Reversal of Fertility Decline

In a terrific paper in the latest issue of Nature, Myrskylä and colleagues (including my sometime collaborator Hans-Peter Kohler) demonstrate that total fertility rate (TFR) — which we typically think of as declining with economic development — actually increases at very high levels of development.  One of the fundamental challenges of social science remains explaining the unprecedented decline in fertility witnessed in the twentieth century.  This fertility decline has gone hand-in-hand with economic development.  As Myrskylä et al. write, “The negative association of fertility with economic and social development has therefore become one of the most solidly established and generally accepted empirical regularities in the social sciences.”

For those social scientists with an evolutionary bent, this observation has been particularly vexing since it appears to violate our expectations regarding resource-holding and reproductive success.  In a great many traditional societies, researchers have documented a positive relationship between wealth and reproductive success.  However, as soon as people are embedded within (and actually integrated with) the structures of a state-level society, this relationship apparently changes: rich people in states appear to have fewer children than poor people.  And as the overall level of wealth of a state increases, the aggregate pattern of fertility also decreases.  Now there are plenty of caveats here.  Many scholars have committed the ecological fallacy in attributing causal explanations at the individual level based on aggregate (“ecological”) data. There is some evidence that the wealthy and well educated actually have marginally higher fertility in certain contexts, but the overwhelming weight of evidence shows that — at least at the aggregate level — increased wealth leads to decreased fertility. Until now.

The authors use the Human Development Index (HDI), a widely used measure of progress in human development.  The HDI combines three dimensions: (1) health, as measured by life expectancy at birth, (2) standard of living, as measured by the logarithm of per capita gross domestic product at purchasing power parity in US dollars, and (3) human capital as measured by adult literacy and the enrollment fraction in primary, secondary, and tertiary school.  HDI is now standardized so that it varies between zero and one.  This makes it easy to compare HDI across countries and through time.  The measure of fertility that Myrskylä and colleagues use is total fertility rate.  This is also probably the most commonly used measure of fertility.  It is the sum of a population’s age-specific fertility rates across a woman’s reproductive years, assuming that the woman survives this span.  It is a demographic fiction, but it is a useful fiction.

What Myrskylä et al. (2009) show (in their figure 1) is that TFR largely declines with HDI in 1975, as expected. The cool, unexpected finding that their paper reports is that in 2005, TFR declines with HDI to a point. When the HDI exceeds 0.9 though, fertility again increases. This plot is cross-sectional: it is a scatter plot of all countries’ HDI-TFR pairs for a particular time period. One reason why we don’t see this upward turn at the highest levels of human development in 1975 is that no countries had achieved this apparent threshold of HDI=0.9. Of course, from this plot we can’t rule out the existence of some “period effect.” That is, maybe there was just something different in society or the economy in 2005 compared to 1975.

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Myrskylä et al. (2009) figure 1 (used with permission of the authors).

In figure 2, the authors plot longitudinal data for individual countries. They show that once HDI enters a window between 0.86-0.9 and TFR bottoms out, further increases in HDI lead to increases in TFR.

Myrskylä et al. (2009) figure 2 (used with permission of the authors)
Myrskylä et al. (2009) figure 2 (used with permission of the authors)

This greatly increases our confidence that there is, in fact, a causal relationship between increased human development and fertility.  The really cool thing about this plot, however, is the exceptions to the general trend that it shows. In particular, Japan, South Korea, and Canada (and to a lesser extent Austria, Australia, and Switzerland) do not show this pattern.  For these countries, further increases in HDI are associated with further declines in TFR. A distinct possibility is that for some countries, increasing human welfare also leads to institutions that permit people (particularly women) to have children and be educationally and economically successful at the same time — that is, not just people who were lucky enough to be born rich.  It’s a shocking idea. The authors write:

[A]n improved understanding of how improved labour-market flexibility, social security and individual welfare, gender and economic equality, human capital and social/family policies can facilitate relatively high levels of fertility in advanced societies is needed. For instance, analyses on Europe show that nowadays a positive relationship is observed between fertility and indicators of innovation in family behaviour or female labour-force participation. Also, at advanced levels of development, governments might explicitly address fertility decline by implementing policies that improve gender equality or the compatibility between economic success, including labour force participation, and family life. Failure to answer to the challenges of development with institutions that facilitate work–family balance and gender equality might explain the exceptional pattern for rich eastern Asian countries that continue to be characterized by a negative HDI–fertility relationship.

These are important problems and this is a fundamental contribution to our understanding of the relationships between economic development, human welfare, and reproductive behavior.

5 thoughts on “Reversal of Fertility Decline”

  1. "This [TFR] is also probably the most commonly used measure of fertility. "

    I agree this is a neat paper. I worry a bit about tempo effects and the use of TFR (i.e, Bongaarts and Feeney). Does the use of TFR trouble you?

  2. When looking at behavioral change, yes, I think it's very important to think about tempo-adjustment. If you look at their figure S.2 in the Supplementary material, they do, in fact, use tempo-adjusted TFR. The data necessary for adjustment are not available for the full range of the study or for all countries. They were able to adjust for 41 countries in 2005 and these are superimposed on figure 1 in figure S.2. As one might imagine, the lowest fertility is higher for the tempo-adjusted calculations but, for the most part, the qualitative features of figure 1 remain intact. Similarly, they are able to estimate their differences-in-differences model with fixed effects for period using adjusted TFR. The results remain: before the coincident bottoming out of TFR and achievement of the 0.86-0.9 HDI window, TFR has a negative slope (albeit not significant at the p<0.05 level); after this point, there is a significant positive slope. The lack of a significant negative slope before the inflection is not surprising, given the fact that TFR adjustment is only possible in the later period and for a small number of countries that mostly have high values of HDI.

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