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  • 12-December-2023

    English

    Doombot: a machine learning algorithm for predicting downturns in OECD countries

    This paper describes an algorithm, 'DoomBot', which selects parsimonious models to predict downturns over different quarterly horizons covering the ensuing two years for 20 OECD countries. The models are country- and horizon-specific and are automatically updated as the estimation sample period is extended, so facilitating out-of-sample evaluation of the algorithm. A limited combination of explanatory variables is chosen from a much larger pool of potential variables that include those that have been most useful in predicting downturns in previous OECD work. The most frequently selected variables are financial variables, especially those relating to credit and house prices, but also include equity prices and various measures of interest rates (such as the slope of the yield curve). Business cycle variables -- survey measure of capacity utilisation, industrial production, GDP and unemployment -- are also selected, but more frequently at very short horizons. The variables selected do not just relate to the domestic economy of the country being considered, but also international aggregates, consistent with findings from previous OECD work. The in-sample fit of the models is very good on standard performance metrics, although the out-of-sample performance is less impressive. The models do, however, provide a clear out-of-sample early warning of the Global Financial Crisis (GFC), especially when considered collectively, although they do generate ‘false alarms’ just ahead of the crisis. The models are less good at predicting the euro area crisis out-of-sample, but it is clear from the evolution of the choice of variables that the algorithm learns from this episode, for example through the more frequent selection of a variable measuring euro area sovereign bond spreads. The latest out-of-sample predictions made in mid-2023, suggest the probability of a downturn is at its greatest and most widespread since the GFC, with the largest contributions to such risks coming from house prices, interest rate developments (as measured by the slope of the yield curve and the rapidity of the change in short rates) and oil prices. On the other hand, warning signals from business cycle variables and equity prices, which are often good downturn predictors at short horizons, are conspicuously absent.
  • 4-December-2023

    English

    Unlocking co-creation for green innovation - An exploration of the diverse contributions of universities

    In the context of the green transition, universities have much to offer in joint green innovation projects with business, government and citizens. As hubs of diverse expertise, universities are uniquely placed to build interdisciplinary teams and bridge gaps between society and industry. Their regional ties also enable them to engage with the local ecosystem. This paper draws from ten international case studies of university partnerships with industry and society in green mobility, green energy and green products, services and processes. The comparative evidence gathered from interviews with representatives from these initiatives examines universities’ practices for green co-creation. Additionally, the paper outlines policy recommendations crucial to supporting these initiatives, essential for the global success of sustainable development efforts.
  • 30-November-2023

    English

    Business innovation statistics and indicators

    The OECD Innovation Indicators database is a compendium of statistics about the innovation activities and outcomes of firms across OECD member countries and partner economies.

    Related Documents
  • 30-November-2023

    English

    Carbon Management: Bioeconomy and Beyond

    The bioeconomy brings opportunities for economic growth while tackling climate change. Fossil carbon resources can be replaced by bio-based carbon resources, especially biomass. To allow these solutions to be scaled up without threats to biodiversity and the environment, it is necessary to develop the bioeconomy as a circular economy. With this carbon management approach, other sources of carbon complement biomass: industrial waste, including gases such as CO and CO2, as well as physically and chemically recycled carbon. In the future, direct air capture (DAC) may become competitive and form part of the solution. These approaches can be considered ‘circular’ because they close material loops and keep carbon recycling in the economy rather than emitting carbon to the atmosphere. This report reviews a number of hybrid technologies that can be deployed to ‘defossilise’ economic sectors and sets out policy options to bring these technologies to commercial scale.
  • 30-November-2023

    English

    Navigating green and digital transitions - Five imperatives for effective STI policy

    This paper discusses five innovation policy imperatives critical to achieving green and digital transitions: coordinated government, stakeholder engagement, policy agility and experimentation, directionality and support for breakthrough innovation. The paper provides policy examples from Germany, based on the OECD Review of Innovation Policy: Germany , and other countries to illustrate in what ways countries have addressed these imperatives. Overall, the quality and scale of these policy responses need to increase if transitions are to succeed. Open questions for future policy research are also highlighted.
  • 24-November-2023

    English

    Using AI to support people with disability in the labour market - Opportunities and challenges

    People with disability face persisting difficulties in the labour market. There are concerns that AI, if managed poorly, could further exacerbate these challenges. Yet, AI also has the potential to create more inclusive and accommodating environments and might help remove some of the barriers faced by people with disability in the labour market. Building on interviews with more than 70 stakeholders, this report explores the potential of AI to foster employment for people with disability, accounting for both the transformative possibilities of AI-powered solutions and the risks attached to the increased use of AI for people with disability. It also identifies obstacles hindering the use of AI and discusses what governments could do to avoid the risks and seize the opportunities of using AI to support people with disability in the labour market.
  • 24-November-2023

    English

    Income-based tax relief for R&D and innovation - An integrated view

    This document provides an integrated view on income-based tax incentives for R&D and innovation. It brings together the latest evidence on the adoption, design, generosity, cost and take-up of income-based tax incentives, and gives new insights into both the long-term and short-term trends in the take-up of income-based tax incentives by business and their cost to governments, including role of policy design changes. Furthermore, the report explores the scope for developing indicators that provide a more complete picture of the value of expenditure- and income-based tax relief for R&D and innovation in the OECD area and beyond.
  • 20-November-2023

    English

    OECD framework for mapping and quantifying government support for business innovation

    This paper resents a measurement framework aiming to support the collection of comprehensive and internationally comparable quantitative and qualitative information on governmental innovation support programmes and instruments. It proposes a taxonomic system with definitions, classifications and reporting conventions aligned with OECD and other international standards. The framework is intended to support future OECD measurement efforts in this area and the analysis of innovation support portfolios within and across countries.
  • 15-November-2023

    English

    Entrepreneurial opportunities and working conditions of self-employed online freelancers in the platform economy - Lessons from the COVID-19 pandemic

    This paper examines the experiences of self-employed online freelancers working on digital labour platforms during the COVID-19 pandemic. It is based on interviews with freelancers and platform managers and experts in Belgium, France, Italy, the Netherlands and Poland. Their experiences during COVID-19 reveal issues of asymmetric power vis-à-vis platforms. Notably, they reported lack of transparency and certainty in their contracts with platforms, lack of power in negotiating with clients, and limited ability to engage with clients on other platforms. In addition, they often experienced difficulties in accessing government temporary supports for businesses during the pandemic. The paper puts forward policy recommendations to address these issues.
  • 13-November-2023

    English

    What technologies are at the core of AI? - An exploration based on patent data

    This report outlines a new methodology and provides a first exploratory analysis of technologies and applications that are at the core of recent advances in AI. Using AI-related keywords and technology classes, the study identifies AI-related patents protected in the United States in 2000-18. Among those, 'core' AI patents are selected based on their counts of AI-related forward citations. The analysis finds that, compared to other (AI and non-AI) patents, they are more original and general, and tend to be broader in technological scope. Technologies related to general AI, robotics, computer/image vision and recognition/detection are consistently listed among core AI patents, with autonomous driving and deep learning having recently become more prominent. Finally, core AI patents tend to spur innovation across AI-related domains, although some technologies – likely AI applications, such as autonomous driving or robotics – appear to increasingly contribute to developments in their own field.
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