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This report provides scenarios for future transport demand and CO2 emissions in North and Central Asia up to 2050 to help decision makers chart pathways to sustainable, resilient transport. The scenarios reflect existing policy initiatives and specific constraints in the region. They also examine the potential impact of policies addressing the challenges and opportunities for transport from Covid-19.
This report provides scenarios for future transport demand and CO2 emissions in South and Southwest Asia up to 2050 to help decision-makers chart pathways to sustainable, resilient transport. The scenarios reflect existing policy initiatives and specific constraints in the region. They also examine the potential impact of policies addressing the challenges and opportunities for transport from Covid-19.
This report provides scenarios for future transport demand and CO2 emissions in Southeast Asia up to 2050 to help decision-makers chart pathways to sustainable, resilient transport. The scenarios reflect existing policy initiatives and specific constraints in the region. They also examine the potential impact of policies addressing the challenges and opportunities for transport from Covid-19.
Iceland’s Education Policy 2030 (EP2030) is an education strategy document that outlines aims to achieve a dynamic and flexible education system to drive economic and social change. Its vision is ‘to accomplish high-quality education through life’, underpinned by the values of resilience, courage, knowledge and happiness. It has five pillars to attain this vision: equity, teaching, skills for the future, well-being, and education system quality. To strengthen the implementability of this document and use it effectively to inform action planning, Iceland should review its design to make it actionable, more closely consider stakeholder engagement approaches, fit implementation to Iceland’s decentralised context, and define a clear implementation strategy. Through this, Iceland will be better positioned to transition from strategy to action, over the course of the next ten years, and accomplish its objectives.
This paper examines the drivers for knowledge exchange in British research-intensive universities, at a time when research impact is coming to be seen as an increasingly important outcome of research in all disciplines. It provides evidence of an over-emphasis of the economic benefits of knowledge exchange in the policy sphere and of a quite different value system amongst academics. Academics’ commitments having been described as occupying a single bounded space, this enhanced understanding of the motivations and needs of academics as they engage in knowledge exchange points to a new way of approaching the facilitation and promotion of knowledge exchange activity.
This paper documents joblessness in OECD countries, provides a detailed diagnosis of structural employment barriers in Belgium, Korea and Norway by applying the OECD Faces of Joblessness methodology to the situation just before the COVID-19 crisis and discusses the policy implications. It shows that individuals experiencing major employment difficulties often face a combination of barriers related to work availability, readiness and incentives. It suggests a number of avenues for enhancing the effectiveness of public support: i) make greater use of statistical profiling tools to adapt programmes to the needs of the jobless and target resources to those at the highest risk of long-term joblessness; ii) better coordinate support provided by employment, health and education services; iii) place a greater emphasis on preventive policies (equal opportunities, life-long learning).
Despite calls for the reform of incentives, including subsidies, harmful to biodiversity, including under the Convention on Biological Diversity and its 2011-2020 Aichi Targets, very few countries to date have undertaken what is considered the first step in this process, namely, to identify and assess the types and magnitudes of any incentives in place at the national level which are harmful for biodiversity or the environment more broadly.
This paper begins with a brief literature review on subsidies harmful to biodiversity, followed by a detailed review and comparison of the existing national level studies to identify and assess subsidies and other incentives harmful to biodiversity or the environment. The report concludes with guidance and good practice insights to identify and assess subsidies and other incentives harmful to biodiversity, at national level.
This work employs a novel approach to identify and characterise firms adopting Artificial Intelligence (AI), using different sources of large microdata. Focusing on the United Kingdom, the analysis combines data on Intellectual Property Rights, website information, online job postings, and firm-level financials for the first time. It shows that a significant share of AI adopters is active in Information and Communication Technologies and professional services, and is located in the South of the United Kingdom, particularly around London. Adopters tend to be highly productive and larger than other firms, while young adopters tend to hire AI workers more intensively. Human capital appears to play an important role, not only for AI adoption but also for firms’ productivity returns. Significant differences in the characteristics of AI adopters emerge when distinguishing between firms carrying out AI innovation, those with an AI core business, and those searching for AI talent.
This paper identifies and measures developments in science, algorithms and technologies related to artificial intelligence (AI). Using information from scientific publications, open source software (OSS) and patents, it finds a marked increase in AI-related developments over recent years. Since 2015, AI-related publications have increased by 23% per year; from 2014 to 2018, AI-related OSS contributions grew at a rate three times greater than other OSS contributions; and AI-related inventions comprised, on average, more than 2.3% of IP5 patent families in 2017. China’s growing role in the AI space also emerges. The analysis relies on a three-pronged approach based on established bibliometric and patent-based methods, and machine learning (ML) implemented on purposely collected OSS data.
This paper identifies different types of climate change mitigation strategies countries adopted over the last two decades and assesses the policy synergies they might generate. The analysis exploits the rich policy repository of the OECD’s Climate Actions and Policies Measurement Framework (CAPMF). This is the most comprehensive and harmonised mitigation policy database to date, covering more than 120 policy instruments and 50 countries over 2000-20. Statistical cluster analysis yields four types of mitigation strategies, which differ in the variety and stringency of mitigation policies. Until the mid-2000s mitigation strategies were similar and based on few policies and low overall stringency. They started to differentiate in the mid-2000s and then in the mid-2010s as some countries enlarged the variety of policy instruments and raised stringency. Regression results indicate that emissions are negatively associated with the overall stringency of the country’s mitigation strategies. Moreover, this relationship is stronger for mitigation strategies comprising a larger set of instruments, pointing to larger policy synergies.
This paper uses information collected and provided by GlassAI to analyse the characteristics and activities of companies and universities in Canada, Germany, the United Kingdom and the United States that mention keywords related to Artificial Intelligence (AI) on their websites. The analysis finds that those companies tend to be young and small, mainly operate in the information and communication sector, have AI at the core of their business, and aim to provide customer solutions. It is noteworthy that the types of AI-related activities reported by them vary across sectors. Additionally, although universities are concentrated in and around large cities, this is not necessarily reflected in the intensity of AI-related activities. Taken together, this novel and timely evidence informs the debate on the most recent stages of digital transformation of the economy.