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on Unemployment, Inequality and Poverty |
| By: | David G. Blanchflower; Alex Bryson |
| Abstract: | Although there is growing evidence that the subjective wellbeing among the young declined in recent years, the evidence is not consistent across surveys. We examine the relationship between age and various measures of wellbeing and illbeing across three major surveys – the Gallup World Poll (GWP, Global Minds (GM) and the Global Flourishing Survey (GFS). The GWP is conducted via face-to-face and telephone surveys; GM surveys are web-based; and GFS uses both telephone and web-based surveys. We focus on 23 countries appearing in all three surveys. The clearest evidence that wellbeing rises with age and illbeing declines with age comes from the web-based surveys in both GM and GFS. The age profiles look very different when surveys are conducted by telephone: the higher rates of illbeing among the young are far less apparent in these surveys. Because survey mode is not randomly assigned, we cannot be sure differences in age profiles of wellbeing and illbeing are causally affected by survey mode. Selection into survey mode, both across and within country, plus differential non-response by survey across the age range, may be playing a role. However, the evidence indicates very different age patterns in wellbeing and illbeing emerge across different survey modes. |
| JEL: | I31 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35058 |
| By: | Bryson, Alex; Kauhanen, Antti; Rouvinen, Petri |
| Abstract: | Abstract Utilizing nationally representative cross-sectional and longitudinal data from Finland (2018–2023), we provide a population-level assessment of the relationship between AI and worker well-being. Contrary to international evidence suggesting a positive or an inverted U-shaped relationship, we find no systematic association between AI use intensity and job satisfaction. However, we do find that work engagement is higher among employees who are personally involved with AI, with the strongest association among intensive users for whom AI is an essential part of their work. Furthermore, technology-replacement fears have remained stable despite rapid AI advancement and do not predict subsequent labour market transitions. An interpretation is that Finland’s high-trust institutional environment and robust social safety nets may effectively moderate the disruptive psychological and economic shocks typically associated with rapid technological change. |
| Keywords: | Artificial intelligence, Job satisfaction, Work engagement, Technology-related fears, Labour market transitions |
| JEL: | J28 L23 |
| Date: | 2026–04–07 |
| URL: | https://d.repec.org/n?u=RePEc:rif:wpaper:137 |
| By: | Nicholas Bloom; Gordon B. Dahl; Dan-Olof Rooth |
| Abstract: | There has been a dramatic rise in disability employment since the pandemic. At the same time, work from home (WFH) has risen four-fold. This paper asks whether the two are causally related. Controlling for compositional changes and labor market tightness, a 1 percentage point increase in WFH increases full-time employment by 1.0% for individuals with a physical disability. The postpandemic increase in working from home explains 68%-85% of the rise in full-time employment. Wage data suggests that WFH increased the supply of workers with a physical disability, likely by reducing commuting costs and enabling better control of working conditions. |
| Keywords: | work from home, disability employment |
| JEL: | J14 J42 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12604 |
| By: | Manuel Arellano (CEMFI, Centro de Estudios Monetarios y Financieros); Orazio Attanasio (Yale University, NBER and CEPR); Margherita Borella (Università di Torino, CeRP-Collegio Carlo Alberto and CEPR); Mariacristina De Nardi (University of Minnesota, Federal Reserve Bank of Minneapolis, CEPR and NBER); Gonzalo Paz-Pardo (European Central Bank) |
| Abstract: | We develop a new approach to estimating earnings, job, and employment dynamics using subjective expectations data from the NY Fed Survey of Consumer Expectations. These data provide beliefs about future earnings offers and acceptance probabilities, offering direct information on counterfactual outcomes and enabling identification under weaker assumptions. Our framework avoids biases from selection and unobserved heterogeneity that affect models using realized outcomes. First-step fixed-effects regressions identify risk, persistence, and transition effects; second-step GMM recovers the covariance structure of unobserved heterogeneities such as ability, mobility, and match quality. We find lower risk and persistence of the individual productivity component than in prior work, but greater heterogeneity in ability and match quality. Simulations show that reduced-form estimates overstate persistence and volatility on individual-level productivity due to job transitions and sorting. After accounting for heterogeneity, volatility declines and becomes flat across the earnings distribution. These results underscore the value of expectations data. |
| Keywords: | Subjective expectations, earnings dynamics models. |
| JEL: | C23 C81 D15 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:cmf:wpaper:wp2026_2605 |