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Marriage and Union Formation in the United States: Recent Trends Across Racial Groups and Economic Backgrounds

Abstract

Family formation in the United States has changed dramatically: marriage has become less common, nonmarital cohabitation has become more common, and racial and economic inequalities in these experiences have increased. We provide insights into recent U.S. trends by presenting cohort estimates for people born between 1970 and 1997, who began forming unions between 1985 and 2015. Using Panel Study of Income Dynamics data, we find that typical ages at marriage and union formation increased faster across these recent cohorts than across cohorts born between 1940 and 1969. As fewer people married at young ages, more cohabited, but the substitution was incomplete. We project steep declines in the probability of ever marrying, declines that are larger among Black people than White people. We provide novel information on the intergenerational nature of family inequalities by measuring parental income, wealth, education, and occupational prestige. Marriage declines are particularly steep among people from low-income backgrounds. Black people are overrepresented in this low-income group because of discrimination and opportunity denial. However, marriage declines are larger among Black people than White people across parental incomes. Further, most racial differences in marriage occur among people from similar socioeconomic backgrounds. Family inequalities increasingly reflect both economic inequalities and broader racial inequalities generated by racist structures; in turn, family inequalities may prolong these other inequalities across generations.

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Data Availability

Data are available from the Panel Study of Income Dynamics: https://psidonline.isr.umich.edu/.

Notes

  1. The distal causes of this persistence are wide-ranging, including systemic racism, which shapes family-formation opportunities.

  2. Because data collection began in 1968, the PSID underrepresents recent immigrant populations.

  3. We should miss fewer cohabitations over time because cohabitation duration increased across recent cohorts (Lamidi et al. 2019; Mernitz 2018). Moreover, very short cohabitations may be less substantively interesting than longer-lasting unions (and they are not absent from our analysis, only underrepresented). No large-scale, nationally representative U.S. survey includes complete cohabitation histories as well as information on parental income and a large number of birth cohorts, as required for this study.

  4. We include two measures of parental wealth: net worth and home value. Net worth sums all financial assets, real assets, and home equity and then subtracts financial obligations. Unfortunately, many of our cohorts have few opportunities for their parental net worth to be observed during childhood because 1984 was the first year in which the PSID collected the information needed to calculate net worth. We thus supplement this measure of wealth with another: home values, about which the PSID has collected information since its inception in 1968. Substantively, housing wealth is the primary asset of most Americans. We set home values to 0 for people who do not own their home. We average parental net worth and (separately) home value across all childhood ages observed, ages 0–17. We code parental education into four categories (less than high school, high school, some college, and four years of college or more education) based on the highest education level completed by either parent observed over the course of childhood. We measure parental occupational prestige based on the maximum prestige score observed from either parent between respondent ages 0 and 17. We capture occupational prestige by linking PSID occupational categories to their prestige scores, following the procedure outlined in Bloome and Furey (2019).

  5. Union formation rarely occurs before age 15. We exclude one respondent based on this restriction.

  6. The first source of censoring is not problematic from an analytic perspective and the second is rare. The third could be problematic if attrition time relates to union-formation chances at that time (conditional on the model’s predictors). Discrete-time event-history models assume that attrition time is noninformative (Allison 2014).

  7. In discrete-time models, the hazard, h, and probability, p, are the same.

  8. \( {E}_{\upbeta_{g,r}}\left[{Y}_{jgr}\left|{X}_{jgr}\right.\right] \) is the conditional expectation of marrying by age 40 in gender group g and racial group r across individuals j. \( {E}_{\upbeta_{g,r}}\left[{Y}_{jg{r}^{\prime }}\left|{X}_{jg{r}^{\prime }}\right.\right] \) is the conditional expectation of marrying by age 40 in gender group g and racial group r′ across individuals j evaluated at the parameter vector βg,r. X contains socioeconomic indicators as well as other basic covariates discussed earlier, such as age, cohort, and their interactions.

  9. Comparing the 1940–1944 and 1964–1969 cohorts, Sweeney (2016:277) reported a 4.6-year increase using NSFG data. Likewise, we estimate a 4.8-year increase comparing the 1940 and 1969 cohorts using PSID data. The similarity between the NSFG and PSID estimates suggests that the PSID estimates are reliable, as does the similarity between our model-based estimates and our nonparametric Kaplan-Meier estimates. The weighted PSID estimates are slightly higher than the NSFG estimates, just as the NSFG estimates are slightly higher than the GSS estimates for the cohorts in both series (Fig. 1). Unweighted PSID estimates are almost identical to the NSFG estimates for the overlapping cohorts.

  10. Monthly probabilities are quite low because they accumulate with age; for example, we estimate that about 39% of women born in 1970 had married by age 24.

  11. Because union formation occurs younger than marriage (and it occurs younger among women than men), the age of most rapid change is lower for union formation than for marriage (and lower for women than for men).

  12. The importance of including age-by-cohort interactions is even larger among Black men and women than among White men and women; we discuss racial differences shortly. Bootstrapped 95% confidence intervals for the difference between our model-based estimates and synthetic cohort-based estimates allow us to reject the null hypothesis that the difference is zero in some, but not all, gender and racial groups; for example, the bootstrapped 95% confidence interval for the difference for White women (men) ranges between –1.2% and 15.6% (3.1% and 25.8%).

  13. Similarly, the Kaplan-Meier estimates for the 1970–1974 birth cohorts are 89.4%, 83.2%, 56.8%, and 61.0% for White women, White men, Black women, and Black men, respectively.

  14. This pattern is evident comparing the Black and White shares in 1970 versus 1990 for men using our life-table estimates and the Martin estimates and for women using the Martin estimates. Our life-table estimates for women suggest a different pattern because our 1970 estimate for Black women is quite low, although our 1980 estimate for Black women corresponds very closely to the 1980 Martin estimate.

  15. We project racial divergence in marriage by age 40. However, we project racial convergence in marriage by age 25. Young White people are catching up to young Black people’s low marriage probabilities, but they are still quite likely to marry between ages 25 and 40; thus, by older ages, White and Black people’s cumulative marriage probabilities diverge.

  16. Notably, union delays were not nearly as stratified by parental income (online appendix, Figs. A4 and A5).

  17. This difference in trends is even more obvious in stratified models—which separately estimate low- and high-income people’s trends (Table 2, columns 4–6)—than in interacted models—which pool people across income backgrounds but allow for separate trends via interactions (Table 2, columns 1–3). Trends among people from high-income backgrounds are more extreme in the interacted models than the stratified models because they are pulled toward the steeper, downward trends observed among people from low-income backgrounds. The high-income trends are more sensitive to model specification than the low-income trends because fewer people stem from high-income than low-income backgrounds. This model sensitivity appears on the scale of lifetime marriage probabilities (Table 2) but not on the scale of monthly marriage hazards (compare Tables A6 and A7 in the online appendix). Small differences in hazards across model specifications compound over the life course to generate large differences in the projected probabilities of marrying by age 40.

  18. Racial differences in cohort trends are evident among people from both low- and high-income backgrounds, although the differences are not statistically significant among people from high-income backgrounds due to small sample sizes within the top-tercile cells for Black men and women (Table A3, online appendix).

  19. When we pool people from low- and high-income backgrounds and include interactions, we project the racial gap among women from low-income (high-income) backgrounds to grow by 15.2 (4.4) percentage points between the 1970–1984 cohorts (Table 2, column 2) versus 13.2 (3.8) percentage points when we instead stratify our models by income background (Table 2, column 5).

  20. Table 3 indicates that the tercile-based compositional share increased about 7–8 percentage points between the 1970 and 1990 cohorts. However, this increase is not statistically significant. Neither is it substantively meaningful because rather than reflecting growing racial gaps in the probability of having high-income parents, it reflects growing differences across income groups in the compositional weights. See the online appendix.

  21. It also reveals the expected decline in the compositional share across cohorts, reflecting the fact that in more recent cohorts, Black men and women were less concentrated in the bottom income deciles.

  22. Point estimates vary between 77% and 99%, depending on cohort and gender, with women’s estimates generally exceeding men’s. Incorporating sampling uncertainty, Table 3 shows that one of the 16 bootstrapped confidence intervals (2 genders × 2 income classification systems × 4 cohorts = 16) includes 50% (with a lower bound of 44.5). But the weight of the evidence suggests that racial differences within economic backgrounds are much more important than racial differences in economic backgrounds themselves (as extreme as they are) in producing aggregate racial differences in marriage. Indeed, several of the bootstrapped intervals contain values exceeding 100%, indicating that racial differences in marriage within parental income groups might be so large that they generate larger aggregate racial gaps in marriage than actually observed (with the observed gaps thus resulting from negative composition effects, with Black men and women from low-income backgrounds marrying more than expected from their parental incomes).

  23. The IHS transformation allows us to maintain 0 and negative values while reducing sensitivity to extreme outliers. This transformation is especially useful for wealth; we use it for both income and wealth for consistency across our dollar-based measures.

  24. In future years, once the young people in this study have reached the ages when their adult family incomes can be reliably measured, researchers should test this implication of our results.

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Acknowledgments

We gratefully acknowledge support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development research grant P01HD087155 and center grant P2CHD041028 as well as the Russell Sage Foundation visiting scholars program. We benefitted from the insightful discussions and comments of the Demography editors and reviewers, William Axinn, Elizabeth Cooksey, Paula Fomby, Lauren Griffin, Anders Holm, Heather Rackin, and Pamela Smock as well as excellent research assistance from Meichu Chen and Jane Furey.

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DB conceptualized the project. DB and SA jointly completed all work.

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Correspondence to Deirdre Bloome.

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Bloome, D., Ang, S. Marriage and Union Formation in the United States: Recent Trends Across Racial Groups and Economic Backgrounds. Demography 57, 1753–1786 (2020). https://doi.org/10.1007/s13524-020-00910-7

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Keywords

  • Marriage
  • Cohabitation
  • Racial inequality
  • Income inequality