Educational Assortative Mating and Couples F ertility Working Paper - PDF document

Educational Assortative Mating and Couples’ F ertility Working Paper to be presented at the 2017 IUSSP conference Alessandra Trimarchi 1 Jan Van Bavel 2 Abstract Scholars usually approach fertility from women’s perspectives. However, omitting partner characteristics may bias the results. We extend previous literature about the effect of partners’ educational characteristics on fertility, considering the level of education and the field of study. First, we estimate the earning potential by educational degree, country, and sex using European Labor Force Surveys. Second, we link the results of these estimations with the Generation and Gender Surveys of eight countries, and we model couples’ transition to first and higher order parities jointly. We find that higher earning potential and lower unemployment risks of both partners delay first births. Next, couples where the man is more educated than the woman have higher second and third birth rates compared to pairings where the woman is more educated than the man. Yet, the former do not statistically differ in their second birth rates from couples where both partners are highly educated. Keywords: assortative mating, education, fertility, joint modelling Acknowledgement The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 312290 for the GENDERBALL project. 1 Alessandra Trimarchi, Centre for Sociological Research/Family and Population Studies, Faculty of Social Sciences, University of Leuven. Email: Alessandra.Trimarchi@kuleuven.be 2 Jan Van Bavel, Centre for Sociological Research/Family and Population Studies, Faculty of Social Sciences, University of Leuven. Email: Jan.VanBavel@kuleuven.be 1

1. Introduction Fertility studies have typically investigated the role of mothers’ characteristics on the transition to first and higher order births. To justify this approach, scholars have pointed to the fact that people tend to mate assortatively, i.e., partners share similar characteristics, values, and lifestyles (Corijn et al. 1996). Since the majority of births occur within unions, failing to control for the partner’s characteristics leads to an omitted variable bias: the results based on the individual may reflect the effect of the partner (Gustafsson and Worku 2006). The omitted variable bias is bigger insofar as the role of partners’ characteristics in fertility differs. Paradoxically, assortative mating is both a justification and a criticism to focus on only one partner when studying fertility. In particular, educational assortative mating has been widely documented (Blossfeld and Timm 2003), and omitting the partner has important consequences when studying the relationship between education and fertility. Kreyenfeld (2002) suggested that a positive association between education and fertility for women could reflect the fact that highly educated women mostly mate with highly educated men. In fact, micro-economic theories of the family predict a positive association between education and fertility for men due to income effects, whereas they predict a negative association for women due to opportunity costs (Becker 1991). Because of these gender differences in the effect of education on fertility, the focus on only one partner muddles the interpretation of results: it becomes unclear whether his or her education matters (Trimarchi and Van Bavel 2017). According to the context, gender differences in work and family involvement tend to have different associations with the educational level and this increases the demand for a couple – level kind of approach to fertility studies (Singles and Hynes 2005). Moreover, patterns of educational assortative mating are changing, and it is interesting to look at couples’ behaviours instead of individual behaviour. Even if educational homogamy remains 2

strong, traditionally, hypergamy was prevailing: if there was a difference in educational attainment, the husband tended to have more education than his wife. However, in more recent cohorts, hypogamy has become more common than hypergamy: more often the woman has more education than the man (Esteve et al. 2012; Grow and Van Bavel 2015). The changes in patterns of educational assortative mating are linked to increasing female participation in higher education. Since the 1990s, the number of highly educated women reaching reproductive ages exceeds the number of highly educated men (DiPrete and Buchmann 2006). Still, while gender inequalities in higher education are disappearing, the gender segregation with regard to the field of study has remained stable over time (Charles and Bradley 2009). The gender segregation of fields of study reflects inequalities in the labour market, ensuing differences concerning the earning potential of men and women given the same level of education (Blau and Khan 2016). Since educational expansion, medium and highly educated people are more heterogeneous groups, and the field of study has been considered a good distinctive trait for their labour market outcomes and cultural resources (Van de Werfhorst 2001; Reimer, Noelke and Kucel 2008). As a result, a growing strand of research considers the field of study a relevant determinant of fertility timing and quantum: it helps in differentiating fertility behaviour for those with an education higher than the upper-secondary level (Hoem et al. 2006a; Hoem et al. 2006b; Martín-García 2009; Bagavos 2010; Van Bavel 2010; Tesching 2012; Begall and Mills 2013). Still, the field of study has not been yet considered for fertility studies on a couple-level. The strand of research that focuses on the role of partners’ relative socioeconomic resources for fertility mainly paid attention to the level of education, employment, and income of partners (Corijn et al. 1996; Kreyenfeld 2002; Gustafsson and Worku 2006; Dribe and Stanfors 2010; Begall 2013; Jalovaara and Miettinen 2013; Vignoli et al. 2012; Nitsche 3

et al. 2015). The use of employment, occupation, and income as independent variables is especially problematic when studying fertility: p artners’ employment , occupation and income are affected by childbearing decisions. In contrast, the decision about the main field of study, which characterizes the highest level of education attained, is taken relatively early in the life course and it tends to be fixed over time. We contribute to the couple-level literature in fertility by proposing a way to limit endogeneity issues due to the lack of time varying information on earnings, employment status and occupation. We estimate the earning potential and unemployment risks for each partner, which are embodied in the educational degree obtained at the time of interview, by using the European Labour Force Surveys (EU-LFS). Next, we linked the results of these estimations with the Generations and Gender Surveys (GGS) of eight European countries given the information on the level of education, field of study, sex and country of residence. By means of a simultaneous equations approach, we estimated the effect of pairing by educational level, earning potential, and unemployment risks on first, second, and third birth rates. The joint model for all birth parities allows us to account for the selection into parenthood, i.e., we account for those un observed characteristics of partners’ that affect their fertility, such as fecundity and personality traits. In the following section we highlight theoretical mechanisms that link partners’ socio -economic resources to fertility and we formulate the hypotheses to be tested. Section 3 focuses on the data and methods used, and it is followed by results and discussion sections. 2. Fertility from a couple’s perspective: the role of education An influential strand of research that focuses on the couple-level looks at the interaction between partners’ desires, intent ions, and preferences to determine who dominates in fertility decision-making. These studies aim to generate a framework of decision-making rules for fertility outcomes (Thomson, McDonald and Bumpass 1990; Thomson 1997; Bauer and 4