Productivity and R&D: an econometric evidence from Spanish firm-level data

This article analyses the relationship between productivity growth and R&D investments of Spanish manufacturing firms during the 1990s. The theoretical model is a version of the Cobb–Douglas production function in its growth rate form. The purpose is to estimate the rate of return to R&D expenditures. The econometric specification is a distributed lag model. The estimation applies the generalized method of moments method. The main empirical finding is that a positive and significant role is played by R&D expenditures on productivity growth. The rate of return to R&D expenditures is 26.598%.     

A contribution to the theory and empirics of Schumpeterian growth with worldwide interactions

This paper proposes an integrated theoretical and methodological framework characterized by technological interactions to explain growth processes from a Schumpeterian perspective. Global interdependence implied by international R&D spillovers needs to be taken into account in both the theoretical and empirical models. For this task, spatial econometrics is the appropriate tool. The econometric model we propose includes the neoclassical growth model as a particular case. We can therefore explicitly test the role of R&D investment in the long-run growth process against the Solow growth model. Finally, the properties of our spatial econometric specification allow the explicit evaluation of the impact of home and foreign R&D spillovers.     

What is the optimal rate of R&D investment to maximize productivity growth?

Governments in modern economies devote much policy attention to enhancing productivity and continue to emphasize its drivers such as investment in R&D. This paper analyzes the relationship between productivity growth and levels of R&D investments. The econometric analysis shows that more than 65 per cent of productivity growth variance is due to its dependence on gross domestic expenditure on R&D expressed as percentage of GDP (GERD). Economic analysis shows that productivity growth = f(GERD) is a concave function downwards due to diminishing returns to research investments. In addition, the research shows that the range of GERD between 2.3 per cent and 2.6 per cent maximizes the long-run impact on productivity growth and it is the key to sustained productivity and technology improvements that are becoming more and more necessary to modern economic growth.     

The contribution of the publicly‐funded R&D capital to productivity growth and an application to the Greek food and beverages industry

This paper follows the dual‐cost function methodology and develops a theoretical specification that assesses the contribution of public R&D capital to the productivity growth. The empirical application focuses on the Greek food and beverages industry. For this purpose it employs a micro‐aggregated annual data set over the period 1976–2002. The regression analysis shows that publicly‐funded R&D capital is a productive input as 8.7% and 7.3% of the total factor productivity growth in the food industry and in the beverages industry respectively is attributed to the publicly‐funded R&D capital. The relationship between publicly‐funded R&D and privately‐purchased inputs is also examined.     

International technology spillovers,human capital and productivity linkages: evidence from the industrial sector

The paper estimates an empirical model that is consistent with a variety of Research and Development (R&D)-driven models of growth where technology is transmitted via trade to other industries, both domestically and internationally, by being embodied in differentiated intermediate goods. The evidence is based on data from 21 manufacturing industries in six European Union countries for the period 1980–1997. The contribution of the paper lies in showing how by including human capital in the model and employing suitable econometric procedures the magnitude of R&D spillovers reported in the existing literature can be affected, while pointing to a major role of human capital in economic growth process.     

Estimating the effect of technological factors from samples affected by collinearity: a data-weighted entropy approach

Measuring the effect of technological activities on productivity growth is an issue that attracted much attention in recent works on empirical econometric studies. Specifically, in the field of regional economics, several attempts have been made in order to quantify the contribution of R&D to labor productivity growth at a regional scale, considering both the internal R&D and the effects obtained by geographical spillovers. The results obtained, however, are characterized by a huge variability and in many cases there is no empirical evidence of positive contributions of R&D activities to productivity growth. Our argument is that this can be a consequence of dealing with samples’ affect by a high level of collinearity. This paper proposes the use of the data-weighted prior (DWP) estimator suggested by Golan (J Econom 101:165–193, 2001). The main advantage of this estimator is that it discriminates between relevant and irrelevant regressors better than other estimators when dealing with highly collinear samples. We evaluate the performance of the DWP estimator by Monte Carlo simulations and illustrate how it works by means of a real-world example.     

R&D-expenditure in an endogenous growth model

The aim of this paper is to analyze the role that aggregate R&D-expenditure plays in economic growth. We introduce a technology of innovation based on expenditure that generates endogenous sustainable growth in absence of any scale effect. This R&D-model permits us to study the effects of some fiscal policies. In particular, we analyze how subsidies to R&D-investment and physical capital accumulation affect the long-run growth rate. For the empirical cross-country analysis we directly derive a structural econometric model.     

International,intersectoral, or unobservable? Measuring R&D spillovers under weak and strong cross-sectional dependence

In the theoretical and empirical growth literature, private and social returns to R&D have been identified as the key drivers of productivity gains and economic development. However, recently the debate on the relative importance of private vis-à-vis social returns has been reinforced by contributions in two emerging fields of the applied econometric literature, namely spatial panel modeling and the common factor approach, which stress the role of cross-sectional dependence as a source for a potential estimation bias linked to the measurement of returns to R&D. In this paper, we account for these methodical advances when estimating sectoral knowledge production functions for OECD countries under weak and strong cross-sectional dependence. By doing so, we are able to uncover technology- and trade-related R&D spillover channels associated with social returns to R&D, while effectively controlling for other types of productivity spillovers and latent macroeconomic shocks. Our results highlight the role played by international-intersectoral R&D spillovers for the social rate of return to R&D, while we get limited evidence for private returns to R&D once cross-sectional dependence is properly accounted for.     

Human capital accumulation in R&D-based growth models

This paper develops a model that reproduces the essential aspects of the recent ICT-based economy using the framework of endogenous growth theory in which a central role is played by human capital accumulation. In particular, it considers a multi-sectoral growth model in discrete time with infinite horizon, endogenous growth, embodied technological progress, horizontal differentiation and “lab-equipment” specification of R&D, and with human capital accumulation (represented by the fact that households devote a fraction of their time to schooling), in order to take into account the crucial role of the latter when new technologies are present. In this model it is possible to obtain some important results, both analytically and through simulations, either in the case of constant productivity of schooling and in the case in which this productivity is a function of technological progress. The first conclusion is that the productivity of schooling affects the long run growth of the economy, contrary to the productivities of the other sectors, hence in this model human capital accumulation is the true engine of growth. It is then possible to study the reaction of the economy to different types of shocks, and to compare the results with the empirical evidence. The conclusion is that the model is able to reproduce such evidence, suggesting that the interaction between ICT and human capital is one of the drivers of the recent economic performance.     

World Productivity Growth: A Model Averaging Approach

Policy makers and the economic researchers who provide them estimates of economic activity need to have an informative and scientifically‐based method to develop a consensus estimate for the most basic of the productivity measures, total factor productivity (TFP) growth. We discuss methods to combine the various estimates based on different empirical specifications that model and estimate productivity growth. We also discuss the various econometric approaches used in the profession to estimate productivity growth. Our focus is on world TFP growth.     

The influences of different R&D types on productivity growth in OECD countries

Productivity has become an important concern for the sustainable development and growth of a country. Countries, such as those in the Organization for Economic Cooperation Development (OECD), that actively innovate and conduct Research and Development (R&D) activities always have high productivity growth, with research to date examining the positive influences of R&D on productivity. R&D activities are classified into three types: basic research, applied research and experimental development. To test the different influences of the different R&D types, panel data from 23 OECD countries for the period 1996–2010 have been constructed and the Data Envelopment Analysis method is used to measure and decompose productivity growth. Moreover, based on Mansfield's [“Basic Research and Productivity Increase in Manufacturing.” The American Economic Review 70: 863–873] model, the influences of each R&D type on productivity growth are tested. The empirical tests show that R&D investments in experimental development and applied research have a positive effect on productivity growth in the immediate period; basic research influences productivity growth with a lengthier lag, even up to three periods.     

R&D and productivity growth: Evidence from the UK

Although the econometric evaluation of R&D has attracted wide interest in many countries, it has not attracted much in the UK. The main objective of this paper is to fill this void, i.e., to estimate the impact of R&D on productivity growth of the UK manufacturing sector. However, there are some additional objectives. Firstly, we estimate the impact of R&D on productivity growth of large and small firms and we discuss a number of theoretical arguments regarding the role of firm size. Secondly, given that the technological infrastructure influences the innovative capacity of a firm, we compare the impact of R&D on productivity growth of high-tech firms with the corresponding impact on productivity growth of low-tech firms. Thirdly, we investigate whether the contribution of R&D to productivity growth has changed over time.

Based on firm-level data (78 firms, 1989–2002), we find that the contribution of R&D is approximately 0.04. Although the R&D-elasticity of large firms (0.044) is higher than the corresponding elasticity of small firms (0.035), the difference is small. In contrast, the R&D-elasticity is considerably high for high-tech sectors (0.11), but statistically insignificant for low-tech sectors. Finally, the investigation of the elasticity of R&D over time revealed an interesting discontinuity showing that although until 1995 the R&D-elasticity was approximately zero, after 1995 it increased dramatically to 0.09. We investigate the potential causes of such non-linearity and we suggest a number of possible explanations.     

R&D and productivity: Internal vs. external R&D - evidence from west german manufacturing industries

The paper explores the productivity effects of investment in external (contract) vs. internal (in-house) R&D in a sample of West-German Manufacturing Industries. The results provide strong evidence of a positive relationship between productivity and the share of external R&D in total R&D. This result is robust to alternative econometric specifications. Thus, findings suggest that the decision between internal and external R&D does matter. Moreover, results imply a nonlinear relationship between productivity and the share of external R&D for higher-technology industries, hinting at decreasing productivity effects of an increasing share of external in total R&D.     

Endogenous fluctuations with procyclical R&D

The literature on endogenous growth cycles predicts the countercyclical allocation of resources to R&D. However, this prediction is not supported by empirical studies. This study considers the R&D-based growth model with endogenous fluctuations introducing population growth and a negative externality that affects the productivity of R&D. We show that this simple modification makes R&D investment procyclical along sustained business cycles using both an overlapping generation framework and an infinitely-lived agent framework.     

New evidence on the sources of EU countries’ productivity growth—industry growth differences from R&D and competition

Recent studies on productivity growth show how competition affects innovation and TFP growth in OECD countries, but do not explicitly account for sectoral parameter heterogeneity. This paper examines whether competition and innovation have a direct effect on labor productivity growth in EU goods-producing industries separated by three different industry types. The results show that the effect of R&D on labor productivity growth is not equal across industries, but rather depends on the innovation activities of sectors. The same is true for competition and labor productivity growth. The empirical evidence indicates that in unleveled industries (i.e. industries characterized by technologically unequal firms) like Specialized Goods Suppliers and Science-Based Innovators strong labor productivity growth originates with decreased competition and increased R&D, thereby supporting Schumpeterian arguments. The findings suggest Schumpeterian effects in Supplier-Dominated Goods-Producing Industries, but reveal decreasing labor productivity growth in these sectors when competition is strongly restricted.     

Knowledge and productivity in the world’s largest manufacturing corporations

This paper develops a model linking firm knowledge with productivity. The model captures three characteristics of firm knowledge (capital, diversity and relatedness) that are tested on a sample of 156 of the world’s largest corporations. Panel data regression models suggest that unlike knowledge diversity, knowledge capital and knowledge relatedness explain a substantial share of the variance of firm productivity. Relatedness matters because it lowers coordination costs between heterogeneous activities. Consequently, the traditional econometric specification has repeatedly underestimated by 15 percent the overall short-run contribution of intangible assets to firm productivity. This underestimation becomes fiercer in high-technology sectors.     

部门间生产率差距、劳动力去工业化与结构性减速

基于中国劳动力就业结构出现过快和过早去工业化的迹象，本文从部门间生产率差距的视角，利用多部门一般均衡模型、数值模拟和计量实证分析方法研究发现：（1）理论上，当服务业劳动生产率增长慢于工业，部门间生产率差距将扩大，导致劳动力去工业化速率加快；且部门间生产率差距的存在使得劳动力去工业化对经济增长产生结构性减速效应。服务业部门生产率加快提升，部门间生产率差距将会缩小，从而减缓去工业化速率和降低结构性减速压力；工业部门生产率提升尽管会扩大部门间生产率差距从而加快劳动力去工业化，但在长期中起到均匀化经济增长速率的作用。（2）利用2001—2018年中国省级和城市级面板数据的计量实证分析发现，部门间生产率差距的存在导致劳动力去工业化的效应在全时段样本下显著，但劳动力去工业化对经济增长的结构性减速效应仅在2009—2018年区间样本下显著，表明近年来中国经济增长减速与部门间生产率差距及其导致的劳动力去工业化相关。（3）赶超成功与失败国家的经验比较也表明，工业与服务业部门劳动生产率的改善与协调是跨越中等收入陷阱以及跨越后实现持续赶超的关键。     

Direct effect of ownership and technology import: Firm level evidence from large and medium-enterprises in Shanghai

This paper explores the direct effect of ownership and technology imports under the framework of neoclassical economic theory. The econometric analysis is based on panel data from a random sample of large and medium-enterprises in Shanghai, during the period of 1998 to 2003. The results show that Sino-foreign joint ventures, Sino-foreign cooperative enterprises and foreign-funded enterprises (SANZI) enjoy higher labor productivity and total factor productivity (TFP) than domestic enterprises. Intra-firm diffusion of non-codified technology, proxied by ownership, is the main source of their better performance, whereas internally transferred codified technology makes little contribution to TFP. For state-owned enterprises, codified technology imports have significantly raised both labor productivity and TFP, but such positive effect is significantly dependent on the S&T human resource. In contrast, no evidence supports that introduction of foreign technology has enhanced the productivity in domestic nonstate-owned enterprises. The empirical results indicate that SANZI do not have a distinct advantage in their codified technology. In addition, inadequate investment in assimilation process and research and development together with inefficient management of science and technology activities, may impede the use of imported technology. __________ Translated from Jingji Yanjiu 经济研究 (Economic Research Journal), 2006, (3): 90–102     

The impact of public capital on the US private economy: new evidence and analysis

This paper presents new evidence on the impact of public capital on the productivity of the US private sector. Using a production function approach, we estimate the impact of public investment on private capital productivity, specifically addressing the empirical critiques of earlier studies. We find evidence of a cointegrating relationship in a dynamic specification of an empirical model that includes public infrastructure as a factor of production, indicating the existence of a long‐run relationship between the US public capital stock and the productivity of the private capital stock. The results are used to explore how the decline in the growth rate of the public capital stock would have affected the performance of the private sector.