This paper gives an overview of fertility data for Germany, Austria and Switzerland. Particular attention is given to the availability of order-specific fertility data. We discuss the quality of data provided by the Statistical Offices, both birth registration data and censuses or microcensuses. In addition, we explore how social science surveys can be used to generate order-specific fertility indicators, and compare fertility estimates across surveys with estimates from vital statistics. Prior studies have shown that there is a ’family bias’ in most surveys, with the fertility of the younger cohorts being overstated, because respondents with young children are easier to reach by the interviewers. Our assessment of various types of surveys from the three different countries does mostly support this notion. However, the ‘family bias’ is most pronounced in family surveys while all-purpose surveys suffer from it to a lesser extent. Weighting the data does not fully cure the ‘family bias’, which we attribute to the fact that number of children is not usually considered a factor in calculating sample weights, as provided by the survey agencie and Statistical Offices. The confounding role of migration in the production of reliable and comparable fertility statistics is also discussed.
Academic women in Austria and Germany have extraordinarily high final levels of childlessness of 45-60%, as documented by prior research. This study investigates how female scientists’ fertility behaviour relates to their childbearing ideals and intentions in Austria. It analyses whether high childlessness and low numbers of children are intended or not. By looking additionally at employment conditions and partnership status, this study points to possible obstacles hindering couples to realise their childbearing desires. Furthermore, it shows how female scientists combine their academic career and childcare. The analysis is based on a sample of female scientists who had applied for a grant at the Austrian Academy of Sciences (n=196). It comprises women aged 25-45 who work in different scientific fields in Austria. Female scientists aged 40-45 have 0.9 children on average and 44% remain childless. However, these levels are far from the number of offspring that young scientists under the age of 35 intend to have. They perceive on average two as their ideal and intended number; only around 10% want to stay childless. Several obstacles which impede childbearing were identified, e.g. the strong work commitment of the female scientists, the need to be geographically mobile and the high prevalence of living apart together relationships. As for the combination of work and family, female scientists return back to work quickly after they have a child. Most do not regard the family as the main caregiver but perceive a division of tasks between the family and the public as preferable.
The paper analyses the advantages and shortcomings of the two approaches of generating indicators of fertility patterns on the example of German speaking countries (Austria, Switzerland and Germany). Individual-level surveys like the Fertility and Family Survey (FFS), Generations and Gender Survey (GGS) or Population Policy Acceptance Survey (PPA) are primary sources for fertility analysis. Investigations from surveys are essential for understanding how socioeconomic and cultural factors determine family formation patterns. The main purpose of surveys is usually not deriving fertility rates, anyway it is important to see how reliable these data can be and whether they cover the reality sufficiently. Survey data are limited due to two crucial issues: sample sizes are too small and time periods are too short to display long time trends. The sample bias related to fertility estimates should be considered carefully – some members of population could be underreported in the sample, which might be corrected by incorporating weights. Hence, a clear validation is important for assessing the degree of reliance due to estimations from survey data. Vital statistics or data from population censuses have an important advantage over survey data because they provide a large number of recorded persons. Furthermore, demographic events are precisely recorded by official registers. However, the detail of the given information is not always sufficient (e.g. lacking information on birth order in Germany and Switzerland). The major question is to see if fertility indicators based on individual-level survey data differ substantially from those reported in vital statistics. Do we always face the same patterns of discrepancies due to the notorious problem of overestimation of fertility levels in surveys? The paper concludes that single and childless women are usually underreported in surveys, overestimating thus the level of fertility. The comparative approach of the paper allows assessing the quality of selected surveys.
The „Generations and Gender Survey (GGS)“ is an important data source for studying the dynamics of families and family relationships, it was out in Austria in 2008/09. After adjustment for age, sex, employment status, country of birth and living arrangements, we revealed a bias towards women with higher parities among the cohorts born until the mid- 1970s. Since parity is an important aspect for fertility analyses, weights were generated for the female sample that additionally adjust for the cohort-specific parity distribution. In this paper, we describe the original prevailing bias and inform the GGS user about the adjustment with the weights for the Austrian GGS. These weights are provided by VID to the international scientific community and are included in the Austrian GGS dataset.