Does Intergenerational Educational Mobility Shape the Well-Being of Young Europeans? Evidence from the European Social Survey

Using pooled European Social Survey data (Rounds 4-7, 2008-2014), we investigate the relationship between intergenerational educational mobility and subjective wellbeing (SWB) for young Europeans (N = 16,050 individuals aged 25-34 from 18 countries). Previous research has been struggling with inconclusive results due to the methodological challenge of disentangling the independent (i.e., "net") effect of social mobility over and above the effects of social origin and destination. We contribute to this line of research by contrasting mobility effects estimated in a conventional linear regression framework with net mobility effects estimated by (non-linear) diagonal mobility models (DMM). We show how model selection influences estimates of mobility effects and how different specifications lead to radically different findings. Using DMM, we estimate how intergenerational educational mobility affects the SWB of young Europeans, differentiating between downward and upward mobility and different country groups. Our results suggest that status loss/gain across generations affects young adults' SWB in addition to the level-effect of ending up in a lower/ higher status position only in Continental Europe

How Intergenerational Mobility Shapes Attitudes toward Work and Welfare

Past experiences and expectations about the future shape how people think about work and welfare. Given the uncertainty many young people face when entering the labor market, we investigate whether 1) young peoples’ experiences of social mobility and 2) their future mobility expectations impact their attitudes regarding the meaning of work and welfare. Drawing on the concepts of self-interest and deservingness, we examine how both the experiences and expectations of intergenerational social mobility influence the ways in which young adults view the so-called moral dimension of work and welfare. Results of logistic regression analyses of around 11,000 young adults in eleven countries suggest that the relationship between mobility and individuals’ views on work and welfare varies depending on the dimension of mobility (economic and social origins, for example), with expected future mobility exerting a stronger effect on attitudes than past mobility experiences. We find that self-interest, not empathy with one’s social origins, appears to be the primary driver of these attitudes

Intergenerational mobility of young Europeans: A comparative analysis of social and political consequences

This thesis sets out to investigate social and political consequences of young Europeans’ experiences of intergenerational mobility, i.e., achieving a higher or lower socioeconomic status than one’s parents. In particular, it aims at providing a better understanding of how young Europeans’ (aged 35 and younger) experience of intergenerational mobility shapes their well-being and normative support for the welfare state. Apart from a descriptive overview on the status quo of intergenerational mobility among young Europeans in three dimensions (educational mobility, economic mobility, and expectations of future mobility), the main objective of the empirical analyses is to investigate the extent to which the psychological experience of intergenerational mobility, independent from the direct impact of one’s own and parental socioeconomic status, affect different dimensions of well-being and political attitudes. To this end, I apply diagonal reference models, the only method suitable to disentangle the effects of mobility, social origin, and social destination. With respect to possible consequences of intergenerational mobility for the young people’s well-being, I investigate several hypotheses about individual and societal differences between mobile and non-mobile individuals. In line with the theoretical prediction that psychological mobility effects are more likely to occur in status-based societies, I find net mobility effects in Continental Europe and the Anglo-Saxon countries. Yet, contrary to the theoretical expectations, I also find net mobility effects in the Nordic countries. In terms of political consequences of intergenerational mobility of young Europeans, I test two competing sets of hypotheses about differences in normative welfare state attitudes between mobile and non-mobile individuals. Thereby, the first set relies on material self-interest as the main determinant for welfare state support, while the second set is based on factors beyond material self-interest, such as deservingness perceptions. The empirical findings do not support the prediction of mobile individuals being more sympathetic with benefit recipients. This arguably owes to the fact that the well-known determinant material self-interest apparently plays a similar role in determining normative welfare state attitudes for the mobile as for the non-mobile

Correction to: Perceived economic self-sufficiency: a country- and generation-comparative approach

After online first publication of the article, it was noticed that the family name of author Panos Tsakloglou was erroneously misspelt as Tsakoglou

Self-reported emotion regulation difficulties are associated with mood but not with the biological stress response to thin ideal exposure

BACKGROUND:Difficulties in emotion regulation have been related to psychological and physiological stress responses such as lower mood and lower parasympathetic activation (HF-HRV) under resting condition, but evidence on the potential link to the hypothalamic-pituitary-adrenal (HPA) axis functioning and to physiological stress responses during a stress task is still scarce. The aim of the study was to investigate stress responses in young women when confronted to a daily stressor such as exposure to thin ideals and to understand the role of correlates of self-reported trait-like emotion regulation difficulties (ERD). METHODS:Heart rate variability (HRV) and salivary cortisol data were collected in a sample of 273 young women aged 18-35 with and without mental disorders during a vivid imagination of thin ideals (experimental condition) or landscapes (control condition). Changes in mood states were measured on a visual analogue scale (0-100). Correlates of trait-like ERD were self-reported using the Difficulties in Emotion Regulation Scale (DERS). RESULTS:Participants with higher ERD showed a stronger decline in self-reported mood after vivid imagination of thin ideals compared to participants with lower ERD in the experimental condition but also a stronger increase of positive mood with increasing ERD in the control condition. ERD were not related to baseline HF-HRV or baseline salivary cortisol levels nor to any physiological response during and after the imagination of thin ideals. DISCUSSION AND CONCLUSION:The results corroborate the role of ERD regarding the immediate psychological impact of daily stressors. Exposition to daily stressors in the laboratory results in discrepant psychological and physiological reactivity. Future studies should investigate under what conditions the complex interrelations between immediate and long-term ERD and biological activation are amenable to assessment in a laboratory setting. The additive effects of multiple exposition to stressors, such as thin ideals in daily life, also need to be addressed

Perceived economic self‑sufficiency: a countryand generation‑comparative approach

We thank Michael Camasso and Radha Jagannathan as well as Asimina Christoforou, Gerbert Kraaykamp, Fay Makantasi, Tiziana Nazio, Kyriakos Pierrakakis, Jacqueline O’Reilly and Jan van Deth for their contribution to the CUPESSE project (Seventh Framework Programme; Grant Agreement No. 61325). CUPESSE received additional funding from the Mannheim Centre for European Social Research (MZES) and the Field of Focus 4 “Self-Regulation and Regulation: Individuals and Organisations” at Heidelberg University. We further acknowledge helpful comments on this article by two anonymous reviewers. Julian Rossello provided valuable research assistance.Electronic supplementary material The online version of this article (https ://doi.org/10.1057/ s4130 4-018-0186-3) contains supplementary material, which is available to authorized users.Existing datasets provided by statistical agencies (e.g. Eurostat) show that the economic and financial crisis that unfolded in 2008 significantly impacted the lives and livelihoods of young people across Europe. Taking these official statistics as a starting point, the collaborative research project “Cultural Pathways to Economic Self-Sufficiency and Entrepreneurship in Europe” (CUPESSE) generated new survey data on the economic and social situation of young Europeans (18–35 years). The CUPESSE dataset allows for country-comparative assessments of young people’s perceptions about their socio-economic situation. Furthermore, the dataset includes a variety of indicators examining the socio-economic situation of both young adults and their parents. In this data article, we introduce the CUPESSE dataset to political and social scientists in an attempt to spark a debate on the measurements, patterns and mechanisms of intergenerational transmission of economic self-sufficiency as well as its political implications.CUPESSE project (Seventh Framework Programme; Grant Agreement No. 61325

Better Overeducated than Unemployed? The Short- and Long-Term Effects of an Overeducated Labour Market Re-entry

Previous studies have shown that overeducation is inferior to adequate employment. For example, overeducated workers have lower earnings, participate less often in continuing education and training, and are less satisfied with their jobs. This article changes perspectives by asking whether it is better for the unemployed to take up a job for which they are overeducated or to remain unemployed and continue the search for adequate employment. Theoretically, we rely on the established confrontation of the stepping-stone and trap hypotheses, which make opposing predictions in terms of long-term employment chances and job quality. Using the German Socio-Economic Panel (1984–2012) and applying a dynamic propensity score matching approach, the analyses reveal an interesting trade-off. Although an overeducated re-entry increases the long-term employment chances persistently, it also implies strong lock-in effects into overeducation for up to 5 years after re-employment. In sum, the results support the stepping-stone hypothesis in terms of future employment chances, but also highlight non-negligible risks of remaining trapped in a job that is below one’s level of educational qualification

Einsatz von Künstlicher Intelligenz in der Deutschen Wirtschaft: Stand der KI-Nutzung im Jahr 2019

Dieser Bericht gibt einen statistisch repräsentativen Überblick zum aktuellen Stand des Einsatzes von Künstlicher Intelligenz (KI) in den Unternehmen in Deutschland im Jahr 2019. Datengrundlage ist eine Sonderauswertung der Deutschen Innovationserhebung des Jahres 2019 sowie einer Zusatzbefragung von KI einsetzenden Unternehmen. KI wurde dabei sehr allgemein als "Technik der Informationsverarbeitung zur eigenständigen Lösung von Problemen durch Computer" definiert. Die Hauptergebnisse sind: * Im Jahr 2019 haben rund 17.500 Unternehmen im Berichtskreis der Innovationserhebung (produzierendes Gewerbe und überwiegend unternehmensorientierte Dienstleistungen) KI in Produkten, Dienstleistungen oder internen Prozessen eingesetzt. Das sind 5,8 % aller Unternehmen im Berichtskreis. * Die Ausgaben für die Entwicklung, Einführung und Pflege von KI-Verfahren beliefen sich im Jahr 2019 auf rund 4,8 Milliarden Euro. Das sind rund 270 Tausend Euro je Unternehmen mit KI-Einsatz. Drei Viertel der KI-Ausgaben sind interne laufende Aufwendungen (insbesondere für Beschäftigte). * In den KI einsetzenden Unternehmen waren im Jahr 2019 rund 50.000 Personen hauptsächlich zu KI tätig. Weitere ca. 89.000 Personen befassten sich zu einem kleineren Teil ihrer Arbeitszeit mit KI. Die ca. 139.000 zu KI tätigen Personen entsprechen 0,84 % aller Beschäftigten im Berichtskreis. * 4,4 % aller Unternehmen im Berichtskreis setzen KI in Produkten oder Dienstleistungen ein und erzielten damit 2019 einen Umsatz von knapp 60 Milliarden Euro. Das entspricht 1,1 % des Umsatzes aller Unternehmen und 7,7 % des Umsatzes der KI einsetzenden Unternehmen. * Nur für einen kleinen Teil der KI einsetzenden Unternehmen (12 %) ist KI essenziell für die Geschäftstätigkeit. Dies bedeutet, dass ca. 2.100 Unternehmen ein stark auf KI basierendes Geschäftsmodell verfolgen. * Nur 16 % der KI einsetzenden Unternehmen haben die KI-Anwendungen selbst entwickelt. In 24 % erfolgte die Entwicklung sowohl durch das Unternehmen selbst als auch durch Dritte. 60 % griffen auf KIEntwicklungen durch Dritte zurück. * Zwei Fünftel der im Jahr 2019 KI einsetzenden Unternehmen nutzen KI bereits seit mehr als 5 Jahren. Dem steht ein gutes Viertel der aktuell KI einsetzenden Unternehmen gegenüber, die KI erstmals in 2018 oder 2019 im Unternehmen eingesetzt haben. * Das am weitesten verbreitete KI-Verfahren ist maschinelles Lernen und maschinelles Beweisen (55 % der KI einsetzenden Unternehmen). Verfahren der Bild- oder Tonerkennung sowie wissensbasierte Systeme werden jeweils von knapp jedem zweiten KI einsetzenden Unternehmen genutzt, Sprach- oder Textverstehen dagegen nur von weniger als einem Drittel. Hauptanwendungsgebiete für KI sind Produkte und Dienstleistungen sowie die Automatisierung von Prozessen. * Rund ein Drittel der KI einsetzenden Unternehmen nutzt für seine KI-Anwendungen ausschließlich interne Hardware, ein gutes Drittel sowohl interne als auch externe Hardware, und knapp ein Drittel greift ausschließlich auf externe Hardwarelösungen (Cloud-Dienste) zurück. * 30 % der KI einsetzenden Unternehmen haben im Jahr 2019 zusätzliche Beschäftigte für KI gesucht. Insgesamt waren in diesen Unternehmen 22.500 KI-Stellen offen. 47 % der Stellen konnten wie geplant besetzt werden, 11 % nur verspätet oder nicht mit den gewünschten Beschäftigten. 43 % der Stellen blieben unbesetzt. * Die von Bewerbenden für diese offenen KI-Stellen geforderten Kenntnisse betrafen fast durchweg Softwareprogrammierung. Zusätzlich waren für drei Viertel der Unternehmen mit offenen KI-Stellen Kenntnisse im Datenbankmanagement oder in Mathematik wichtig