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on Innovation |
| By: | Davide M. Coluccia; Gaia Dossi |
| Abstract: | This paper documents that out-migration promotes the diffusion of innovation from the country of destination to the country of origin of migrants. Between 1870 and 1940, nearly four million British immigrants settled in the United States. We construct a novel individual-level dataset linking British immigrants in the US to the UK census, and we digitize the universe of UK patents from 1853 to 1899. Using a triple-differences design, we show that migration ties contribute to technology diffusion from the destination to the origin country. The text analysis of patents reveals that emigration promotes technology transfer and fosters the production of high-impact innovation. Return migration is an important driver of this "return innovation" effect. However, the interactions between emigrants and their origin communities - families and neighbors - promote technology diffusion even in the absence of migrants' physical return. |
| Keywords: | age of mass migration, innovation, networks, out-migration |
| Date: | 2025–01–27 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2069 |
| By: | Stefania Albanesi (Department of Economics, University of Miami) |
| Abstract: | We examine the link between labour market developments and new technologies such as artificial intelligence (AI) and software in 16 European countries over the period 2011- 2019. Using data for occupations at the 3-digit level in Europe, we find that on average employment shares have increased in occupations more exposed to AI. This is particularly the case for occupations with a relatively higher proportion of younger and skilled workers. This evidence is in line with the Skill Biased Technological Change theory. While there exists heterogeneity across countries, only very few countries show a decline in employment shares of occupations more exposed to AI-enabled automation. Country heterogeneity for this result seems to be linked to the pace of technology diffusion and education, but also to the level of product market regulation (competition) and employment protection laws. In contrast to the findings for employment, we find little evidence for a relationship between wages and potential exposures to new technologies. |
| Keywords: | artificial intelligence, employment, skills, occupations |
| JEL: | J23 O33 |
| Date: | 2023–06–15 |
| URL: | https://d.repec.org/n?u=RePEc:mia:wpaper:wp2023-01 |
| By: | Eric Iversen; Arvid Raknerud (Statistics Norway); Marit Klemetsen; Brita Bye (Statistics Norway) |
| Abstract: | What difference does government support of business R&D make to the rate of innovation? Addressing this important question has deep theoretical roots and broadening practical applications in OECD countries. The analysis of output additionality has been hampered by incomplete data combined with adaption of problematic methodologies. In this light, we contribute to the formative literature in three main ways: we analyze comprehensive panel data of Norwegian enterprises over a 20-year period; we include trademarks and industrial designs as well as patents to broaden measures of innovation output; and we apply machine learning methods to estimate treatment effect functions, thereby addressing the problem of a practically unlimited number of potential confounding factors. Our findings support and elaborate earlier work that fiscal stimulus tends to have greatest impact on previously non-innovative firms. The impact of support measures, alone or in combination, is on the extensive rather than intensive margin. For previously R&D-active firms, our results indicate that public support has low additionality and even risks crowding-out private financing of R&D. |
| Keywords: | Innovation; R&D support; Output additionality; Intellectual property rights; Patents; Trademarks; Public policy instruments; Lasso; Double selection; Poisson regression |
| JEL: | C33 C52 O31 O34 O38 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:ssb:dispap:1020 |
| By: | Dirk Czarnitzki; Robin Lepers; Maikel Pellens |
| Abstract: | The circular economy represents a systematic shift in production and consumption, aimed at extending the life cycle of products and materials while minimizing resource use and waste. Achieving the goals of the circular economy presents firms with the challenge of innovating new products, technologies, and business models, however. This paper explores the role of artificial intelligence as an enabler of circular economy innovations. Through an empirical analysis of the German Community Innovation Survey, we show that firms investing in artificial intelligence are more likely to introduce circular economy innovations than those that do not. Additionally, the results indicate that the use of artificial intelligence enhances firms’ abilities to lower production externalities (for instance, reducing pollution) through these innovations. The findings of this paper underscore artificial intelligence’s potential to accelerate the transition to the circular economy. |
| Keywords: | Circular economy, Innovation, Artificial intelligence |
| Date: | 2025–01–23 |
| URL: | https://d.repec.org/n?u=RePEc:ete:msiper:758339 |
| By: | Carleton, Tamara; Cockayne, William |
| Abstract: | A rise of government funding agencies dedicated to radical innovation has occurred in recent years. When launching bold and ambitious programs marked by radical uncertainty and unknowable outcomes, how do innovation-funding organizations deliberately provoke risk-taking behavior in potential applicants? This study focuses on the interplay between risk perception and decision making for deliberate high-risk decisions. We compare the language used in 81 public funding calls and new program solicitations from four US government funding entities, which comprise DARPA (Defense Advanced Research Projects Agency), the Defense Innovation Unit, the NASA Innovative Advanced Concepts program, and ARPA-H. A list of potential signal phrases was derived, indicating a spectrum of corresponding risk levels for an innovation opportunity. A survey with 92 evaluators validated that certain keywords served as provocations to trigger risk taking in the pursuit of transformative breakthroughs and frontier science. Our work contributes to a lexicon of signal phrases for provoking and communicating innovation, especially for far-reaching programs. More broadly, understanding the impact of language on decision making under high-risk conditions can inform national innovation policy and strategy for other funding organizations seeking to induce scientific and technological advancement in the United States and globally. |
| Date: | 2025–01–20 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:aqgf8 |
| By: | Patrick Llerena; Corentin Lobet; Andr\'e Lorentz |
| Abstract: | We propose a disaggregated representation of production using an agent-based fund-flow model that emphasizes inefficiencies, such as factor idleness and production instability, and allows us to explore their emergence through simulations. The model incorporates productivity dynamics (learning and depreciation) and is extended with time-saving process innovations. Specifically, we assume workers possess inherent creativity that flourishes during idle periods. The firm, rather than laying off idle workers, is assumed to harness this potential by involving them in the innovation process. Results show that a firm's organizational and managerial decisions, the temporal structure of the production system, the degree of workers' learning and forgetting, and the pace of innovation are critical factors influencing production efficiency in both the short and long term. The coevolution of production and innovation processes emerges in our model through the two-sided effects of idleness: the loss of skills through forgetting and the deflection of time from the production of goods to the production of ideas giving birth to idleness-driven innovations. In doing so, it allows us to question the status of labour as an adjustment variable in a productive organisation. The paper concludes by discussing potential solutions to this issue and suggesting avenues for future research. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.09778 |
| By: | Silvia Appelt; Matej Bajgar; Chiara Criscuolo; Fernando Galindo-Rueda |
| Abstract: | Recent firm-level studies find R&D tax incentives to be much more effective at stimulating firms' R&D investment than what aggregate analyses indicate. Based on a distributed analysis of official R&D survey and administrative tax relief micro-data for 19 OECD countries, we show that two factors can reconcile these contrasting results. Firstly, a limited uptake of R&D tax incentives in most countries makes aggregate studies underestimate the effectiveness of R&D tax incentives. Secondly, R&D tax incentives are (much) less effective for large and R&D-intensive firms, which account for a small share of R&D-performing firms but most aggregate R&D tax relief, making firm-level studies overstate the aggregate effectiveness of R&D tax incentives. |
| Keywords: | mental health, employment, earnings, policy evaluation, psychological therapies |
| Date: | 2025–01–29 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2071 |
| By: | Julio Saavedra |
| Abstract: | AbstractThe European Union faces several simultaneous threats to its competitiveness: weakness in the industries of the future, insufficient innovation, expensive energy, the need to green its economy, and geopolitical and trade shifts, to name but a few. The EconPol Europe Annual Conference, on whose proceedings this policy brief is based, focused on three aspects that could make a substantial contribution to securing prosperity in the EU, but are in a lamentable state: they all currently fall far short of their potential. These are the power of the single market, the level of its innovation, and the capacity to defend itself. Both the high-level speakers at the conference as well as EconPol and ifo research make clear that some low-hanging fruit are there for the taking, if only the political will were there, a good dose of national chauvinism could be overcome, and an effective communication campaign were undertaken to explain to voters why some measures are not only necessary, but unavoidable. Key MessagesTo secure its future prosperity, Europe needs to tackle three principal challenges to its competitiveness: leveraging the power of its single market, improving its level of innovation, and building the capacity to defend itself.Policy measures to reduce non-tariff barriers for the EU’s trade in services should include the EU-wide standardization of qualifications, and the digitalization of public administrations and services.To boost growth by fostering disruptive technologies, EU innovation policy should be technology-neutral, competitively awarded, and designed to lever-age the powers of public procurement and of the EU single market. Maintaining peace by preparing for war must be the guiding principle when it comes to European defense policy. The EU must create a single market for defense and implement a collectively borrowed fund, similar to the €750 billion COVID recovery fund. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:econpb:_68 |
| By: | VEUGELERS Reinhilde; AMARAL-GARCIA Sofia (European Commission - JRC) |
| Abstract: | The EU is challenged by a persistent leadership gap in the global health innovation landscape, with the US leading in corporate health innovation and venture capital (VC) funding. The EU health innovation landscape is more concentrated in older "incumbent leading firms, " while the US has a more dynamic landscape with higher R&D growth rates. Financing constraints are highly relevant in the health sector, particularly for startups and scale-ups with risky breakthrough ideas and technologies. The EU-US gap in dynamic innovative performance in health may be partly due to differences in access to risk finance, particularly venture capital. This paper analyzes trends in VC financing for health-related innovations in Europe compared to the US, using data from Dealroom. The results show that the weakness of the European health VC market continues to hold in the early and late stages, where less progress seems to have been made. Some of the main findings include the following: the EU is lagging behind the US in the number of health VC deals, with a larger gap in late-stage deals; European deal sizes are below the US, with a larger gap in late-stage deals, the EU has a lower occurrence of co-investment deals, which does not help reduce the gap in health VC deals. Overall, the European health VC market is particularly missing larger-sized investors (investment funds) with late-stage deals. To address this gap, policy attention is needed to identify and reduce barriers for European health VC investors to grow to a critical scale and engage in a higher number and larger-sized deals. All in all, Europe should further develop and strengthen its strongest asset, i.e., its Open Single Market, reducing the fragmentation in flows of venture capital, reaching a truly single European Venture Capital market. For an EU open strategic autonomy industrial policy for health, an open single market for health remains the critical instrument to further develop and monitor. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:ipt:wpaper:202501 |
| By: | Theresa Gullo; Benjamin Page; David Weiner; Heidi L. Williams |
| Abstract: | Many US federal agencies model the economic and budgetary effects of research and development (R&D) investments -- both public R&D and private R&D -- as if R&D were the same as any other form of investment, such as physical capital investment. However, in recent decades a broad base of evidence has developed suggesting that such modeling may result in projections that are not well-aligned with the actual economic and budgetary effects of R&D investments. In this paper, we attempt to synthesize the economic evidence relevant to estimating the economic and budgetary effects of R&D, and examine how and where this research literature could potentially be incorporated into the standard projections produced by various federal agencies. |
| JEL: | O0 O30 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33402 |
| By: | Mahyar Habibi |
| Abstract: | This paper explores the economic underpinnings of open sourcing advanced large language models (LLMs) by for-profit companies. Empirical analysis reveals that: (1) LLMs are compatible with R&D portfolios of numerous technologically differentiated firms; (2) open-sourcing likelihood decreases with an LLM's performance edge over rivals, but increases for models from large tech companies; and (3) open-sourcing an advanced LLM led to an increase in research-related activities. Motivated by these findings, a theoretical framework is developed to examine factors influencing a profit-maximizing firm's open-sourcing decision. The analysis frames this decision as a trade-off between accelerating technology growth and securing immediate financial returns. A key prediction from the theoretical analysis is an inverted-U-shaped relationship between the owner's size, measured by its share of LLM-compatible applications, and its propensity to open source the LLM. This finding suggests that moderate market concentration may be beneficial to the open source ecosystems of multi-purpose software technologies. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.11581 |
| By: | Siddharth, L.; Luo, Jianxi |
| Abstract: | The rapid integration of AI in products, services, and innovation processes has enabled transformative applications, raising global concerns about the trustworthiness of AI features and the corresponding development processes. In this paper, we provide a perspective on how design and innovation processes can be adapted to ensure the trustworthiness of AI-centric artefacts. We review generic recommendations for trustworthy AI provided by various organisations and scholars. By leveraging the “double-hump” model of data-driven innovation, we explain and illustrate how trustworthy AI could be integrated into the design and innovation processes. We then propose research directions, data, and methods that could help gather an empirical understanding of trustworthiness and thus lead to an assessment of existing AI artefacts for trustworthiness. Since there is a disparity among domains and organisations in terms of AI-related risk and maturity, we expect that the proposed process model and the assessment methods could contribute towards a reliable road map for the development and assessment of trustworthy AI. |
| Date: | 2025–01–20 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:a3d6z |