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Publications & Documents


  • 8-July-2021

    English

    New evidence on intangibles, diffusion and productivity

    This paper presents new evidence on the impact of intangible capital on productivity dispersion within industries. It first shows that rise in productivity dispersion after 2000 is more pronounced in intangible-intensive industries; then analyses the link between intangible capital intensity and productivity dispersion both at the top and at the bottom of the productivity distribution, and in different industries. The findings suggest that industries that have experienced a stronger increase in intangible investment have also seen a steeper rise in productivity dispersion both at the top and at the bottom of the productivity distribution. While the results at the top seem to be associated with the scalability of intangible capital – which is likely to disproportionally benefit high-productivity firms and incumbents – dispersion at the bottom appears to be linked to complementarities between intangible investment and factors like digital intensity, trade openness and venture capital.
  • 8-July-2021

    English

    The return on human (STEM) capital in Belgium

    Whilst overall productivity growth is stalling, firms at the frontier are still able to capture the benefits of the newest technologies and business practices. This paper uses linked employer-employee data covering all Belgian firms over a period of almost 20 years and investigates the differences in human capital between highly productive firms and less productive firms. We find a clear positive correlation between the share of high-skilled and STEM workers in a firm's workforce and its productivity. We obtain elasticities of 0.20 to 0.70 for a firm's productivity as a function of the share of high-skilled workers. For STEM (science, technology, engineering, mathematics) workers, of all skill levels, we find elasticities of 0.20 to 0.45. More importantly, the elasticity of STEM workers is increasing over time, whereas the elasticity of high-skilled workers is decreasing. This is possibly linked with the increasing number of tertiary education graduates and at the same time increased difficulties in filling STEM-related vacancies. Specifically, for high-skilled STEM workers in the manufacturing sector, the productivity gain can be as much as 4 times higher than the gain from hiring additional high-skilled non-STEM workers. To ensure that government efforts to increase the adoption of the latest technologies and business practices within firms lead to sustainable productivity gains, such actions should be accompanied by measures to increase the supply and mobility of human (STEM) capital. Without a proper supply of skills, firms will not be able to reap the full benefits of the digital revolution.
  • 28-June-2021

    English

    Workshop on access to research data from public funding: The case of marine data

    This webinar on 28 June aims to reflect on the growing importance of marine data for society and solutions to make the provision of public marine research data more sustainable. discussions will be structured around sustainability issues for data infrastructure (particularly funding aspects) and the importance of International co-operation for access to research data.

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  • 28-June-2021

    English

    Targeting R&D intensity in Finnish innovation policy

    Finland has been setting research and development (R&D) intensity targets for almost 50 years. This paper explores the Finnish national policy experience in fostering public and private investments in R&D. Three key insights are the following: a) a systemic and integrated policy approach needs an impactful co-ordination and governance mechanism; b) a balanced innovation system with well-working joint public-private partnership efforts and mechanisms will do better in absorbing shocks; c) a key strategy to absorb shocks to the economy and society is to invest in long-term capabilities. This study also provides an overview of the factors influencing the level of R&D intensity. The current 4% target to be reached by 2030 was set in 2019 but thus far relatively few policy actions have been introduced to operationalise it. With these dynamics and uncertainty, it remains to be seen if the target will be reached by 2030.
  • 28-June-2021

    English

    Measuring the AI content of government-funded R&D projects - A proof of concept for the OECD Fundstat initiative

    This report presents the results of a proof of concept for a new analytical infrastructure ('Fundstat') for analysing government funding of R&D at the project level, exploiting the wealth of text-based information about funded projects. Reflecting the growth in popularity of artificial intelligence (AI) and the OECD Council Recommendation on AI’s emphasis on R&D investment, the report focuses on analysing government investments into AI-related R&D. Using text mining tools, it documents the creation of a list of key terms used to identify AI-related R&D projects contained in 13 funding databases from eight OECD countries and the EU, provides estimates for the total number and volume of government R&D funding, and characterises their AI funding portfolio. The methods and findings developed in this study also serve as a prototype for a new distributed mechanism capable of measuring and analysing government R&D support across key OECD priority areas and topics.
  • 28-June-2021

    English

    Tools for trustworthy AI - A framework to compare implementation tools for trustworthy AI systems

    As artificial intelligence (AI) advances across economies and societies, stakeholder communities are actively exploring how best to encourage the design, development, deployment and use of AI that is human-centred and trustworthy. This report presents a framework for comparing tools and practices to implement trustworthy AI systems as set out in the OECD AI Principles. The framework aims to help collect, structure and share information, knowledge and lessons learned to date on tools, practices and approaches for implementing trustworthy AI. As such, it provides a way to compare tools in different use contexts. The framework will serve as the basis for the development of an interactive, publicly available database on the OECD.AI Policy Observatory. This report informs ongoing OECD work towards helping policy makers and other stakeholders implement the OECD AI Principles in practice.
  • 23-juin-2021

    Français

    Comment la pandémie de COVID-19 va-t-elle remodeler la science, la technologie et l’innovation ?

    Les effets disparates de la crise du COVID-19 sur la R-D dans les différents secteurs, l’accélération de l’adoption des outils numériques et des techniques connexes, et l’évolution du degré d’ouverture, de l’inclusivité et de l’agilité des écosystèmes de recherche et d’innovation sont autant de facteurs qui façonnent l’avenir de la STI.

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  • 23-June-2021

    English

    How will COVID-19 reshape science, technology and innovation?

    Factors shaping the future of STI include the unequal effects of the pandemic on R&D across sectors, the accelerated adoption of digital tools and techniques, and changes in the openness, inclusiveness and agility of research and innovation ecosystems.

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  • 21-June-2021

    English

    OECD Biotechnology Update

    Read our newsletter to stay up-to-date with all the latest OECD work on biotechnology.

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  • 18-June-2021

    English

    State of implementation of the OECD AI Principles - Insights from national AI policies

    This is the first report on the state of implementation of the policy recommendations to governments contained in the OECD Principles on Artificial Intelligence adopted in May 2019. This report presents a conceptual framework, provides findings, identifies good practices, and examines emerging trends in AI policy, particularly on how countries are implementing the five recommendations to policy makers contained in the OECD AI Principles. The report builds both on the expert input provided at meetings of the OECD.AI Network of Experts working group on national AI policies that took place online from February 2020 to April 2021 and on the EC-OECD database of national AI strategies and policies. As policy makers and AI actors around the world move from principles to implementation, this report aims to inform the implementation of the OECD AI Principles. This report is also a contribution to the OECD AI Policy Observatory.
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