After reviewing a paper for JAMA Network Open I was invited to write a comment about it. The paper is here, reporting a large drop in the percentage of mothers who are planning or thinking about having another child in a sample from New York City in mid-2020. After summarizing the results, I wrote this:
Before the COVID-19 pandemic, the US was in a period of declining fertility following the 2008 financial crisis and subsequent recession—a decline that was linked to economic precarity and hardship [2]. Then, in 2020, the total number of US births decreased 3.8%, which was the largest annual decline on a percentage basis since the early 1970s. The decreases were steeper at the end of the year, −6% in November and −8% in December, compared with 2019 [3]. In some large states with public monthly reports (California, Florida, and Ohio), it appears that January and February 2021 had fewer births still, with some recovery in the months that followed [4]. This timing suggests a direct association with the onset of the pandemic and closures that began in the spring of 2020. The evidence presented by Kahn and colleagues [1] supports this interpretation and suggests that when people faced the uncertainty and hardships associated with the pandemic, one common response was to pull back from plans to add children to their families. Future research will examine whether family decision-making in more advantaged families was similarly affected.
The current evidence concerns shifts in pregnancy planning. However, in the US, a substantial portion of births results from unintended or mistimed pregnancies, and these are concentrated among disadvantaged women [5]. The inability to predict, much less control, the trajectory of their lives leads many women to postpone the lifelong commitments implied by intentional births, but also makes unintentional pregnancy more likely. How the pandemic may have affected such births is not yet known. If mobility restrictions, unemployment, illness, care work burdens, and social distancing all reduced social interaction, coupled with increased motivation to prevent pregnancy, we may suspect unintended births will have declined as well.
The impacts of the pandemic within and between families points to the complex interrelationships among family structure, health disparities, and social inequality in the US [6]. The COVID-19 pandemic has been an inequality-exacerbating event on a large scale, widening existing health disparities, especially along the lines of socioeconomic status, race, and ethnicity. Excess mortality among Black and Hispanic populations in 2020, directly and indirectly related to the pandemic, far outstripped that seen among non-Hispanic White populations and contributed to the decrease in overall US life expectancy that exceeded that seen in peer countries [7]. In light of disparate impacts of COVID-19 itself and the social and economic fallout of the pandemic, research should concentrate on widening inequalities in fertility and family well-being, and their relationship to health disparities.
Corresponding Author: Philip N. Cohen, PhD, Maryland Population Research Center, Department of Sociology, University of Maryland, Parren J. Mitchell Art Sociology Building, College Park, MD 20742 (pnc@umd.edu).
Conflict of Interest Disclosures: None reported.
References
Kahn LG, Trasande L, Liu M, Mehta-Lee SS, Brubaker SG, Jacobson MH. Factors associated with changes in pregnancy intention among women who were mothers of young children in New York City following the COVID-19 outbreak. JAMA Netw Open. 2021;4(9):e2124273. doi:10.1001/jamanetworkopen.2021.24273
Seltzer N. Beyond the great recession: labor market polarization and ongoing fertility decline in the United States. Demography. 2019;56(4):1463-1493. doi:10.1007/s13524-019-00790-6
Cohen PN. Baby bust: falling fertility in US counties is associated with COVID-19 prevalence and mobility reductions. SocArXiv, March 17, 2021. doi:10.31235/osf.io/qwxz3
Hartnett CS, Gemmill A. Recent trends in US childbearing intentions. Demography. 2020;57(6):2035-2045. doi:10.1007/s13524-020-00929-w
Thomeer MB, Yahirun J, Colón-López A. How families matter for health inequality during the COVID-19 pandemic. J Fam Theory Rev. 2020;12(4):448-463. doi:10.1111/jftr.12398
Woolf SH, Masters RK, Aron LY. Effect of the covid-19 pandemic in 2020 on life expectancy across populations in the USA and other high income countries: simulations of provisional mortality data. BMJ. 2021;373(n1343):n1343. doi:10.1136/bmj.n1343
CNN’s Dr. Sanjay Gupta has a podcast called Chasing Life about coming out of the pandemic. Associate producer Grace Walker interviewed me for an episode titled, “Let’s Talk About Making Babies (Or Deciding Not To).” In it reporter Chloe Melas starts with the story of a Black couple (two women, one of them trans) seeking to have children. At about minute 21, she turns to the fertility decline in the US. The transcript of that part is below. This episode would be good for teaching.
Chloe Melas: But we can’t forget – not everyone wants to have children. And that’s OK. According to the CDC, the number of births in the United States fell by 4% last year – the largest annual decline since 1973. Given the global pandemic, for demographers like Philip Cohen of the University of Maryland, this isn’t too surprising.
Philip Cohen: What we’ve learned in the last century or so is that when there are crises birth rates go down. It’s partly deliberate, that is, people decide to hold off on having children, or decide against having children, because they’re unsure about the future, they’re unsure they’ll be able to care for them, they think they might lose their job, they think their mother might lose her job – all the things that go into the calculations of when and whether to have children.
CM: 2020 is not an outlier. Cohen says birthrates have been on a downward trend for quite a while.
PNC: We were sort of focusing on issues like work-family balance, childcare, healthcare, housing, the expenses of raising children, and the difficulty of raising children, which had been putting pressure on people to reduce their number of children. That’s the main reason. At the same time, when people have more opportunities to do other things in their lives, they’re also inclined to have fewer children, or delay having children. So especially for women, when opportunities improve, the number of children they have tends to go down, because on average they’re more likely to choose something else.
CM: Hispanic women in particular are seeing some of the largest declines. From 2007 to 2017 birth rates fell by 31%. Experts attribute this drop to more Hispanic women joining the workforce, and waiting longer to start families than previous generations. Overall, the data doesn’t lie. Fewer people are having kids. That could lead to smaller kindergarten classrooms, as well as larger demands on Social Security, given the aging population. But Cohen and others think there could be positives, too. For example, fewer people means less of an environmental impact on the planet. So it’s really a glass half empty, glass half full kind of situation. The point is, I think this pandemic has really made many of us reflect on what we want our future to look like, including our future families. Some have been inspired to freeze their eggs, some to seek out help for infertility, and some have decided against having kids while others have been inspired to do so.
The text and figures of this short paper are below, and it’s also available as a PDF on SocArXiv, in more citable form. The Stata code and other materials are up as well, here. It’s pretty drafty — very happy to hear any feedback.
Preamble: When Sabrina Tavernise, Claire Cain Miller, Quoctrung Bui and Robert Gebeloff wrote their excellent New York Times piece, Why American Women Everywhere Are Delaying Motherhood, they elevated one important aspect of the wider conversation about falling fertility rates — the good news that women with improving economic opportunities often delay or forego having children because that’s what they’d rather do.
But it’s tricky to analyze this. Consider one woman they quote, who said, “I can’t get pregnant, I can’t get pregnant… I have to have a career and a job. If I don’t, it’s like everything my parents did goes in vain.” Or another, who is waiting to have children till she finishes a dental hygienist degree, who said, “I’m trying to go higher. I grew up around dysfunctional things. I feel like if I succeed, my children won’t have to.” If people can’t afford decent childcare (yet), or won’t have a job that pays enough to afford the parenting they want to provide until they finish a degree — so they delay parenthood while investing in their careers — are they not having a baby because there are promising opportunities, or because of economic insecurity? These are edge cases, I guess, but it seems like they extend to a lot of people right now. That’s what motivated me to do this analysis.
Hard times and falling fertility in the United States
by Philip N. Cohen
Abstract
Recent reports have suggested that falling fertility in the US since the 2008 recession is being driven by women with advantaged status in the labor market taking advantage of career opportunities. This paper takes issue with that conclusion. Although high incomes are associated with lower fertility in general, both in the cross section and over time (within and between countries), economic crises also lead to lower fertility. I offer a new descriptive analysis using data from the American Community Survey for 2000-2019. In the U.S. case, the fertility decline was widespread after the 2008 recession, but most concentrated among younger women. Although women with above average education have long had lower birth rates, the analysis shows that birth rates fell most for women in states with higher than average unemployment rates, especially among those with below average education. This is consistent with evidence that birth rates are falling, and births delayed, by economic insecurity and hardship.
Introduction
A New York Times article by Sabrina Tavernise et al. was titled, “Why American Women Everywhere Are Delaying Motherhood” (Tavernise et al. 2021). Although it did not provide a simple answer to the question, it did offer this: “As more women of all social classes have prioritized education and career, delaying childbearing has become a broad pattern among American women almost everywhere.” And it included a figure showing birth rates falling faster in counties with faster job growth. Reading that article, the writer Jill Filipovic concluded, “the women who are driving this downturn [in fertility] are those who have the most advantage and the greatest range of choices, and whose prospects look brightest” (Filipovic 2021). This paper takes issue with that conclusion.
Clearly, one driver of delayed childbearing is the desire to maximize career opportunities, but there is also the weight of uncertainty and insecurity, especially regarding the costs of parenting. Filipovic (2021) also wrote, “Children? In this economy?” These two tendencies appear to generate opposing economic effects: A strong economy gives mothers more rewarding opportunities that childrearing threatens (reducing fertility), while also providing greater economic security to make parenting more affordable and desirable (increasing fertility). These two pathways for economic influence on fertility trends are not easily separable in research – or necessarily exclusive in personal experience. In what follows I will briefly situate falling US fertility in the wider historical and global context, and then offer a descriptive analysis of the US trend in births from 2000 to 2019, focusing on relative education and state unemployment rates.
Review and context
Historically, economic growth and development have been key determinants of fertility decline (Herzer, Strulik, and Vollmer 2012; Myrskylä, Kohler, and Billari 2009), although by no means the only ones, and with coupling that is sometimes loose and variable (Bongaarts 2017). In the broadest terms, both historically and in the present, higher average incomes at the societal level are strongly associated with lower fertility rates; and this relationship recurs within the United States as well, as shown in the cross section in Figure 1.
Figure 1. Total fertility rate by GDP per capita: Countries and U.S. states, 2019. Note: Markers are scaled by population. US states linear fit weighted by population. Source: World Bank, US Census Bureau, National Center for Health Statistics, Bureau of Economic Analysis.
A lower standard of living is associated with higher birth rates. However, economic crises cause declines in fertility (Currie and Schwandt 2014), and this was especially true around the 2008 recession in the U.S. (Comolli 2017; Schneider 2015) and other high-income countries (Gaddy 2021). The crisis interrupted what had been a mild recovery from falling total fertility rates in high-income countries, leading to a decline from 1.74 in 2008 to 1.57 by 2019 (Figure 2).
Figure 2. Total fertility rate in the 10 largest high-income countries: 1990-2019. Note: Countries with at least $30,000 GDP per capita at PPP. Source: World Bank.
Figure 2 shows that the pattern of a peak around 2008 followed by a lasting decline is widespread (with the notable exceptions of Germany and Japan, whose TFRs were already very low), although the post-crisis decline was much steeper in the U.S. than in most other high income countries. Figure 3 puts the post-crisis TFR decline in global context, showing the change in TFR between the highest point in 2007-2009 and the lowest point in 2017-2019 for each country, by GDP per capita. (For example, the U.S. had a TFR peak of 2.12 in 2007, and its lowest point in 2017-2019 was 1.71 in 2019, so its score is -.41.) Fertility decline is positively associated with per capita income, as low-income countries continued the TFR declines they were experiencing before the crisis. However, among the high-income countries the relationship reversed (the inflection point in Panel A is $36,600, not shown). Thus, the sharp drop in fertility in the U.S. after the 2008 economic crisis is indicative of a larger pattern of post-crisis fertility trends. Globally, fertility is higher but falling in lower-income countries; fertility is lower in high-income counties, but fell further during the recent period of economic hardship or uncertainty. As a result of falling at both low and high ends of the economic scale, therefore, global TFR declined from 2.57 in 2007 to 2.40 in 2019 (by these World Bank data).
Figure 3. Difference in total fertility rate between the highest point in 2007-2009 and the lowest point in 2017-2019, by GDP per capita. Note: Markers scaled by population; largest countries labeled. Source: World Bank.
The mechanisms for these relationships – higher standard of living and rising unemployment both lead to lower fertility – defy simple characterization. The social scale (individual to global) may condition the relationship; there may be different effects of relative versus absolute economic wellbeing (long term and short term); development effects may be nonlinear (Myrskylä, Kohler, and Billari 2009); and the individual or cultural perception of these social facts is important as well (Brauner-Otto and Geist 2018). Note also that, as fertility rates fall with development, the question of having no children versus fewer has emerged as a more important distinction, which further complicates the interpretation of TFR trends (Hartnett and Gemmill 2020).
U.S. recessions
In the case of recent U.S. recessions, the negative impact on fertility was largest for young women. After the 2001 recession, birth rates only fell for women under age 25. In the wake of the more severe 2008 economic crisis, birth rates fell for all ages of women up to age 40 (above which rates continued to increase every year until 2020) although the drop was still steepest below age 25 (Cohen 2018). For the youngest women, births have continued to fall every year since, while those over age 35 saw some rebound from 2012 to 2019 (Figure 4). Clearly, during this period many women postponed births from their teens or twenties into their thirties and forties. The extent to which they will end up with lower fertility on a cohort basis depends on how late they continue (or begin) bearing children (Beaujouan 2020).
Figure 4. Annual change in U.S. births per 1,000 women, by age: 2001-2020. Source: National Center for Health Statistics.
Contrary to the suggestion that fertility decline is chiefly the result of improving opportunities for women, the pattern of delaying births is consistent with evidence that structural changes in the economy, the decline in goods-producing industries and the rise of less secure and predictable service industry jobs, are largely responsible for the lack of a fertility rebound after the 2008 recession, especially for Black and Hispanic women (Seltzer 2019). Lower education is also associated with greater uncertainty about having children among young people (Brauner-Otto and Geist 2018). For women in more precarious circumstances, especially those who are not married, these influences may be observed in the effect of unemployment rates on birth rates at the state level (Schneider and Hastings 2015). The available evidence supports the conclusion that the 2008 recession produced a large drop in fertility that did not recover before 2020 at least in part because the economic uncertainty it amplified has not receded – making it both a short-term and long-term event.
Birth rates recovered some for older women, however – over 30 or so – which is consistent with fertility delay. But this delay does not necessarily favor the opportunity cost versus economic constraint explanations. On one hand are people with higher levels of education (anticipated or realized) who plan to wait until their education is complete. On the other hand are those with less education who are most economically insecure, whose delays reflect navigating the challenges of relationship instability, housing, health care, childcare and other costs with lesser earning potential. This latter group may end up delaying either until they attain more security or until they face the prospect of running out of childbearing years. Both groups are deliberately delaying births partly for economic reasons, but the higher-education group is much more likely to have planned births while the latter have higher rates of unintended or mistimed births (Hayford and Guzzo 2016).
The opportunity cost of women’s childbearing, in classical models, is simply the earnings lost from time spent childrearing – the product of the hours of employment lost and the expected hourly wage (Cramer 1979). Although rising income potential for women has surely contributed to the long-run decline of fertility rates, in the U.S. that mechanism has not been determinative. Women experienced large increases in earnings for decades during which fertility rates did not fall. As the total fertility rate rose from its low point in 1976 (1.74) to the post-Baby Boom peak in 2007 (2.12) – defying the trend in many other high-income countries – the average weekly earnings of full-time working women ages 18-44 rose by 16% in constant dollars (Figure 5).
Figure 5. Median weekly earnings of full-time employed women ages 18-44, and total fertility rate. Source: Current Population Survey Annual Social and Economic Survey, and Human Fertility Database.
Clearly, other factors beyond lost earnings calculations are at work. However, there is no simple way to distinguish those who make direct cost comparisons, where investments in time and money take away from other needs and opportunities, from those who delay out of concern over future economic security, which weighs on people at all income levels and generates reluctance to make lifelong commitments (Pugh 2015). But the implications of these two effects are opposing. For people who don’t want to lose opportunities, a strong economy with abundant jobs implies lower fertility. For people who are afraid to commit to childrearing because of insecurity about their economic fortunes, a weak economy should decrease fertility. The experience of the post-2008 period provides strong evidence for the greater weight of the latter mechanism.
US births, 2000-2019
If opportunity costs were the primary consideration for women, one might expect an inverse relationship between job market growth and fertility rates: more jobs, fewer babies; fewer jobs, more babies. This is the pattern reported by Tavernise et al. (2021), who found that birthrates after the 2008 crisis fell more in counties with “growing labor markets” – which they attribute to the combination of improving opportunities for women and the high costs of childcare. However, their analysis did not attend to chronological ordering. They identified counties as having strong job growth if they were in the top quintile of counties for labor market percent change for the period 2007 to 2019, and compared them with counties in the bottom quintile of counties on the same measure with regard to birth rates (author correspondence). Thus, their analysis used a 2007-2019 summary measure to predict birth rates for each year from 1990 to 2019, making the results difficult to interpret.
In addition to using contemporaneous economic data, whereas Tavernise et al. (2021) used county-level birth rates, in this analysis I use individual characteristics and state-level data. I construct indicators of individual- and state-level relative advantage during the period before and after the 2008 economic crisis, from 2000 to 2019. Individual data are from the 2000-2019 American Community Survey (ACS) via IPUMS (Ruggles et al. 2021). I include in the analysis women ages 15-44, and use the fertility question, which asks whether they had a baby in the previous 12 months. I analyze this as a dichotomous dependent variable, using ordinary least squares regression. Results are graphed as marginal effects at the means, using Stata’s margins command. The sample size is 9,415,960 million women, 605,150 (6.4%) of whom had a baby in the previous year (multiple births are counted only once).
In models with controls, I control for age in five-year bins, race/ethnicity (White, Black, American Indian, Asian/Pacific Islander, Other/multiple-race, and Hispanic), citizenship (U.S.-born, born abroad to American parents, naturalized, and not a citizen), marital status (married, spouse absent, separated, divorced, widowed, and never married), education (less than high school, high school graduate, some college, and BA or higher degree), as well as (in some models) the state unemployment rate (lagged two years), and state fixed effects. State unemployment rates are from Local Area Unemployment Statistics (Bureau of Labor Statistics 2021). ACS person weights are used in all analyses.
For states, I use the unemployment rate in each state for each year, and divide the states at the median, so those with the median or higher unemployment for each year are coded as high unemployment states, and low unemployment otherwise (this variable is lagged two years, because the ACS asks whether each woman has had a birth in the previous 12 months, but does not specify the month of the birth, or the date of the interview). For individuals, the identification of economic advantage is difficult with the cross-sectional data I use here, because incomes are likely to fall in the year of a birth, and education may be determined endogenously with fertility as women age (Hartnett and Gemmill 2020), so income and education cannot simply be used to identify economic status. Instead, I identify women as low education if they have less than the median level of education for women of their age in their state for each year (using single years of age, and 26 categories of educational attainment), and high education otherwise. Thus, individual women in my sample are coded as in a high or low unemployment state relative to the rest of the country each year, and as having high or low education relative other women of their age and state and year. Using the ACS migration variable, I code women into the state they lived in the previous year, which is more likely to identify where they lived when they determined whether to have a baby (which also means I exclude women who were not living in the U.S. in the year before the survey).
Figure 6 shows the unadjusted probability of birth for women in high- and low-unemployment states for the period 2000-2019. This shows the drop in birth rates after 2008, which is steeper for women who live in high-unemployment states, especially before 2017. This is what we would expect from previous research on the 2008 financial crisis: a greater falloff in birth rates where the economy suffered more.
Figure 6. Probability of birth in the previous year: 2000-2019, by state unemployment relative to the national media (marginal effects at the means). Women ages 15-44. Based on state of residence in the previous year; unemployment lagged two years.
Next, I split the sample again by women’s own education relative to the median for those of the same age, year, and state. Those less than that median are coded as low education, those at or higher than the median are coded as high education. Figure 7 shows these results (again, unadjusted for control variables), showing that those with lower education (the top two lines) have higher birth rates throughout the period. After 2008, within both the high- and low-education groups, those in high-unemployment states had longer and steeper declines in birth rates (at least until 2019). The steepest decline is among low-education, high-unemployment women: those facing the greatest economic hardship at both the individual and state level. Finally, Figure 8 repeats the model shown in Figure 7, but with the control variables described above, and with state fixed effects. The pattern is very similar, but the differences associated with state unemployment are attenuated, especially for those with low education.
Figure 7. Probability of birth in the previous year: 2000-2019, by education relative to the age-state median, and state unemployment relative to the national media (marginal effects at the means). Women ages 15-44. Based on state of residence in the previous year; unemployment lagged two years.
Figure 8. Probability of birth in the previous year: 2000-2019, by education relative to the age-state median, and state unemployment relative to the national media, with controls for age, race/ethnicity, citizenship, marital status, and state fixed effects (marginal effects at the means). Women ages 15-44. Based on state of residence in the previous year; unemployment lagged two years.
Discussion
Although birth rates fell for all four groups of women in this analysis after the 2008 recession, these results reflect that paradoxical nature of economic trends and birth rates. Women with higher education (and greater potential earnings) have lower birthrates, consistent with the opportunity cost reasoning described in Tavernise et al. (2021) and elsewhere. However, women in states with higher unemployment rates – especially when they have high relative education – also have lower birthrates, and in these states saw greater declines after the 2008 crisis. This is consistent with the evidence of negative effects of economic uncertainty and stress. And it goes against the suggestion that stronger job markets drive down fertility rates for women with higher earning potential, at least in the post-2008 period. In the long run, perhaps, economic opportunities reduce childbearing by increasing job market opportunities for potential mothers, but in recent years this effect has been swamped by the downward pressure of economic troubles. US birth rates fell further in 2020, apparently driven down by the COVID-19 pandemic, which raised uncertainty – and fear for the future – to new heights (Cohen 2021; Sobotka et al. 2021). We don’t yet know the breakdown of the shifts in fertility for that year, but if the effects were similar to those of the 2008 economic crisis, we would expect to see greater declines among those who were most vulnerable.
References
Beaujouan, Eva. 2020. “Latest-Late Fertility? Decline and Resurgence of Late Parenthood Across the Low-Fertility Countries.” Population and Development Review 46 (2): 219–47. https://doi.org/10.1111/padr.12334.
Brauner-Otto, Sarah R., and Claudia Geist. 2018. “Uncertainty, Doubts, and Delays: Economic Circumstances and Childbearing Expectations Among Emerging Adults.” Journal of Family and Economic Issues 39 (1): 88–102. https://doi.org/10.1007/s10834-017-9548-1.
Bureau of Labor Statistics. 2021. “States and Selected Areas: Employment Status of the Civilian Noninstitutional Population, January 1976 to Date, Seasonally Adjusted.” 2021. https://www.bls.gov/web/laus/ststdsadata.txt.
Cohen, Philip N. 2018. Enduring Bonds: Inequality, Marriage, Parenting, and Everything Else That Makes Families Great and Terrible. Oakland, California: University of California Press.
———. 2021. “Baby Bust: Falling Fertility in US Counties Is Associated with COVID-19 Prevalence and Mobility Reductions.” SocArXiv. https://doi.org/10.31235/osf.io/qwxz3.
Comolli, Chiara Ludovica. 2017. “The Fertility Response to the Great Recession in Europe and the United States: Structural Economic Conditions and Perceived Economic Uncertainty.” Demographic Research 36 (51): 1549–1600. https://doi.org/10.4054/DemRes.2017.36.51.
Cramer, James C. 1979. “Employment Trends Ofyoung Mothers and the Opportunity Cost of Babies in the United States.” Demography 16 (2): 177–97. https://doi.org/10.2307/2061137.
Currie, Janet, and Hannes Schwandt. 2014. “Short- and Long-Term Effects of Unemployment on Fertility.” Proceedings of the National Academy of Sciences 111 (41): 14734–39. https://doi.org/10.1073/pnas.1408975111.
Gaddy, Hampton Gray. 2021. “A Decade of TFR Declines Suggests No Relationship between Development and Sub-Replacement Fertility Rebounds.” Demographic Research 44 (5): 125–42. https://doi.org/10.4054/DemRes.2021.44.5.
Hartnett, Caroline Sten, and Alison Gemmill. 2020. “Recent Trends in U.S. Childbearing Intentions.” Demography 57 (6): 2035–45. https://doi.org/10.1007/s13524-020-00929-w.
Hayford, Sarah R., and Karen Benjamin Guzzo. 2016. “Fifty Years of Unintended Births: Education Gradients in Unintended Fertility in the US, 1960-2013.” Population and Development Review 42 (2): 313–41.
Herzer, Dierk, Holger Strulik, and Sebastian Vollmer. 2012. “The Long-Run Determinants of Fertility: One Century of Demographic Change 1900–1999.” Journal of Economic Growth 17 (4): 357–85. https://doi.org/10.1007/s10887-012-9085-6.
Myrskylä, Mikko, Hans-Peter Kohler, and Francesco C. Billari. 2009. “Advances in Development Reverse Fertility Declines.” Nature 460 (7256): 741–43. https://doi.org/10.1038/nature08230.
Pugh, Allison J. 2015. The Tumbleweed Society: Working and Caring in an Age of Insecurity. 1 edition. New York, NY: Oxford University Press.
Ruggles, Steven, Sarah Flood, Sophia Foster, Ronald Goeken, Jose Pacas, Megan Schouweiler, and Matthew Sobek. 2021. “IPUMS USA: Version 11.0 [Dataset].” 2021. doi.org/10.18128/D010.V11.0.
Schneider, Daniel. 2015. “The Great Recession, Fertility, and Uncertainty: Evidence From the United States.” Journal of Marriage and Family 77 (5): 1144–56. https://doi.org/10.1111/jomf.12212.
Schneider, Daniel, and Orestes P. Hastings. 2015. “Socioeconomic Variation in the Effect of Economic Conditions on Marriage and Nonmarital Fertility in the United States: Evidence From the Great Recession.” Demography 52 (6): 1893–1915. https://doi.org/10.1007/s13524-015-0437-7.
Seltzer, Nathan. 2019. “Beyond the Great Recession: Labor Market Polarization and Ongoing Fertility Decline in the United States.” Demography 56 (4): 1463–93. https://doi.org/10.1007/s13524-019-00790-6.
Sobotka, Tomas, Aiva Jasilioniene, Ainhoa Alustiza Galarza, Kryštof Zeman, Laszlo Nemeth, and Dmitri Jdanov. 2021. “Baby Bust in the Wake of the COVID-19 Pandemic? First Results from the New STFF Data Series.” SocArXiv. https://doi.org/10.31235/osf.io/mvy62.
Having spent a few months collecting data on birth rates over the last year, and a few months pouring over pandemic data, I took the time to bring the two together and assess the relationship between some basic pandemic indicators and the latest fertility outcomes. The result is a short paper I titled, “Baby Bust: Falling Fertility in US Counties Is Associated with COVID-19 Prevalence and Mobility Reductions,” now available on SocArXiv, with links to the data and Stata code for replication.
Here’s the abstract:
The United States experienced a 3.8 percent decline in births for 2020 compared with 2019, but the rate of decline was much faster at the end of the year (8 percent in December), suggesting dramatic early effects of the COVID-19 pandemic, which began affecting social life in late March 2020. Using birth data from Florida and Ohio counties through February 2021, this analysis examines whether and how much falling birth rates were associated with local pandemic conditions, specifically infection rates and reductions in geographic mobility. Results show that the vast majority of counties experienced declining births, suggestive of a general influence of the pandemic, but also that declines were steeper in places with greater prevalence of COVID-19 infections and more extensive reductions in mobility. The latter result is consistent with more direct influences of the pandemic on family planning or sexual behavior. The idea that social isolation would cause an increase in subsequent births receives no support.
Here’s the main result in graphic form, showing that births fell more in January/February in those counties with more COVID-19 cases, and those with more mobility limitation (as measured by Google), through the end of last May:
However, note also that births fell almost everywhere (87% of the population lives in a fertility-falling county), so it didn’t take a high case count or shutdown to produce the effect.
There will be a lot more research on all this to come, I just wanted to get this out to help establish a few basic findings and motivate more research. I’d love your feedback or suggestions.
I was considering assigning the students in my Family Demography seminar to watch the documentary, One Child Nation: The Truth Behind the Propaganda, so I watched it. The movies uses the tragic family history of one of the directors, Nanfu Wang, to tell the story of the Chinese birth planning policy that began in 1979 and extended through many modifications until 2015. Nothing against watching it, but it’s not good. The one-child policy wasn’t good either, of course, leading to many violations of human rights and a lot of suffering and death.
Before watching the movie, I’m glad I read the review by Susan Greenhalgh, an anthropologist who spent about 25 years studying the one-child policy and related questions (summarized in three books and many articles, here). It’s short and you should read it, but just to summarize a couple of key historical points:
The policy was “the cornerstone of a massively complex and consequential state project to modernize China’s population,” and can’t be understood in the context of birth control alone.
Many people opposed and resisted the policy, but reducing birth rates was a commonly-understood goal, for both gender equality and economic development, and many women were glad the government supported them in that effort. The “vast majority” felt “deep ambivalence” about the policy, weighing individual desires against the perceived need to sacrifice for the common good.
The policy was unevenly applied and enforced (it was especially harsh in the provinces featured in the film), and after 1993 enforcement became less egregious.
Exceptions were added starting in the early 1980s, until by the late 1990s the majority of the population was not subject to a one-child rule.
There are some other specific errors and distortions, including the dramatic, incorrect claim that “the one-child policy [was] written into China’s constitution” in 1982 (as Greenhalgh writes, “the 1982 Constitution says only: “both husbands and wives are duty-bound to practice birth planning”). And the decision to translate all uses of the term “birth planning” as “one-child policy.” That said, the stories of forced abortions, sterilizations, and infanticide are wrenching and ring true.
I have two things to add to Greenhalgh’s review. First, a simple data illustration to show that China, really, is not a “one-child nation.” Using Chinese census data, here is the total number of children (by age 35-39) born to three groups of Chinese women, arranged according to their ages in 1980, about when the one-child policy began.
The shift left shows the decline in number of children born: the mean fell from 3.8 to 2.5 to 1.8 in these data. (Measuring Chinese fertility is complicated, but the census provides a reasonable ballpark.) But the main thing I want to show is that among the last group — those who were beginning their childbearing years when the policy took effect — 61% had two or more children. The idea that China became a “one-child nation” under the policy is false.
Second, the movie takes a hard turn in the middle and focuses on international adoption, and the illegal trafficking of mostly second-born girls to orphanages that sought to place them abroad. This was a very serious problem. But the movie tells the story of the most notorious scandal (for which many people served jail terms) as if it were the common practice, and centers on the savior-like behavior of American activists helping adopted children trace their familial roots. Granting that of course that corruption was terrible, and that the motivations of many (some?) adoptive parents (including me) were good, from China’s point of view it’s not a central story in the history of the one-child policy. As the movie notes, 130,000 Chinese children were adopted abroad during the period, during which time hundreds of millions were born.
Greenhalgh summarizes on this point, calling the film a:
“familiar coercion narrative, complete with villain (the state), victims (rural enforcers and targets), and savior (an American couple offering DNA services to match adopted girls in the U.S. with birth parents in China). The characters (at least the victims and saviors) have some emotional complexity, but they still play the stock roles in an oft-told tale. For American viewers, this narrative is comforting, because it provides a simple, morally clear way to react to troubling developments unfolding in a faraway, little understood land. And by using China (communist, state-controlled childbearing) as a foil for the U.S. (liberal, relative reproductive freedom), the film leaves us feeling smug about the assumed superiority of our own system.”
The many centuries of Chinese patriarchy are a dark part of the human story, and in some ways is unique. For example — relevant to this recent histyory — female infanticide and selling girls has a long history (a history that includes foot binding and other atrocities). The Chinese Communist Party, for all its misdeeds, did not create this problem. Gender inequality in China, including the decline in fertility — which was mostly accomplished before 1979 — has markedly improved since 1949. Greenhalgh concludes: “In China, before the state began managing childbearing, reproductive decisions were made by the patriarchal family. Since the shift to a two-child policy, they have been subject to the strong if indirect control of market forces. One form of control may be preferable to another, but freedom over our bodies is an illusion.”
[Update: California released revised birth numbers, which added a trivial number to previous months, except December, where they added a few thousand, so now the state has a 10% decline for the month, relative to 2019. I hadn’t seen a revision that large before.]
Lots of people are talking about falling birth rates — even more than they were before. First a data snapshot, then a link roundup.
For US states, we have numbers through December for Arizona, California, Florida, Hawaii, and Ohio. They are all showing substantial declines in birth rates from previous years. Most dramatically, California just posted December numbers, and revised the numbers from earlier months, now showing a 19% 10% drop in December. After adding about 500 births to November and a few to October, the drop in those two months is now 9%. The state’s overall drop for the year is now 6.2%. These are, to put it mildly, very larges declines in historical terms. Even if California adds 500 to December later, it will still be down 18%. Yikes. One thing we don’t yet know is how much of this is driven by people moving around, rather than just changes in birth rates. California in 2019 had more people leaving the state (before the pandemic) than before, and presumably there have been essentially no international immigrants in 2020. Hawaii also has some “birth tourism”, which probably didn’t happen in 2020, and has had a bad year for tourism generally. So much remains to be learned.
Here are the state trends (figure updated Feb 18):
From the few non-US places that I’m getting monthly data so far, the trend is not so dramatic. Although British Columbia posted a steep drop in December. I don’t know why I keep hoping Scotland will settle down their numbers… (updated Feb 18):
Here are some recent items from elsewhere on this topic:
Laura Lindberg in Ms.: The Coming COVID Baby Bust. “Past patterns and emerging evidence suggest we are going to see a COVID Baby Bust. But how long will it last and how big will it be?”
That led to some local TV, including this from KARE11 in Minneapolis:
Good news / bad news clarification
There’s an unfortunate piece of editing in the NBCLX piece, where I’m quoted like this: “Well, this is a bad situation. [cut] The declines we’re seeing now are pretty substantial.” To clarify — and I said this in the interview, but accidents happen — I am not saying the decline in births is a bad situation, I’m saying the pandemic is a bad situation, which is causing a decline in births. Unfortunately, this has slipped. As when the Independentquoted the piece (without talking to me) and said, “Speaking to the outlet, Philip Cohen, a sociologist and demographer at the University of Maryland, called the decline a ‘bad situation’.”
The data for this project is available here: osf.io/pvz3g/. You’re free to use it.
For more on fertility decline, including whether it’s good or bad, and where it might be going, follow the fertility tag.
Acknowledgement: We have lots of good conversation about this on Twitter, where there is great demography going on. Also, Lisa Carlson, a graduate student at Bowling Green State University, who works in the National Center for Family and Marriage Research, pointed me toward some of this state data, which I appreciate.
Joe Pinsker at the Atlantic has a piece out on the coming (probable) baby bust. In it he reviews existing evidence for a coming decline in births as a result of the pandemic, especially including historical comparisons and Google search data. Could we see this already?
Pinsker writes:
The baby bust isn’t expected to begin in earnest until December. And it could take a bit longer than that, Sarah Hayford, a sociologist at Ohio State University, told me, if parents-to-be didn’t adjust their plans in response to the pandemic immediately back in March, when its duration wasn’t widely apparent.
If people immediately changed their plans in February, we might see a decline in births in October, but Hayford is right that’s early. And what about September, for which I’ve already observed declining births in Florida and California? If people who were pregnant already in January had miscarriages or abortions because of the pandemic, that would result in fewer births in September, but how big could that effect be? So maybe the Florida and California data are flukes, or data errors, or lots of pregnant people left those states and gave birth elsewhere (or pregnant people who normally come didn’t arrive). Perhaps more likely is that 2020 was already going to be a down year. As I told Pinsker:
“It might actually be that we were already heading for a record drop in births this year … If that’s the case, then birth rates in 2021 are probably going to be even more shockingly low.”
Anyway, we’ll find out soon enough. And to that end I’ve started assembling a dataset of monthly births where I can find them, which so far includes Florida, California, Oregon, Arizona, North Carolina, Ohio, Hawaii, Sweden, Finland, Scotland, and the Netherlands, to varying degrees of timeliness. As of today we have October data for some of them:
As of now Florida and California remain the strongest cases for a pandemic effect. But they are also both likely to add some more births to October (in November’s report, California increased the September number by 3%).
Anyway, lots of speculation while we’re killing time. You can get the little dataset here on the Open Science Framework: https://osf.io/pvz3g/. Check the date on the .csv or .xlsx file to see what I last updated it. I’ll add more countries or states if I find out about them.
I think the big demographic story of 2021 is likely to be the very large decline in births. I think everything points that way and I think it’s going to be quite shocking when we see how big it is. — Philip Cohen, October 27, 2020
I gave a talk yesterday at the University of California, Irvine Center for Demographic and Social Analysis. The slides are here under CC-BY license. The video is below.
After reviewing the state of the economic and social shock of the pandemic, with implications for family processes and events (sex, contraception, pregnancy, birth, marriage, and divorce), I presented some new information on births and marriage.
Here is the data on births, in Florida and California, the only states I found that have monthly updated birth numbers through September (subject to revision, but probably not by much). Both show large declines in births in 2020. Which seems hard to link to the pandemic, gestation times being what they are (but maybe more reasonable than last month’s report). There may already be more miscarriages and abortions, or maybe fewer premature births? I don’t know. If these declines have nothing to do with the pandemic, and they’re just the continuation of our trend toward lower birth rates, then that’s pretty shocking, too.
This is the total births by month and year, with 2018 and 2019 compared with 2020 so far:
Here are the monthly totals compared with the annual average decline in over the previous three years, which is 2.9% in California and 0.7% in Florida, which I call “predicted.”
In September 2020 versus September 2019, births were 6.1% lower in Florida and 9.6% lower in California. There is a lot of big news in the news these days, but I think this is still pretty big news. Again, if this has nothing to do with the pandemic that’s even more shocking.
At this writing we are a few days shy of 35 weeks from February 1st. If I read this right, 10% of US births occur at 36 weeks of gestation or less. But the most recent complete data I see is from August, so it’s early. However, most fertilized human eggs do not come to term, being lost either before (30%) or after (30-40%) implantation. That’s from a paper by Jenna Nobles and Amar Hamoudi, who write:
Evidence suggests that multiple mechanisms may be involved in pregnancy survival, including those that affect placental development and function, fetal oxidative stress, fetal neurological development, and likely many others. These, in turn, are shaped by more distal processes that affect maternal nutrition, maternal exposure to biological and psychosocial stress, maternal exposure to infection, and management of chronic conditions. Pregnancy survival varies with women’s body mass index, consumption of folic acid, and in some studies, reports of stressful life events (citations removed).
The pandemic might reasonably have contributed to a higher rate of pregnancy loss from these factors. And then there are abortions, which people have probably needed more even though they had less access to them (see this report from Guttmacher). So the net effect is unclear.
Setting aside how the pandemic might have affected fertility intentions and planning (I assume this is negative, as reported by Guttmacher), there might already be fewer births, from loss and abortion.
I haven’t looked at every state, but Florida and California report births by month. In Florida, there were 9.5% fewer babies born in August 2020 than in the previous year (they revise these as they go, but the August number has been stable for a little while, so probably won’t increase much). In California there were 9.6% fewer births in August of this year compared with last year. Here are the monthly trends, including the last three years (I included Florida’s September number as of today, but that will certainly rise):
This is going to be tricky because birth rates were already falling in many places. But the average decline in the last three years was 2.9% in California and 0.7% in Florida, so these numbers clearly outpace that naïve expectation. Also, what about spring? Maybe the pandemic was already causing a decline in live births in California in March (from immigrants not coming or staying in Mexico or other countries?), but if the decline in March was unrelated, then it’s not clear how to interpret the drop in August. So it will be complicated. But this is a bona fide blip in the expected direction, so I’m posting it with a question mark.
I assume other people will be way ahead of me on this, though I haven’t seen anything. Feel free to post other analyses in the comments.
The pandemic could be affecting the number of abortions, miscarriages, or infant deaths, but unless those effects are large it should be too early to see effects on the total birth rate, given that we’re only about 7 months into it here. So for possible birth indicators I did a little Google search analysis using the public Google Trends data.
I found three searches that were pretty well correlated in the weekly series: “am I pregnant”, “pregnancy test,” and “morning sickness”, which all should have something to do with the frequency of new pregnancies. I ran Google Trends back five years, created an index from these searches (alpha = .68) , smoothed it a little, and this is what I got:
There was already a big drop in 2019 from the previous three years (reasonable, based on recent trends), and then 2020 started out with a further drop. But then it spiked downward in March before rebounding back to its lower level. So, maybe that implies birth rates will keep falling but not off the charts compared with recent trends.
I also checked “missed period,” which was not well correlated with the others, and got this:
Again, 2019 was already showing some decline, and 2020 started out lower than that, and now searches for “missed period” are running lower than last year, but not more in the middle of the year than they were in the beginning. So, inconclusive for pandemic effect.
Weddings
Here’s a new take on the Google trends for weddings. I took the averages of searches for “wedding invitations”, “wedding shower”, “bridal shower”, “wedding shower”, and “wedding dresses” (alpha=.94). With a little smoothing, here is 2020 compared with the average of the four previous years (unlike pregnancy searches, this one didn’t show a marked decline in 2019 compared with previous years).
March and April showed catastrophic declines in searches for wedding topics, and the rebound so far has been weak. However, weddings aren’t the same as marriages. Maybe people who had to cancel their weddings still got married down at whatever the pandemic equivalent of the courthouse is. So here’s the same analysis just for the search term “marriage license.” This shows a steep but not as catastrophic drop-off in March and April, and a stronger rebound. So maybe the decline in drop in marriages won’t be as big as the drop in weddings.
Actual marriages
I previously showed the steep decline in recorded marriages in Florida. Here’s an update.
Florida lists recorded marriages by county and month, one month behind (see Table 17). They update as they go, so as of today August marriages are probably still not all recorded. The comparison with previous years shows a collapse in March and April, and then some rebounding. August is preliminary and will come up some.
Marriages in Florida normally peak between March and May. Of course it’s too early to say how many of these were just being postponed. The cumulative trend shows that through July Florida is down 24,000 marriages, or 27%, compared with last year.
Divorce ideation
When the going gets tough, the afflicted want to get divorced, but maybe they can’t. It’s expensive and time consuming and maybe people think it will upset the children even more. (I’ve written about divorce and recessions here and here). So my initial assumption going into the pandemic was that there would be a stall in divorces even though the intent to divorce would rise, followed by a rebound when people get a chance to act on their wishes.
Here I use Google search trends for four searches: “divorce lawyer”, “divorce attorney”, “get a divorce”, and “how to divorce”. The alpha for this index is .69 (when I just use the attorney and lawyer, the alpha is .86, but the result looks the same, so I’m showing the wider index). The results show a drop in divorce ideation in March into April, followed by a rebound to a level a little above the previous year average. Note this pandemic-spring drop is a lot less pronounced than the wedding and marriage collapses above.
Actual divorces
Divorces take time, of course. Like births, I wouldn’t expect to see definitive results right away. In fact, it’s hard to know how long divorces are in process before they show up as recorded. However, in my favorite real-time demography state, Florida, they have been recording divorces every month, and have a look at this:
It’s a giant plunge in recorded divorces, almost 60% in April, followed by a weaker rebound. Again, the records are not yet complete, especially for August, so we’ll see. But comparing these patterns, it might be that there was a short suspension in divorce ideation as people were distracted by the crisis, followed by a rebound which hasn’t yet translated into divorce filings. Googling about divorce seems cheap and easy (and faster) compared with pulling it off, but this might mean there is growing pent up demand for divorce, which is bad (and may imply greater risks of conflict and violence).
Young adults living “at home”
I previous wrote about young adults living with their parents and grandparents using the June and then July Current Population Survey data made available by IPUMS.org. Subsequently, the Pew Research Center did something very similar using the data through July (with additional breakdowns and historical context). Pew used living with parents, apparently including those in households where the parents are not the householders. I prefer my definition — young adults living in the home of parents (also, or grandparents) — which fits better with the popular concept of living “at home.” So if your parents come to live with you, that’s different.
Anyway, here’s the update through August, which shows the percentage of young adults living at home falling back some from the June peak. I will be very interested to follow this through the fall.
Update: By October this trend had returned almost back to pre-pandemic levels:
In October the percentage of young adults living with the parents or grandparents was almost back to normal pic.twitter.com/WTMebCV3hs
Stata code for the living at home analysis is available here: https://osf.io/2xrhc/.
The pandemic and its attendant economic crisis is having massive effects on many aspects of family life. These early indicators are just possible targets of future analysis. There is a lot of other related work going on, which I’ve not taken the time to link to here. Please feel free to recommend other work in the comments.
Family Inequality 