The absent or tenuous population-level association between early life fertility and completed fertility was coined, broadly, “fertility recuperation”, and its most common demographic foot-print in literature is the comparison of fertility rates by age between two consecutive cohorts. However, this analysis does not provide a quantitative framework and does not distinguish whether recuperation is a focalized process, mainly because each age-based fertility rate is itself the outcome of postponing and recuperation at the same time. In this study I propose breaking down total fertility into the age at first birth and the total fertility rate thereafter; this break down works for aggregated and individual indicators of fertility in a straightforward manner. I apply this framework to characterize the recuperation among European countries as the interplay between changes in the age at first birth and changes in the fertility rate thereafter. Using survey data, I found that recuperation is present only in West European Countries, and that birth cohorts where recuperation is first found are characterized by higher total fertility rates of old mothers (meaning women that have a first birth at a late age). Old mothers, in fact, entirely explain the appearance of recuperation.
Kreyenfeld, M. and Zeman, K. and Burkimsher, M. and Jaschinski, I.
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.