Second Birth Fertility in Germany: Social Class, Gender, and the Role of Economic Uncertainty

Kreyenfeld, Michaela; Konietzka, Dirk; Lambert, Philippe; Ramos, Vincent Jerald Article — Published Version Second Birth Fertility in Germany: Social Class, Gender, and the Role of Economic Uncertainty European Journal of Population Provided in Cooperation with: Springer Nature Suggested Citation: Kreyenfeld, Michaela; Konietzka, Dirk; Lambert, Philippe; Ramos, Vincent Jerald (2023) : Second Birth Fertility in Germany: Social Class, Gender, and the Role of Economic Uncertainty, European Journal of Population, ISSN 1572-9885, Springer Netherlands, Dordrecht, Vol. 39, Iss. 1, https://doi.org/10.1007/s10680-023-09656-5 This Version is available at: https://hdl.handle.net/10419/313679 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Vol.:(0123456789) European Journal of Population (2023) 39:5 https://doi.org/10.1007/s10680-023-09656-5 1 3 ORIGINAL RESEARCH Second Birth Fertility inGermany: Social Class, Gender, andtheRole ofEconomic Uncertainty MichaelaKreyenfeld1 · DirkKonietzka2· PhilippeLambert3,4· VincentJeraldRamos1,5 Received: 23 August 2022 / Accepted: 15 January 2023 / Published online: 2 March 2023 © The Author(s) 2023 Abstract Building on a thick strand of the literature on the determinants of higher-order births, this study uses a gender and class perspective to analyse second birth progression rates in Germany. Using data from the German Socio-Economic Panel from 1990 to 2020, individuals are classified based on their occupation into: upper service, lower service, skilled manual/higher-grade routine nonmanual, and semi-/unskilled manual/lower-grade routine nonmanual classes. Results highlight the “economic advantage” of men and women in service classes who experience strongly elevated second birth rates. Finally, we demonstrate that upward career mobility post-first birth is associated with higher second birth rates, particularly among men. Keywords Fertility· Germany· Uncertainty· Social class· Employment 1 Introduction Classical demography has devoted substantial attention to the issue of class differences in marriage and fertility behaviour. Malthus (1998 [1798]) is unquestionably the most foundational scholar in this context. A general premise of his work is that there is a strong negative class–fertility gradient. He argued that the higher social classes, which at that time were composed of landlords and members of the aristocracy, would limit their number of children out of a “fear of lowering their condition in life” (ibid.: 6). He also assumed that although the lower * Michaela Kreyenfeld [email protected] 1 Hertie School, Berlin, Germany 2 TU Braunschweig, Braunschweig, Germany 3 Université de Liège, Liège, Belgium 4 Université Catholique de Louvain, Louvain-la-Neuve, Belgium 5 Humboldt University Berlin, Berlin, Germany M.Kreyenfeld et al. 1 3 5 Page 2 of 27 social classes often lacked the necessary wealth and economic security to support a large family, their unrestrained sexual behaviour would result in high fertility. Malthus’ writings certainly reflect a striking degree of presumptuousness and a strong bias towards believing that the behaviour of his own social class was rational and conscientious (Petersen, 1990; Pullen, 2019). Nevertheless, his framework generated clear and testable hypotheses regarding the association between class, economic security, and fertility behaviour. Notestein (1936: p. 29) later elaborated on this perspective by asserting that class differences would “narrow or perhaps even reverse” if the fertility of the lower classes could be brought “more completely under control”. In contrast to early classical demographic research (Brentano, 1910; Malthus, 1998 [1798]; Sallume & Notestein, 1932; Notestein, 1936), contemporary demography has devoted relatively little attention to the role of social class differences in fertility behaviour. Fertility researchers only rarely refer to this concept and instead tend to focus on differences in birth dynamics by education (e.g. Bartus etal., 2013; Nitsche etal., 2018; Nisén etal., 2021), earnings (e.g. Andersson etal., 2014; Heckman & Walker, 1990), or employment (Hofman etal., 2017; Matysiak & Vignoli, 2008). Further, the role of economic uncertainty in fertility has garnered substantial attention among fertility researchers (Vignoli etal., 2020), particularly in the context of the global financial crisis (e.g. Goldstein etal., 2013; Schneider, 2015, 2017) and the recent COVID-19 pandemic (e.g. Guetto etal., 2021b). Given the increase in levels of labour market uncertainty, analyses of differences in behaviour across social classes may help to shed new light on contemporary fertility behaviour. Following the Weberian distinction between “class” (Klasse) and “status” (Stand), one’s “status” is rooted in social recognition and esteem (prestige). Social class is defined through people’s labour market positions, which are at the root of their long-term life chances, their economic vulnerabilities, and their employment risks (Erikson & Goldthorpe, 1992; Goldthorpe, 2007, 2010; Grusky & Sørensen, 1998). Within this framework, social classes represent firmly theorised and validated occupation-based categories that reflect economic uncertainties. The main goal of this paper is to elaborate on the concept of social class in the analysis of contemporary fertility behaviour. Moreover, we provide empirical evidence on the relationship between social class and second birth rates in postreunification Germany. Studying a single parity may be criticised as a “piecemeal approach” (Heckman & Walker, 1990, p.1416). However, there are benefits related to such a “piecemeal approach” when the interest is in the relation between social class and fertility. Assuming that people typically achieve a certain class position by the time they have their first child, the advantage of focusing on the second birth is that it enables us to examine how people’s class mobility after the first birth affects their subsequent fertility behaviour. The analysis relies on a proportional hazard model in which we use a piecewise constant specification for the underlying process. Some concerns have been raised that proportional hazard models may conflate timing and quantum effects (Bartus etal., 2013; Kreyenfeld, 2002). Thus, we address these using a cure fraction model that disentangles the two components. 1 3 Second Birth Fertility inGermany: Social Class, Gender, and… Page 3 of 27 5 2 Theoretical Considerations andPrior Research 2.1 Prior Research onUncertainty andFertility The Great Recession of 2008 has led to renewed scholarly interest in the role of economic uncertainty in fertility behaviour. This broad strand of the literature relies on objective measures of macroeconomic and labour market conditions, such as unemployment and fixed-term employment, as proxies for uncertainty (Alderotti et al., 2021). Recognising that uncertainty is high when economic conditions are dire, these studies generally agree that fertility rates are procyclical: i.e. they decrease during business cycle troughs, and increase during peaks (Adsera, 2005, 2011; Cazzola etal., 2016; Currie etal., 2014; Goldstein etal., 2013; Gozgor etal., 2021; Karaman Örsal & Goldstein, 2018; Sobotka etal., 2011). On the one hand, these short-run declines in period fertility may eventually translate into a “true” decline in completed cohort fertility, which implies a decrease in the total number of children that women of a certain cohort will have. On the other hand, these short-run declines in period fertility may be explained in part by postponement. For instance, Adsera (2011) found that first and second births occurred later in European countries that experienced high and persistent unemployment in the 1980s. However, one challenge that most of these studies encounter is that isolating fertility postponement (tempo effect) from a permanent decline in fertility (quantum effect) can be difficult (Sobotka etal., 2011). In addition to unemployment rates, an important strand of the literature has also considered other measures of economic uncertainty, including GDP (Luci- Greulich & Thévenon, 2014; Matysiak et al., 2021), consumer confidence (Comolli, 2017; Schneider, 2015), and press coverage of economic developments (Gozgor etal., 2021; Guetto etal., 2021a; Schneider, 2015). These studies have also provided support for the claim that adverse economic conditions are negatively correlated with fertility. Particularly during the global financial crisis of 2007–08, which was characterised by sudden and steep increases in unemployment, firm closures, and, more broadly, negative reports on the state of the economy, Schneider (2015) found that states in the USA that were hit hardest by the recession also had the largest decreases in general fertility rates. The fertility declines in these states at the height of the recession were attributed not just to the overall increase in uncertainty and economic hardship in these areas, but also to the increase in contraceptive use among selected population subgroups, particularly among unmarried women and women from lower-income backgrounds (Schneider, 2015, 2017). The findings mentioned above are complemented by an equally thick strand of the literature that has used subjective measures of economic uncertainty as determinants of fertility behaviour. These indicators are usually constructed from items in individual and household surveys that ask respondents whether they are worried about their own finances or the general state of the economy. Studies that used subjective measures of economic uncertainty have found that its effect on fertility is more nuanced; that is, that economic uncertainty seems to affect only M.Kreyenfeld et al. 1 3 5 Page 4 of 27 select population subgroups. Kreyenfeld (2010) and Hofmann and Hohmeyer (2013) have both reported that there is little support for the claim that financial worries translate into first birth postponement. However, studies that have taken levels of education into account have shown that economic uncertainty accelerates the transition to the first birth among less educated women (Kreyenfeld, 2010, 2015). Indeed, there is strong evidence of differences in fertility behaviour in response to economic uncertainty by gender, population subgroup, and birth order. In addition, a large body of research has examined how financial worries affect not just fertility behaviour, but fertility intentions. It has, for example, been shown that subjective economic uncertainty negatively affects birth intentions and that this relationship is more pronounced among men, given that men are often expected to take on a “primary provider role” (Busetta etal., 2019; Fahlén & Oláh, 2018; Kuhnt etal., 2021). Finally, a relatively recent body of research has also pointed to the role of future narratives of uncertainty as a determinant of fertility intentions (Brauner- Otto & Geist, 2018; Gatta etal., 2021; Vignoli etal., 2020). 2.2 Social Class Position andEconomic Uncertainty Many of the above-mentioned studies have grappled with the question of how a valid operational definition of economic uncertainty can be found. Having children is a long-term and binding commitment. Thus, it is not only people’s current economic conditions, but also their future employment prospects that influence their decisions about whether and, if so, when to have children. In this context, the concept “social class”, which is well established in research on social stratification and mobility, provides a potentially useful link. The theoretical backbone of contemporary class concepts is that in capitalist societies, individual life chances are essentially shaped by labour market, occupational, and employment conditions. Thus, social class is not interchangeable with education or income. Instead, it is a well-defined and “parsimonious indicator of the social positions of individuals” that helps us to “better understand fundamental forms of social relations and inequalities to which income is merely epiphenomenal” (Conelly etal., 2016: p. 3). Class researchers typically aggregate similar occupations into broader socio-economic class categories (Erikson etal., 1979; Goldthorpe, 2007; Oesch, 2006; Wright, 1985). Although class concepts differ with respect to their theoretical underpinnings and the basic mechanisms that are assumed to define and to distinguish classes, the prevalent class schemes, as developed by Erikson etal. (1979), Goldthorpe (2007), Wright (1985), and Oesch (2006), are aligned in terms of their basic occupational distinctions. For this study, the class schema proposed by Goldthorpe (2007) is particularly useful, as it suggests that occupational classes are inherently defined through employment relations. Accordingly, it is assumed that members of the same social classes have similar overall life chances, and are also exposed to similar degrees of economic vulnerability and uncertainty. Goldthorpe (2007: pp. 110–118) differentiated occupations based on whether the related tasks are difficult to monitor, and by whether the human assets required 1 3 Second Birth Fertility inGermany: Social Class, Gender, and… Page 5 of 27 5 for the occupations are specific. At the one extreme are occupations in which the tasks are difficult to monitor. People in these occupations usually have highly specific human assets (knowledge and expertise). At the other extreme are occupations in which the tasks are easy to supervise, and the quantity of work output is easy to measure. Furthermore, the human assets needed in these occupations are not specific. According to Goldthorpe (2007), the “nature of the tasks” and the “specificity of the human assets” determine the employment relationship. Based on this premise, he distinguishes nine categories, as described below (for details, see also the “Data, variables, and analytical strategy” section).1 Unskilled and semi-skilled manual workers [VIIa] and lower-grade routine nonmanual employees [IIIb] are often employed under short-term contracts. This implies that the jobs these categories take generally do not involve a long-term commitment from either the employer or the employee (Erikson & Goldthorpe, 1992: p. 41). Thus, the workers in these classes are subject to considerable economic uncertainty. The typical occupations in these classes include waiter, cleaner, shop assistant, housekeeper, taxi driver, and truck or van driver. In contrast to them, occupations in the upper and lower service classes [I, II] are mostly embedded in larger organisations, and “involve a longer term and generally more diffuse exchange” (ibid.: p. 103). Most importantly, the rewards associated with these occupations typically include “prospective elements”, such as employment security and “welldefined career opportunities” (ibid.: p. 103). Although the service classes have also been affected by the rise of fixed-term contracts, members of these classes generally enjoy greater employment stability than unskilled and semi-skilled labourers or routine nonmanual employees. These occupations include lawyer, scientist, engineer, higher-grade manager, in the German case also secondary school teacher (upper service class), as well as nurse, kindergarten teacher, technician, and lower-grade manager (lower service class). The skilled manual workers and supervisors [V, VI] as well as the higher routine nonmanual employees [IIIa] hold an intermediate position. These occupations involve mixed forms of employment relationships. The type of work done is either more difficult to monitor than un-/semi-skilled work, or it requires medium levels of specific human assets/human capital. The typical occupations in this category include machine operator, plumber, and electrician. Small employers/self-employed, farmers, and agricultural workers occupy separate classes [IVabc, VIIb]. These categories will not be considered in this investigation as they are small and heterogeneous. Although class concepts do not necessarily entail a 1 Goldthorpe (2007: p.104) distinguishes the following nine classes: I professional and managers, higher grade; II professional and managers, lower grade; IIIa routine nonmanual employees, higher grade; IIIb routine nonmanual employees, lower grade; IVabc small proprietors, self-employed; V technicians, lower-grade supervisors of manual workers; VI skilled manual workers; VIIa semi- and unskilled manual workers (other than in agriculture); and VIIb agricultural workers. M.Kreyenfeld et al. 1 3 5 Page 6 of 27 hierarchical ordering (Conelly etal., 2016), social classes can be ranked by their degree of employment risk, with levels of economic vulnerability and uncertainty being highest among the un- and semi-skilled workers and lower-grade routine nonmanual employees, and lowest among the upper service class. 2.3 Prior Research onOccupational Class andFertility While social class is a well-established concept in research on social inequality, only a relatively thin strand of recent literature has focused on the relationship between social class and fertility. Moreover, they have often adopted different strategies for classifying occupations. Some of the early studies, which were published when a large fraction of the population was still working in the agricultural sector, were particularly concerned with the elevated fertility of people working as farmers or farm labourers. An example is the study by Dinkel (1952), who argued that people in different occupations have different “ways of life” in terms of the practices and values that affect fertility. He showed that in the early twentieth century, farm owners and labourers had fertility rates that were 40–72% higher than those of professionals, depending on the region of residence in the USA. He attributed this gap in part to the labour needs of farming households (Dinkel, 1952; Maloney etal., 2014). Similar patterns have also been observed in Sweden in the mid-1900s, where farmers were shown to have the highest fertility rates among all occupational groups (Dribe and Scalone, 2014). More recent work has challenged these findings. For example, Köppen etal. (2017) found a drastic increase in childlessness among male farmers in France starting with the 1960s cohorts. More recent research has also emphasised the importance of incorporating a gender perspective into explanations of relationships between social class and fertility (Szreter, 2015). It has been reported that since the 1990s in Sweden, women’s occupational class has had a U-shaped relationship with the transition to parenthood, with women in low-skilled and high-skilled occupations having higher birth risks than women in medium-skilled occupations (Dribe & Smith, 2021). Research on Austria has found that women whose educational levels typically lead them to have lower-class occupations are less likely to remain childless than women whose educational levels lead them to have higher-class occupations (Neyer etal., 2017). Begal and Mills (2013) used data from the Netherlands to study the birth behaviour of women of the 1940–1985 cohort by groups of occupations and found that women in teaching-related occupations transitioned relatively quickly to first birth. Their results also indicated that women in communicative jobs (healthcare, teaching) transitioned relatively rapidly to higher-order fertility, while women in technologyrelated occupations had comparatively low higher-order birth risks.2 The studies that come closest to using the established sociological concepts of social class and analysing its relation to fertility generally find a positive relationship 2 In the Latin American context, scholars have also examined the class and fertility nexus (Castro Torres 2021). However, instead of relying on occupation-based class concepts, they measured social class using a large battery of variables, including electricity and water supply. 1 3 Second Birth Fertility inGermany: Social Class, Gender, and… Page 7 of 27 5 of being in a higher social class with second-order births (Baizan, 2020, 2021; Ekert-Jaffe etal., 2002). Using event history and simultaneous equation models on longitudinal data reveal elevated risks of women in the higher professional class in the transition to second birth in Spain (Baizan, 2020), as well as Austria, France, Norway, and the UK (Baizan, 2021). Gender also matters in this nexus—Ekert-Jaffe etal. (2002) find no strong variation in women’s fertility depending on their social class. However, they observed that the second birth rates of women with a spouse in a higher managerial position were well above average. Building on this strand of the literature, we likewise incorporate in our analysis the role of gender and economic uncertainty. 2.4 Hypotheses As Goldthorpe (2007) argued, social classes are based on people’s occupations and employment positions, which provide them with differing levels of socio-economic resources, including with varying degrees of employment security. Employment security is rooted in the nature of the job-related tasks the employee is expected to perform and in the kind of job contract deemed necessary to incentivise the employee to perform the tasks. Accordingly, class positions differ with respect to employee–employer commitment levels and trust relationships, and in terms of the long-term character of employment contracts. Assuming that fertility choices are long-term, binding biographical decisions that require some degree of economic certainty, it can also be assumed that fertility behaviour differs by social class. Given the more advantaged positions of the upper service class, individuals in this class should have the highest second birth rates, while the semi-/unskilled workers and the lower-grade routine nonmanual employees should have the lowest second birth rates (hypothesis 1). Compared to their income and earnings, peoples’ class positions are rather stable traits that mirror their long-term employment and lifetime chances. However, the childbearing years coincide with a period in people’s lives in which they are typically seeking to advance in their professional career or are participating in education or vocational training. In Germany, as in most other European countries, the age at first birth has risen to about age 30 for women and to about age 32 for men. Although the scholarly literature often assumes that class positions are rather fixed beyond age 30, upward mobility—and, to a lesser extent, downward mobility—may occur beyond that age. As having a higher-class position is linked to greater economic security, we assume that upward mobility will lead to higher second birth rates (hypothesis 2). Traditional concepts have understood social class as a household concept, where the social class of an individual in a household is defined over the social class of the (male) prime earner (Goldthorpe, 1983). Feminist scholars have challenged that view, calling for a gender and individual perspective on social class (see, for example, Baxter, 1994; Bonney, 2007: p. 146). We define social class as an individual trait defined over one’s own occupation. Still, labour market options are strongly gendered in most societies, also in the case of reunited Germany, which is the focus M.Kreyenfeld et al. 1 3 5 Page 8 of 27 of this investigation. Important family policy reforms were enacted in recent years in Germany, most notably the expansion of childcare in 2005 and the reform of parental leave benefits in 2007. Scholars have argued that these reforms have been consequential, as they represent a sharp departure from Germany’s previously well-estab- lished path of providing policy support for a conservative family model centred on the male breadwinner (Fleckenstein, 2011). While the full-time employment rates of mothers have increased in recent years, employment patterns after the first birth are still strongly gendered, particularly in West Germany. Against this background, we assume that social class is a stronger predictor of men’s than of women’s fertility transitions (hypothesis 3). Finally, people’s class positions reflect their long-term employment chances and their levels of economic security and vulnerability. Among the benefits of the German Socio-Economic Panel (GSOEP) dataset, which we will use in our investigation, is that it includes not only measures of social class, but also items that estimate levels of economic uncertainty and vulnerability, such as the subjective feeling of having financial worries. This information allows us to study whether and, if so, how this measure correlates with the respondents’ social class positions. It also enables us to explore whether the effect of social class is robust to the inclusion of more direct measures of uncertainty. Generally, we expect to find that having financial worries may explain some of the class differences. Thus, we assume that the effect of social class becomes weaker after controlling for other measures of uncertainty (hypothesis 4). Beyond these four guiding research hypotheses, the analyses will take into account the possibility that social class has a distinct influence on the timing and the quantum of second birth fertility. Because they tend to be older when they have their first child, members of the service class are likely to face a “time squeeze” that leads them to progress more rapidly to the second birth than, for example, members of the unskilled and semi-skilled and the routine nonmanual classes, who often have their first child at a younger age. We will use a cure fraction model to check whether a more fine-grained modelling approach that differentiates between timing and quantum effects generates the same results as standard event history models. 3 Data, Variables, andAnalytical Strategy 3.1 Data andAnalytical Sample Data for this investigation come from the German Socio-Economic Panel (GSOEP) release 37 (Socio-Economic Panel, 2022). The GSOEP is a yearly household panel that was launched in 1984. The original sample includes West German respondents and an oversample of migrants from the former labour recruitment countries. Since 1 3 Second Birth Fertility inGermany: Social Class, Gender, and… Page 15 of 27 5 Table 3 Piecewise constant event history model. Relative second birth risks (hazard ratios) Source: SOEP, v37, 1990–2020. Own unweighted estimates Note:Further variables in the model for “other” social mobility and “missing” for financial worries and education. *p < 0.1; **p < 0.05; ***p < 0.01 Men Women M1 M2 W1 W2 Age of first child Age first child 0–1 Ref. Ref. Ref. Ref. Age first child 2–3 1.66*** 1.65*** 1.58*** 1.59*** Age first child 4–5 0.82** 0.81** 0.85 0.86 Age first child 6–11 0.32*** 0.32*** 0.34*** 0.34*** Age at first birth Age 18–23 1.04 1.04 1.13 1.15 Age 24–28 1.15* 1.15* 1.04 1.05 Age 29–32 Ref. Ref. Ref. Ref. Age 33–55 0.71*** 0.71*** 0.48*** 0.48*** Region West Germany Ref. Ref. Ref. Ref. East Germany 0.60*** 0.60*** 0.66*** 0.68*** Migration background Native Ref. Ref. Ref. Ref. Migration background 1.02 1.03 1.09 1.10 Social class at first birth Upper service Ref Ref Ref Ref Lower service 0.79** 0.79*** 0.75*** 0.76*** Skilled 0.78** 0.78*** 0.81* 0.83* Semi-/unskilled 0.58*** 0.58*** 0.62*** 0.64*** Not employed 0.86 0.86 0.64*** 0.64*** Education Low (no degree) Ref. Ref. Ref. Ref. Medium (vocational) 1.09 1.08 1.22** 1.22** High (university) 1.33** 1.34** 1.39*** 1.37*** Social mobility Upward 1.26** 1.27** 1.32* 1.31 Stable Ref. Ref. Ref. Ref. Downward 0.88 0.88 1.00 1.01 Not employed 0.89 0.90 1.17** 1.18** Financial worries Very worried 1.02 0.80*** Somewhat worried 1.15** 0.87** Not worried Ref. Ref. Sample size Person-months 108,241 108,241 132,348 132,348 Events 1161 1161 1371 1371 M.Kreyenfeld et al. 1 3 5 Page 16 of 27 the first childbirth. Furthermore, there is a strong negative correlation between the age at first childbirth and the progression rates to the next childbirth. Moreover, the second birth rates are roughly 40% lower in East than in West Germany. This finding is very much in line with prior research on the East–West differences in higher-order childbearing behaviour (Arránz Becker et al., 2010). We find no relevant differences between native and migrant populations. This may be surprising, as it is often assumed that the migrant population has higher fertility than the native population. It should be noted that this study focuses on second-order births, for which native migrant differences tend to be less pronounced. Furthermore, apart from migrants of Turkish origin, many of the more recent migrants in Germany come from Central and Eastern European countries that are characterised by low second birth rates. The analysis shows that the men’s social class is strongly related to their second birth behaviour (Model M1): i.e. the lower the social class, the lower the second birth rate. The groups that stand out are the semi-skilled and unskilled classes, as their second birth rate is 42% lower than that of the reference group (upper service class positions). The pattern for women is similar, but the differences are attenuated (Model W1). Class mobility also plays out differently for women and men. Among men, upward mobility is associated with an increase of roughly 25% in the second birth rate, while downward mobility and nonemployment are unrelated to the second birth rate. The parameter for upward mobility for women is in the same direction and of similar magnitude as for men, but it is only weakly significantly different from the reference category (stable class position). This weak significance may not come as a surprise, given the small fraction of women who experienced social upward mobility after their first birth (seeTable6 in appendix). Models M2 and W2 display the results from the models that include the additional measures of economic uncertainty (subjective financial worries). While the men’s financial worries do not seem to influence the second birth rates (Model M2), the women’s financial worries are associated with a postponement of second childbearing (Model W2). The second birth rates of women who reported being very worried are 20% lower than those of women who reported being not worried. Women who said they are somewhat worried have a birth rate that is 17% lower than those without worries. The effect size seems strong, and the inclusion of this variable also increased the model fit (log-likelihood ratio test was conducted, p < 0.05). However, it does not greatly affect the class pattern. Thus, among women, there seems to be an independent effect of subjective worries that is not captured by their own class position.7 7 For illustrative purposes, we have also estimated a median duration time to second birth by social class from Model M1 and W1 (Table 2). Such an approach requires assumptions on the covariate constellations. We estimated values for the following constellation: A German citizen in West Germany with medium education who had the first child between ages 24 and 28, and who did not experience upward mobility. For the male model (M1), the estimated median duration to second birth for the upper service class is 3years, while it is roughly 4.5years for the semi-/unskilled class. For the female model (W1), the estimated median duration to second birth for the upper service class is about 3.2years, while it is about 5years for the semi-/unskilled class. 1 3 Second Birth Fertility inGermany: Social Class, Gender, and… Page 17 of 27 5 4.2 Partner’s Social Class andSecond Birth Fertility Figure1 displays the results from the models whichadditionally controls also for the partner’s class position. The figures include the hazard ratios from the model that includes the partner’s class (M3 and W3) as well as results from a model that does not include it. It contains furthermorethe same covariates as in the prior analysis (M2 and W2). Note, however, that this part of the analysis was restricted to respondents with valid information on partner’s class characteristics so that the parameters slightly deviate from the previous investigation. As can be depicted from the figure, patterns for the male sample remain unchanged regardless of whether partner’s social class is controlled or not. However, patterns are attenuated for the female sample, suggesting that men’s social class has a more positive impact on second birth transitions than women’s in the German context. Still, the overall pattern remains unchanged: The higher the social class of both women and men, the higher is the second birth rate. 4.3 Timing andQuantum Effects Table4 reports the results from the cure fraction models. The model results for the male sample show that the previously reported “class effects” are mainly quantum effects. Thus, we can ascertain that there is a positive class and fertility nexus. The members of the upper service class are the most likely to progress to the second birth, and the semi/unskilled workers and lower-grade routine nonmanual employees are the least likely to have a second child. We also find that the age at first fatherhood has a distinct influence on the timing and the quantum of male second birth fertility. Panel 1: Male sample Panel 2: Female sample Fig. 1 Piecewise constant event history model. Relative second birth risks (hazard ratios). Note: The analysis was conducted on the sample with respondents with valid information on partner’s class position (n = 81,669 person-months for male sample; n = 83,654 person-months for female sample). Further variables in the model are age of first child, age at first birth, education, region, migration status, own social class, social mobility, and financial worries. Hazard ratio for “not employed” is not displayed in the figures due to the small sample size in the male sample. *p < 0.1; **p < 0.05; ***p < 0.01. (Source: SOEP, v37, 1990–2020. Own unweighted estimates) M.Kreyenfeld et al. 1 3 5 Page 18 of 27 While a late age at first fatherhood leads to the first and second child being more closely spaced, it also lowers the quantum of fertility. We find that a migration background increases quantum, but the parameter is onlysignificant in the male sample. Further, the reduced hazard rate that we found for East Germany in the previous investigation seems to be related to both timing andquantum effects. Further, men’s higher levels of education seem to affect second birth quantum, but not timing. In many respects, the results for the female sample concur with the results for the male sample. Most of the class differences can be attributed to quantum effects. A pronounced pattern is found for women who were not employed in the year of the first childbirth: i.e. they are rather unlikely to have a second child, but if they have a second child, they often have it at short durations after first birth. The age at first childbearing has the same effect in the female sample as in the male sample. Table 4 Cure fraction model. Relative second birth risks (hazard ratios). (Source: SOEP, v37, 1990– 2020. Own unweighted estimates) Note:*p < 0.1; **p < 0.05; ***p < 0.01. Person-months and events are slightly different from Table2 as the analysis was not censored after 12years Men Women Quantum Timing Quantum Timing Age at first birth Age 18–23 1.16 0.77 1.49*** 0.60*** Age 24–28 1.24*** 0.84* 1.19** 0.74*** Age 29–32 Ref. Ref. Ref. Ref. Age 33–55 0.61*** 1.45*** 0.44*** 1.45*** Region West Germany Ref. Ref. Ref. Ref. East Germany 0.62*** 0.85 0.73*** 0.77*** Migration background Native Ref. Ref. Ref. Ref. Migration background 1.13* 0.82** 1.08 1.02 Education Low Ref. Ref. Ref. Ref. Medium 1.10 1.18* 1.28*** 0.98 High 1.38** 1.10 1.39*** 1.06 Social class at first birth Upper service Ref. Ref. Ref. Ref. Lower service 0.85* 0.86 0.72*** 1.13 Skilled 0.90 0.78** 0.77** 1.27** Semi-/unskilled 0.64*** 0.90 0.61*** 1.16 Not employed 0.78 1.12 0.61*** 1.42** Null model (no covariates) − 6268 − 7446 Final model − 6190 − 7345 Person-months 127,701 158,161 Events 1171 1381 1 3 Second Birth Fertility inGermany: Social Class, Gender, and… Page 19 of 27 5 An early age at childbearing increases the quantum, but it also increases the birth interval. Late childbearing has the opposite effect, as it lowers the quantum, but it shortens the birth interval. 5 Conclusion While classical demography had a strong interest in the relationship between social class and fertility, contemporary fertility research rarely uses the class concept to investigate birth behaviour. Instead, scholars mostly focus on income, education, and employment when examining how labour market conditions are related to fertility behaviour. However, the global financial crisis, the COVID-19 pandemic, and, more recently, the recession that is expected to follow the Russian war of aggression in Ukraine have led to increasing scholarly interest in the uncertainty and fertility nexus. Nonetheless, there is still considerable ambivalence about how to properly operationalise economic uncertainty and long-term employment chances. In this context, it is conspicuous that most demographers have failed to take into consideration the large body of sociological work on the relationship between social class, economic vulnerability, and life chances. We argued in this paper that social class is a well-theorised concept with firmly validated categories that has been effectively employed in sociological labour market research and that can also prove useful in demographic investigations. The empirical part of this investigation focused on second birth fertility in postreunification Germany (1990–2020). We chose to look at second childbearing in order to explore how class mobility after the first childbirth affected birth behaviour. The results of the descriptive investigation indicated that women were less likely than men to experience upward mobility. Furthermore, while we found that moving up the social ladder increased men’s second birth risks significantly, we only observed a statistically weak association between women’s mobility and their second birth fertility. We also found that the association between social class and second birth fertility was stronger in the male than in the female sample. Nevertheless, the overall pattern was similar for both genders, with members of the upper service classes having the highest birth rates and members of the unskilled manual/ lower routine nonmanual classes having the lowest birth rates. We also examined the question of whether subjective feelings of uncertainty explained the differences by class. Our findings indicated that while having financial worries was associated with lower second birth rates, particularly among the female sample, the inclusion of this variable did not change the class patterns. An important methodological question we considered was whether the model results would be robust if timing and quantum effects were differentiated. To this end, we employed cure fraction models. The cure fraction model showed that the age at first childbearing had a very different impact on the timing and the quantum of fertility: i.e. a later age at childbirth reduced the quantum, but it led to a closer spacing of the first and the second child. The model also showed that the class differences were mostly quantum effects. While our investigation generated novel results on the class–fertility nexus, there are important limitations to this investigation that should be mentioned. First, we M.Kreyenfeld et al. 1 3 5 Page 20 of 27 focused on second births. As the transition to the first birth usually coincides with the phase of life when people are getting established in the labour market, first birth analyses would have required additional considerations. Moreover, as higher-order births are rare in Germany, we would not have sufficient case numbers to study third- or higher-order births. Thus, while our focus on second births may be justified, the analysis of a single transition may still be characterised as a “piecemeal approach” (Heckman & Walker, 1990, p.1416). We cannot rule out the possibility that the patterns for other birth parties are different from the patterns we found for second births. Furthermore, there may be selection into the study population based on social class characteristics. Earlier studies have revealed that highly educated women in German are more likely to remain childless than less educated. As social class and education are correlated, one may conclude that women who belong to the upper service class and are at risk of second birth are a selective population. It may be that it is their particular characteristics that have selected them into the pool of mothers also drive their higher progression to the next child (see, for example, Bartus etal., 2013; Kreyenfeld, 2002). Second, we assumed that social class is a solid and firmly validated indicator of economic uncertainty, economic vulnerability, and long-term life chances. The GSOEP offers various additional variables that indicate different facets of economic uncertainty and economic standing (e.g. labour market earnings, term-limited working contracts, worries about global economic development). Among the many variables that this dataset offers, we picked having financial worries to illustrate how social class correlates with other measures of economic insecurity. We included this variable in our model, but it did not ultimately explain much of the class differences. The “stepwise procedure” we used may be criticised for failing to sufficiently account for other measures of uncertainty that may affect the relationship between social class and fertility behaviour. Possibly, more elaborated mediation analysis that account for the complex interplay of social class and various dimensions of uncertainty may be a way forward here (Kuha etal., 2021). Appendix See Figs.2 and 3 . See Tables 5, 6, 7, 8. 1 3 Second Birth Fertility inGermany: Social Class, Gender, and… Page 21 of 27 5 Fig. 2 Kaplan–Meier survival functions to the second birth by social class at the first birth and gender. Note: It should be noted that the survivals are not weighted. As the GSOEP oversamples certain groups, such as migrant populations and East Germans, caution is advised when considering the descriptive results, as they do not control for migration status and region (as is done in the multiple regression). Individuals who were unemployed when they had their first child are not included, as they represent an only small fraction of the men, and including them would have resulted in unstable estimates of the survival curves. (Source: SOEP, v37, 1990–2020. Own unweighted estimates) Panel 1: Male sample Panel 2: Female sample Fig. 3 Robustness Checks: Piecewise constant event history model. Relative second birth risks (hazard ratios). Note: (n = 108,241person-months for male sample; n = 132,348 person-months for female sample). Hazard ratio for “not employed” is not displayed in the figures due to the small sample size in the male sample. M0: Further variables in the model are age of first child, region, migration status, social mobility. M0 + AGEKID1: M0 + age at first birth. M0 + AGEKID1 + EDU: M0 + age at first birth + education. * p < 0.1; ** p < 0.05; *** p < 0.01. (Source: SOEP, v37, 1990–2020. Own unweighted estimates) M.Kreyenfeld et al. 1 3 5 Page 22 of 27 Table 5 Sample statistics, timeconstant covariates, column %. (Source: SOEP, v37, 1990– 2020, unweighted estimates) Men Women Social class in the year of the first birth Upper service 19 10 Lower service 19 26 Skilled 36 24 Semi-/unskilled 19 23 Not employed 7 18 Partner’s social class at first birth Upper service 8 13 Lower service 20 12 Skilled 19 22 Semi-/unskilled 16 11 Not employed 13 4 No partner/missing 25 38 Migration background Native 70 71 Migration background 30 29 Age at first birth (mean) 30.8 28.1 Sample size Persons 2282 2819 Second births 1161 1371 Table 6 Sample statistics, timevarying covariates by personmonths, column %. (Source: SOEP, v37, 1990–2020, unweighted estimates) There are some few (< 1%) missings for financial worries Men Women Mobility Stable 67 38 Upward 9 5 Downward 7 5 Not employed 14 52 Other 2 1 Education Low 11 12 Medium 63 62 High 24 23 Missing 2 3 Financial worries No worries 20 22 Stable 53 56 Great worries 27 21 Region West Germany 78 77 East Germany 22 23 Sample size Person-months 108,241 132,384 Second births 1161 1371 1 3 Second Birth Fertility inGermany: Social Class, Gender, and… Page 23 of 27 5 Funding Open Access funding enabled and organized by Projekt DEAL. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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