Technology variation vs. R&D uncertainty: What matters most for energy patent success?

R&D is an uncertain activity with highly skewed outcomes. Nonetheless, most recent empirical studies and modeling estimates of the potential of technological change focus on the average returns to research and development (R&D) for a composite technology and contain little or no information about the distribution of returns to R&D – which could be important for capturing the range of costs associated with climate change mitigation policies – by individual technologies. Through an empirical study of patent citation data, this paper adds to the literature on the outcomes of energy R&D by focusing on the behavior of the most successful innovations for six energy technologies, allowing us to determine whether uncertainty or differences in technologies matter most for success. We highlight two key results. First, we compare the results from an aggregate analysis of six energy technologies to technology-by-technology results. Our results show that existing work that assumes diminishing returns but assumes one generic technology is too simplistic and misses important differences between more successful and less successful technologies. Second, we use quantile regression techniques to learn more about patents that have a high positive error term in our regressions – that is, patents that receive many more citations than predicted based on observable characteristics. We find that differences across technologies, rather than differences across quantiles within technologies, are more important. The value of successful technologies persists longer than those of less successful technologies, providing evidence that success is the culmination of several advances building upon one another, rather than resulting from one single breakthrough. Diminishing returns to research activities appear most problematic during rapid increases of research investment, such as experienced by solar energy in the 1970s.     

Technology variation vs. R&D uncertainty: What matters most for energy patent success?

R&D is an uncertain activity with highly skewed outcomes. Nonetheless, most recent empirical studies and modeling estimates of the potential of technological change focus on the average returns to research and development (R&D) for a composite technology and contain little or no information about the distribution of returns to R&D – which could be important for capturing the range of costs associated with climate change mitigation policies – by individual technologies. Through an empirical study of patent citation data, this paper adds to the literature on the outcomes of energy R&D by focusing on the behavior of the most successful innovations for six energy technologies, allowing us to determine whether uncertainty or differences in technologies matter most for success. We highlight two key results. First, we compare the results from an aggregate analysis of six energy technologies to technology-by-technology results. Our results show that existing work that assumes diminishing returns but assumes one generic technology is too simplistic and misses important differences between more successful and less successful technologies. Second, we use quantile regression techniques to learn more about patents that have a high positive error term in our regressions – that is, patents that receive many more citations than predicted based on observable characteristics. We find that differences across technologies, rather than differences across quantiles within technologies, are more important. The value of successful technologies persists longer than those of less successful technologies, providing evidence that success is the culmination of several advances building upon one another, rather than resulting from one single breakthrough. Diminishing returns to research activities appear most problematic during rapid increases of research investment, such as experienced by solar energy in the 1970s.     

Learning from successes and failures in pharmaceutical R&D

In this paper, we build a cumulative innovation model to understand the role of both success and failure in the learning dynamics that characterize pharmaceutical R&D. We test the prediction of our model by means of a unique dataset that combines patent information with R&D projects, thus distinguishing patents related to successfully marketed products from those covering candidate drugs that failed in clinical trials. Results confirm model predictions showing that patents associated with successfully completed projects receive more citations than those associated with failed projects. However, we also show that failed projects can be in turn cited more often than patents lacking clinical or preclinical information. We further explore the ‘black box’ of innovation, providing evidence that both successes and failures contribute to R&D investment decisions and knowledge dynamics in science-driven sectors.     

The role of diminishing returns in neo-Schumpeterian growth theory

Summary. This paper generalizes Segerstrom [5], a dynamic general equilibrium model of endogenous growth through quality improvements in which innovation and imitation are modeled as the outcomes of research and development (R&D) races. Specific factors introduced into the technologies of both R&D activities achieve diminishing returns to scale in R&D. The comparative-static results of subsidies to R&D activities depend on the degree of diminishing returns to scale in R&D. When there is (is not) a sufficient degree of diminishing returns to R&D, a subsidy to innovative activity increases (decreases) innovative activity. Received: July 8, 1994; revised version: June 9, 1997     

Public Technology Infrastructure,R&D Sourcing,and Research Joint Ventures

In this paper, we define public technology infrastructure to mean public resources that bring new R&D into existence. Examples are public research that yields knowledge spillovers and government contracts that broker new research. Using this definition we explore the effect of public infrastructure on cooperative R&D, especially R&D sourcing and research joint ventures (RJVs). Our findings strongly suggest that public infrastructure promotes cooperative R&D. We begin by studying the role of federal laboratories in R&D sourcing by private laboratories, finding that sourcing increases as a result. Then we examine patents arising from RJVs sponsored by the Advanced Technology Program (ATP). We find that R&D subsidies as well as difficulty and novelty increase patents produced by the RJVs. Contractual oversight by ATP has no direct effect but an indirect effect appears to exist, since firms value ATP oversight more highly for more difficult and novel projects, and these produce more patents.     

US PATENT CITATIONS DATA AND INDUSTRIAL KNOWLEDGE SPILLOVERS

The aim of this paper is to empirically evaluate the US interindustry knowledge spillover using the NBER patents data file (1963–1999). Reputing the patent backward citations as a good proxy of the patent's knowledge spillover, we proceed by building a time series to each US manufacturing industry patent citations and their lags. Then, we generate the time series of the external and the internal knowledge flow indices, showing that traditional sectors are more technology-dependent from the others than the new one. Here, in the spirit of Pavitt [Pavitt, Research Policy 13, 343–73, 1984]. We derive a new taxonomy of innovation focusing on the ideas instead of the goods production in order to obtain the innovation linkage and trajectories. Once we determined that each sector's most cited patents are typically belong to the ‘new’ sectors, we evaluate the high- and low-tech sectors innovation effect on the whole economy innovation process. Confirming that the high-tech sectors, and its R&D expenditures, are the most important, we conclude that it is the giant's shoulders, substance of the whole economy.     

Patent portfolios and knowledge flow(s) of photovoltaic companies

The current trend towards green energy is encouraging manufacturers to invest in photovoltaic technologies. In order to guarantee R&D and optimal operational performance, operators should be able to identify the technological advantages of their competitors for the conduct R&D and to ensure adequate technological knowledge intake. Therefore, from the perspective of patent portfolios and knowledge flow(s) of photovoltaic companies, this study adopted two approaches namely, patent counts and patent citations, to discuss the technical capability of R&D portfolios and the technological knowledge flow. Three patent indices were utilised for the integration of R&D portfolios which include: technology attractiveness, relative patent position, and revealed patent advantage. Technological knowledge flow allows construction of a patent citation network through backward citation of patents. Sources and movement directions of technological knowledge are measured by calculating the relative citation propensity. R&D portfolios and knowledge flow are complementary perspectives of each photovoltaic company.     

An empirical analysis of firm process and product patenting

This paper presents an empriical study of the determinants of firm patenting. Since industrial research and development (R&D) encompasses a variety of activities, this study distinguishes between patents on process innovations and patents on product innovations. The property rights provided by a patent may differ between process and product patents, which suggests that the determinants of process innovations and product innovations may difer as well.

Several recent studies have distinguished between research directed toward process innovations and research directed toward product innovations. Scherer (1983a) included measures of process R&D spending and product R&D spending in regressions for inter-industry differences in productivity growth. Link and Lunn (1984) found that the returns to process-related R&D activity exceed the returns to product-related R&D activity. Link (1982) found inter-firm differences in the allocation of R&D spending for process innovations and product innovations. Lunn (1986) found differences in the determinants, as well as the effects, of process patenting and product patenting at the industry level. This paper examines whether the determinants of product and process patenting differ at the firm level.     

A computational analysis of R&D support programs

We compare two common government R&D support programs, R&D tax credits and direct R&D grants. To study their effectiveness and the extent to which their design matters, we analyze these programs within a dynamic equilibrium model of imperfectly competitive industries. Adopting comprehensive welfare measures that take into account government, producer and consumer surpluses, we find that both schemes exhibit positive social returns. Mid-range R&D-intensive sectors exhibit higher social returns than either high or low R&D-intensive sectors. Both incentive schemes generate positive measures of R&D input additionality of magnitudes consistent with empirical R&D research. However, R&D grants that require firms to allocate subsidy funds to R&D spur less R&D than a more flexible R&D tax credit. Subsidy schemes can even induce competing firms to over-spend on R&D, generating negative producer surplus and possibly negative social returns.     

Economic policy,the new economy and the social rate of return to R&D in UK manufacturing

This article focuses on the question of whether public policy changes and/or the new economy have influenced the social returns to R&D expenditure in UK manufacturing over the three decades up to the end of the millennium. The basic methodology is reasonably straightforward, to estimate a production function in which, in addition to labour and fixed capital, R&D appears separately in a form that directly enables estimates of the social return to investment in knowledge and how it has changed over time. The results suggest that neither changes in government R&D policy nor the new economy have raised social returns to R&D.     

Research and development and labour productivity: do high-tech firms exhibit labour- or capital-saving technical change?

Employment and output in the advanced technology sectors have generally exhibited above-average growth for more than two decades. While this industry accounts for a relatively small share of total employment, the majority of private sector research and development (R&D) expenditures in the US is concentrated within seven sub-sectors. However, little attention has been paid as to whether high-tech productivity exhibits Hicksian capital or labour ‘savings’ bias or tendency to displace either factor input over time. Biased technical change can occur as economies transition between growth regimes. An augmented production function is employed to analyse the additional impact of R&D activity on firm-level labour productivity. A panel data set comprised of high-tech firms located across the advanced economies, China and India from 1990 to 2013 is used in the analysis. Labour-saving technical change was present across the advanced technology sectors and most countries. The expanded models of labour productivity that used fixed effects with lagged regressors confirmed the prior results as well as finding that R&D per employee, relative R&D intensity and firm market share contribute to firm-level labour productivity growth across countries and sectors. Additional support was found for diminishing returns to scale but not for R&D spillover effects.     

Technological opportunity and the growth of knowledge: A Schumpeterian approach to measurement

A model of endogenous growth, based on Schumpeter's notion of trustified capitalism, is developed and applied to firm-level data for the period 1973–1991. The model relates the market value of a firm to its current profits and to its R&D expenditures. The relationship depends upon the expected rate of knowledge growth, the expected value of an innovation and the elasticity of the R&D production function. Over the sample period, investors expected knowledge to grow at an average rate of 5 percent, a measure which reflects both process innovations and new product discoveries. Elasticities of the R&D production functions are estimated for thirteen industry groups and interpreted as measures of technological opportunity. There is no evidence of secular decline in technological opportunity over the sample period, but there is some evidence of diminishing returns to R&D intensity. Variations in technological opportunity over time are not correlated across industries. In contrast, the expected rates of knowledge growth at the industry level are highly correlated with the aggregate expected rate.     

Patents and R&D expenditure effects on equity returns in pharmaceutical industry

As costs of pharmaceutical R&D soar and productivity falls, the role of research pipelines in firm valuations is changing. To date, surprisingly little work has been published on the effects of R&D pipeline performance on equity returns, while controlling for coincident factors, such as legacy patents and presence of blockbuster drugs in production. Using 1996–2013 data for nine largest pharmaceutical companies in the world, this article assesses the role of the above factors on returns to pharmaceutical companies equity. We show significant positive link between changes in the number of blockbusters on patent six months prior and returns in excess of pharmaceutical equity index. The number of patents granted by United States Patent and Trademark Office in a quarter is also a significant factor. On the other hand, we find that increases in R&D expenditure in large-cap pharmaceutical companies are viewed negatively by investors in the short term.     

Inventing together: exploring the nature of international knowledge spillovers in Latin America

This paper studies the nature, sources and determinants of international patenting activity in Latin American countries (LACs) and examines the extent to which LACs benefit from R&D that is performed in the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). By using patents and patent citations from the United States Patent and Trademark Office, we trace sectoral knowledge flows from G-5 countries to LACs. We study the impact of three channels of knowledge flows: foreign R&D, patent citation-related spillovers, and face-to-face contact spillovers. Our results, based on data for Argentina, Brazil, Chile, Colombia and Mexico, suggest that international knowledge spillovers from the G-5 countries were a significant determinant of inventive activity during the period 1988–2003. We find that the stock of ideas produced in the USA has a strong impact on the international patenting activity of these countries. Moreover, controlling for US-driven R&D effects, bilateral patent citations and face-to-face relationships between inventors are both important additional mechanisms of knowledge transmission. Some of our results suggest that the latter mechanism is more important than the former.     

The 1988 EC directive on biotechnological inventions and the UK biotechnology industry

The article, based on a recent survey of UK biotechnology companies, highlights the complex interaction between the organization of R&D and the patenting policy in the biotech industry. Some of the more interesting findings include: the limited extent of private investment in biotechnological R&D; the existence of two markedly different R&D strategies (product- vs. process-based); the distinction between first- and second-generation patents and their effects on market structure. The core of the article deals with the likely effects on patenting behaviour of changes in patent law - both as envisaged in the October 1988 Directive and as suggested by recent theoretical research on the economics of patents. The Directive in its current form is reported to have no discernible effect on the extent and organization of R&D, whereas the industry's response to a series of hypothetical changes suggests that any definition or patentability standards has far-reaching repercussions on: (1) the allocation of resources between research and development; (2) the conditions of entry into the industry; (3) the balance of bargaining power between firms of unequal size (or pursuing different R&D strategies); and ultimately (4) the allocation of technological surplus between consumers and producers.     

Are there diminishing returns to R&D?

Semi-endogenous models and, to some extent, also Schumpeterian models are based on the assumption of diminishing returns to R&D. This paper shows that the null hypothesis of constant returns to R&D cannot be rejected for the OECD countries.     

Knowledge appropriability, firm size, and growth

Empirical evidence shows that the number of patents per R&D dollar declines with firm size. In this paper, we propose a Schumpeterian growth model that accounts for this evidence. We analyze an economy with firms that engage in cost-reducing innovation resulting from the accumulation of both codified and tacit knowledge: the former occurs through the purchase of patents, while the latter is the result of R&D conducted in-house by firms. We study the relation between knowledge appropriability and market structure, and we show that a shift from patents to in-house research occurs as firm size gets larger. Since innovation statistics concentrate mainly on patents, this process of research reallocation results into an under-estimation of innovative activity and is responsible for the declining ratio of patents to R&D expenditure. Survey data on UK-based firms provide support to our results.     

Firm size and types of innovation

We propose a general theory of innovation that illustrates the relative benefits of performing process versus product R&D when firm size is endogenous. A firm's size, scope, and R&D portfolio are shown to reflect the same underlying characteristic of the firm, namely manufacturing efficiency. We demonstrate that efficient firms become larger, have greater scope, and perform more of both process and product R&D. In light of decreasing returns to R&D, this implies small firms obtain more product innovations per dollar of R&D than large firms, which is consistent with evidence we present that small firms are more innovative than large firms as they obtain more patent counts and citations per dollar of R&D.     

R&D productivity: A global multi-industry comparison

This study considers the productivity of R&D expenditures on an international and multi-industry basis. Using 1992 data reported by Business Week on 117 companies in the United States, Europe, and Japan, we examined two measures of innovative output, patents and impact-adjusted patents, in relationship to R&D spending. Our results clearly show a decreasing returns to scale of R&D expenditure. Although this pattern holds true regardless of industry or global region, the level of return and rate of decreasing returns vary by both industry and international region.     

R&D, patents and stock return volatility

Recent finance literature highlights the role of technological change in increasing firm specific (idiosyncratic) and aggregate stock return volatility, yet innovation data is not used in these analyses, leaving the direct relationship between innovation and stock return volatility untested. The paper investigates the relationship between volatility and innovation using firm level patent data. The analysis builds on the empirical work by Mazzucato (Rev Econ Dyn 5:318–345, 2002; J Evol Econ 13(5):491–512, 2003) where it is found that stock return volatility is highest during periods in the industry life-cycle when innovation is the most ‘radical’. In this paper we ask whether firms which invest more in innovation (more R&D and more patents) and/or which have more important innovations (patents with more citations) experience more volatility in their returns. Given that returns should in theory be higher, on average, for higher risk stocks, we also look at the effect of innovation on the level of returns. To take into account the competition between firms within industries, firm returns and volatility are measured relative to the industry average. We focus the analysis on firms in the pharmaceutical industry between 1974 and 1999. Results suggest that there is a positive and significant relationship between volatility, R&D intensity and the various patent related measures—especially when the innovation measures are filtered to distinguish the very innovative firms from the less innovate ones.