Abstract
Many authors argue that levels of childlessness and fertility are a function of changing gender relations, but the mechanisms behind this association remain unclear and mainly untested. This study argues that the societal variation in gender role attitudes explains the link: a great variation in attitudes among potential partners leads to uncertainty and conflicts, which depresses people’s propensity for parenthood. This idea is tested with multilevel logistic regression models for 6305 individuals in 38 countries on all continents, using ISSP 2012 data. Measures for the average gender role attitude in the society as well as the dispersion in attitudes are regressed on whether individuals have at least one child or are childless. Attitudes are captured using factor analysis and are opinions towards the gendered division of given tasks and privileges, such as childrearing or the uptake of parental leave. The dispersion in attitudes is the standard deviation of the factor variable in the given country. The analysis gives support to the hypothesis: the greater the variation in gender role attitudes, the higher the chance for individuals to remain childless. The association is significant and holds against various robustness checks.
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To describe different forms of gender relations, mainly the contrast between the male breadwinner and the dual earner gender roles, various terms are used: gender-asymmetric, traditional, old or unequal versus gender-symmetric, new, modern, gender-equal or gender-equitable. Particularly, the term ‘gender-equitable’ could be misleading though as different societies and societies at different times might regard different gender roles as equitable (cf. McDonald 2013).
In an endnote next to a graph on the ‘Relationship between gender egalitarianism and partnership stability, late 1980s’ Esping-Andersen and Billari (2015, p. 22) discuss the comparison of two measures for ‘the hegemony of gender norms: either a simple headcount (share of egalitarians in the population) or the coefficient of variation (to capture the degree of value uniformity in the population). Our estimations produce essentially the same result’ (Esping-Andersen and Billari 2015, p. 26). For binary variables, coefficient of variation is no suitable indicator for the degree of uniformity or variation (Vogt and Johnson 2011, p. 59). Standard deviation and variance are measures for the degree of variation in a dummy variable, but a distinct interpretation of variation and mean value provides little insight: variation and mean value determine each other mathematically. For each mean value, there is only one mathematically possible value for variance of standard deviation. For each value of standard deviation, there are two possible corresponding mean values, one being \(.5+x\), the other \(.5-x\). An example: if the mean value of a binary variable is .75, the standard deviation is forced to be .44. A population with a standard deviation of .44 could have one of the two mean values \(.5+.25=.75\) or \(.5-.25=.25\). In the case of Esping-Andersen and Billari (2015), all mean values are greater than .5. Thus, within their range of data, mean values perfectly predict levels of variation and vice versa. Using the coefficient of variation, the standard deviation divided by the mean value, is not a suitable measure for the degree of variation of a dummy variable. To give an example, let us compare two populations of each 100 individuals. Population A is egalitarian: 90 individuals hold egalitarian views, 10 non-egalitarian ones. Population B is the opposite case: 10 individuals hold egalitarian views, 90 non-egalitarian ones. Intuition and standard deviation (or variance) would suggest that both populations have the same degree of variation or hegemony in attitudes (standard deviation = .30, variance = .09). The coefficient of variation would show a very different picture: it is 3.02 for population A and .36 for population B (consider also that on binary outcomes the assignment of ones and zeros is arbitrary: there is no compelling reason why egalitarians should be coded one and non-egalitarians zero, rather than the other way around). In fact by using the coefficient of variation Esping-Andersen and Billari (2015) measure practically nothing else than the mean value: in the range of their mean values, going from around .5 to close to 1, the correlation between mean value and coefficient of variation is − .99 (tested on a dummy dataset).
Research shows that societal attitudes/public opinion (among numerous other factors) influence policy in democratic systems; how big this influence is, and how much it relies on salience of a specific policy/a policy field, is largely contested though (Burstein 2003). Most, but not all, countries in the sample are democratic. Research on public opinion and policy in non-democratic settings is very limited, but also suggests potential influences (Horne 2010).
For some countries, ISSP 2012 was part of a larger national survey, e.g. in the USA, ISSP 2012 was part of the General Social Survey 2012, and in Germany, it was part of the German General Social Survey (ALLBUS) 2012.
Country-level shares of parenthood in the ISSP sample are largely consistent with other sources (see online appendix for details).
The goal is to find a convincing variable that captures gender role attitudes—and it is no problem if that variable is correlated with other measures and attitudes—so promax, which does not force the different factors to be uncorrelated, is chosen here.
These countries are: Argentina, Canada, Finland, Germany, Great Britain, Hungary, Ireland, India, Japan, Lithuania, Mexico, Poland, Sweden, Slovenia and USA
This seems to be especially valid for some European countries: in Switzerland, France or Germany more than one in four agrees to the statement that ‘All in all, family life suffers when the woman has a full-time job’. Among those who agree with this statement, the majority rejects traditional gender-separated spheres (‘A man’s job is to earn money; a woman’s job is to look after the home and family’) and a third or more expresses gender-egalitarian childrearing ideals (stated view that parental leave should be equally distributed between the mother and the father).
This seems to be especially valid for some countries in Eastern Europe and outside of Europe. In Russia, China or Mexico, the majority believes that mothers of young children should work at least part-time. (‘Do you think that women should work outside the home full-time, part-time or not at all under the following circumstances? When there is a child under school age’.) Nevertheless, the majority of this group believe that this will actually have negative consequences for the child (agreement to: ‘A pre-school child is likely to suffer if his or her mother works’.) Also, more than a third of those who favour maternal employment actually support gender-separate spheres (agreement to: ‘A man’s job is to earn money; a woman’s job is to look after the home and family’).
Predicted value for parenthood and childlessness Germany: 87.9 and 12.1%, for United Kingdom: 92.5 and 7.5%. This equals a difference of 4.6% points and a difference of 5.2% in parenthood or 38.0% in childlessness.
Running the base model with the restricted sample of model 5 brings coherent results which suggests that the sample-restriction does not confound the picture.
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Acknowledgements
I thank Henriette Engelhardt-Wölfler, Gøsta Esping-Andersen, and Francesco Billari for their advice and support. The work has also benefited from very helpful comments from Léa Pessin and Michael Gebel. Further thanks go to the participants of the EDUREP conference in Vienna 2015, the Internal BAGSS Conference 2016 in Bamberg, the Annual Meeting of the German Demographic Association 2016 in Leipzig and the 2nd Human Fertility Database Symposium in Berlin 2016.
Funding
This work was supported by the Bamberg Graduate School of Social Sciences which is funded by the German Research Foundation (DFG) under the German Excellence Initiative (GSC1024).
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Hudde, A. Societal Agreement on Gender Role Attitudes and Childlessness in 38 Countries. Eur J Population 34, 745–767 (2018). https://doi.org/10.1007/s10680-017-9459-8
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DOI: https://doi.org/10.1007/s10680-017-9459-8