Latest Documents

This paper describes the methodology used for crosswalking occupation-based measures of Green ('environmentally friendly') and Brown ('polluting') jobs from the Standard Occupational Classification (SOC) system to the International Standard Occupation Classification (ISCO) 08 at the most detailed (4-digit) level. The original, task-based Greenness scores by Vona et al. (2018) are provided at the 8-digit SOC level, and the industry-based Brownness measures are provided in 6-digit SOC. Crosswalking these measures requires several choices in terms of weighting and aggregating, which this paper describes in detail. The robustness of the resulting measures to the different weighting options and underlying assumption is tested using Linked Employer-Employee data from Portugal. An empirical application to the Productivity-Greenness link at the firm level shows the robustness of this link to different weighting choices, and confirms that all of the different measures derived are consistent in measuring the Greenness of jobs.

This report provides input to a national review of the public research funding system in Sweden. It is designed to inform a broader dialogue that is taking place amongst different research stakeholders in Sweden. The report contains proposals and options for changes for Swedish public funding of research and innovation to effectively promote research excellence, support innovation and respond to societal needs. These proposals are supported by relevant international examples. The analysis takes into account insights from the OECD review of innovation policy in Sweden in 2016 and recent OECD work on different aspects of public research funding and research infrastructure.

This report uses business consultations to investigate private-sector views on privacy and data protection rules for cross-border data flows. It aims to inform a more comprehensive understanding of challenges and ways forward for the policy agenda of ‘data free flow with trust’. While frameworks aimed at generating trust and facilitating data flows build on commonalities and elements of convergence, businesses identify challenges to fully operationalise them at the global level. In particular, businesses indicate the need for coherent principles and rules that are transparent and predictable, provide a practical balance between certainty and flexibility, and offer solutions that match business realities. Finally, the report highlights the need for greater international regulatory co-operation and leveraging the full range of options to uphold trust around privacy and data protection globally.

The rapid pace of technological change, coupled with a pressing need for solutions to address grand societal challenges and global crises, heightens the challenge for policy makers to develop science, technology and innovation policies at speed, in situations of high uncertainty and, in some cases, around potentially controversial technology fields. Technology assessment (TA) has a long history of providing decision-makers with timely strategic intelligence on emerging technologies. Current demands are pushing TA to evolve in order to fulfil diverse functions: to illuminate the societal, economic, environmental and other consequences of new technologies; to inform public opinion; and to guide research and development. Drawing on nine case studies, this report analyses the response of TA practices to these changing drivers and demands to support policies for new and emerging technologies. It also identifies a set of principles to guide good contemporary TA practice.

This report analyses subsidies provided to steel producers by examining firm-level data from the Organisation for Economic Co-operation and Development (OECD) and conducting desk research. It reveals that subsidy trends persist even in the face of existing overcapacity. Between 2008 and 2020, steel companies in partner economies obtained an average of 10.7 times more subsidies per crude steel production capacity unit than their counterparts in OECD countries. These subsidies took the form of cash grants, cash awards, and cost reimbursements. The report also finds that the national context significantly influences a jurisdiction's inclination to support its steel sector and the transparency of such subsidies. Some jurisdictions have prioritised the growth of their domestic steel industry by establishing firm goals for crude steel production, export, or concentration. Meanwhile, others have engaged in international collaboration to address global challenges related to the decarbonisation of the steel industry.

Despite the increasing adoption of income-based tax incentives for R&D and innovation in the OECD area and beyond, evidence on the availability, design, generosity and actual cost of these incentives remains scarce. This report helps fill this gap by documenting government efforts to provide preferential tax treatment of economic outputs of innovation activities. Drawing on the responses of national contact points to the OECD KNOWINTAX surveys carried out in 2020 and 2021, it presents new evidence on the cost (foregone tax revenues) and uptake of income-based-tax incentives by businesses in 2019, and tracks their distribution by firm size and industry and their evolution over the 2000-2019 period.

AI language models are a key component of natural language processing (NLP), a field of artificial intelligence (AI) focused on enabling computers to understand and generate human language. Language models and other NLP approaches involve developing algorithms and models that can process, analyse and generate natural language text or speech trained on vast amounts of data using techniques ranging from rule-based approaches to statistical models and deep learning. The application of language models is diverse and includes text completion, language translation, chatbots, virtual assistants and speech recognition. This report offers an overview of the AI language model and NLP landscape with current and emerging policy responses from around the world. It explores the basic building blocks of language models from a technical perspective using the OECD Framework for the Classification of AI Systems. The report also presents policy considerations through the lens of the OECD AI Principles.

This report analyses the use of artificial intelligence (AI) in firms across 11 countries. Based on harmonised statistical code (AI diffuse) applied to official firm-level surveys, it finds that the use of AI is prevalent in ICT and Professional Services and more widespread across large – and to some extent across young – firms. AI users tend to be more productive, especially the largest ones. Complementary assets, including ICT skills, high-speed digital infrastructure, and the use of other digital technologies, which are significantly related to the use of AI, appear to play a critical role in the productivity advantages of AI users.