Events

We present an empirical analysis of the effects of patent thickets at the European Patent Office on entry into patenting by UK firms. Using a direct measure of patent thicket density, we provide evidence for the existence and growth of patent thickets in specific industries, notably in telecommunications, audiovisual technology, and computer technology. Our analysis indicates that the density of patent thickets is associated with reduced entry into patenting in the particular technology area (controlling for the level of patenting in that area). We find this effect to be particularly pronounced for electronics and telecommunications. It is also stronger for smaller than for large companies.

A question of considerable interest in a world of tightened resources is the relationship between research outputs to research inputs. At the national level, policy makers want to know the degree to which more funding leads to more research. At the micro level, funding agencies want to know the degree to which research can be attributed to the funds invested in researchers. These types of questions are sometimes answered by relating the amount of direct funding investigators receive from a foundation or agency to the number of articles published in the next two or three years.

The approach of relating publications to agency funding (PAF) highlights two issues encountered in examining the relationship between research inputs and outputs. The first is one of attribution: exactly which articles should be attributed to what funding stream? In the PAF approach all articles published in the next few years are attributed to total agency funding received in a given year. Yet some articles undoubtedly result from funding received prior to the year being studied while others relate to funding received in future years.  The PAF approach also assumes that all articles can be attributed to funding from one agency. Yet many researchers have funding from more than one agency.

The PAF approach also assumes that the manner in which funding is bundled has no effect on the productivity of the lab. There are two dimensions to this neutrality assumption. First, it assumes that it makes no difference whether a principal investigator (PI) has four grants a year that sum to $1million or one grant for $1 million. Second, the PAF approach implicitly assumes that output is unrelated to the composition of the funding portfolio in terms of the relative size of each grant.

The presented paper by Michele Pezzoni (Ecole Polytechnique Federale de Lausanne, Switzerland), Jacques Mairesse (CREST-ENSAE, France, UNU-Merit, the Netherlands, and NBER), Paula Stephan (Georgia State University and NBER), and Julia Lane (American Institutes of Research) investigates the attribution and neutrality issues, using data from the California Institute of Technology for the period 2000-2010. Our data are fine-grained and allow us to observe the size of the award, the source of the funding, and the length of funding at the PI level, thus creating a panel data base with three dimensions: PI, grant and time. We measure research productivity in terms of publication counts (QUANTITY) and the average Impact Factor of the journals in which the publications are published (QUALITY).

We find that the relationship between inputs and outputs persists after addressing attribution issues and estimating the relationship at the grant level. The simulations we run provide evidence that the neutrality assumption does not hold and that productivity increases the more highly concentrated is the PI’s grant portfolio. This is consistent with the presence of economies of scale in grant administration. It is also consistent with the fact that grants of small size are used to support more risky research agendas.

We outline a set of steps that could lead to new quantitative analysis and understanding of science policy based on scientifically grounded conceptual framework and large-scale computational analysis of scientific activity. Getting the right conceptual and empirical framework matters, lest resources and people get squandered because incentives are wrong. Getting an empirical framework based on something other than anecdotes matters, to avoid substantive misunderstandings about the process of science. Seizing the opportunity presented by the explosion in digital information about research products and processes, will require both substantial effort to acquire, integrate, curate, and evolve large quantities of information from many sources, and much innovation in both science policy research and computational methods.

In this paper, we design two laboratory experiments to analyze the causal effects of competition on step-by-step innovation. Innovations result from costly R&D investments and move technology up one step. Competition is inversely measured by the ex post rents for firms that operate at the same technological level, i.e. for neck-and-neck firms. First, we find that increased competition leads to a significant increase in R&D investments by neck-and-neck firms. Second, increased competition decreases R&D investments by firms that are lagging behind, in particular if the time horizon is short. Third, we find that increased competition affects industry composition by reducing the fraction of sectors where firms are neck-and-neck. All these results are consistent with the predictions of step-by-step innovation models.

Current economic analyses of intellectual property regimes on international trade reveal ambiguous results, suggesting a general positive impact on trade flows but with strong dependence on the status of trade openness, national innovation system, qualitative development level of industrial structures or the focussed industrial sectors. This project targets on the analysis of factors which influence the impact of intellectual property on international trade competitiveness of economies, industrial sectors or enterprises. It focuses on the integrated analysis of relevant determinants in four areas: 1. factors of national innovation system, 2. structures of intellectual property protection policies and strategies applied by economic subjects, 3. factors of innovation and competition conduct, and 4. factors of competitive position in international trade. The project analyses export orientated sectors of the German economy at the aggregated national and disaggregated sectoral level and selected multinational enterprises between 2004 and 2014.

We know little about the effects of patent licensing because licensing information is notoriously difficult to find. Using publicly available data we construct a novel means of indirectly identifying academic patents that have been licensed to large corporations. We estimate the signaling effects of patent licensing on subsequent innovation. We find that after licensing patents have considerably more citations. The signaling effect of licensing by universities with a large flow of patents is similar for public and private universities. For universities with a small flow of patents, relative to Small public universities, a license of a patent owned by a private university to a large company leads to significantly more citations. The results suggest that licensing of small private university patents sends significantly stronger and more informative signal to out-of-state innovators who, influenced by the perceptions about university technology management practices across different types of universities, might be generally suspicious about the quality and potential of patents owned by small private universities.

In a complex and dynamic technological environment, firms are often unable to sustain continuous high levels of productivity over long periods of time without accessing knowledge from beyond their boundaries; even leading firms require external knowledge to develop new innovations.  In the pharmaceutical industry, for instance, an increasing proportion of firm revenue is generated from products derived from technology discovered outside the firm. Ceccagnoli et al. (2010) support this notion: in 60 percent of new branded drugs introduced over a 20-year period, more than half of the patents protecting them originated outside the firm.  More specifically, Edwards et al. (2003) report that virtually all drugs with biotechnology origins emanate, in fact, from universities.  It is likely, however, that this dependence is understated because the analysis focused only on patents attached to new products identified in the FDA Orange Book.  Nonetheless, it demonstrates the critical importance placed on the supply of new technologies through the earlier stages of the external research value chain.

Our focus is on the flow of technologies out of university (non-profit) labs to biotechnology firms and from there on to pharmaceutical firms. Given that few biotechnology firms have the resources and complementary assets to fully develop products it is expected that most externally generated products will pass through this downstream gateway. More specifically, we focus not only on the supply of projects from universities to biotechnology firms but also on the supply of projects that make it to the second link between biotechnology and pharmaceutical firms and, more importantly, several underlying characteristics of these inventions (e.g., stage of development, disease category and NIH funding).

When licensed to firms, university biotechnology inventions are typically very early stage. As such, technical development is necessary before the invention can be marketed. The uncertainty typically discussed is either technological uncertainty (that is, will the invention work) or market uncertainty (that is, will the product be profitable). We demonstrate in this paper that a third type of uncertainty, entrepreneurial uncertainty) is also very important. Entrepreneurial uncertainty is uncertainty as to the applicability of the invention (the application for which it is, in fact, useful--in this context, disease category). For example, a technology might be license from the university to the biotechnology firm for use in cancer, but when sublicensed to a second firm, the disease category might be cardiovascular.

In this paper we examine changes in the stage of development and disease indication from initial to sublicense. We estimate econometric models explaining whether a licensed inventions is sublicensed as well as the time between the patent priority date and the initial license and the time between the initial license to sublicense. Independent variables include stage of development, disease category, license characteristics (exclusivity, payment terms, etc.), National Institutes of Health funding, etc.

Trademarks (TMs) shape the competitive landscape of markets for goods and services in all countries through branding and conveying information and quality inherent in products. Yet, researchers are largely unable to conduct rigorous empirical analysis of TMs in the global economy because TM data and economic data are organized differently and cannot be analyzed jointly at the industry or sector level. We propose an ‘Algorithmic Links with Probabilities’ (ALP) approach to match TM data to economic data and enable these data to speak to each other. Specifically, we construct a NICE Class Level concordance that maps TM data into trade and industry categories forward and backward. This concordance allows researchers to analyze differences in TM usage across concordance for TMs to characterize patterns in TM applications across countries and industries. We use the concordance to investigate some of the key determinants of international technology transfer by comparing bilateral TM applications and bilateral patent applications. We find that international patenting and TM strategies largely conform with domestic patterns with significant differences in intellectual property usage across sectors. We conclude with a discussion of possible extensions of this work, including deeper indicator-level concordances and further analyses that are possible once TM data are linked with economic activity data.

While Schumpeter is the most quoted author in ongoing academic debates on innovation and entrepreneurship, those who cite him almost always catch the letter, but miss the spirit, of his work. This is especially true for his early writings. My aim is to strip away some conventional ideas about what should count as "Schumpeterian", or "Neo-Schumpeterian" -- in order to reveal again Schumpeter as a radical thinker -- and to argue why he is still, after more than 100 years, the best starting point by far today for anyone wanting to understand what I call "deep innovation".