Previous research shows that countries with opt-out consent systems for organ donation conduct significantly more deceased-donor organ transplantations than those with opt-in systems. This paper investigates whether the higher transplantation rates in opt-out systems translate into equally lower death rates among organ patients registered on a waiting list (i.e., organ-patient mortality rates). We show that the difference between consent systems regarding kidney- and liver-patient mortality rates is significantly smaller than the difference in deceased-donor transplantation rates. This is likely due to different incentives between the consent systems. We find empirical evidence that opt-out systems reduce incentives for living donations, which explains our findings for kidneys. The results imply that focusing on deceased-donor transplantation rates alone paints an incomplete picture of opt-out systems’ benefits, and that there are important differences between organs in this respect.

This article also appeared in The Latest Research in Health Policy - Virtual Issue of the Journal of Policy Analysis and Management. 

See also this chapter (in Dutch) in the KVS Preadviezen 2021: Ongelijk Nederland.

This paper investigates whether encouraging children to become more physically active in their everyday life affects their primary school performance. We use data from a field quasi-experiment called the Active Living Program, which aimed to increase active modes of transportation to school and active play among 8- to 12-year-olds living in low socioeconomic status (SES) areas in the Netherlands. Difference-in-differences estimations reveal that while the interventions increase time spent on physical activity during school hours, they negatively affect school performance, especially among the worst-performing students. Further analyses reveal that increased restlessness during instruction time is a potential mechanism for this negative effect. Our results suggest that the commonly found positive effects of exercising or participating in sports on educational outcomes may not be generalizable to physical activity in everyday life. Policymakers and educators who seek to increase physical activity in everyday life need to weigh the health and well-being benefits against the probability of increasing inequality in school performance. 

This dissertation evaluates the direct and certain indirect effects of the Active Living Program (a field experiment that stimulates children to become more physically active in their everyday lives), and opt-out consent for organ donation (a system in which you automatically become organ donor upon death unless you indicated otherwise). Both policies achieve most of their direct effects: the Active Living Program increases the amount of time children spend on physical activity during school-time, and opt-out consent for organ donation is related to significantly more transplants from deceased donors. However, both policies also appear to have undesirable indirect effects. The Active Living Program unintentionally worsens school performance, especially among the lowest-performing students and among boys, and it increases ADHD-like symptoms in boys. The thesis also shows that for kidneys and livers—by far the most commonly transplanted organs—the higher deceased-donor transplantation rates in opt-out systems give a false impression that presumed consent is related to lower organ-patient mortality rates. 

[ English below ]

En 2022, 7,1 millions de personnes soutiennent un parent, un conjoint, un enfant ou un ami en situation de handicap ou de perte d’autonomie vivant en logement ordinaire en France métropolitaine. Ces proches aidants apportent régulièrement une aide à la vie quotidienne, un soutien moral ou une aide financière ou matérielle en raison des problèmes de santé, d’un handicap ou de l’avancée en âge d’un aidé. 

Trois fois sur dix, cette aide dite « informelle » est assumée par l’aidant seul, sans autres aidants, ni proches, ni professionnels ou bénévoles. De plus, sa nature est variée : un tiers des proches aidants cumulent soutien moral, aide à la vie quotidienne et aide financière ou matérielle. Le temps consacré aux activités de la vie quotidienne va de moins d’une heure par jour (44 %) à 35 heures ou plus par semaine (11 %). 

Les aidants sont majoritairement des femmes (58 %) et ont en moyenne 52 ans et 11 mois. Ceux qui soutiennent leurs parents (35 %) constituent le groupe le plus nombreux ; leur temps d’aide est cependant plus limité et moins souvent assumé par eux seuls. À l’inverse, l’aide est souvent assumée par un proche seul lorsqu’elle est apportée à un conjoint (24 % des situations d’aide). Les parents accompagnant leur enfant en situation de handicap (19 %) figurent parmi ceux qui assurent le plus souvent des soins personnels et ont les charges horaires les plus lourdes. Quant aux autres aidants, ils apportent plus fréquemment uniquement un soutien moral. 

Enfin, six aidants sur dix travaillent, sont en recherche d’emploi ou étudiants, soit huit sur dix d’âge actif. Parmi ces derniers, presque la moitié ont aussi un enfant à charge qui n’est pas l’aidé ; ils doivent alors concilier leur rôle d’aidant avec leur vie familiale et leurs autres responsabilités.

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In 2022, 7.1 million people in metropolitan France supported a parent, spouse, child, or friend living in a private household who had a disability or loss of autonomy. These informal caregivers regularly provide help with daily living activities, emotional support, or financial or material assistance due to the care recipient’s health problems, disability, or advanced age.

In three out of ten cases, this so-called “informal” care is provided by the caregiver alone, without the support of other informal caregivers, relatives, professionals, or volunteers. The nature of the care provided is diverse: one third of informal caregivers combine emotional support, assistance with daily living, and financial or material help. Time spent on assistance with daily living activities ranges from less than one hour per day (44%) to 35 hours or more per week (11%).

Caregivers are predominantly women (58%) and are on average 52 years and 11 months old. Those caring for their parents (35%) represent the largest group; however, they generally spend less time providing care and are less often the sole caregiver. By contrast, care is more often provided by a single caregiver when it is given to a spouse (24% of caregiving situations). Parents caring for a child with a disability (19%) are among those most frequently providing personal care and face the heaviest time burdens. Other caregivers are more likely to provide emotional support only.

Finally, six in ten caregivers are employed, seeking work, or studying—eight in ten among those of working age. Among the latter, nearly half also have a dependent child who is not the care recipient, requiring them to balance their caregiving role with family life and other responsibilities.

While means-tested benefits such as minimum income benefits (MIB) and unemployment assistance (UA) are an essential safety net for low-income people and the unemployed, incomplete take-up is the rule rather than the exception. Building on desk research, open-ended surveys and semi-structured interviews, this paper investigates the opportunities and risks of using artificial intelligence (AI) for managing these means-tested benefits. This ranges from providing information to individuals, through determining eligibility based on pre-determined statutory criteria and identifying undue payments, to notifying individuals about their eligibility status. One of the key opportunities of using AI for these purposes is that this may improve the timeliness and take-up of MIB and UA. However, it may also lead to systematically biased eligibility assessments or increase inequalities, amongst others. Finally, the paper explores potential policy directions to help countries seize AI’s opportunities while addressing its risks, when using it for MIB or UA management.

AI can bring significant benefits to the workplace. In the OECD AI surveys of employers and workers, four in five workers say that AI improved their performance at work and three in five say that it increased their enjoyment of work. But the benefits of AI depend on addressing the associated risks. Taking the effect of AI into account, occupations at highest risk of automation account for about 27% of employment in OECD countries. Workers also express concerns around increased work intensity, the collection and use of data, and increasing inequality. To support the adoption of trustworthy AI in the workplace, this policy paper identifies the main risks that need to be addressed when using AI in the workplace. It identifies the main policy gaps and offers possible policy avenues specific to labour markets.

This chapter provides an overview of countries’ policy action affecting the development and use of artificial intelligence (AI) in the workplace. It looks at public policies to protect workers’ fundamental rights, ensure transparency and explainability of AI systems, and clarify accountability across the AI value chain. It explores how existing non-AI-specific laws – such as those pertaining anti-discrimination and data protection – can serve as a foundation for the governance of AI used in workplace settings. While in some countries, courts have successfully applied these laws to AI-related cases in the workplace, there may be a need for AI- and workplace‑specific policies. To date, most countries primarily rely on soft law for AI-specific matters, but a number of countries are developing new AI-specific legislative proposals applicable to AI in the workplace.

For many workers, the effects of artificial intelligence (AI) will be visible not in terms of lost employment but through changes in the tasks they perform at work and changes in job quality. This chapter reviews the current empirical evidence of the effect of AI on job quality and inclusiveness. For workers with the skills to complement AI, task changes should be accompanied by rising wages, but wages could decline for workers who find themselves squeezed into a diminished share of tasks due to automation. AI may affect job quality through other mechanisms as well. For example, it can reduce tedious or dangerous tasks, but it may also leave workers with a higher-paced work environment. The chapter further shows that using AI to support managers’ tasks affects the job quality of their subordinates. Finally, the chapter shows that using AI affects workplace inclusiveness and fairness, with implications for job quality.

The COVID-19 pandemic further exacerbated the long-standing skills shortages in the health workforce across countries. Equipping health workers with the right skills is essential to respond to future health crises, to prepare for increasing use of digital technologies, and to plan for demographic change. This joint report by the OECD and ILO aims to enable more resilient health workforces by helping countries to assess future demand in terms of both numbers of health workers and skills needs, and to prepare appropriate policy responses. The report provides a comparative overview of practices in 16 countries to anticipate future skill needs in the health workforce, and of how such information is used by policy makers and social partners to foster a better alignment with labour market needs. Analysis is based on interviews with institutions that are responsible for anticipating skill needs in the health workforce, a virtual peer-learning workshop and desk research.

Improving the alignment between the skills required by employers and those of workers is increasingly challenging. The OECD Skills for Jobs database is designed for policymakers, practitioners and the general public to understand where gaps are emerging between skill supply and demand. The third update out now covers 43 countries, leverages a new methodology for calculating the importance of skills in occupations based on online job vacancies, and includes information on more detailed digital skills.

See also this post on the OECD Skills and Work blog.

Skills imbalances arise when the demand for and supply of skills are not well-aligned. Understanding where those imbalances are is a first step towards developing skills policies and programmes that are aligned with the needs of the labour market. The OECD Skills for Jobs indicators measure skills shortages, surpluses and mismatches across labour markets around the world. This report describes the methodology behind the indicators and the results for South Africa. It provides detailed insights into the occupations, sectors and skills that are facing shortages and surpluses, as well as into the match between individuals’ education and their jobs.

This working paper looks at the labour market outcomes of individuals who hold a medium-level VET qualification (defined as upper or post-secondary non-tertiary education with vocational orientation) today, as well as how they have changed in the past 10 to 15 years and what can be expected in the medium-term. Based on the findings, the report discusses key policy directions to improve VET graduates’ access to high-quality jobs. 

See also this chapter in the OECD Employment Outlook 2020, and this post on the OECD Skills and Work blog.

This booklet highlights seven action points on how to involve social partners to make adult learning work for the future. It provides practical insights for stakeholders who are directly involved in the design, implementation and monitoring of adult learning policies, including policymakers and social partners. Each action point draws on research evidence and provides insights on how to translate it into practice by highlighting promising policies in OECD and emerging countries. 

See also this post on the OECD Skills and Work blog. 

This brochure presents empirical evidence drawn from the OECD Skills for Jobs (S4J) database developed in cooperation and with the financial support of the JPMorgan Chase Foundation. Data confirm that the shift towards a knowledge-based digital economy is already under way and that governments, workers and firms altogether face many challenges ahead. Results show that skill demands have gradually shifted towards a more intensive use of cognitive and interpersonal skills and that high-skilled occupations are in strong demand across most OECD countries. 

See also this post on the OECD Skills and Work blog.

This working paper shows that using Artificial Intelligence (AI) for training has the potential to improve the targeting of and access to adult learning systems. In order to ensure that AI yields benefits for all, it will be necessary to address potential drawbacks in terms of more demanding skills requirements, greater inequalities in access to data, technology and infrastructure, and important ethical issues.

See also this post on the OECD Skills and Work blog.

Policy-makers have long recognised that participation in adult learning is key to unlock benefits of a changing world of work. While much has been written about the need for progress in this area, many good initiatives struggle to translate into real change on the ground, as they get stuck in the difficulties of policy implementation. Drawing on the experience of six countries that have significantly increased participation over the past decades, this report identifies the main factors behind successful policies and programmes. Based on an analysis of 17 reforms deemed the most important for the observed increases in participation, five key lessons emerge on the design, implementation and evaluation of adult learning reforms.

See also this post on the OECD Skills and Work blog.