Hard times and falling fertility in the United States

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.

Bongaarts, John. 2017. “Africa’s Unique Fertility Transition.” Population and Development Review 43 (S1): 39–58. https://doi.org/10.1111/j.1728-4457.2016.00164.x.

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.

Filipovic, Jill. 2021. “Opinion | Women Are Having Fewer Babies Because They Have More Choices.” The New York Times, June 27, 2021, sec. Opinion. https://www.nytimes.com/2021/06/27/opinion/falling-birthrate-women-babies.html.

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.

Tavernise, Sabrina, Claire Cain Miller, Quoctrung Bui, and Robert Gebeloff. 2021. “Why American Women Everywhere Are Delaying Motherhood.” The New York Times, June 16, 2021, sec. U.S. https://www.nytimes.com/2021/06/16/us/declining-birthrate-motherhood.html.

The COVID-19 epidemic in rural U.S. counties

I’ve been working on the COVID-19 epidemic in rural U.S. counties, and have now posted a paper on SocArXiv, here: https://osf.io/preprints/socarxiv/pnqrd/. Here’s the abstract, then some figures below:

Having first reached epidemic proportions in coastal metropolitan areas, COVID-19 has spread around the country. Reported case rates vary across counties from zero to 125 per thousand population (around a state prison in the rural county of Trousdale, Tennessee). Overall, rural counties are underrepresented relative to their share of the population, but a growing proportion of all daily cases and deaths have been reported in rural counties. This analysis uses daily reports for all counties to present the trends and distribution of COVID-19 cases and deaths in rural counties, from late March to May 16, 2020. I describe the relationship between population density and case rates in rural and non-rural counties. Then I focus on noteworthy outbreaks linked to prisons, meat and poultry plants, and nursing homes, many of which are linked to high concentrations of Hispanic, American Indian, and Black populations. The growing epidemic in rural counties is apparently driven by outbreaks concentrated in these institutional settings, which are conducive to transmission. The impact of the epidemic in rural areas may be heightening due to their weaker health infrastructure and more vulnerable populations, especially due to age, socioeconomic status, and health conditions. As a result, the epidemic may contribute to the ongoing decline of health, economic, and social conditions in rural areas.

Here are COVID-19 cases in rural counties across the country. Note that the South, Mid-Atlantic, Michigan, and New England have the most (fewer in West and upper Midwest). When you look at cases per capita, you see the concentration in the South and isolated others.

F1 rural county cases maps

COVID is still underrepresented in rural counties, but their share of the national burden is increasing, as they keep adding more than 2,000 cases and just under 100 deaths per day.

F2 new cases and deaths

Transmission dynamics are different in rural counties. They show a weaker relationship between pop density and cases. This suggests to me that there are more idiosyncratic factors at work (prisons, meat plants, nursing homes), which are high concentrations of vulnerable people.

F3 population density and cases

These are the rural outbreak cases I identified, for which I could find obvious epidemic centers in institutions: Prisons, meatpacking and poultry plants, and nursing homes. These 28 select counties account for 15% of the rural burden.

F4 rural county selected cases

In addition to the institutional concentration, these outbreak cases also show distinct overrepresentation of Hispanic, American Indian, and Black populations. Here are some of the outbreak cases plotted against minority concentrations.

F5 rural county minority scatters

And here’s a table of those selected cases:

crt2

Lots more to be done, obviously. It’s a strong limitation to be restricted to case and death counts at the county level. Someone could go get lists of prisons and meatpacking plants and nursing homes and run them through this, etc. But I wanted to raise this issue substantively. By posting the paper on SocArXiv, without peer review, I’m offering it up for comment and criticism. Also, I’m sharing the code (which links to the data, all public): osf.io/wd2n6/. Messy but usable.

A related thought on writing a paper about COVID19 right now: The lit review is daunting. There are thousands of papers, most on preprint servers. Is this bad? No. I use various tools to decide what’s reliable to learn from. If it’s outside my area, I’m more likely to rely on peer-reviewed journals, or those that are widely citied or reported. But the vast quantity available still helps me see what people are working on, what terms, and types of data they use. I learned a tremendous amount. Much respect to the thousands of researchers who are doing what they can to respond to this global crisis.

The continuation of babies

There is no guarantee that a happy, healthy, equal, and harmonious population wants to produce enough children to maintain or grow its total size.

Anna Louie Sussman wrote an essay in the New York Times, given the unfortunate title “The End of Babies” (about which more below). I like a lot of it, and I have substantial disagreements with the framing.

It’s about falling fertility and capitalism. This is a great summary, though I would replace “not necessarily a bad thing” with “usually a very good thing”:

Declining fertility typically accompanies the spread of economic development, and it is not necessarily a bad thing. At its best, it reflects better educational and career opportunities for women, increasing acceptance of the choice to be child-free, and rising standards of living.

At its worst, though, it reflects a profound failure: of employers and governments to make parenting and work compatible; of our collective ability to solve the climate crisis so that children seem a rational prospect; of our increasingly unequal global economy. In these instances, having fewer children is less a choice than the poignant consequence of a set of unsavory circumstances.

Sussman sees the “bigger picture” as this:

Our current version of global capitalism … has generated shocking wealth for some, and precarity for many more. These economic conditions generate social conditions inimical to starting families: Our workweeks are longer and our wages lower, leaving us less time and money to meet, court and fall in love. Our increasingly winner-take-all economies require that children get intensive parenting and costly educations, creating rising anxiety around what sort of life a would-be parent might provide. A lifetime of messaging directs us toward other pursuits instead: education, work, travel.

This paragraph uses a sort of 1% versus 99% framing with is exaggerated but not unreasonable. This, however, is just exaggerated:

It seems clear that what we have come to think of as “late capitalism” — that is, not just the economic system, but all its attendant inequalities, indignities, opportunities and absurdities — has become hostile to reproduction. Around the world, economic, social and environmental conditions function as a diffuse, barely perceptible contraceptive.

Lost in this, by now, is all the good parts about falling fertility mentioned previously. Remember, contraceptives are good, and most people use them deliberately to help control their lives, and they do it because social and environmental conditions have made it possible to have more control over one’s life than ever before, while offering unprecedented opportunities for women beyond child-rearing.

In short, I agree with Sussman’s description of how some people in rich societies would like to have more children than they do, I just don’t think it’s anything like a universal or even general experience in our era. And there is a puzzle confounding the premise: within rich countries, or at least the USA, privileged people, who presumably have more control over their lives and destinies, still have fewer children than those who are more powerless. I once wrote:

There is an argument that Americans are having fewer children than they want to because of our stone age work-family policies, especially poor family leave support and the high costs of good childcare. I’m sure that’s happening to some degree, but it’s still the case that more privileged people, who should be able to overcome those things more readily — people with college degrees and Whites — have lower fertility rates than people who are getting squeezed more.

Like a lot of work in this area, Sussman’s assessment that people want more children — which generates the image of the “reproductive malaise [that] has settled over,” in this case, Denmark — is based on surveys showing people’s “ideal” family size is larger than the average number of children actually born per family. But the interpretation of this gap is not so straightforward. Maybe people think three is the ideal number of children, but they also think a PhD is the ideal amount of education, and so they compromise, with some having one kid and a PhD, and some having three kids and a no college degree. This is an empirical question. What’s historically unprecedented and still so new that we don’t know what to make of it socially is the fact that this is a choice at all for so many people.

As I previously reported, the proportion of US women whose “ideal” number of children is higher than they number they had by age 40 has risen, from less than 15% among women born in the 1930s to almost a quarter for women born in the early 1970s. If you break that trend down by BA/no-BA education level, you can see that women with BA degrees are pushing it upward:

ideal fam size gss ba

So maybe college graduate women are having fewer than their ideal number of children like I’m earning less than the ideal amount of money — I think I could be making more money, but then I wouldn’t be able to sit around in my pajamas blogging with my dog, so I compromise. Of course, like some of the people in Sussman’s piece, a lot of people are justifiably unhappy about this, feeling they can’t compromise between forces pulling them in opposite directions. And so the result is dissatisfaction, maybe even malaise. I just don’t think we know how many people feel that way, or even whether the feeling is much more prevalent than it used to be.

Denmark

Sussman uses Denmark as one case study. This is her summary:

If any country should be stocked with babies, it is Denmark. The country is one of the wealthiest in Europe. New parents enjoy 12 months’ paid family leave and highly subsidized day care. Women under 40 can get state-funded in vitro fertilization. But Denmark’s fertility rate, at 1.7 births per woman, is roughly on par with that of the United States. A reproductive malaise has settled over this otherwise happy land.

But where is the evidence for this malaise? Denmark’s fertility rate has been low and relatively stable, while it is the USA’s that has plummeted since 2007, which is why the countries are now at the same level. The malaise that is settling is here — Denmark’s has already settled.

To elaborate on Denmark: There was a rapid drop in fertility from the mid-1960s through the mid-1980s, followed by a rebound, and then relative stability for about 25 years. During that time, as the population continued to grow slowly, women were reaching age 40 with between 1.8 and 1.9 children on average. Rather than slipping into a chasm, it looks more like the affluent people of Denmark have settled into a moderately low-fertility regime.

denmark.xlsx

“Replacement” fertility, of about 2.1 births per woman, doesn’t mean a society is healthy or happy. Maybe late capitalism with a decent welfare state is not “hostile to reproduction,” maybe it just doesn’t quite get to 2.1.

How bad is that? Like the USA (see my last projections), Denmark will have population decline if they keep on this path, discounting immigration. Because they have been at low fertility for a while, the country is close to seeing actual decline based on birth rates alone. Here is what would happen over the next hundred years if current trends persist and there are no immigrants: The population would eventually contract 31%.

denmark.xlsx

A 31% population drop a century from now would make for a pretty different Denmark (as will another few feet of sea-level rise). But there is time to get there — the drop would only be 6% in the next three decades. And of course if they don’t want this, they could easily cushion the fall with immigration. In any event, there is nothing here that suggests the “end of babies” or the abandonment of reproduction — families would continue having an average of 1.8 children each, as they have for the last several decades.

A population below replacement fertility might seem diseased, but it might also just be the aggregation of a lot of people exercising their newfound freedoms in newly discovered ways, including having fewer or no children. I agree with Sussman when she writes:

The problem, to be clear, is not really one of “population” …. Hundreds of thousands of babies are born on this planet every day; people all over the world have shown they are willing to migrate to wealthier countries for jobs. Rather, the problem is the quiet human tragedies, born of preventable constraints — an employer’s indifference, a belated realization, a poisoned body — that make the wanted child impossible.

To the extent those tragedies occur, we should prevent or ameliorate them. And to the extent they are concentrated among people or groups who already experience marginalization, isolation, or exploitation, it’s a social problem that’s part of our burgeoning inequality suite. Healthcare, housing, education, and family leave all come to mind as helpful, even if they can’t solve the existential crisis of late capitalism. But two cautions. First, I’m not convinced such tragedies are more common than they used to be, just because people are having fewer children than they used to. Remember, we also have fewer people trapped into having large families they don’t want (forced-birther policies notwithstanding).

And second, crucially, even if we address these issues of self-determination, there is no guarantee that a happy, healthy, equal, and harmonious population wants to produce enough children to maintain or grow its total size. We may eventually have to learn to live with fewer people, locally and globally, even if we’re all happy with the number of children we have.

What comes around

In the meantime, I think it’s confusing and ultimately unhelpful to confound what are essentially orthogonal issues. We should care about the problems Sussman raises regardless of population trends.

And that brings me to an aside on New York Times coverage. It was just 11 years ago, in 2008, that a different New York Times story about the existential threat of falling fertility, this one in the Magazine and titled “No Babies?”, singled out Scandinavian countries — with total fertility rates of 1.8 — as positive examples, bucking the trend toward “lowest-low” fertility demonstrated by Southern European countries, due to their “vigorous social-welfare systems.” That’s the same social welfare system, and the same total fertility rate, that Sussman characterizes as a “reproductive malaise” in Denmark today.

And there are illustrations of children playing alone in both cases. Because “the end of babies” and a world with “no babies” is best illustrated with a picture of the last child on earth alone in a playground. Great illustrations — just not of our societies.

nytchildrenalone

That said…

You can’t really pin sudden fertility swings on things like “late capitalism,” which are decades in the making. It was just February of 2009 that I was writing one of my first blog posts, “Why Are American Women Having More Children?” as U.S. total fertility rose to 2.1 for the first time since 1971. I think it was late capitalism, too, but the U.S. TFR was 13% higher than Denmark’s (they are now the same), and everyone was talking about American mothers “opting out” of the labor force to stay home with their four children. On the other hand is socialist Finland — a country with a lot of what I want from social policy, including low inequality and poverty, and lots of family leave — which has seen a fertility decline since 2010 that could reasonably be called a crash. The government estimates the TFR in 2019 is 1.32-1.34, down from 1.86 a decade ago!

Here are the trends in select countries:

country fertilitiy trends.xlsx

Does this mean the people in Finland are suddenly much less happy  relative to those in Denmark, which has seen a recent uptick in fertility rates? I have no idea. I can make population projections if you tell me the fertility rate, but I can’t tell you what the fertility rate will be in the future (and neither can you). A tiny bit humbling, honestly.

Wilcox plagiarism denial and ethics review

Recently I made the serious accusation that Brad Wilcox and his colleagues plagiarized me in a New York Times op-ed. After the blog post, I sent a letter to the Times and got no response. And until now Wilcox had not responded. But now thanks to an errant group email I had the chance to poke him, and he responded, in relevant part:

You missed the point of the NYT op-ed, which was to stress the intriguing J-Curve in women’s marital happiness when you look at religion and gender ideology. We also thought it interesting to note there is a rather similar J-Curve in women’s marital happiness in the GSS when it comes to political ideology, although the political ideology story was somewhat closer to a U-Curve in the GSS. Our NYT argument was not inspired by you, and our extension of the argument to a widely used dataset is not plagiarism.

Most of that comment is irrelevant to the question of whether the figure they published was ripped off from my blog; the only argument he makes is to underline the word notTo help readers judge for themselves, here is the sequence again, maybe presented more clearly than I did it last time.

Wilcox and Nicholas Wolfinger published this, claiming Republicans have happier marriages:

marital-quality-fig-1

I responded by showing that that when you break out the categories more you get a U-shape instead:

marital-happiness-partyid.xlsx

Subsequently, I repeated the analysis, with newer data, using political views instead of party identification (the U-shape on the right):

hapmar16c

This is the scheme, and almost exactly the results, that Wilcox and colleagues then published in the NYT, now including one more year of data:

bwnyt

The data used, the control variables, and the results, are almost identical to analysis I did in response to their work. His response is, “Our NYT argument was not inspired by you.” So that’s that.

Ethics aside

Of course, only he knows what’s in his heart. But the premise of his plagiarism denial is an appeal to trust. So, do you trust him?

Lies

There is a long history here, and it’s hard to know where to start if you’re just joining. Wilcox has been a liberal villain since he took over the National Marriage Project and then organized what became (unfortunately) known as the Regnerus study (see below), and a conservative darling since the top administration at the University of Virginia overturned the recommendation of his department and dean to grant him tenure.

So here are some highlights, setting aside questions of research quality and sticking to ethical issues.

Wilcox led the coalition that raised $785,000, from several foundations, used to generate the paper published under Mark Regnerus’s name, intended to sway the courts against marriage equality. He helped design the study, and led the development of the media plan, and arranged for the paper to be submitted to Social Science Research, and then arranged for himself to be one of the anonymous peer reviewers. To do this, he lied to the editor, by omission, about his contribution the study — saying only that he “served on the advisory board.”

And then when the scandal blew up he lied about his role at the Witherspoon Institute, which provided most of the funding, saying he “never served as an officer or a staffer at the Witherspoon Institute, and I never had the authority to make funding or programmatic decisions at the Institute,” and that he was “not acting in an official Witherspoon capacity.” He was in fact the director of the institute’s Program on Family, Marriage, and Democracy, which funded the study, and the email record showed him approving budget requests and plans. To protect his reputation and cover up the lie, that position (which he described as “honorific”) has been scrubbed from his CV and the Witherspoon website. (In the emails uncovered later, the president of Witherspoon, Luis Tellez wrote, “we will include some money for you [Regnerus] and Brad on account of the time and effort you will be devoting to this,” but the amount he may have received has not been revealed — the grants aren’t on his CV.)

This is covered under the Regnerus and Wilcox tags on the blog, and told in gripping fashion in a chapter of my book, Enduring Bonds.

You might hold it against him that he organized a conspiracy to fight marriage equality, but even if you think that’s just partisan nitpickery, the fact that the research was the result of a “coalition” (their word) that included a network of right-wing activists, and that their roles were not disclosed in the publication, is facially an ethical violation. And the fact that it involved a series of public and private lies, which he has never acknowledged, goes to the issue of trust in every subsequent case.

Money

Here I can’t say what ethical rule Wilcox may have broken. Academia is a game that runs on trust, and in his financial dealings Wilcox has not been forthcoming. There is money flowing through his work, but the source and purpose that money is not disclosed when the work is published. For example, in the NYT piece Wilcox is identified only as a professor at the University of Virginia, even though the research reported there was published by the Institute for Family Studies. His faculty position, and tenure, are signals of his trustworthiness, which he uses to bolster the reputation of his partisan efforts.

The Institute for Family Studies is a non-profit organization that Wilcox created in 2009, originally called the Ridge Foundation. For the first four years the tax filings list him as the president, then director. Since 2013, when it changed its name to IFS, he has been listed as a senior fellow. Through 2017, the organization paid him more than $330,000, and he was the highest paid person. The funders are right-wing foundations.

Most academics want people to know about their grants and the support for their research. On his CV at the University of Virginia, however, Wilcox does not list the Institute for Family Studies in the “Employment” section, or include it among the grants he has received. Even though it is an organization he created and built up, so far grossing almost $3 million in total revenue. It is only mentioned in a section titled “Education Honors and Awards,” where he lists himself as a “Senior Fellow, Institute for Family Studies.” An education honor and award he gave himself, apparently.

He also doesn’t list his position on the Marco Rubio campaign’s Marriage & Family Advisory Board, where he was among those who “understand” that “Windsor and Obergefell are only the most recent example of our failure as a society to understand what marriage is and why it matters”

Wilcox uses his academic position to support and legitimize his partisan efforts, and his partisan work to produce work under his academic title (of course IFS says it’s nonpartisan but that’s meaningless). If he kept them really separate that would be one thing — we don’t need to know what church academics belong to or what campaigns they support, except as required by law — but if he’s going to blend them together I think he incurs an ethical disclosure obligation.

Wilcox isn’t the only person to scrub Withserspoon from his academic record — which is funny because the Witherspoon Institute is housed at Princeton University (where Wilcox got his PhD). And the fact of removing Witherspoon from a CV was used to discredit a different anti-marriage-equality academic expert, Joseph Price at Brigham Young, in the Michigan trial that led to the Obergefell decision, because it made it seem he was trying to hide his political motivations in testifying against marriage equality. Here is the exchange:

price-lie

Court proceedings are useful for bringing out certain principles. In this case I think they help illustrate my point: If Brad Wilcox wants people to trust his motivations, he should disclose the sources of support for his work.

Survey says 23% of Whites think Whites are more intelligent than Blacks

In response to a request from New York Times reporter Amy Harmon, I used the General Social Survey (GSS) to address the question: “How Many Whites think Whites are more intelligent than Blacks?”

She made the request as part of her research for this story about how White supremacists are selectively manipulating genetics research, under the banner of “race realism,” to spread their ideas. This analysis didn’t end up in her story, but I put the tables and a brief write-up, with the code, here: https://osf.io/xt4j8/.

GSS asks about both Whites and Blacks: “Do people in these groups tend to be unintelligent or tend to be intelligent?” The responses were coded on a seven-point scale from “unintelligent” to “intelligent.” Without asking people to make a comparison, then, the survey allows us to identify people who rate White intelligence higher than Black intelligence.

For a contemporary estimate, I pooled three surveys (2012, 2014, and 2016). You can see how Whites rated the intelligence of Blacks and Whites in this table. Cells on the diagonal show Whites who rated Blacks and Whites equally. Cells below the diagonal show the percentages of Whites who rated White intelligence higher.

gssracismt1

The table shows that 23 percent of Whites assess the intelligence of Whites as greater than the intelligence of Blacks, according to the General Social Survey, compared with 8 percent who said the reverse. This 23 percent is down from more than 50 percent in 1990, but only a few points lower than it was a decade ago. The assessment that Whites are more intelligent than Blacks is more common among male, older, less formally educated, and conservative Whites, and (in multivariate models only) among Democrats compared to Republicans. Here are the marginal results from a linear regression model predicting whether Whites think Whites are more intelligent than Blacks.

gssracismf2

This is just one slice of racist beliefs as told to survey takers. In a previous analysis, Sean McElwee and I showed that the tendency of Whites to describe Blacks as violent and lazy was more common among Trump supporters, and Republicans generally, but a substantial minority of Democrats expressed those views as well. Racism, in its structural as well as interpersonal forms, is a lot bigger and more complicated than expressed beliefs on a survey, but I think it’s useful to analyze patterns like this as well.

Breaking: Matt Richtel book homepage bogus statistic removed

For at least three years, the website for New York Times reporter Matt Richtel’s book, A Deadly Wandering, about the dangers of texting and driving, has prominently featured a bogus internet meme statistic claiming that 11 teens per die from texting and driving accidents every day. I first debunked it in 2014, by simply pointing out that not even 11 teens die per day from all auto accidents regardless of cause.

I wrote about it again here. I also complained that Richtel had a financial interest in hyping teen texting deaths, and that it was unreasonable to say traffic fatalities were “soaring at a rate not seen in 50 years,” when in fact fatalities were almost at a 50-year low (down more than 60% from 1966, on a per capita basis, and still below the pre-recession levels).

I emailed Richtel, as well as the publisher. I tweeted. All to no avail — until sometime between last September (the last archived copy at the Wayback Machine) and today, when I saw they had finally removed the bogus statistic. Here’s the change:

richtel fixed

The footnote stayed the same, which is funny because it’s not a “statistic” anymore (it never was on the IIHSFF site).

Anyway, because I complained so much it’s important to acknowledge the change.

Meanwhile, while Richtel and his publisher were taking three years to do 10 minutes work to correct an egregious factual error, the meme was still going around. I happened to see it today as I was reading an editorial in the Moscow-Pullman (Idaho) Daily News, in support of our lawsuit against Trump (long story), when I saw this letter:

Letter: Texting while driving is more lethal than school shootings
May 29, 2018

Kudos to the Daily News Editorial Board for having the courage to state (“Our View: Gun reform alone can’t prevent mass killings,” May 23) “it is not the guns killing people, it is the people pulling the trigger …” It sounds like something the NRA would say. And the real problem facing us is ” how to prevent weapons from getting into the wrong hands ” As a longtime NRA member I support all rational steps taken to do exactly that.

Blaming the NRA or gun manufacturers for school shooting deaths is akin to blaming Facebook and/or Apple iPhones and/or Ford Motor Company for teen texting-while-driving deaths, which some reports say cause an average of 11 teen deaths in America every day. It’s not Facebook or the cellphone or the automobile maker that runs that car through the red light or up a tree. It’s the distracted person behind the wheel. Let’s see what kind of reaction we get when we try to separate those young people from their cellphones for their own safety and that of those in the car with them. Mom and dad, have at it.

Texting while driving is vastly more lethal to our teens than school shootings.

Bill Tozer, Moscow

Bogus statistical memes have consequences.

See all the texting posts under this tag.

Abortion is not a holocaust, and feminism is not about convenience

a photo of a cute pig next to a 16-cell human embryo .
Pig (left) and human.

Quick, disorganized comment on abortion.

New York Times columnist Ross Douthat, who opposes abortion rights, recently wrote in defense of the Kevin Williamson, fired from the Atlantic, for saying this, before he was hired:

Someone challenged me about my views on abortion, saying, “If you really thought it was a crime you would support things like life in prison, no parole, for treating it as a homicide.” And I do support that. In fact, as I wrote, what I have in mind is hanging.

Douthat thinks feminists are just as extreme as this, but even worse because they’re on the wrong side (the side in favor of the baby holocaust).

Douthat is concerned that abortion is “justified with the hazy theology of individualism.” When he says that what he’s insulting is feminism. He’s mocking us for being stupid (hazy) atheists who don’t realize secularism is just another theology (like Chris Smith does). And “individualism” refers to the idea that women have rights. Privilege is congratulating yourself for exposing oppressed people’s struggle for liberation as actually being about their individual self-gratification.

In claiming to make a moral argument, he pits this claim to women’s individualistic convenience against the holocaust:

the distinctive and sometimes awful burdens that pregnancy imposes on women have become an excuse to build a grotesque legal regime in which the most vulnerable human beings can be vacuumed out or dismembered, killed for reasons of eugenics or convenience or any reason at all.

There are no men, no patriarchy, in this telling, and that’s telling. It is important to say, which Douthat won’t, that abortion rights are women’s rights, that women’s rights are not about some decadent “individual” rights but about systemic group oppression perpetrated over millennia, especially by religion (especially by Douthat’s religion, Catholicism).

Douthat wants to take the abortion debate to the moral plane of “the killing of millions of innocents” (his phrase) versus feminist selfish self-indulgence. He is egging on his fellow anti-feminists, pushing them to take this extremist position while decrying the extremism of feminists. Organized anti-feminism doesn’t want to say abortion is really really murder because then women will turn against them, because women aren’t idiots. The mainstream abortion rights movement doesn’t want to say fetuses are human because it makes abortion seem worse, plus for early-term pregnancies it’s really not true. Still, we should argue about abortion as if it’s a decision that matters, not only as if it’s the restriction of the right to make that decision that matters. Unfortunately, Roe v. Wade was not decided on the principle that women can take a fetal life when it’s inside their own body, but on the principle of respecting women’s privacy rights to make personal decisions. This makes it harder to have the real feminist argument. I’m with Douthat that we should have a real moral argument, which he in his sneering at “individualism” actually refuses to engage.

Only religion can say all fetuses are instantly human; any scientific understanding exposes this incontrovertibly as just crazy talk. But abortion rights don’t depend on fetuses not being human at all. If you want to take the argument off the religious turf, you have to acknowledge that there is no moral instant when a fetus becomes human — science can’t locate that transformation more precisely than sometime between conception and birth. For that matter, there is no moral bright line between human and animal as far as suffering and death, that separates a human from a chimpanzee from a pig from a dog. (Many of us are, after all, not fully human ourselves, but part homo neanderthalensis.) There is moralizing, but not morality, in approving the grotesquely cruel slaughter of billions of sentient animals for “convenience or any reason at all,” while labeling women who abort sixteen-cell fetuses as murderers.

Ending life is a serious moral decision, of the kind Douthat and others are comfortable letting men take in many ways, in wars, and corporate decisions, and state policies, and slaughterhouses. Abortion rights mean women deserve that responsibility, too. Abortion rights don’t rest on the inconsequentialness of the decision but on the humanity of women. There is no reason to shy away from that. Catharine MacKinnon, who is aging well on this, wrote in 1983:

My stance is that the abortion choice must be legally available and must be women’s, but not because the fetus is not a form of life. In the usual argument, the abortion decision is made contingent on whether the fetus is a form of life. I cannot follow that. Why should women not make life or death decisions?

That’s my attempt to defend abortion rights without relying on euphemism and evasion or the hazy theology of individualism.

Kids these days really know how to throw off a narrative on gender and families

The most important thing is that Stephanie Coontz has written another very good, and very important, New York Times essay. It describes a “slippage” in support for gender equality among young people these days, and warns that without improved work-family policies, progress toward egalitarian family arrangements may be imperiled. The piece also announced a package of short papers in a Council on Contemporary Families symposium, which provided the supporting evidence. (This kind of work, incidentally, is why I’m a proud member, and board member, of CCF.) If you haven’t read Stephanie’s essay, I recommend reading it now, and if you forget to come back here that’s fine.

Anyway, an unfortunate confluence of events created some chaos after the piece came out. First, the NYTimes wrote a headline, “Do Millennial Men Want Stay-at-Home Wives?”, that emphasized only one piece of the evidence. It referred to a figure showing General Social Survey data on the trend in very young men and women (ages 18-25) disagreeing with the statement, “It is much better for everyone involved if the man is the achiever outside the home and the woman takes care of the home and family.” (That is the classic FEFAM question, to GSS fans, asked since 1977. I’ve used it myself, and it figures in the key analysis of stalled gender progress by Cotter, Hermsen, and Vanneman.)

This was the figure, showing a marked divergence between men and women:

scfefam

The second event was the unfortunate timing: between the time Stephanie wrote the piece and the day it appeared, the General Social Survey released its 2016 round of data (it’s been running every two years). The survey is fickle. It’s very good quality and has many great demographic and attitude items running for 40 years, making it the best source for analyzing many social trends. But it’s not that big. In 2014 it had 2,867 respondents, of whom only 141 were ages 18-25. So it wasn’t surprising that the 2016 numbers were different from the 2014 numbers, but the scale of the blip was shocking, as reported independently by Emily Beam and Neal Caren. Here is what the updated trend looks like:

scfefam-16

Yikes. As exciting as it is for survey analysts to see such a wild swing, it’s not what anyone wants to see the day after their NYTimes piece drops. We can’t know yet what happened, but on further inspection, at least we can say that it’s not limited to the youngest group and its small sample. Among men ages 26-54, the percentage disagreement with FEFAM also jumped, from 73.7 to 78.3 (women 26-54 were up one point).* In fact, 2014 may have been as big a blip as 2016, you just wouldn’t notice because it continued the trend.

Anyway, back for a minute to the main point. Joanna Pepin, who co-wrote one of the symposium pieces with David Cotter (and who is also an advisee of mine), has pointed out that the divergence between men and women is secondary to the main trend, which is the reversal of progress on FEFAM for both men and women since the mid-1990s. They used the Monitoring the Future survey, and find a big drop in FEFAM disagreement among high school seniors — regardless of gender. Here’s their key figure, with the FEFAM trend shown in green (their full paper is available on SocArXiv):

figure-3

So that is the most important news: a big reversal among young adults on attitudes toward homemaker-breadwinner family arrangements.

Now, If you’ve now read Stephanie’s piece, and Joanna’s, and you’re back, here’s a little more on the minor kerfuffle that arose over the new data.

When to call a trend a trend

I don’t think Stephanie was wrong to use the GSS trend, although it might have been better to widen the age range, or pool the data over several years. The bigger problem was the headline selling that divergence as the main story, which it wasn’t in the grand scheme. (The fact that so many jumped on the story shows how good they are at headline writing.) But even that wasn’t really wrong, given the information they had. The Op-Ed staff checked the facts, and the facts were the facts. Until yesterday.

To confirm this, I ran some tests on the gender divergence in the data they used (I started with code that Neal shared; it’s at the bottom). I started at 1994, the last peak of the trend, to look for the divergence after that, which is what Stephanie referred to. First, here is what you get if you run a logistic model that controls for race/ethnicity and individual years of age (two things that changed over the last two decades), and enters the years individually in an interaction with gender (those are 95% confidence intervals).

fefam-yr.JPG

If you stop at 2014, it looks like men are pulling away from women (in the direction of “traditional” attitudes), but it’s not definitive. And obviously 2016 is an issue. To help with the small samples, I ran a linear test of the year trend, that is, entering year as a continuous variable instead of individual years. I did it ended at 2014 and then through 2016. Here are the results:

fefam-log

In the 1994-2014 model, the Male*Year interaction is statistically significant at conventional levels, which in my opinion means it’s legit to say men were pulling away from women. Of course 2016 ruined that; if you had 2016 and didn’t use it, that would be really wrong. There are other ways to slice it, but at some point we have to call a trend a trend and deal with it. It was a reasonable decision. Of course, new data always comes along (until the last trend of all, whatever that is), no trend lasts forever; it’s just a shame when it comes along the next day. In addition, though I’m not showing it because it’s boring, if you didn’t disaggregate the trends by gender, you would also see a significant decline in FEFAM disagreement after 1994, which gets to Joanna’s point.

Anyway, score one for sociology Twitter. People came up with the data, shared code and results, and discussed interpretations. It got back to Stephanie and the NYTimes editors, and within a day they added an addendum to the original piece:

Update: After this article was posted, 2016 data from the General Social Survey became available, adding some nuance to this analysis. The latest numbers show a rebound in young men’s disagreement with the claim that male-breadwinner families are superior. The trend still confirms a rise in traditionalism among high school seniors and 18-to-25-year-olds, but the new data shows that this rise is no longer driven mainly by young men, as it was in the General Social Survey results from 1994 through 2014.

This is pretty much how it’s supposed to work. As the Car Guys used to say, if you never stall you’re wearing out your clutch (sorry, Millennials). If you never overshoot an analysis of trends you’re probably waiting too long to get the information out.

* Note: I originally accidentally described this as “over 25.” 


You can get the data here. Here’s the STATA code:

/* recodes */

recode fefam (1/2=0) (3/4=1), gen(fefam_d)
gen young=age>=18&age<=25
recode sex (2=0), gen(male)

/* the model for the figure */

logit fefam_d i.year##i.male i.age i.race if year>=1994 & young==1 [pweight = wtssall]
margins year##male
marginsplot

/* the models for the table */

logit fefam_d c.year##i.male i.age i.race if year>=1994 & young==1 & year<=2014 [pweight = wtssall]
logit fefam_d c.year##i.male i.age i.race if year>=1994 & young==1 [pweight = wtssall]

More bad reporting on texting and driving, and new data

The New York Times‘ problem of misrepresenting the relationship between phones and traffic fatalities, which seems to have begun with Matt Richtel, has just gotten worse.

Richtel sells books on the fear of texting and driving (which, of course, is dangerous), and the website for his book still — despite my repeated entreaties, public and private — leads with the bad, false, unsourced Internet meme, that “the texting-while-driving epidemic continues to claim 11 teen lives per day.” (As a reporter, how could you sleep one night with that BS up under your name? Mind boggling.)

Anyway, the new entrant is David Leohnardt. At the heavy risk of jeopardizing future opportunities to publish on the Times op-ed page, I tweeted that his recent column included “one of the dumbest things I’ve ever read in the NYTimes.” Washington Post WonkBlog writer Jeff Guo pointed out Leonardt’s column, which claimed that, with regard to the recent spike in traffic deaths, “The only plausible cause is the texting, calling, watching, and posting that people now do while operating a large piece of machinery.” The column contained not a piece of evidence to support that claim (though there were some awful anecdotes), which is why I said it was dumb.

Which is too bad. But even though the spike in traffic deaths is concerning, reporting should not be wrong.

Early estimates from the National Safety Council (which uses a different method than the Federal NHTSA) show a 6% increase in traffic fatalities for 2016. Leonhardt, working really hard to make that absolutely as alarming as possible, produced this graph, showing percent change in fatalities over successive two year periods going back to 1980:

C6aFWA5U4AEzK8I

Because it’s hard to add up the pluses and minuses in your head, It would be really easy — really really easy — to look at Leonhardt’s chart and think fatalities are higher now than they were in 1980. But rather than pointing out that fatalities per person have fallen by half since 1980, he instead writes, “It’s the first significant rise in a half century,” which would be true except for the significant rise in every single decade of the last half century.

This is a lot like when Richtel described the 2015 rise as, “soaring at a rate not seen in 50 years.” Not that the rate was not seen in 50 years, of course, just that the soaring of the rate hadn’t been (or so the NYT Science Desk told me when I complained).

Adding 6% to the NHTSA numbers for 2015, I get the follow graph, showing the trends in deaths per person in the population, and deaths per mile traveled, as changes since 1970. (The deaths per mile haven’t been released for the whole year yet; click to enlarge.)

PercentWhite

That is a troubling spike, which takes us all the way back to 2009 fatality rates. We should make the roads safer, by using them less and using them more safely. But come on, NYTimes.

Read the whole, completely aggravating series, under the texting tag.

Is the New York Times trapped in an economics echo chamber?

Ask a stupid question.

When Justin Wolfers wrote about the dominance of economists in the pages of the New York Times, he concluded, “our popularity reflects the discerning tastes of our audience in the marketplace of ideas.” I discussed the evidence for that in this post, which focused on the particular organizational features of the NYT. At the time it didn’t occur to me that his data — relying on uses of “economist” in the paper — would be corrupted by false attributions. So this is a small data story and a larger point.

The small data story comes from a personal reflection by Dionne Searcey, who wrote about work-family conflict in her new post as West Africa Bureau Chief for the NYT. It was a perfectly reasonable piece, except for one thing:

Much has been written about work-life balance, about women getting ahead in their careers and trying to have it all. I often find that if you scratch beneath the surface of many successful working moms, they have husbands who work from home or have flexible schedules and possibly a trust fund. Or in many cases, you find a mom who does more than her fair share at home — or at least feels as if she does. Economists have a name for it, “the second shift.”

Wait, “economists”? The Second Shift is a classic work of sociology by Arlie Hochschild and Anne Machung first published in 1989 and revised twice. Why “economists”? The (very good) article that Searcey linked to was called, “The Second Shift: Men Do More at Home, but Not as Much as They Think,” written by journalist Claire Cain Miller, focusing principally on the research of several sociologists, led by Jill Yavorsky (a sociology PhD candidate at Ohio State with whom I have collaborated). There are no economists cited or quoted in the story.

The small data story is that this mention of economists will go into Wolfers’ count of the influence of economists in the marketplace of ideas, but it’s a false positive — it’s the influence of sociologists being falsely attributed to economists.

But why would Searcey say “economists”? The answer lies in the organizational culture of the NYT. Here’s why.

Here are my two tweets on the piece:

Considerately, Searcey replied:

How odd. When I pointed out again that the story she linked to was about sociologists talking about the second shift, she didn’t reply.

I recently wrote that economists don’t cite sociologists’ work as much as sociologists cite economists even when the two groups are working on the same questions with obvious implications for both. What about the second shift? A JSTOR search reveals 473 cases of “second shift” and “housework” in journals identified as sociology by the database. The same search in the realm of economics produces just 35 mentions (no fewer than 6 of which were written by sociologists).

So, why did Searcey think she “was referring to how economists talk about the second shift”? My only explanation is that it’s because the piece was published in the NYT section The Upshot. As I wrote in my Contexts post, Upshot

is edited by David Leonhardt, who was an economics columnist before he was promoted to Washington bureau chief in 2011. That promotion was a dramatic move, elevating an economics writer who hadn’t been a Washington political reporter. Upshot is a “data journalism” hub, which often (but not always) implies an economic focus. (On the opinion pages, economist Paul Krugman writes a column twice a week, and Joseph Stiglitz moderated a long series on inequality.) This can’t be the whole story, but in broad strokes it’s fair to say the paper as an organization moved in the direction of business and economics.

Upshot is, of course, where Wolfers was writing in praise of the idea-market power of economists. Is this just the free market of ideas allowing the most persuasive to rise to the top? Searcey’s errors suggests that it is not. Rather, the organizational status of economics has corrupted her perceptions so that if something appears there she simply believes it reflects economics (and no editor notices).

Incidentally David Leonhardt (whom I’ve written about several times) has been promoted to Op-Ed page columnist and associate editorial page editor.