Publications & Documents

This volume presents the financial literacy results of the OECD Programme for International Student Assessment (PISA) 2022 and examines 15-year-old students’ understanding of money matters in 20 countries and economies. It explores the links between their financial literacy and their competencies in mathematics and reading, and differences across socio-demographic groups. It also offers an overview of their experiences with money, their financial behaviour and attitudes, and their exposure to financial literacy at home and in school.

The results of the PISA 2022 financial literacy assessment show that many 15-year-olds should be better prepared for their financial future, as they are not able to apply their financial knowledge to real-life situations. In every participating country and economy, students from disadvantaged socio-economic backgrounds performed significantly worse than their advantaged peers. PISA data also show that students who discuss money matters with their parents, and those who make autonomous decisions about how to spend their money, achieve higher levels of financial literacy. This PISA in Focus examines the proportion of students who do not achieve baseline financial literacy and explores the links between socio-economic backgrounds, parental interactions and financial literacy performance.

Inclusive and sustainable economic growth in the six Western Balkan (WB6) economies depends on greater economic competitiveness. Although the gap is closing gradually, the standards of living in WB6 are well below those of the OECD and EU. Accelerating the rate of socio-economic convergence will require a holistic and growth oriented approach to policy making. This is the fourth study of the region (formerly under the title 'Competitiveness in South East Europe') and it comprehensively assesses policy reforms in the WB6 economies across 15 policy areas key to strengthening their competitiveness. It enables WB6 economies to compare economic performance against regional peers, as well as EU-OECD good practices and standards, and to design future policies based on rich evidence and actionable policy recommendations. The regional profile presents assessment findings across five policy clusters crucial to accelerating socio-economic convergence of the WB6 by fostering regional co-operation: business environment, skills, infrastructure and connectivity, digital transformation and greening. Economy-specific profiles complement the regional assessment, offering each WB6 economy an in-depth analysis of their policies supporting competitiveness. They also track the implementation of the previous 2021 study's recommendations and provide additional ones tailored to the economies’ evolving challenges. These recommendations aim to inform structural economic reforms and facilitate the region’s socio-economic convergence towards the standards of the EU and OECD.

Recent AI technological advances, particularly the rise of generative AI, have raised many data governance and privacy questions. However, AI and privacy policy communities often address these issues independently, with approaches that vary between jurisdictions and legal systems. These silos can generate misunderstandings, add complexities in regulatory compliance and enforcement, and prevent capitalising on commonalities between national frameworks. This report focuses on the privacy risks and opportunities stemming from recent AI developments. It maps the principles set in the OECD Privacy Guidelines to the OECD AI Principles, takes stock of national and regional initiatives, and suggests potential areas for collaboration. The report supports the implementation of the OECD Privacy Guidelines alongside the OECD AI Principles. By advocating for international co-operation, the report aims to guide the development of AI systems that respect and support privacy.

The Network on Labour market, economic, and social outcomes of learning (LSO Expert Network) has diligently worked on the selection of indicators for monitoring adult learning policies. Their inaugural theoretical framework on adult learning, published in 2013, covered a broad spectrum of policy areas. This comprehensive scope reflected both the focus of existing data sources and the challenges encountered in data collection efforts. Over the past decade, significant policy shifts have occurred, reshaping adult learning systems both domestically and internationally. Concurrently, there have been improvements in the availability and frequency of data pertaining to adult learning. In response to these developments, this working paper presents an updated theoretical framework on adult learning, aiming to enhance the identification of statistical data concerning adult learning systems and facilitate the selection of pertinent indicators for monitoring purposes. Additionally, the paper offers detailed insights into national priorities and practices within this domain.

For the first time ever, PISA measured the creative thinking skills of 15-year-old students across the world. Alongside assessments in mathematics, science and reading, students in 64 countries and economies sat an innovative test that assessed their capacity to generate diverse and original ideas, as well as to evaluate and improve upon others’ ideas in creative tasks. These ranged from written and visual expression to scientific and social problem solving. This PISA in Focus highlights some of the main findings from Volume III of PISA 2022. It focuses on the main factors linked to students’ creative thinking performance, including their proficiency in other academic subjects, their gender, socio-economic profile, views on creativity, attitudes, social-emotional characteristics and their school environment.

Le Programme international de l’OCDE pour le suivi des acquis des élèves (PISA) analyse les connaissances et les compétences des élèves dans le monde entier. La présente version abrégée est la traduction partielle de la version anglaise du volume III, La pensée créative en milieu scolaire – l’un des cinq volumes qui présentent les résultats du huitième cycle d’évaluation du PISA. Elle contient le résumé ainsi que le chapitre 7 « Tirer des enseignements des données ». Pour la première fois en 2022, l’enquête PISA a cherché à évaluer dans 64 pays et économies la capacité des élèves à faire preuve de créativité, c’est-à-dire la capacité des élèves à proposer des idées originales et variées. Ce volume détaille la performance des élèves en matière de pensée créative dans différents contextes et comment les attitudes et résultats à cet égard varient au sein des pays et économies et entre eux. Il analyse les différences de performance en se basant sur diverses caractéristiques des élèves, notamment le sexe et le milieu socio-économique, ainsi que sur les caractéristiques de l’établissement fréquenté. Ce volume donne également un aperçu de l’attitude des chefs d’établissement et des enseignants envers la pensée créative, en examinant dans quelle mesure les possibilités d’exercer sa créativité diffèrent selon les établissements et de quelle façon elles déterminent les résultats des élèves.

As part of broader digitalisation efforts, half of public employment services (PES) in OECD countries are employing Artificial Intelligence (AI) to enhance their services. AI is being adopted across all key tasks of PES, including most commonly to match jobseekers with vacancies. While several PES have been using such tools for a decade, adoption of AI has been increasing in recent years as these become more accessible. New AI use cases have emerged to assist employers in designing vacancy postings and jobseekers in their career management and job-search strategies. AI initiatives have significant impact on PES clients, changing how they interact with the PES and receive support, and PES staff, altering their day-to-day work. As PES seek to maximise the opportunities brought by AI, proactive steps should be taken to mitigate associated risks. Key considerations for PES include prioritising transparency of AI algorithms and explainability of results, establishing governance frameworks, ensuring end-users (staff and clients) are included and supported in the development and adoption process, and committing to rigorous monitoring and evaluation to increase the positive and manage any negative impact of AI solutions.