Our research explained to engineers (or brave economists)
Innovation takes place in a complex adaptive system. A multitude of agents interact with each other in a variety of ways and self-edict rules and norms that govern their behaviors. Agents in the ‘innovation system’ are individuals and institutions. Individuals include creative actors: scientists, engineers, inventors and entrepreneurs but also financial actors such as bankers and venture capitalists and political actors. Institutions include private companies such as startups and large companies, universities, public research organizations, governments and their agencies, and providers of funds. The innovation system is also multi-layered because innovation takes place on a local and global scale. It is also multi-faceted in the sense that there are many such systems around the world, each being adapted to the socio-economic conditions in which they evolve.
We seek to characterize the system by identifying causal patterns, that is, we go beyond correlation and identify actual levers of the system. We do so by using econometrics, which is a collection of statistical methods suited to the analysis of economic data. Much like researchers in some fields rely on spectrometric identification of organic compounds, we rely on econometric identification of economic relationships. The overarching objective of our research is to propose ways to fine-tune the system, or fix it if necessary. In essence, our task as economists is very similar to that of engineers.
Research at the IIPP chair is central to the knowledge economy. Innovation becomes ever more important to sustain the long-term growth of nations and takes place in an ever-more complex environment. It is therefore critical to have a sound understanding of the inner working of the innovation system and to propose ways to improve it. As we believe that our research matters to society, we devote special effort to sharing research findings with policymakers and all stakeholders in order to pull ourselves out of the ivory tower.
Our research is not constrained by any boundaries. We study both individual and institutional actors of the system. For instance, papers [1] and [2] study individuals (inventors and investors, respectively) whereas paper [3] studies a government agency, namely the patent office. We study both the micro and macro layers of the system, as well as the interaction between these layers. For instance, paper [4] takes a micro perspective, paper [5] takes a macro perspective, and paper [6] studies the micro impact of a macro phenomenon. We study individual systems but also compare systems with each other. Paper [7] studies one face of the system whereas paper [8] compares the many-faces of the system. Finally, we also contribute to the development of tools (paper [9]) and econometric techniques (paper [10]) to improve best practice in the field.
Our research explained to economists (or brave engineers)
The overarching objective of our research is to provide the policy environment that best addresses the needs of the knowledge economy. This objective is met by advancing knowledge in the field of evidence-based innovation policy and developing novel measurement methodologies for intangibles. Most of our efforts are focused on three areas: Intellectual Property Policy; Measurement of Intangibles; and Measurement of Scientific Productivity.
Intellectual Property (IP) Policy Two main topics are the optimal design of the IP system and the role of IP in the market for technology. As an illustration of the first topic, we are studying how fees affect the demand for IP protection. We have produced world-first estimates of the price elasticity of demand for patents [A, B, C] and have showed that patent fees can be used to filter out low-quality patent applications [D]. Current work focuses on understanding how the structure of fees affects the backlog at patent offices [E]. The second topic seeks to advance knowledge on the effect of IP in the market for technology [F, G] and in particular on SME and startup financing [G, H]. For example we have shown in [H] that the collateralization of patents facilitates startups’ access to venture debt loans.
Measurement of Intangibles As developed countries move into the knowledge economy, it becomes important to measure its components in a scientifically rigorous way. We have focused our efforts on issues related to the measurement of innovation activities and to the measurement of higher education systems. Regarding the first topic, we seek to improve the measurement of innovation with patent data [I, J, K]. For example, we have proposed in [K] a novel patent-based indicator that is made freely available. Current work focuses on trademark data. Regarding the second topic, we have suggested a series of measures for benchmarking higher education systems [L, M] with a view of helping governments share best practices amongst themselves.
Measurement of Scientific Productivity The increased competitiveness of allocation of research funds calls for an improved understanding of the productivity of scientists. This new line of research seeks to move beyond traditional bibliometric indicators and propose radically new ways of thinking about productivity. In particular, we aim to better grasp scientists’ contribution to knowledge and measure the ‘real impact’ of science.