The uneven impact of high inflation

Abstract

The OECD Papers on Well-being and Inequalities Series -managed by the OECD Centre on Well-being, Inclusion, Sustainability and Equal Opportunity (WISE) -features Working Papers on the measurement agenda for well-being, inclusion, sustainability and equal opportunity as well as papers seeking to deepen the understanding of the drivers of these issues, the ways in which they interact and how they evolve. These papers are prepared by OECD staff, external experts or by outside consultants working on OECD projects. This Working Paper should not be reported as representing the official views of the OECD or of its Member countries or of the European Union or its Member States. The opinions expressed and arguments employed are those of the authors.Working Papers describe preliminary results or research in progress by the authors and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on this Working Paper are welcomed, and may be sent to the OECD Centre on Well-Being, Inclusion, Sustainability and Equal Opportunity, email

Hard work, privilege or luck? Exploring people’s views of what matters most to get ahead in life

“…Socio-economic factors, such as coming from a wealthy family or having well-educated parents, are considered a key driver of upward mobility for more than one-in-three respondents (Figure 3, Panel A). As with disability, this belief is consistent with the case of a large body of evidence showing that unequal starting points have a lasting impact on a wide range of well-being outcomes later in life (Bowles and Gintis, 2002 [13]; D'Addio, 2007 [14]; Causa and Johansson, 2009 [15]; Corak, 2013 [16]; OECD, 2018 [1]). For example.…”

L’insécurité économique en Europe et ses remèdes possibles

“…Note : l'exposition à l'intelligence artificielle (IA) est déterminée d'après Kanders et al (2020 [6]), qui applique à des milliers de tâches exécutées dans les pays européens les scores d'adéquation à l'apprentissage automatique établis par Brynjolfsson, Mitchell et Rock (2018 [7]). Elle est donnée par le pourcentage de tâches qui ne font pas obstacle à l'IA.…”

“…La taille de chaque disque est proportionnelle au pourcentage de travailleurs concernés pour la profession correspondante. En Partie A, les disques ont été colorés en fonction du nombre de transitions professionnelles particulièrement viables et souhaitables possibles pour chaque groupe de professions -les couleurs allant du rouge foncé (5 transitions), à l'orange (7)…”

Economic insecurity in Europe and potential policy responses

“…Artificial intelligence has not (yet) led to a reduction in employment: some highly skilled workers have had better employment prospects after the introduction of artificial intelligence, and there is some evidence that those exposed to artificial intelligence have seen their wages increase, as they spend more time on complex work tasks, while artificial intelligence undertakes simpler tasks (OECD, 2023 [2]). Economic insecurity and its association with exposure to AI and automation risk, major ISCO-08 occupation groups Note: Exposure to artificial intelligence (AI) is based on Kanders et al (2020 [6]), who map the suitability for machine learning scores developed by Brynjolfsson, Mitchell and Rock (2018 [7]) to thousands of tasks in European countries. Exposure is measured as the share of tasks that are not bottlenecks to AI.…”

“…Each bubble's size indicates the share of workers in a given occupation. In Panel A, bubbles are coloured based on the number of highly viable and desirable job transitions that are likely in each occupation group -ranging from dark red (5 transitions), to orange (7), yellow (8), light blue (10), medium blue (11), and finally dark blue (19-22). Highly viable transitions are those with a good fit for an individual's current occupation (based on their education, skills, experience, and types of work activities), while desirable transitions are those where the job mover can make at least 75% of their current occupation's median earnings (Kanders et al, 2020[6]).…”