All time references are in CEST
Socio-demographic and socio-economic variables in different data sources |
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| Session Organisers |
Dr Silke Schneider (GESIS - Leibniz Institute for the Social Sciences) Professor Christof Wolf (GESIS - Leibniz Institute for the Social Sciences) |
| Time | Wednesday 19 July, 11:00 - 12:30 |
| Room | U6-01f |
Because many research questions in the social sciences revolve around questions of social differentiation and social inequality most data collections include measures of socio-demographic and socio-economic variables. In stark contrast to the theoretical importance of these dimensions stands the mostly missing national or international standards for measuring the respective concepts.
During the past years some work in this regard has been done with respect to some of these dimensions, e.g. education. But for most of the variables in the “background variables block” only little systematic work was carried out. Furthermore, the empirical research up to now has almost exclusively focused on measuring aspects of differentiation and inequality in social surveys. Because social research is increasingly also using other data sources, such as social media posts or data from tracking devises, the issue of measuring socio-demographic and socio-economic variables has become even more complex. For these new datatypes such variables are either available in very reduced form only, and thus have poor information value, or entirely absent. Inclusion of socio-demographic and socio-economic variables would, however, enormously increase the analysis potential of such data.
This session brings together contributions on the measurement of socio-demographic and socio-economic variables in surveys and other individual level data collections. Welcome issues to be discussed are, among others, measurement/detection of attributes, data quality, comparability (across data sources within countries, for data sources across time, as well as across countries), harmonization and standardization.
Keywords: socio-demographics, variables, harmonization, comparability
Professor Aviad Tur-Sinai (The Max Stern Yezreel Valley College) - Presenting Author
Dr Marina Motsenok (Ben-Gurion University of the Negev)
Among the economic decisions that people expect to make in their lives, some relate to the need to establish priorities for their activities and when to undertake them. Some of these activities concern events in the present; others involve constructing processes foreseen mainly in the future. A deeper understanding of the determinants and considerations that may assure individuals and their households an appropriate economic horizon and quality of life is needed. One of the main processes in ensuring financial and economic strength is the financial planning horizon, in which individuals determine the most important time horizon for their saving and spending. The study focuses on mapping and understanding the set of characteristics that determine older adults’ financial planning horizons.
This study yields a deep and broad picture of the determinants of the financial planning horizon of people aged 50+, using data from four waves of SHARE that elicit information on older adults’ present and childhood (n=35,719, 52.69% female).
The study shows that individuals’ financial hardship and/or exposure to hunger in childhood lower the probability of preferring a lengthy planning horizon for their future saving and spending; people at a high cognitive ability tend to plan their saving and spending to the long term; and individuals’ and households’ economic decisions hinge on their households’ economic capacity. Among those of working age, a perfect substitution is found between individuals’ characteristics in childhood and their economic characteristics and cognitive ability in the present.
Given the steady upturn in life expectancy and the ongoing need to assure the older population an optimal standard of living, the current study provides a deeper look and a better understanding of the full set of determinants and characteristics that may assure individuals and their households an adequate economic horizon and quality of life.
Mr Harry Ganzeboom (VU University Amsterdam) - Presenting Author
In comparative research, the level of education is routinely measured using one of two methods. The qualification method measures the level by highest (or most recently achieved) diploma. Best practice here is to measure the qualifications in country-specific term and then to post-harmonize these using a common denominator. The recent development of the three-digit International Standard Classification of Education 2011 (ISCED-2011) has become a major game-changer in this methodology, because for the first time a detailed and rigorous harmonization framework has become available, which allows the research to scale to qualifications to an internationally valid linear metric (Schröder & Ganzeboom 2014). Alternatively, comparative research measures level of education using its duration, best collected as a question to respondents about the (net) length of their educational careers. Both methods have their pro’s and con’s, and their fervent proponents and opponents (Braun & Müller 1997; Schneider 2009). We examine these arguments and conclude that the discussions have overlooked the fact that qualification measures and duration measures are strongly correlated and can usefully be regarded as parallel indicators of the same underlying construct.
We then examine the quality of the qualification and duration measures empirically using a Saris & Andrews (1991) Multi-Trait Multi-Method model. This reformulation of the classical MTMM models allows one to derive separate validity and reliability coefficients. The model is tested on ISSP data 2002-2016 from the Netherlands, in which both qualification and duration measures have been obtained for respondent and partner. The model is also estimated on EU-SILC household data, in which both types of measurement have been obtained for all members of the household (both partners and children). The provisional estimates indicate almost equal validity of the qualification measures
Dr Diana Schacht (DJI Munich) - Presenting Author
Dr Claudia Recksiedler (DJI Munich)
Dr Simone Schüller (DJI Munich)
Professor Christina Boll (DJI Munich)
Dr Christine Entleitner-Phleps (DJI Munich)
Dr Claudia Langmeyer (DJI Munich)
Professor Sabine Walper (DJI Munich)
Dr Claudia Zerle-Elsäßer (DJI Munich)
The landscape of families and their living arrangements have changed rapidly in Germany over the last decades, similar to those in many other Western countries. Steady increases in separations and divorces and non-marital childbirth have led to an increase of post-separation family constellations. Particularly the group of single parents, which used to be mainly widowed women or young, unmarried mothers of lower socioeconomic status, is becoming increasingly heterogeneous with regard to their socio-demographic characteristics. Furthermore, trends of increased paternal involvement and faster re-partnering may increase the heterogeneity of post-separation family models.
However, it is difficult to adequately identify and describe the increasing heterogeneity of post-separation families because stepfamilies and continuously partnered two-parent families cannot be distinguished in the administrative data. Also, in many of the large surveys in Germany, little is known about the existence or involvement of a nonresidential biological parent, and it is often not possible to retrieve information on more than one residential household per child if children alternate between the separated parents.
Our study aims at closing these gaps by introducing a comprehensive module on the child-residence and childcare division patterns, coparenting, communication, and conflict between post-separation parents, that was implemented in the 2021 survey wave of the representative panel study “Growing up in Germany”.
We present this module, its added value, and research potentials in combination with the wide range of other information collected in the survey (e.g., economic deprivation, subjective well-being, health, education, and every-day family practices). We compare the sociodemographic group of single-parent households identifiable in the administrative data with the heterogeneity of post-separation family models in the module. Moreover, we discuss how other large international panel surveys cover post-separation families and outline possible future pathways for standardization.
Professor Anna Kiersztyn (University of Warsaw) - Presenting Author
Dr Katarzyna Kopycka (University of Warsaw)
In this presentation we introduce a novel measure of employment precarity (EP) applicable to longitudinal career data. We propose a sequence-based index of EP suitable for cross-national comparisons and discuss its empirical application.
EP is an important aspect of social inequality, giving rise to inequalities in other life domains. As such, it is of theoretical importance as an explanatory variable in studies of health and well-being, political attitudes, fertility decisions, and others. However, cross-national comparative research on precarity and its outcomes is hampered by measurement problems. We argue that the use of fixed-term employment indicators as a proxy for EP in cross-national analyses raises comparability issues, as these variables apply a single label to workers in different situations, depending on country-specific labor market regimes. Furthermore, they exclude the increasingly important categories of freelance workers and dependent self-employed. We also claim that adequate measurement of EP requires: (a) analyzing career sequences rather than work characteristics at one time point, to account for the heterogeneity of career dynamics (stepping-stone vs. entrapment effects); (b) using measures of the objective employment situation of individuals rather than their subjective perceptions, which are affected by psychological coping and reference group comparisons.
We conceptualize EP as career sequences involving high job turnover, periods of joblessness, and low income. These experiences carry a similar meaning across institutional contexts, enabling cross-country comparisons, and may be captured using information usually available in national panel datasets. Building on existing approaches to constructing synthetic indexes characterizing sequence data, we propose a Cross-National Precarity Index (CNPI) to quantify the longitudinal severity of the adverse experiences listed above. We then offer illustrations of the possible empirical applications of CNPI using data from the German Socioeconomic Panel and National Longitudinal Survey of Youth (NLSY97).