的最优创新补贴方式,并以2010—2020年认定为高新技术企业的上市公司为样本进行实证检验。研究结果显示：一方面,创新补贴能够通过激励企业增加研发投入而促进实现技术突破;另一方面,虽然研发补贴和税收优惠与企业研发投入之间均存在显著的正反馈机制,但其激励效果会因企业规模和所有制不同而产生差异。如果补贴方式和补贴对象不能精准匹配,则其产生的创新补贴激励空隙可能会阻碍关键核心技术突破,需要政府引导企业通过“三重投资”实现技术突破。     

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 the impact of R&;D on Productivity from a Econometric Time Series Perspective

In this paper we argue that the standard sequential reduction approach to modelling dynamic relationships may be sub-optimal when long lag lengths are required and especially when the intermediate lags may be less important. A flexible model search approach is adopted using the insights of Bayesian Model probabilities, and new information criteria based on forecasting performance. This approach is facilitated by exploiting Genetic Algorithms. Using data on U.K. and U.S. agriculture the bivariate time series relationship between R&D expenditure and productivity is analysed. Long lags are found in the relationship between R&D expenditures and productivity in the U.K. and in the U.S. which remain undiscovered when using the orthodox approach. This finding is of particular importance in the debate on the optimal level of public R&D funding.JEL Classification: C22, C51, Q16     

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.     

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.     

科研单位R＆D支出来源、用途与其专利申请量之关系研究

本文实证分析了科研单住R＆D支出来源、用途与其专利申请产出之间的关系,结果表明专利申请产出与R＆D支出来源与用途有关,促进科研单位来源于政府资金的R＆D支出的专利产出,将在很大程度上提高我国专利申请量,也是充分利用我国科研单住专利申请产出能力的关键.研究结果还表明,基础研究同样可以产出专利申请,这也为我国应提高基础研究投入提供了一个理由.     

R&D and productivity: A broad cross-section cross-country look

The empirical literature on R&D and productivity has shown that there is indeed a positive influence of R&D investment on output growth. However, the exact relation depends to a large extent on the approach chosen (i.e., functional form). Because most studies concentrate on a limited number of countries or sectors and use their own specific methodology, comparison is difficult. This paper aims at providing a broad overview of cross-country and cross-sector differences in the relation between (direct) R&D and output growth, using a common methodology, so that comparison is easier. The functional form used is a translog production function, which is applied to data for 15 manufacturing sectors and 9 principal OECD countries.     

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.     

国际贸易、技术进步和中国工业行业的生产率增长

内生增长理论认为技术进步是经济增长最为重要的助推力,推动技术进步的力量是对研发的投资和国际贸易的发展。随着经济贸易与信息技术的飞速发展,社会对国际贸易、技术进步的关注程度日渐提升。通过深入分析国际贸易与工业行业生产率之间的关系,可以有针对性地应用有效手段对国际贸易进行调整,使其可以继续带动技术的进步并促进工业行业生产率的提升。基于此,论文探究了我国国际贸易、技术进步与工业行业生产率增长的关系,阐述了国际贸易、技术进步对于工业行业生产率的真实影响。     

How does R&D intensity influence firm explorativeness? Evidence of R&D active firms in four advanced countries

Despite R&D is seen as a starting point of innovation, firms usually confront a trade-off in allocating limited R&D resources to either exploratory or exploitative activities. Relative to the latter, the former produces a more distinctive variation from the prior knowledge base and helps the firm tap into new opportunity. Given the increasing importance of firm explorativeness in the fast changing environments, the influence of R&D investment on firm explorativeness is not yet conclusive in the literature, not to mention whether the increased R&D investment induces firms to become more explorative. This study aims to generate insight into how and when firm explorativeness is determined by their R&D intensity. As a notion of the use of knowledge new to the organization, firm explorativeness is treated as the degree of using knowledge new to the organization in the pursuit of innovation. Based on a panel data of 1267 firm-year observations in four advanced countries during 1999–2003, the results reveal that a higher level of R&D intensity makes firms more exploitative and less explorative. Nevertheless, the negative relationship between R&D intensity and firm explorativeness is found to be alleviated in the presence of technological opportunity or financial slack. The configurational model sheds further light on the combined and relative weight of two moderators.     

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’.      

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.     

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.     

Self-organization of R&D search in complex technology spaces

We extend an earlier model of innovation dynamics based on percolation by adding endogenous R&D search by economically motivated firms. The {0, 1} seeding of the technology lattice is now replaced by draws from a lognormal distribution for technology ‘difficulty’. Firms are rewarded for successful innovations by increases in their R&D budget. We compare two regimes. In the first, firms are fixed in a region of technology space. In the second, they can change their location by myopically comparing progress in their local neighborhoods and probabilistically moving to the region with the highest recent progress. We call this the moving or self-organizational regime (SO). The SO regime always outperforms the fixed one, but its performance is a complex function of the ‘rationality’ of firm search (in terms of search radius and speed of movement). The clustering of firms in the SO regime grows rapidly and then fluctuates in a complex way around a high value that increases with the search radius. We also investigate the size distributions of the innovations generated in each regime. In the fixed one, the distribution is approximately lognormal and certainly not fat tailed. In the SO regime, the distributions are radically different. They are much more highly right skewed and show scaling over at least 2 decades with a slope around one, for a wide range of parameter settings. Thus we argue that firm self-organization leads to self-organized criticality. The online version of the original article can be found under doi:.     

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.     

Introduction: Input–Output Analysis of Interindustry R&D Spillovers

As an introduction to this special issue on intersectoral R&D spillovers, I shall first explain what these spillovers are and how economists try to estimate them. I shall then describe the seven papers selected for this issue from the expanding literature on R&D spillovers, summarize their major results and suggest further avenues of research in this area.     

研发支出会计处理方式综合比较研究

随着企业自主研发活动战略地位的加强,研发支出的会计处理方式也日益引起关注。本文综合国内外有关研究成果,系统探讨了现行及建议的各种处理方式及其优缺点,以期揭示研发支出会计处理方式的发展趋势及应注意的问题。     

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.