RETIREMENT RESEARCH July 2018, Number 18-14 IS THE DROP IN FERTILITY TEMPORARY OR PERMANENT? By Alicia H. Munnell, Anqi Chen, and Geoffrey T. Sanzenbacher* Introduction The U.S. fertility rate has declined sharply since the order to examine this issue further, the second section Great Recession. The question is whether this decline explores the extent to which the decline in fertility is a temporary response to the economic downturn can be explained by the Great Recession and assesses or a drift to the lower levels seen in some other large the prospects of a cyclical rebound. Given that the developed countries. The future of the fertility rate is case for a cyclical rebound seems difficult to make, important in that it determines the age structure of the third section turns to structural factors that affect the population, the ratio of workers to retirees and, fertility – race/ethnicity, education, religion, and the hence, the finances of the Social Security system opportunity cost for women as measured by the ratio (which operates largely on a pay-as-you-go basis). of female-to-male wages. Estimating – across states – According to the 2018 Social Security Trustees Report, the relationship between these basic factors and each a total fertility rate of 1.8 children per woman instead state’s total fertility rate in 2001 and 2016 suggests of 2.0 would increase the program’s 75-year deficit by that these structural factors can explain much of the 0.41 percent of taxable payrolls or a present value of decline. The final section concludes that the bulk of almost $2 trillion. the evidence suggests that the total fertility rate is not This brief summarizes work to date that exploits going to bounce back to pre-recession levels, which state-level variation in the fertility rate to determine – in the absence of more immigration – would make the extent to which fertility rates are a response to the nation’s key social programs more expensive go- the Great Recession as opposed to underlying demo- ing forward. graphic factors.1 The discussion proceeds as follows. The first section provides a primer on the various measures Trends in Fertility of fertility and documents trends in fertility rates. At first blush, the various measures tell a mixed story of Fertility is measured in a number of ways, and cur- whether lower fertility is temporary or permanent. In rently the various measures do not all tell the same story. * Alicia H. Munnell is director of the Center for Retirement Research at Boston College (CRR) and the Peter F. Drucker Professor of Management Sciences at Boston College’s Carroll School of Management. Anqi Chen is assistant director of savings research at the CRR. Geoffrey T. Sanzenbacher is associate director for research at the CRR. The authors wish to thank Sam Preston, Alison Gemmill, and Josh Goldstein for very helpful comments. This brief was made possible through support from the Peter G. Peterson Foundation and the Ford Foundation. The statements made and views expressed are solely the responsibility of the authors. 2 Center for Retirement Research General Fertility Rate throughout her reproductive years if she were to experience, at each point in her life, the birth rates The National Center for Health Statistics recently currently observed at that age. While the TFR does reported that, in 2017, the general fertility rate had de- not measure actual lifetime fertility, it does provide clined to a record low of 60.2 births per 1,000 women a current estimate. It also has the advantage of not of childbearing age (see Figure 1). This measure has being affected by the age structure of the population. grabbed the attention of the press and politicians. Currently, the TFR is at its second lowest point in The question is the extent to which this pattern, in U.S. history (see Figure 2). the wake of the Great Recession, reflects a decision by younger women to postpone having children rather than to have fewer children. If, indeed, women are Figure 2. Total Fertility Rate (Hypothetical simply delaying, the birth rate should pick up. The Lifetime Births per Woman) 1915-2017 measure of real interest is how many children the 4 average woman will have over the entire span of her 1957 3.68 childbearing years. 3 Figure 1. General Fertility Rate (Births per 2 Thousand Women Ages 15-49), 1915-2017 1976 2017 150 1.74 1.76 1 1957 122.9 100 0 1915 1935 1955 1975 1995 2015 1976 65.0 2017 60.2 Sources: NVSR (2016-2017); and HFD (1915-2015). 50 Completed Fertility Rate 0 While the TFR is a convenient way to produce current 1915 1935 1955 1975 1995 2015 estimates of how many children a woman will have over her lifetime, the only way to have an accurate Sources: Centers for Disease Control & Prevention (CDC), U.S. National Vital Statistics Reports (NVSR) (2016-2017); measure of fertility is to identify the number of births Max Planck Institute for Demographic Research and Vienna women have actually experienced by the end of their Institute of Demography, Human Fertility Database (HFD) childbearing years. The completed fertility rate is one (1915-2015). such measure and, contrary to the TFR, suggests no reason for concern at all. This number has actually been inching up a bit, with the most recent cohort of Total Fertility Rate (TFR) 49-year-olds having averaged about 2.1 children over their lifetime (see Figure 3 on the next page). This One measure of lifetime fertility is the Total Fertility measure, of course, is backward looking and provides Rate (TFR). The TFR for a given year is the average limited insights on the fertility plans of younger number of children that would be born to a woman women. Issue in Brief 3 Figure 3. Completed Fertility Rate, 1960-2016 if the expectations of today’s 20-24-year-olds follow the historic pattern, they would be expected to have fewer 4 than two children over their lifetime. 1983 The picture that emerges from the discussion of 3.25 the various measures of fertility is hard to decipher. 3 On the one hand, the general fertility rate – births per 2016 thousand women – is at an all-time low, and the TFR 2.10 – births to a hypothetical woman over her lifetime – is 2 at its second lowest level. On the other hand, com- 2003 pleted births remain above 2.0 as do expectations of 1.97 lifetime births. The question, thus, is whether the 1 current low levels of general and total fertility are simply a cyclical response to the Great Recession or a symptom of structural changes. 0 1960 1970 1980 1990 2000 2010 Note: Completed fertility is measured for women who have The Cyclical Story reached age 49 in that calendar year. Sources: HFD (1940-2015); and NVSR (2016). What can the business cycle explain? This analysis relies on the TFR measure of fertility, which is gener- ally used by demographers and is not affected by dif- Fertility Expectations ferences in the age structure across states. The first step in the cyclical analysis is a scatter plot that relates One final measure used to evaluate fertility trends is the change in TFR to the change in the unemploy- fertility expectations. The National Survey of Family ment rate during the Great Recession and subsequent Growth shows that birth expectations for women ages expansion. Each dot in Figure 5 represents one of 20-24 have declined by 0.17 children since the turn of the 50 states plus D.C. The red dots show how much the century (see Figure 4). Moreover, demographers each state’s TFR declined in relation to how much its report that women generally over-predict how many children they will have by around 0.3 children.2 Thus, Figure 5. Relationship Between Change in TFR and Change in Unemployment Rate During Great Figure 4. Total Births Expected among Women Recession and Subsequent Expansion, by State Ages 20-24, Various Years 0.50 2007 -2009 recession 3 Average number of additional children expected 2010 -2016 expansion Average number of children ever born 2.32 2.42 2.40 2.44 2.40 0.25 2.32 2.27 Change in TFR y = -0.03x + 0.03 2 1.34 1.50 1.48 0.00 1.77 1.92 1.90 1.85 1 -0.25 0.98 0.92 0.92 0.55 0.52 0.50 0.42 0 -0.50 -10- -10 50 -5 0 51 5 0 10 Change in unemployment Note: Recession years are defined as the years between the Note: Before 2002, only married women were surveyed. peak and trough of real GDP for each state. Sources: Centers for Disease Control & Prevention, National Sources: Authors’ calculations from U.S. Bureau of Labor Survey of Family Growth (NSFG) (various years). Statistics (BLS) (2005-2016); and CDC, Vital Statistics Natality Birth Data (VSNBD) (2005-2016). 4 Center for Retirement Research unemployment rate increased during the recession. expansions and recessions from 1976-2016.3 It turns The black dots represent the relationship during the out that the TFR is generally very cyclical – it goes subsequent expansion. down in recessions (the lines are generally in the First consider the recession. The TFR declined lower right quadrant) and up in expansions (the lines for all states during the recession, since all the red are generally in the upper left quadrant), with some dots fall in the lower-right quadrant. And the size of anomalous results for the relatively mild cycle in the downturn and the change in the state’s TFR are the early 1990s. However, the pattern for the recent correlated. The correlation was a statistically signifi- recovery is very different; fertility has declined as the cant -0.03 – that is, when the unemployment rate economy has recovered. increased by one-percentage point on average the TFR While it is very clear that the TFR has not re- declined by about 0.03 kids. bounded as in previous expansions, the reasons for Now consider the recovery. One might expect its persistent decline are not clear. The two pos- that, once the economy recovered, fertility would also sible stories are either that the taste for children has recover and fall along the dotted-red line. But this changed or that women are simply postponing having did not happen. Instead, during the recovery all the children. black dots are once again below zero showing that The age at which women have their first child has the recovery was accompanied by a further decline in increased markedly, and increases in the age of child- the TFR. It is also interesting to note that during the bearing can artificially depress the TFR.4 It is pos- expansion, no apparent relationship exists between sible, however, to construct a “tempo-adjusted” TFR the change in unemployment in each state and the that accounts for the rising childbearing age.5 The change in the state’s TFR. results show that while this adjusted-TFR is higher It could be that in the United States, the TFR than the conventional TFR, it is also decreasing, sug- generally does not increase during recoveries – after gesting that the taste for children may be changing all, much of the literature on this topic is based on (see Figure 7). international evidence. To assess this notion, Fig- ure 6 shows the historical relationship between the U.S. economy and the TFR in the 50 states over the Figure 7. TFR and Tempo-Adjusted TFR, 1976-2016 2.5 TFR Figure 6. Pattern of Change in TFR Across States Adjusted TFR 2.3 During Expansions and Recessions, 1976-2016 0.50 2.1 0.25 Change in TFR 1.9 0.00 1.7 -0.25 -0.50 1.5 -10 -5 0 5 10 1976 1986 1996 2006 2016 Change in unemployment rate 1976-1980 expansion 1980-1982 recession Sources: Authors’ calculations using the HFD (1976-2015); 1982-1990 expansion 1990-1991 recession 1991-2000 expansion 2001 recession and NVSR (2016). 2002-2007 expansion 2007-2009 recession 2009-2016 expansion Note: Recession years are defined as the years between the The conclusion that emerges from this section is peak and trough of real GDP for each state. that while, historically, the TFR appears to have been Sources: Authors’ calculations from BLS (1976-2016); and pro-cyclical – turning down when the economy falters CDC, VSNBD (1976-2016). and increasing when it recovers – that relationship Issue in Brief 5 has not held in the most recent recovery when the Figure 8. TFR By Ethnicity, 1976-2016 TFR has continued to decline. Moreover, even a TFR measure that adjusts for the delay in childbearing 3.0 All shows fertility heading lower.6 White Black 2.5 Hispanic The Structural Story 2.0 If the case for a cyclical rebound is difficult to make, then the fundamental factors that determine the TFR have likely changed. The empirical approach is to 1.5 look across states in 2001 and estimate the relation- ship between the most basic correlates of fertility and 1.0 then to re-estimate that relationship in 2016 in an 1976 1986 1996 2006 2016 attempt to explain the decline in the TFR from 2.03 to 1.82 over the 2001-2016 period. Source: Authors’ calculations from NVSR(1976-2016). Correlates of Fertility Education. Women with more education tradition- ally have fewer children. The direction of causation Researchers have identified many factors that could is unclear. Women with a taste for children might affect fertility such as the political climate, social choose not to pursue educational and employment programs, or abortion legislation, but these consid- opportunities or women with a taste for a career could erations are almost certainly derivative of the popu- decide not to have as many children. In any event, lation’s underlying characteristics – race/ethnicity, near the end of their childbearing years (ages 40-44), education, and religion – that establish the taste for women with higher levels of educational attainment children.7 In addition, the nature of the work avail- have averaged fewer children than their less-educated able to women reflects the opportunity costs of having counterparts (see Figure 9). This pattern is important children. Therefore, the following discussion focuses on four factors: race/ethnicity, education, religion, and the ratio of female-to-male wages. Figure 9. Mean Number of Children Ever Born to Race/Ethnicity. Traditionally U.S. fertility has var- Women Ages 40-44, by Education, 1976-2016 ied by race and ethnicity, with Hispanics having the 4 highest rates, followed by blacks, and then whites (see High school or less Figure 8). By 2001, however, the TFR for blacks had Some college dropped noticeably to the national average. In 2001, College or more fertility among Hispanics was significantly higher 3 than that of whites, but between 2001 and 2016, it declined sharply and seems to be converging to the white fertility rate.8 This convergence has coincided 2 with the decline in immigration since the Great Recession, largely a result of the reversal of unauthor- ized immigration.9 Absent a surge in immigration, the recent decline in Hispanic fertility could persist 1 1976 1980 1983 1987 1992 1998 2004 2010 2016 since U.S.-born Hispanics have lower birth rates than those born in other countries. Source: Authors’ calculations from Current Population Sur- vey, Fertility Supplement (1976-2016). 6 Center for Retirement Research because the percentage of women with a college edu- Figure 10. Number of Children Ever Born for cation or more has increased dramatically in recent Women Ages 40-45, by Religious Affiliation, 2013- years. By 2016, more than 40 percent of women fell 2015 into this highly educated group, while those with a 3 high school education or less dropped sharply. This 2.6 shifting mix puts downward pressure on the TFR.10 2.2 Religion. An extensive literature explores the re- 2.0 2 lationship between religion and fertility in the United 1.6 1.5 States.11 Indeed, the most recent National Survey of Family Growth (which asks “What religion are you 1 now, if any?”) shows observable differences in fertility across different religions for women near the end of their childbearing years (see Figure 10). Those with 0 no religion have the lowest fertility rate. Female-to-Male Wage Ratio. While the previous three categories – race/ethnicity, education, and religion – affect women’s attitudes towards having children, the final factor attempts to get at the cost of Source: NSFG (2013-2015). children. The opportunity costs of having children are higher for women with better labor market op- tions. A high female-to-male wage ratio means that women give up a substantial amount if they take off Regression Results time to have children. In 2001, this ratio varied from The empirical approach is to look across states to see a high of 86 percent in Washington, DC to a low of if the factors identified above – that have nothing to about 50 percent in Wyoming. do with the Great Recession – can explain the decline In short, the variables expected to explain fertility in the nation’s TFR between 2001 and 2016.12 The across states are: women’s relative earnings in the results are as expected (see Figure 11). States with state, the percentage of women who are Hispanic or a higher Hispanic population have a higher TFR, black, the percentage of women with a college degree, although the effect has virtually disappeared in recent and the percentage of the population that does not years. And states with more college educated women, belong to a religious congregation. a higher share of non-religious people, and a higher female-to-male wage ratio have a lower TFR. Figure 11. Estimated Effects of Select State-level Characteristics on TFR for 2001-2003 and 2014-2016 Share Hispanic 2001-2003 2014-2016 Share Black Share college or more Share non-church members Female-male wage ratio -0.02 0.00 0.02 Note: Solid bars indicate statistically significant at the 1-percent level. Sources: Authors’ calculations from HFD (1976-2015); NVSR (2016); U.S. Census Bureau, American Community Survey (ACS) (2001-2003 and 2014-2016); and U.S. Religion Census, Religious Congregations and Membership Study (RCMS) (2000 and 2010). Issue in Brief 7 The question is the extent to which the regression Conclusion results can explain the decline in fertility over the pe- riod 2001-2016. The tool for answering this question The question is whether the decline in U.S. fertility is an Oaxaca-Blinder decomposition analysis, which since the Great Recession is a temporary response to proceeds in two stages. The first decomposition holds the economic downturn or a slow drift to the levels constant the effects and predicts what would happen seen in some other large developed countries. if only the proportions of the population changed The analysis of the relationship between the between 2001 and 2016. These results, shown in the economy and the TFR confirms that the performance gray bars, indicate that, all else equal, the increase in of fertility in the current expansion is anomalous. Hispanic population would have actually increased While historically the TFR appears to have been pro- the TFR by 0.01, whereas the increases in college cyclical – turning down when the economy falters and educated women and the female-to-male wage ratio increasing when it recovers – that relationship has not would have depressed the TFR by 0.07 and 0.04 re- held in the current recovery as the TFR has continued spectively (see Figure 12). The second decomposition to decline. Moreover, even an adjusted-TFR that ac- holds constant the population proportions and pre- counts for the trend toward women having children dicts what would happen if only the effects changed later is heading lower. Thus, the case for a cyclical between 2001 and 2016. The results, shown in red rebound seems difficult to make. bars, suggest that Hispanics having fewer children At the same time, the percentage of women who explains a drop of 0.10 in the TFR. Non-members of are Hispanic, the percentage of women with a college religious congregations are also having fewer children education, the percentage of the population unaffili- and this trend explains a 0.16 drop. Working in the ated with a religious congregation, and the female- other direction – although not statistically significant to-male wage ratio explain much of the variation in – is the female-to-male wage ratio. The sum of all the total fertility rates across states in both 2001 and these effects suggests that it is not necessary to appeal 2016. The decline in the fertility rate between 2001 to the Great Recession to explain the decline in U.S. and 2016, it appears, can be explained by Hispanics fertility in the 21st century. having fewer children, an increase in the number of women with a college degree, fewer births among those unaffiliated with a religious congregation, and Figure 12. Results from Oaxaca-Blinder an increase in the female-to-male wage ratio. One Decomposition might conclude that it is not necessary to appeal to 0.3 the Great Recession to explain the decline in U.S. 0.22 E ect of change in proportions fertility in the 21st century. 0.2 E ect of change in coe cients 0.1 0.01 0.0 0.00-0.02 -0.02 0.00 -0.1 -0.04 -0.07 -0.10 -0.2 -0.16 -0.19 -0.3 Total Share Share Share Share Female- change in Hispanic Black college non-ch urch male TFR or more members wage ratio Note: Solid bars indicate statistically significant at the 5-per- cent or 1-percent level. Sources: Authors’ calculations from ACS (2001-2003 and 2014-2016); and RCMS (2000 and 2010). 8 Center for Retirement Research Endnotes 1 Munnell, Chen, and Sanzenbacher (2019 forthcom- 8 Importantly, data from the National Survey of Fam- ing). ily Growth show that the difference in fertility between whites and Hispanics persists even after controlling 2 Morgan (2001) and Morgan and Rackin (2010) for education. suggest this over-prediction likely reflects changes in career opportunities, marital status, partner’s expecta- 9 Passel and Gonzalez-Barrera (2012). tions, and subfecundity. Gemmill (2018 forthcom- ing) examines the expectations and life trajectories of 10 Interestingly, schooling appears to have become permanently childless women and finds that about less closely associated with fertility in recent years, 44 percent of women who remain childless transition despite the fact that educational differentials in into not expecting children later in life. women’s earnings became much steeper (Blau 1998; and Goldin and Katz 2007). Recent surveys show that 3 The estimates are based on a fixed-effect equation young women with a college education expect to have relating the change in the unemployment rate (lagged more than two children just like those with less edu- one year) and the change in fertility, as well as their cation. Although they are currently behind in terms interactions. The equation also includes dummy of childbearing, they expect to catch up as they get variables for each state to control for unobservable older. Part of the explanation for more childbearing differences among states. among well-educated women may be that as childcare becomes more available, they can substitute paid help 4 The TFR will understate completed cohort fertil- for their own time in raising children. In addition, ity in years that women postpone childbearing and since employers want to keep valuable employees, overstate cohort fertility in years that women advance college-educated women could expect the least career childbearing. disruption from childbearing (Gustafsson et al. 1996; and Waldfogel 1997). 5 The estimates were based on methods from Bon- gaarts and Bongaarts and Feeney (2000) and Gold- 11 Early studies on variations in fertility across stein, Sobotka, and Jasilioniene (2009). religions focused on differences between Catholics and Protestants (Freedman, Whelpton, and Campbell 6 This pattern is consistent with findings in the 1959; Westoff and Ryder 1971; and Whelpton, Camp- literature. Orsal, Karaman, and Goldstein (2010) bell, and Patterson 1966). These studies attributed addressed this issue by examining the relationship the higher fertility rates among Catholics to doctrines between a TFR-adjusted measure to account for later prohibiting birth control as well as educational and childbearing and the unemployment rate and found income differences from immigrant Catholic popu- a statistically significant relationship, suggesting lations. Other religious groups with pro-natalist that unemployment not only leads to postponement doctrines also have higher fertility rates, most notably in childbearing but also to fewer children. Another Mormons and fundamentalist Protestants (Heaton study (Currie and Schwandt 2014) examined how the 1986; and Hout, Greeley, and Wilde 2001). McQuil- fertility of each cohort of women in each state related lian (2004) provides a framework on how religious to the unemployment rate experienced by that cohort identities can affect fertility. First, religions set moral at different ages. The results showed that women in codes and values about specific fertility-related behav- their early 20s are most affected by high unemploy- ior such as sexuality, gender roles, and the place of a ment rates and that the negative effects on fertility family in society. Second, religious groups enforce grow over time. conformity through social influence or sanctions. In the end, religion becomes akin to culture and consti- 7 For examples of factors identified in previous tutes an important aspect of individual identity. research, see Lesthaeghe and Neidert (2006) for the political climate, Moffitt (1999) for social programs, 12 To avoid stability concerns, the data were pooled and Klerman (1999) for abortion legislation. so that the first equation was based on 2001-2003 and the second on 2014-2016. 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