Abstract
Fertility rates have long been falling in many developed countries, while educational attainment in those countries has risen. We attempt to reconcile these two trends with a novel application of two recent models to generate plausibly causal effects of education that can explain these decreases in fertility. Using Canadian data, we exploit changes in compulsory schooling laws to find that education “compresses” the fertility distribution—women are more likely to have at least one child but less likely to have multiple children. We demonstrate that the mechanism for this effect is the positive impact of education on earnings and marriage.
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Notes
In the USA, total fertility decreased from about 3.5 children per woman in 1960 to roughly 2.0 children in 2010, while Canada saw a decline in total fertility from 3.9 children in 1960 to 1.6 in 2010. In England and Wales, the comparable rates are 2.7 in 1960 and 1.9 in 2010; in Ireland, 3.8 in 1960 and 2.1 in 2010; in Finland, 2.7 in 1960 and 1.9 in 2010; in the Netherlands, 3.1 in 1960 and 1.8 in 2010; in Italy, 2.4 in 1960 and 1.5 in 2010; in France, 2.9 in 1960 and 2.0 in 2010; in Germany, 2.4 in 1960 and 1.4 in 2010.
For example, fertility among American women aged 40 to 50 years old in 2012 varied substantially by educational attainment—from about 2.6 for those with less than a HS degree to about 1.8 for women with a bachelor’s degree and 1.7 for those with a graduate or professional degree. Moreover, while just less than 12% of those with less than a high school degree were childless, nearly one-quarter of women with a graduate or professional degree had no children when surveyed.
Despite the high degree of within-country similarities when it comes to education, Canada is a linguistically diverse country with a large number of Francophone citizens in addition to the larger English-speaking group. Such differences suggest potential heterogeneous impacts of education on fertility, but since most Francophones reside in one province (Quebec) and since the variation in compulsory schooling we exploit is at the provincial level, we can not validly assess such differences.
CSLs appeared in British Columbia shortly afterward, in 1873, with most Canadian provinces enacting them by the end of the first decade of the twentieth century.
The deference shown to rural areas, mostly based on their agrarian nature and extensive use of child labor, is also apparent in the Adolescent School Attendance Act of 1921, whereby Ontario increased the compulsory age of attendance from 14 to 16 years old, but only for young adults living in urban areas. Perhaps not surprisingly, newly required 14 and 15 year olds were exempted from the law if they were employed at home or for wages, and if they possessed a parent-endorsed “certificate of employment,” which exempted youth from minimum school leaving laws, were often obtained by passing equivalency tests, typically at the level of grade 7 or 8, but sometimes merely tested basic skills like reading or writing. These young adults were still required to attend part-time instruction in the evenings, where such classes existed.
It should be noted that more recent models such as Galor (2012) have identified some shortcomings within these models, but the discussion of this work provides context for more recent papers within this review.
Becker et al. (1990) develop a theoretical model to demonstrate that, in the context of economic growth and development, increased investment in educational attainment may lead to equilibrium with smaller families—directly in accordance with the quantity-quality model.
It should be noted that Galor (2012) has argued that the tests of the quantity-quality trade-off within the Beckerian model can be questioned because of flawed assumptions within the theoretical model. We discuss these results for context.
McCrary and Royer (2011) also find no relationship between such education and child health, which again is the focus of their study.
Unlike ALM, we do not examine the fertility of a cohort of parents.
While we acknowledge that CSL-induced education may impact the desired fertility of males in ways that may, in turn, impact the effect of such increases in education on women’s actual fertility, which is our ultimate question of interest, we follow Aaronson et al. (2014) and focus only on women’s behavior in our model and in our ultimate empirical analysis.
The confidential data sets were only accessible through secure sites and contained information not collected for the publicly-available extracts of the decennial censuses. In particular, the confidential files contain specific information about earnings in the prior year, as well as specific amounts of education obtained by the household member and an individual’s exact date of birth.
A Canadian “province” is analogous to an American state. There are ten provinces in Canada and three territories; the sample analyzed within this study will include only data drawn from individuals born in one of the ten provinces.
In particular, the analysis was replicated with a cut-off age of 42 and 44, and the results are essentially the same as will be reported.
Information on the specific timing for changes in these laws is presented in Appendix Table 6. Note that we assign all CSL measures so that they correspond to when a woman is of usual school age.
For more detail, see Angrist et al. (1996).
More accurately, since we use longitudinal data, the concern is whether changes in the instrument are uncorrelated with changes in factors in the error term that might independently affect fertility-related outcomes.
A more formal analysis of the trends reveals that: there is a statistically significant shift in the trend line in Fig. 1 after the law change; the slope trend line is statistically significant prior to the law change, but not statistically significant after the law change, and; the slope of the trend line is not statistically significant before the law change, but is statistically significant after the law change. The regressions that underlie these results are available upon request.
The fact that we are estimating local average treatment effects which estimate the impact of additional education on those induced to comply with compulsory schooling laws may also drive these seemingly large results. Indeed, to extrapolate to the entire population would involve multiplying the coefficients in question by the fraction of the population impacted by compulsory schooling laws (roughly 20% of our sample) as well as their average effect on educational attainment (between roughly 0.5 and 0.9 years).
We test the ZIP specification against a standard count-data model with a Vuong test, and the results reject the standard Poisson model in favor of the ZIP model.
We thank an anonymous referee for raising this possibility.
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Acknowledgements
We thank editor Oded Galor and three anonymous referees, as well as David Blau, Isaac Ehrlich, Daeho Kim, Randy Olson, Mel Stephens, Arthur Sweetman, Casey Warman, and seminar participants at McMaster University, SUNY-Buffalo, The Ohio State University, Dalhousie University, Waterloo University, and the NBER. We are especially indebted to Phil Oreopoulos for his helpful comments and for sharing useful data with us. Both authors recognize funding from SSHRC while this paper was being completed.
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DeCicca, P., Krashinsky, H. The effect of education on overall fertility. J Popul Econ 36, 471–503 (2023). https://doi.org/10.1007/s00148-022-00897-y
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DOI: https://doi.org/10.1007/s00148-022-00897-y