Employment

This paper estimates the data intensity of occupations/sectors (i.e. the share of job postings per occupation/sector related to the production of data) using natural language processing (NLP) on job advertisements in the United Kingdom, Canada and the United States. Online job advertisement data collected by Lightcast provide timely and disaggregated insights into labour demand and skill requirements of different professions. The paper makes three major contributions. First, indicators created from the Lightcast data add to the understanding of digital skills in the labour market. Second, the results may advance the measurement of data assets in national account statistics. Third, the NLP methodology can handle up to 66 languages and can be adapted to measure concepts beyond digital skills. Results provide a ranking of data intensity across occupations, with data analytics activities contributing most to aggregate data intensity shares in all three countries. At the sectoral level, the emerging picture is more heterogeneous across countries. Differences in labour demand primarily explain those variations, with low data-intensive professions contributing most to aggregate data intensity in the United Kingdom. Estimates of investment in data, using a sum of costs approach and sectoral intensity shares, point to lower levels in the United Kingdom and Canada than in the United States.

Protecting people, rather than specific jobs, plays a key role in promoting labour-market inclusiveness and dynamism. Effective unemployment benefits reduce inequality, and facilitate a good match between workers’ skills and job requirements. They are a crucial policy lever for adapting to the major societal, technological and environmental transitions of our time. This report on the United States is the second of a number of OECD country reviews of income support policies. Each report analyses key policy challenges, discusses recent reform initiatives, and identifies good practices from other OECD countries. The report examines the reach and generosity of unemployment insurance and other income support for working age households, with a special focus on disadvantaged labour market groups. What are key gaps in benefit receipt between wage- and salaried employees and non-standard workers (part-time workers, those on temporary contracts, and self-employed workers including own-account workers)? What factors, including race/ethnicity and gender, drive non-entitlement to unemployment compensation? The report examines these questions, considers the impact of recent extensions to the unemployment insurance programme in response to the COVID pandemic, and outlines policy directions for strengthening out-of-work support.

The paper discusses the implications of recent advances in artificial intelligence for knowledge workers, focusing on possible complementarities and substitution between machine translation tools and language professionals. The emergence of machine translation tools could enhance social welfare through enhanced opportunities for inter-language communication but also create new threats because of persisting low levels of accuracy and quality in the translation output. The paper uses data on online job vacancies to map the evolution of the demand for language professionals between 2015 and 2019 in 10 countries and illustrates the set of skills that are considered important by employers seeking to hire language professionals through job vacancies posted on line.

New OECD surveys of employers and workers in the manufacturing and finance sectors of seven countries shed new light on the impact that Artificial Intelligence has on the workplace —an under-researched area to date due to lack of data. The findings suggest that both workers and their employers are generally very positive about the impact of AI on performance and working conditions. However, there are also concerns, including about job loss—an issue that should be closely monitored. The surveys also indicate that, while many workers trust their employers when it comes to the implementation of AI in the workplace, more can be done to improve trust. In particular, the surveys show that both training and worker consultation are associated with better outcomes for workers.

As societies become increasingly digital, cyber security has become a priority for individuals, companies and nations. The number of cyber attacks is exceeding defence capabilities, and one reason for this is the lack of an adequately skilled cyber security workforce. This report analyses the demand for cyber security professionals in Australia, Canada, New Zealand, the United Kingdom and the United States using information contained in online job postings. The analysis looks at recent trends in the demand for workers in different types of cyber security roles, the geographical distribution of cyber security job postings, and the changing skill requirements for professionals in this field. The report also looks at the supply side, zooming in on the landscape of cyber security education and training programmes in England (United Kingdom). It describes the different types of programmes provided in further and higher education, the profile of learners in these programmes and their outcomes. Finally, the report also looks at policies and initiatives adopted in England to make cyber security education and training programmes more accessible and relevant. This report is part of a larger initiative examining the evolution of policies and experiences in the cyber security profession around the world.

This study responds to six key questions about the impact that the demand for Artificial Intelligence (AI) skills is having on labour markets. What are the occupations where AI skills are most relevant? How do different AI-relevant skills combine in job requirements? How quickly is the demand for AI-related skills diffusing across labour markets and what is the relationship between AI skill demands and the demand for cognitive skills across jobs? Finally, are AI skills leading to a wage premium and how different are the wage returns associated with AI and routine skills? To shed light on these aspects, this study leverages Natural Language Processing (NLP) algorithms to analyse the information contained in millions of job postings collected from the internet.

Being able to swim empowers individuals to make choices, have agency, and be free to choose core aspects of their life, such as working safely on or near water. It is also associated with lifelong health benefits and reduces the risk of drowning. Using data from the Lloyd’s Register Foundation World Risk Poll 2019, this paper provides the first global estimates of adults’ ability to swim without assistance. Individuals in high-income countries are considerably more likely to report being able to swim without assistance than individuals in low-income countries. Disparities also exist within countries. In particular, women are less likely to be able to swim without assistance than men in virtually all countries, birth cohorts, and levels of education. Investing in reducing inequalities in life skills, such as swimming, can foster economic development and empowerment, especially in light of threats, such as climate change.

Rising self-employment rates in U.S. tax data that are absent in survey data have led to speculation that tax records capture a rise in new 'gig' work that surveys miss. Drawing on the universe of Internal Revenue Service (IRS) tax returns, we show that trends in firm-reported payments to 'gig' and other contract workers do not explain the rise in self-employment reported to the IRS; rather, that increase is driven by self-reported earnings of individuals in the EITC phase-in range. We isolate pure reporting responses from real labor supply responses by examining births of workers’ first children around an end-of-year cutoff for credit eligibility that creates exogenous variation in tax rates at the end of the tax year after labor supply decisions are already sunk. We find that exposing workers with sunk labor supply to negative marginal tax rates results in large increases in their propensity to self-report self-employment—only a small minority of which leads to bunching at kink-points. Consistent with pure strategic reporting behavior, we find no impact on reporting among taxpayers with no incentive to report additional income and no effects on firm-reported payments of any kind. Moreover, we find these reporting responses have grown over time as knowledge of tax incentives has become widespread. Quantitatively, our results suggest that as much as 59 percent of the growth in self-employment rates, and all counter-cyclicality, can be attributed to changes in reporting behavior that are independent of changes in the nature of work. Our findings suggest caution is warranted before deferring to administrative data over survey data when measuring labor market trends.

The paper is the first in a series of two papers mapping young people’s environmental sustainability competence in EU and OECD countries that were prepared as background for the forthcoming OECD Skills Outlook 2023 publication. The papers are the results of a collaboration between the OECD Centre for Skills and the European Commission - Joint Research Centre (Unit B4) on students’ environmental sustainability competence. The second paper is titled: ‘The environmental sustainability competence toolbox: From leaving a better planet to our children to leaving better children for our planet’.

The paper is the second in a series of two papers mapping young people’s environmental sustainability competence in EU and OECD countries that were prepared as background for the forthcoming OECD Skills Outlook 2023 publication. The papers are the results of a collaboration between the OECD Centre for Skills and the European Commission - Joint Research Centre (Unit B4) on students’ environmental sustainability competence. The first paper is titled ‘Young people’s environmental sustainability competence: Emotional, cognitive, behavioural and attitudinal dimensions in EU and OECD countries.