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on Innovation |
| By: | Klein, Michael |
| Abstract: | I develop an endogenous growth model that separates firm decisions to invent, patent, and commercialize new innovations. I use the model to examine how multiple dimensions of patent policy impact economic growth by shaping these relative incentives. I pay particular attention to the role of patenting requirements that dictate how far along the development process an inventor must progress to obtain a patent. The model formalizes how strengthening such requirements generates competing effects on economic growth; stronger requirements reduce ex ante research incentives by increasing the expected cost of patenting, but increase ex post incentives to fully develop patented inventions into commercial innovations by decreasing the additional cost associated with commercialization. Overall, my analysis supports the use of patenting requirements as an effective policy tool to improve economic outcomes by shifting incentives away from invention in the pursuit of patents and towards the development of commercial innovations. |
| Keywords: | Patent policy; Patenting requirements; Invention; Innovation; Economic growth |
| JEL: | O31 O34 O43 |
| Date: | 2024–09–16 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:122283 |
| By: | Joonkyu Choi; Nathan Goldschlag; John Haltiwanger; J. Daniel Kim |
| Abstract: | Using administrative data from the U.S. Census Bureau, we introduce a new public-use database that tracks activities across firm growth distributions over time. With these new data, we uncover several key trends for high-growth firms---critical engines of innovation and economic growth. First, the share of firms that are high-growth has steadily decreased over the past four decades, driven not only by falling rates of entrepreneurship but also languishing growth among existing firms. Second, this decline is particularly pronounced among young and small firms, while the share of high-growth firms has been relatively stable among large and old firms. We also find rich variation across states and sectors. To facilitate future research, we highlight how these data can be used to address various research questions. |
| Keywords: | Organizational Growth; Entrepreneurship; High-Growth Firms; Business Dynamism; Publicly Available Dataset |
| JEL: | L11 L25 L26 O30 O40 |
| Date: | 2024–09–20 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2024-74 |
| By: | Kattel, Rainer |
| Abstract: | The European Union, in the face of mounting geo-political and climate challenges, needs a more effective innovation policy. Currently, its broad experimentalist approach to innovation policies gives Member States and regions autonomy for policy design. However, this often needs more effective organisations and capabilities to take advantage of the policy space. Thus, European countries face quite a substantial rethinking of how innovation policy is designed and implemented through innovation agencies. This policy paper argues that on all levels of European governance, policymakers should pay closer attention to designing and developing organisational ecosystems for innovation, focusing on fostering new capabilities. The paper starts with the assumption that European innovation agencies today face two broad challenges. First, they are tasked with, or engaged in, transforming socio-technical systems (e.g., food, mobility); and second, socio-technical systems fall under over-lapping systems of governance (e.g., food system includes elements from energy, waste management, health, and other policy areas), typically governed by different bodies. The transformation challenge indicates that innovation agencies require a broad spectrum of new capabilities across multiple systems. The governance challenge indicates the need for inter-organisational or distributed capabilities (e.g., division of labour and coordination across multiple organisations). This report discusses how innovation agencies are responding to this dual challenge and what critical steps could be taken to increase their capabilities to tackle the challenges effectively. |
| Keywords: | innovation, governance, innovation agencies, agile stability |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:oefsew:304309 |
| By: | Latifi, Albina; Winker, Peter; Lenz, David |
| JEL: | C49 C55 O30 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:vfsc24:302371 |
| By: | Koen Frenken; Frank Neffke; ; ; |
| Abstract: | The global economy operates as a complex system that allocates resources in a decentralized way across myriad agents. Over time, it exhibits an impressive rate of collective learning as evidenced by its growing productivity and the expanding variety of output it generates. However, growth, productivity and learning are not distributed equally across locations. On the contrary, wealth, opportunity, economic activity and innovation tend to all concentrate in a relatively small number of affluent places. Various strands of complexity Science have contributed to our understanding of these phenomena. However, they have done so in disconnected debates and communities. In this chapter, we use the framework of Economic Complexity to synthesize insights derived from three distinct literatures: urban scaling, evolutionary economic geography and global production networks. Economic complexity proposes that production requires access to capabilities, such that increasing the variety of economic production requires acquiring or accessing new capabilities. From this synthesis, we derive a research agenda that aims to understand how local economies develop, not only as individual units exploring their adjacent possible, but as parts of a system that allows local economies to mix their capabilities with those of distant counterparts by relying on the interplay of multinational corporations, global value chains and institutions to coordinate interactions at the local and global scale. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2431 |
| By: | Nicolas Ameye; Jacques Bughin; Nicolas van Zeebroeck |
| Date: | 2024–10–14 |
| URL: | https://d.repec.org/n?u=RePEc:ulb:ulbeco:2013/378623 |
| By: | Wei Cheng; Bruce A. Weinberg |
| Abstract: | The adoption of new ideas is critical for realizing their full potential and for advancing the knowledge frontier but it involves analyzing innovators, potential adopters, and the networks that connect them. This paper applies natural language processing, network analysis, and a novel fixed effects strategy to study how the aging of the biomedical research workforce affects idea adoption. We show that the relationship between adoption and innovator career age varies with network distance. Specifically, at short distances, young innovators’ ideas are adopted the most, while at greater network distances, mid-career innovators’ ideas have the highest adoption. The main reason for this contrast is that young innovators are close to young potential adopters who are more open to new ideas, but mid-career innovators are more central in networks. Overall adoption is hump-shaped in the career age of innovators. Simulations show that the aging of innovators and of potential adopters have comparable effects on the adoption of important new ideas. |
| JEL: | D85 J11 O33 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33030 |
| By: | Draca, Mirko (CEP, London School of Economics ; Warwick University and CAGE Research Centre); Nathan, Max (CEP, London School of Economics ; Warwick University and CAGE Research Centre ; University College London); Nguyen-Tien, Viet (CEP, London School of Economics ; POID, London School of Economics); Oliveira-Cunha, Juliana (CEP, London School of Economics ; IGC, London School of Economics); Rosso, Anna (CEP, London School of Economics ; University of Insubria); Valero, Anna (CEP, London School of Economics ; POID, London School of Economics) |
| Abstract: | Which types of human capital influence the adoption of advanced technologies? We study the skill-biased adoption of information and communication technologies (ICT) across two waves in the UK. Specifically, we compare the new wave of cloud and machine learning / AI technologies during the 2010s - pre-LLM - with the previous wave of personal computer adoption in the 1990s and early 2000s. At the area-level we see the emergence of a distinct STEM-biased adoption effect for the second wave of cloud and machine learning / AI technologies (ML/AI), alongside a general skill-biased effect. A one-standard deviation increase in the baseline share of STEM workers in areas is associated with around 0.3 of a standard deviation higher adoption of cloud and ML/AI. We find similar effects at the firm level where we are able to test for the influence of a wide range of skills. In turn, this STEM-biased adoption pattern has encouraged the concentration of these technologies, leading to more acute differences between high-tech and low-tech areas and firms. In contrast with classical technology diffusion, recent cloud and ML/AI adoption in the UK seems more likely to widen inequalities than reduce them |
| Keywords: | Technology Diffusion ; ICT ; Human Capital ; STEM JEL Codes: D22 ; J24 ; O33 ; R11 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1521 |
| By: | Flora Bellone (Université Côte d'Azur, CNRS, GREDEG, France; OFCE, SciencePo); Arnaud Persenda (Université Côte d'Azur, CNRS, GREDEG, France); Paolo Zeppini (Université Côte d'Azur, CNRS, GREDEG, France; University of Bath, UK) |
| Abstract: | In this paper we revisit the emergence of China as a dominant player within the world economy by using the innovative framework of autocatalytic networks. Specifically, we build and apply an autocatalylic sets detection algorithm to a world input-output (IO) network built from the WIOD database, covering the 2000-2014 period. From this analysis, we identify two key turning points in the course of China development: First, the year 2005, when a Chinese densifying local autocatalytic set branched to a global one, unraveling the complementarity between domestic and international cyclical IO connections in the course of China development. Second, the year 2013, when key Chinese industries replace their U.S. counterparts at the core of the global autocatalytic set, revealing an economic rivalry between these two large economies specifically for their role and position in the global production network. |
| Keywords: | Autocatalytic networks, Trade, Input-Output tables, China |
| JEL: | F63 O14 D57 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:gre:wpaper:2024-26 |
| By: | Rodepeter, Elisa; Gschnaidtner, Christoph; Hottenrott, Hanna |
| JEL: | L26 O32 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:vfsc24:302358 |