Measuring R and D Productivity

Measuring the productivity of an R&D organization is extremely tricky. Productivity is usually defined as a ratio of an output, like number of cars produced on an assembly line, to an input, like the wages paid the workers. While R&D may have a measurable input, the output is often intangible and difficult to quantify. This is further complicated because the return from an R&D department may not be realized for one or two decades,which means the time lag is much higher than in factory measurements. Furthermore, many researchers believe that this kind of measurement may be counterproductive,since the mere act of measurement could reduce R&D productivity. Nevertheless, companies continue to evaluate R&D with the crude methods available as they desperately look for more effective, quantitative methods

Total factor productivity effects of interregional knowledge spillovers in manufacturing industries across Europe

The objective of this study is to identify knowledge spillovers that spread across regions in Europe and vary in magnitude for different industries. The study uses a panel of 203 NUTS-2 regions covering the 15 pre-2004 EU-member-states to estimate the impact over the period 1998-2003, and distinguish between five major industries. The study implements a fixed effects panel data regression model with spatial autocorrelation to estimate effects using patent applications as a measure of R&D output to capture the contribution of R&D (direct and spilled-over) to regional productivity at the industry level. The results suggest that interregional knowledge spillovers and their productivity effects are to a substantial degree geographically localised and this finding is consistent with the localisation hypothesis of knowledge spillovers. There is a substantial amount of heterogeneity across industries with evidence that two industries (electronics, and chemical industries) produce interregional knowledge spillovers that have positive and highly significant productivity effects. The study, moreover, confirms the importance of spatial autoregressive disturbance in the fixed effects model for measuring the TFP impact of interregional knowledge spillovers at the industry level.Total factor productivity, manufacturing industries, knowledge spillovers,patents, European regions, spatial econometrics

Technological Change and R&D Activities as a Factor of Economic Growth

The aim of this thesis is to concurrently evaluate the significance of technological change as an ultimate driver of productivity performance and economic growth, while also examining the role of research and development (R&D) investments in economic growth. The most important question in my thesis is: what creates growth? Factors for this creation could be various, but special attention is paid to firm performance and its changes over the firm size distribution. Measuring productivity growth and R&D performance is important as accurate estimation of R&D investment would help a firm to optimize its R&D spending and avoid unproductive expenditures. Moreover, R&D investment depends on a firm’s technological opportunities and expected profitability. In the empirical part, I examine firm growth rates in Finland. The results show the significant positive impact of R&D on growth. I found that the growth impact varies with firm size, showing a positive relationship for small and medium-sized firms but a negative relationship for large firms. Additionally, I observe positive autocorrelation for all types of firms

Innovation in Scotland : analysis of the community innovation survey 2009

Strengthening levels of innovation is one of the cornerstones of the Scottish Government‟s Economic Strategy. Innovation is a key catalyst for productivity growth as new ideas drive enterprise, create new products and markets and improve efficiency, delivering benefits to firms, customers and society. It is a crucial factor in determining competitiveness and national progress. Until recently, the most common and well known measure of innovation has been the ratio of national expenditure on R&D to GDP. Data shows that there has been a significant gap in business research and development (R&D) expenditure between Scotland and the UK, EU and OECD averages in recent years. Scottish Business Enterprise R&D (BERD) expenditure was 0.56% of Scottish GDP in 2009, lower than the rate for the UK as a whole (1.11%) and the EU (1.17%). Compared to other UK Government regions, Scotland ranked in 10th place out of the 12 regions. However, while R&D is useful for measuring technology-based activities, it is increasingly recognised that this is only one element of the broader concept of innovation and is frequently more relevant for manufacturing than for services. Evidence shows that firms introduce new products and services onto the market without necessarily performing R&D. A lot of innovation activity is based on (or embodied in) advanced machinery and computer systems purchased to implement new or improved processes and deliver new products and services. Innovation can also be purchased through rights to use patents, licences, trademarks and software. Innovation can also encompass training and new design and marketing processes. Evidence also shows that many firms adopt multiple, complementary innovation strategies, with the most innovative firms introducing both product and process innovations as well as marketing or organisational innovations. Therefore, productivity growth can be achieved through advances in technology combined with new approaches to creating and delivering of goods and services. There is now a solid body of evidence describing the relationship between research, innovation and economic development. The evidence suggests that investment in „intangible assets‟ that give rise to innovation (R&D, software, human capital and new organisational structures) now accounts for up to 12% of GDP in some countries and contributes as much to labour productivity growth as investment in tangible assets such as machinery and equipment. According to OECD estimates, investment in intangible assets accounted for around a quarter of labour productivity growth in the UK and other countries between 1995 and 2006. The Community Innovation Survey (CIS) allows an assessment of business innovation performance, wider than just R&D expenditure, across European Union countries. CIS collects a range of information from businesses on the types of innovation they are involved in, motivation for innovation, spending on a range of innovation activities beyond R&D, collaboration and linkages between businesses or with public research organisations, as well as data on sales from product innovations. In light of the growing recognition that innovation encompasses a wider range of activities, and that broader metrics are required to reflect this, the Innovation Survey provides a key data set to measure innovation within businesses

When Do Research Consortia Work Well and Why? Evidence from Japanese Panel Data

We examine the impact of a large number of Japanese government-sponsored research consortia on the research productivity of participating firms by measuring their patenting in the targeted technologies before, during, and after participation. Consistent with the theoretical predictions of Katz (1986) and others, we find consortium outcomes are positively associated with the level of potential R&D spillovers within the consortium and (weakly) negatively associated with the degree of product market competition among consortium members. Furthermore, our evidence suggests that consortia are most effective when they focus on basic research.

Specialisation precedes diversification: R&D productivity effects

We model how R&D enters the innovation system in four ways (intramural, extramural, cooperative, and spillover). Despite measuring three different spillovers together, for a very large sample of European enterprises we conclude that the productivity effects of spillovers were at best smaller than intramural R&D productivity effects. We also find that building on the greater skills and experience of enterprises already undertaking R&D (intensity) raised labour productivity more than providing support for those beginning R&D (extensity). Optimal extramural R&D intensity was higher than the actual level; sample firms could boost productivity either by abandoning extramural R&D or by doing much more. There were substantial differences in our sample between enterprises and countries in terms of R&D spillovers. Greater multinational corporation incidence in new EU members accounted for these countries' high direct R&D intensity productivity, regardless of their generally low overall labour productivity. Absorptive capacity made little difference to the utilisation of spillovers

Measuring the productivity of national R&D systems: challenges in cross-national comparisons of R&D input and publication output indicators

Article / Letter to editorCWT

Measuring the productivity of national R&D systems: challenges in cross-national comparisons of R&D input and publication output indicators

Article / Letter to editorCWT

Measuring firm-level productivity convergence in the UK: the role of taxation and R&D investment

This paper examines the direct effects of corporate tax on firm productivity along with the interaction effects of tax policy and R&D activity on productivity at firm level for over 13,062 firms during 2004-2011. Our main findings are first, that there is evidence for productivity convergence and we find that there is a positive robust relationship between R&D and firm productivity, whereas tax policy has a negative distortionary effect on TFP. Second, firms with greater export orientation do not seem to achieve much improvement in productivity, whereas the favourable productivity effect in the case of R&D-based firms suggests that if there are tax incentives in place for R&D type activity, it can promote innovation and drive productivity convergence (lagging firms closing the technology gap with those at the frontier), particularly so when there is a continued decline in overall economic activity. The results also show a significant non-linear effect of tax rate on firm-level productivity, identifying an inverse U-shaped relationship

MEASURING RESEARCH BENEFITS WITH IMPORT BAN RESTRICTIONS, QUALITY CHANGES, NON-MARKET INFLUENCES ON ADOPTION AND FOOD SECURITY INCENTIVES

Hundreds of studies have been conducted since Griliches (1958) suggested a method for measuring the benefits to agricultural research. Alston et al. (2000) reviewed 292 studies that reported 1,886 observations of returns to agricultural R&D. While some studies consider complicated cases, most studies have focused solely on R&D policy. However, it is common that agricultural R&D policy is combined with other policies, such as a price support, subsidy policy, non-market inducement, and import restrictions. Naturally, when the benefits of agricultural research are measured without taking the related policies into account, biased estimates are likely. The South Korean rice industry provides a good example where several factors affected the adoption of new technology, causing the complications in the measurement of the research benefits. The agricultural R&D policy in Korea for rice was combined with factors such as an import ban, a price support and government purchase program, yield-quality tradeoffs, and arguments that there are external benefits, like a public good, associated with self-sufficiency. It is therefore important to evaluate the benefits of agricultural research appropriately and carefully given these conditions. The revolution in rice production in Asia was triggered in 1966 with the development of IR8 by the International Rice Research Institute (IRRI). As soon as the potential of IR8 was recognized, IR8 was released to Asian rice-producing countries (IRRI). Korea also received small sets of breeding materials from the IRRI (Chandler, 1992). In 1972, Korea introduced the first high-yielding variety developed through agricultural research in Korea. However, the high yielding âTong-ilâ rice was inferior in taste to conventional rice. The argument that prevailed in the 1970s (and continues to the present day) is that self-sufficiency in rice is a public good in Korea. This attitude affected the adoption of Tong-il. The Korean government strongly encouraged farmers to adopt the new varieties through a government purchase policy as well as non-market government inducements. The government purchase policy that had been in place since 1950s was expanded in the 1970s. Most of the Tong-il rice produced was purchased and used by the government or released back on the market at discounted prices. Local officials and extension workers were provides incentives to achieve high local adoption rates. In some extreme cases, officials and extension workers physically removed other rice from fields that had already been planted. An import ban was also imposed to maintain high domestic prices. The economic evaluation of high yielding rice involves innovations to deal with several elements: ⢠The basic economics of agricultural research and development (productivity-enhancing technology): measuring agricultural research benefits without considering the complicating factors. A new method to measure a supply shift caused by agricultural R&D will be presented, considering spillovers. ⢠The trade policy that affected returns to higher yields: world price is considered as an opportunity cost. The research benefit in open economy will be smaller than the benefit in closed economy. ⢠The price support and government purchase program for a fixed amount of rice from each farm: considering that the remaining amounts were sold in the market, this policy acts like a decoupled income transfer that does not affect the payoff of agricultural research. ⢠The yield-quality tradeoffs of the technology: this tradeoff should be evaluated as a loss because the gross benefits of research would increase if there had not been a quality change. ⢠Non-market incentives for the adoption of Tong-il rice: the effect of non-market adoption is similar to that of regulation in that it generally prevents profit-maximizers from making adjustments. ⢠The public good argument related to âfood securityâ and self-sufficiency. This paper measures the net research benefits derived from the development of Tong-il performed in Korea given this complex setting. Despite the importance of this case, no studies have measure the payoff to investments to development and adoption of high yielding varieties under the multitude of policies and other complications outlined above. Conceptual studies and a few examples from other countries have dealt with some of these issues, but no study has evaluated the issues fully in a real and important setting. For example, Lokollo (2002) explored the effects of modern technology on its adoption and productivity in Indonesia. The Philippines have also implemented a government purchase policy like Korea during the green revolution period (Martinez, Shively and Masters, 1998). Both of the cases are very similar to the Korean case, in that the green revolution was attained through several government policies. However, neither of them sought to analyze the agricultural R&D effects in the complicating setting, like the Korean case. One difficulty of the R&D-related studies lies in measuring a supply shift caused by agricultural research. To measure research-induced supply shifts, many R&D-related studies introduced complicating methods, such as production functions, supply-response functions, and productivity functions. One innovation of this paper is to present a new formula for measuring a research-induced supply shift. A horizontal supply shift (J) evaluated at the current price can be measured as follows, J=h/(1-δ+δh), where h indicate yield gains of new varieties over old varieties and adoption rate of high-yielding varieties, respectively. In the above formula, only two parameters are used and they are usually available in most cases. No specific forms of supply-and demand functions or elasticities are assumed. The net returns to research on Tong-il is quite large when all the complicating factors listed above were ignored, but substantially smaller once those factors are accounted for. A tentative conclusion is that the effect of the innovation is likely to be much smaller if the development and dissemination of new technology evaluated along with the applicable market-distorting policies. This research is important in order to properly account for this episode in the economic history of agricultural development of Korea. This paper also provides lessons for other developing countries, which take a similar path with the Korean case to their agricultural development. We expect the presentation to generate considerable interest. It deals with a major event that involves important current issues in the development of agriculture and food security in developing countries. The paper applies innovations in the economics of agricultural R&D, which has long been a major topic for agricultural economists.Research and Development/Tech Change/Emerging Technologies,