Video

Speaker: Stefani Scherer University of Trento
Employment remains among the most important factors to protect individuals and their families from economic poverty. However, recent years have witnessed an alarming increase of in-work poverty (IWP), thus of being poor notwithstanding employment.

Speaker: Alicia Adsera, Princeton School of Public and Social Affairs

Married men earn more than single men do, while married women work less than single women do. Whether the differences arise from selection (those with more potential earnings are more likely to marry) or from specialization (within marriage, men specialize in labor market skills) has been long debated. Are those cohabiting working and earning more like married or single individuals? How does the presence of children explain these differences?

Speaker: Paweł Bukowski, London School of Economics and Political Science
Presentation based on paper joint with Gregory Clark, Attila Gaspar and Rita Peto.
In this study, social mobility rates in Hungary 1949-2017, for upper class and underclass families were measure, using surnames to measure social status.

Speaker: Lucas van der Velde, Warsaw School of Economics
How does extending family influence attitudes and behaviour? Does it make people more conservative?

Speaker: Andre Grow, Max Planck Institute for Demographic Research
An increasing number of scholars advocate the use of Facebook’s advertising platform to recruit participants for survey research. This approach has been applied in the context of both surveys of the general population and surveys of hard-to-reach subpopulations. In this presentation, I will discuss this new approach to respondent recruitment in some detail, focusing on advantages, challenges, and practical considerations.

Speaker:
Daniele Vignoli, University of Florence
The sociological and demographic literatures have widely demonstrated that fertility decisions are constrained by individuals’ previous life experiences and socioeconomic status – the “shadow of the past”. However, rising uncertainty in contemporary societies necessitates an analytical framework that acknowledges the influence of the future in the fertility decision-making process.

Speaker: Paola Profeta, Director, Msc Politics and Policy Analysis, Bocconi University; Director, AXA Research Lab on Gender EqualityPresident, European Public Choice Society
Does removing the constraints of time and place of work increase the utility of workers and firms?
The outbreak of the 2019 novel coronavirus is threatening the growth of the economy worldwide. To contain the spread of the coronavirus and curb the contagion, workers have been allowed to work outside their workplace, thanks to the use of technology.
The coronavirus induced home-office as the only way to continue working during the pandemic and avoid the collapse of the economy.

Speaker: Eva Fodor, Co-Director, CEU Democracy Institute, Associate Professor, Department of Gender Studies, Central European University

As most other EU countries, Hungary implemented severe lockdown measures during the 1 st wave of the pandemic in the spring of 202, including the closure of the schools and childcare facilities. This meant that for several months a vastly increased volume of childcare had to be supplied by individual households without much institutional help. In the end of May 2020, we conducted a representative survey in Hungary to find out how the pandemic affected the gendered division of these childcare and other types of care duties. In this talk I will review the results of our survey, consider its implications for women’s paid labor market participation and assess their long-term consequences in light of the growing international comparative literature and a qualitative study conducted simultaneously in Hungary.

Speaker: Sylvia Fuller,
University Job loss can be difficult to navigate for individuals and their families, and is an increasingly salient concern in the COVID-19 pandemic. This talk draws on forthcoming research to illuminate the relationship between gender, parental status, and job loss prior to and during the COVID-19 pandemic in Canada. Pooled data from Statistics Canada’s Workplace and Employee Survey from 1999-2005 reveals the extent to which intersections of gender and parental status are associated with pre-pandemic risks of job loss and its consequences: re-employment, unemployment, and quality of new jobs relative to those that were lost. We find that parenthood reduces the probability of job loss for prime-age men with young children, but only when employer discretion is involved. Despite similar risks of job loss relative to other groups, mothers of young children are the least likely to be re-employed in the subsequent year, mainly because of their higher levels of labour market withdrawal rather than unemployment. Holding out for “family friendly” work arrangements does not seem to account for this pattern. Job loss dynamics thus not only reflect but also reinforce asymmetrical breadwinning and caring roles for mothers and fathers of preschool-aged children. Labour Force Survey Data over the course of the pandemic also reveal asymmetrical effects for mothers and fathers that magnify gender differences in employment among parents.

Speaker: Marcello D'Orazio, Italian National Institute of Statistics (Istat)

Statistical matching (aka data fusion or synthetic matching) denotes a wide set of statistical techniques aimed at exploiting data collected in independent (sample) surveys referred to the same target population; the purpose is that of investigating the relationship between variables not jointly observed in the same survey. These techniques date back to the ‘60s, but they became very popular around 2000 (Rässler’s monograph published in 2002; D’Orazio at al monograph in 2006); they represent a way to respond to increasing user’s demand of new statistical outputs but avoiding the negative implications of enlarging questionnaires of exiting surveys (to collect a wider set of data) in terms of response burden and accuracy of collected data. Most of the statistical techniques proposed for data fusion purposes are adaptions of methods developed to deal with missing values in surveys; they include both parametric and nonparametric methods that can serve for estimating a target parameter (correlation or regression coefficient) or just creating a “synthetic” data source at microdata level.
Despite the efforts, many of the applications of data fusion techniques to integrate independent surveys not designed to be integrated a posteriori turned out unsuccessful; mainly because of the many unmet underlying assumptions and constraints. In National Statistics Offices the lesson learnt led to redesign some of the household surveys having in mind also the integration purposes.
The webinar will give an overview of the most popular statistical matching techniques and the underlying assumptions, that play a key role in their application. The webinar will also highlight the critical points in designing a statistical matching application.

Speaker: Melanie Arntz, University of Heidelberg

The role of skill-biased technological change for increasing wage inequality is well documented. However, technological change may improve equality of opportunity if it increases returns to individual abilities relative to the returns to parental background. In line with this, we find that the wage penalty associated with a disadvantaged family background declined. Our analysis shows that this development is consistently linked to technological progress. The introduction and the use of new technologies in certain occupations explain the rising share of workers with disadvantaged parental background in those occupations as well as their rising relative wages. Moreover, we provide evidence that the depreciation of parents’ occupation-specific knowledge and networks during rapid technological transformations is a major force behind these shifts. Hence, technological change turns out to be an equalizing force that creates labor market opportunities for workers from a disadvantaged family background.

Speaker: Massimo Anelli, Bocconi University
Robots have radically changed the demand for skills and the role of workers in production. This phenomenon has replaced routine and mostly physical work of blue collar workers, but it has also created positive employment spillovers in other occupations and sectors that require more social interaction and managing skills. This study examines how the exposure to robots and its heterogeneous effects on the labor market opportunities of men and women affected demographic behavior. Researchers focused on the United States and find that in regions that were more exposed to robots, gender gaps in income and labor force participation declined, reducing the relative economic stature of men. Regions affected by intense robot penetration experienced also an increase in both divorce and cohabitation and a decline -albeit non-significant- in the number of new marriages. While there was no change in the overall fertility rate, marital fertility declined, and there was an increase in out-of-wedlock births. The findings are consistent with the prediction of the classical Becker's model (1974) and provide further support to the hypothesis that changes in labor market structures that affect the prospects of men may reduce their marriage-market value and affect marital and fertility behavior.

Speaker: Tomáš Sobotka
Vienna Institute of Demography (Austrian Academy of Sciences) / Wittgenstein Centre for Demography and Global Human Capital
Increasing control over reproduction has brought one of the major social transformations in modern times—a wide-scale shift to a small family size that is now under way all around the world. Despite long-lasting experience of low and very low fertility across the highly developed countries, period fertility rates in many countries remain unstable and difficult to predict.