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Open government data has become a vital instrument for addressing both longstanding and emerging policy issues. In particular, the recent pandemic and the green transition have underscored the need for governments to ensure access to timely, relevant, and high-quality data to foster resilience and facilitate a comprehensive whole-of-society response. This paper presents the main findings of the fourth edition of the OECD Open, Useful, and Re-usable data (OURdata) Index for 2023, which benchmarks efforts made by governments to design and implement national open government data policies. It encompasses over 670 data points collected from 36 OECD countries and 4 accession countries throughout 2022.

This report aims to showcase the value of implementing a Bayesian framework to analyse and report results from international large-scale surveys and provide guidance to users who want to analyse the data using this approach. The motivation for this report stems from the recognition that Bayesian statistical inference is fast becoming a popular methodological framework for the analysis of educational data generally, and large-scale surveys more specifically. The report argues that Bayesian statistical methods can provide a more nuanced analysis of results of policy relevance compared to standard frequentist approaches commonly found in large-scale survey reports. The data utilised for this report comes from the OECD Teaching and Learning International Survey (TALIS). The report provides steps in implementing a Bayesian analysis and proposes a workflow that can be applied not only to TALIS but to large-scale surveys in general. The report closes with discussion of other Bayesian approaches to international large-scale survey data, in particularly for predictive modelling.

Croatia’s labour market has made important progress over the past decade. Employment rates are rising, reducing the gap with OECD countries, and poverty has fallen. While important weaknesses remain, many dimensions of equity and working conditions are similar to OECD countries. Continuing this progress is essential for Croatia’s incomes and well-being to converge with OECD countries, to counter accelerating population ageing and to make the most of emerging opportunities, including from digitalisation and the green economy transition. For employers, filling increasingly advanced skill needs is a growing obstacle. Relatively few of the young and older adults are in work – contributing to weakening skills, lower incomes and higher poverty risks. Addressing these challenges will require dramatically expanding participation in re-skilling and adult education programmes, and raising the workforce’s flexibility, for example by strengthening active labour market policies, improving the housing market’s dynamism and making the most of immigrants’ and returned emigrants’ skills. This Working Paper relates to the 2023 OECD Economic Survey of Croatia.

Artificial intelligence (AI) is transforming economies and promising new opportunities for productivity, growth, and resilience. Countries are responding with national AI strategies to capitalise on these transformations. However, no country today has data on, or a targeted plan for, national AI compute capacity. This policy blind-spot may jeopardise domestic economic goals. This report provides the first blueprint for policy makers to help assess and plan for the national AI compute capacity needed to enable productivity gains and capture AI’s full economic potential. It provides guidance for policy makers on how to develop a national AI compute plan along three dimensions: capacity (availability and use), effectiveness (people, policy, innovation, access), and resilience (security, sovereignty, sustainability). The report also defines AI compute, takes stock of indicators, datasets, and proxies for measuring national AI compute capacity, and identifies obstacles to measuring and benchmarking national AI compute capacity across countries.

This paper outlines key issues and provides insights to government leaders looking to design and implement initiatives that require joint working across public agencies. The first part of this paper defines key concepts and explores the benefits and related costs of cross-agency initiatives. The second discusses various contextual elements that need to be considered when making decisions about how to design cross-agency initiatives, including the nature of the objectives, the systems of government, and relationships among potential partners. The third section looks at different models across four fundamental elements: governance; people (team support), funding, and performance monitoring. The final section looks at some of the main systemic elements that can support cross-agency initiatives success.

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.

This paper presents a methodological supervisory framework to help central banks and financial supervisors assess biodiversity-related financial risks, impacts and dependencies in the financial sector, including transmission channels for physical and transition risks. This framework is designed to translate biodiversity risks into financial risks. It draws on a previous mapping of existing approaches, while also accounting for broader nature-related financial risks. While acknowledging different national circumstances, this methodological framework is designed to be applicable broadly for central banks, supervisors and commercial banks across different countries.

The Autonomous Province of Bolzano-Bozen, Italy, has embraced the 2030 Agenda through a sustainability pact including its sustainable development strategy "Everyday for Future". The strategy defines seven fields of action that were derived from the SDGs framework to promote sustainability across policy areas such as the conservation of the natural environment, the reduction of greenhouse gas emissions, competitiveness and social justice. The SDGs offer a clear framework to tackle the province’s main territorial development challenges, such as climate change, the transition to sustainable agriculture, mobility, tourism, and affordable housing. This report provides guidance on how to harness the implementation of the SDGs to address these challenges through concrete measures across the seven fields of action, identify and manage synergies and trade-offs between sectoral policies and, in turn, help the province implement Everyday for Future.

To achieve its vision to become one of the most attractive and competitive regions in Europe by 2025, the Rhine-Neckar Metropolitan Region put in place eleven fields of action that promote sustainability across policy areas, such as sustainable and needs-based mobility, regional innovation promotion, regional energy transition and education of the future. This report offers guidance on how the metropolitan region could harness the SDGs as an integrated framework to address its main challenges, including climate change, the impacts of digitalisation on the labour market, territorial disparities among urban and rural areas as well as the co-ordination of actors and policies across three different federal states, notably on funding.

  • 27 Jul 2023
  • Ana Cinta González Cabral, Silvia Appelt, Tibor Hanappi, Fernando Galindo-Rueda, Pierce O’Reilly, Massimo Bucci
  • Pages: 65

The use of tax incentives that provide preferential tax treatment to the incomes arising from research and development (R&D) and innovation activities, such as intellectual property regimes, has accelerated over the last two decades. The globalisation of R&D together with the greater mobility of intangible income may have contributed to the rise in such incentives to attract and retain R&D and innovation activity while preventing the transfer of taxable base to other countries. This paper documents the changes to the availability and design of income-based tax incentives from 2000 onwards for 48 countries, including all OECD countries and EU countries. Building on this, the paper analyses trends in the generosity of income-based tax support over time by building indicators of effective tax rates that can provide insights into the impact of Action 5 of the OECD/G20 Base Erosion and Profit Shifting project.

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.

  • 21 Feb 2023
  • Tomoya Okubo, Wayne Houlden, Paul Montuoro, Nate Reinertsen, Chi Sum Tse, Tanja Bastianic
  • Pages: 34

Artificial Intelligence (AI) scoring for constructed-response items, using recent advancements in multilingual, deep learning techniques utilising models pre-trained with a massive multilingual text corpus, is examined using international large-scale assessment data. Historical student responses to Reading and Science literacy cognitive items developed under the PISA analytical framework are used as training data for deep learning together with multilingual data to construct an AI model. The trained AI models are then used to score and the results compared with human-scored data. The score distributions estimated based on the AI-scored data and the human-scored data are highly consistent with each other; furthermore, even item-level psychometric properties of the majority of items showed high levels of agreement, although a few items showed discrepancies. This study demonstrates a practical procedure for using a multilingual data approach, and this new AI-scoring methodology reached a practical level of quality, even in the context of an international large-scale assessment.

The EU’s ambitious Green Deal aims at achieving net zero emissions by 2050. The EU is starting from a relatively good position. It has successfully reduced greenhouse gas emissions over the past decade. But further efforts are needed to reach the net zero target. These include an extension of emission trading to agriculture and the phase-out of generous subsidies for fossil fuels. Such efforts should be complemented by additional measures to shift to clean energy, notably more integrated electricity markets and deeper capital markets that provide the necessary investment in new technologies. Accelerating the green transition will also involve costs for displaced workers. Bolstering workers’ mobility and training will help improve labour reallocation and reduce transition costs.

Over half of Korea’s population lives in the Seoul Metropolitan Area. This report looks at how the region’s transport system and land uses serve different socio-economic groups and offers insights for reducing inequalities in access. Are services and opportunities equally accessible to all residents of the Seoul Metropolitan Area? Which factors influence accessibility gaps? How can transport planning and decision making take into account accessibility and equity considerations?tr

Climate change presents a major social, economic and political challenge for the Slovak Republic. The majority of municipal administrations are unaware of the potential climate risks they face today and in the coming years. Identifying risks posed by climate change and its inevitable impacts is an essential part of developing adaptation policies. While national adaptation policies have historically been formulated in an ad hoc manner, an evidence-based approach that relies on data is increasingly informing policy decisions. This paper provides an overview of the country’s adaptation policy context and presents a methodology – and the results of its application – for measuring climate change risks with respect to heat, drought and extreme precipitation. The results aim to inform future budget allocation decisions for climate change adaptation.

Automation of vehicles and in the workplace is transforming the transport industry. This report investigates the impacts of automation on the workforce in urban transport. It explores ways to help the labour market transition towards automated technologies without social disruptions. The report also examines how algorithms could improve employment opportunities and job quality in the transport industry.

This paper shows that climate-related forced displacement is insufficiently addressed in two fundamental commitments made towards the United Nations Framework Convention on Climate Change (UNFCCC) between 2015 and 2023: National Adaptation Plans (NAPs) and Nationally Determined Contributions (NDCs). It describes the important role NAPs and NDCs play in prioritising the tackling of certain aspects of climate change adaptation, identifies gaps on forced displacement, and proposes ways of adding it among their policy objectives, and of mobilising finance to reach them.

High employment growth has sustained Israel’s high GDP growth in recent decades, but demographic change and labour market duality put future growth at risk. Policy action is required to stimulate employment and raise labour productivity, especially among population groups with weaker labour market outcomes. A particular concern is closing employment gaps of Haredim and Arab Israelis and ensuring gender equality in the workplace, which would simultaneously improve opportunities for all Israelis and the aggregate labour productivity of the economy. This will require setting appropriate work incentives and providing better support for working parents; improving skills at all stages of the learning cycle; as well as increasing mobility and improving reallocation towards high-productivity jobs and firms, in particular in the high-tech sector.

This report presents research and findings on accountability and risk in AI systems by providing an overview of how risk-management frameworks and the AI system lifecycle can be integrated to promote trustworthy AI. It also explores processes and technical attributes that can facilitate the implementation of values-based principles for trustworthy AI and identifies tools and mechanisms to define, assess, treat, and govern risks at each stage of the AI system lifecycle.

This report leverages OECD frameworks – including the OECD AI Principles, the AI system lifecycle, and the OECD framework for classifying AI systems – and recognised risk-management and due-diligence frameworks like the ISO 31000 risk-management framework, the OECD Due Diligence Guidance for Responsible Business Conduct, and the US National Institute of Standards and Technology’s AI risk-management framework.

In the backdrop of the COVID-19 pandemic, ensuring the safety of health care services remains a serious, ongoing challenge. This once-in-a-century global health crisis exposed the vulnerability of healthcare delivery systems and the subsequent risks of patient harm. Given the scale of the occurrence and costs of preventable patient safety events, intervention and investment are still relatively modest. Good patient safety governance focuses on what leaders and policy makers can do to improve system performance and reduce the financial burden of avoidable care. Moreover, it is essential in driving progress in improving safety outcomes. This report examines how patient safety governance mechanisms in OECD countries have withstood the test of COVID-19 and provides recommendations for countries in further improving patient safety governance and strengthening health system resilience.

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