A growing body of research documents the importance of studying elites for understanding inequality (Keister and Lee 2017; Nau 2013; Rahman Khan 2012; Rivera 2016). The top one percent of income earners, in particular, has attracted considerable attention because they control enormous quantities of resources in the United States. The term “one percent” entered popular discourse during the Occupy Wall Street movement in 2011, which renewed scholarly and public interest in inequality and the concentration of income (and wealth) (Stiglitz 2012). Research on top households shows that inequality between the one percent and the remaining 99 percent has been rising since the 1980s with few signs of decelerating (Saez and Zucman 2016). Understanding elites is important because top households not only control considerable financial resources but also benefit disproportionately from the power, security, and opportunities high income confers (Bartels 2008; Gilens and Page 2014; Page, Bartels, and Seawright 2013). Despite growing interest in elites and the one percent, little is known about who has access to top income positions.

Gender issues are noticeably absent from research on elites, yet gender is likely to be one of the most salient factors determining who occupies top income positions. Most scholars depict one percent status as a household position that is equally enjoyed by, often, married couples. However, this focus ignores whose income—men’s or women’s—is primarily responsible for whether a household is in the one percent, thereby obscuring who accrues the full extent of the rewards associated with having elite status. Individuals who are in the one percent based entirely on their own income (i.e., without including their spouse’s income) likely accumulate more social and political power than their spouses (Bartels 2008; Gilens 2012; Gilens and Page 2014; Ostrander 1984). A breadwinner in a top-income household may also have greater power in the household, allowing that person to dictate the household’s division of labor, location of residence, charitable giving, and other important decisions (Chesley and Flood 2017; Cooke et al. 2009; Yörük 2010). It clearly matters whose income is responsible for whether a household is in the one percent, but researchers have not systematically examined whether women have access to top income positions, nor have they explored gender differences in the factors (e.g., human capital, marriage) associated with these elite positions.

Although women have made significant economic gains since the 1960s, during what has been called the gender revolution (DiPrete and Buchmann 2013; England 2010), controversy surrounds the degree to which their economic progress has continued since the 1990s. Some evidence suggests the gender revolution has slowed or even stopped (for a review, see England 2010). A vibrant body of research documents that women’s progress has stalled in earnings (Cohen, Huffman, and Knauer 2009; Gauchat, Kelly, and Wallace 2012; Hegewisch, Williams, and Harbin 2012), occupational integration (Blau, Brummund, and Liu 2012; Cohen et al. 2009), and labor force representation (Fortin 2015). Yet, critics have noted that this research may understate continued gender progress and be misleading because it generalizes group-specific income trends to conclude that all gender progress has stalled (Bergmann 2011; McCall 2011). It is possible that progress could vary across the income distribution and that the gender revolution is ongoing for women who are highly accomplished.

The evidence is mixed regarding whether women’s own accomplishments give them access to top income positions as individuals. On the one hand, one-half of professional school graduates are women (DiPrete and Buchmann 2013); women also own about one-third of nonfarm businesses (National Women’s Business Council 2012) and occupy an increasing number of board seats and executive positions in S&P 1500 companies (Warner 2014). These human capital gains could translate into greater access to elite-level incomes. On the other hand, compared with men, women become entrepreneurs at much lower rates and have businesses that fail at higher rates (Fairlie and Robb 2009); women are also underrepresented in top leadership positions (Skaggs, Stainback, and Duncan 2012). As a result, it is unclear the extent to which women have access to one percent status based on their own incomes or if women access the one percent mainly via their partner’s income after getting married.

In this study, we provide an in-depth analysis of gender income dynamics in the one percent. We have three main goals. The first goal is to assess the extent to which women’s income contributes to one percent status for households. To do so, we study whether women’s income is necessary or sufficient for a household to be in the one percent. Our second goal is to assess how education, self-employment, marriage, and spousal characteristics are associated with one percent status and how these associations differ by gender. We are particularly interested in whether there are individual pathways (through higher education or self-employment) associated with women having personal one percent status (i.e., earning sufficient income to meet or exceed the one percent household income threshold on their own), or whether women’s access to the one percent primarily occurs at the household level (via marriage) when their partner’s income is included. We also examine whether the education level and self-employment status of women’s partners are associated with women being in the one % that is, we explore whether marrying a man with “good prospects” increases women’s chances of being part of a one percent household. Our third goal is to examine whether women have experienced gains, relative to men, in having personal one percent income status since the mid- to late-1990s. Our findings underscore the importance of considering gender explicitly in studies of the one percent, and they have broad implications for illustrating who dominates elite income positions.

Accordingly, it is unclear the extent to which one percent households rely on women’s income to meet the one percent threshold and whether women’s own characteristics (e.g., education, entrepreneurship) give them access to personal one percent status independent of their partner’s incomes. It is possible that most women are members of the one percent exclusively because of their partner’s income and that men occupy most breadwinning positions in one percent couples. Also unclear is whether gender income dynamics in elite households have changed over time. That is, we know little about whether women have made progress, relative to men, in converting their own income into personal one percent status since the mid- to late-1990s, when gender progress began to stall ( England 2010 ). Uncovering gender patterns in the one percent will improve understanding of inequality broadly and clarify whether gender progress has continued or stalled for those at the top of the income distribution.

Dual-income relationships were once rare, but the majority of couples now have two earners, reflecting increases in women’s education levels and labor force participation ( Raley, Mattingly, and Bianchi 2006 ). Marital partners have also become more similar on characteristics predicting top income status such as education and income ( Qian 2017 ; Schwartz 2010 ). Such gains could make women’s income necessary for a household to have one percent status and, in some cases, allow women’s income alone to be sufficient for moving a household into the top one percent.

During the 2000s, advancements in closing the gender wage gap also stalled, at least at the median ( Hegewisch et al. 2012 ). Although the number of female-owned businesses and self-employed women increased rapidly between 1997 and 2007, gains in the amount of revenue earned and number of workers employed by women-owned businesses were minimal over this same period ( U.S. Department of Commerce 2010 ). These limited revenue and employee gains may constrain women’s abilities to convert entrepreneurship into high income. Given such patterns and the rarity of major legislative changes (e.g., state-sponsored childcare) designed to facilitate gender progress since the mid- to late-1990s, women have likely made little progress in closing the gender gap in personal one percent status. We thus expect the following:

Although women made significant economic advances following passage of the 1964 Civil Rights Act, progress toward gender parity in income appears to have stalled since the 1990s in ways that could affect the gender composition of individuals who have personal one percent status in more recent years ( England 2010 ). The pace at which women entered high-paying male-dominated jobs and top-level management occupations slowed; and labor force participation rates for professional and managerial women also declined, potentially restricting the number of women qualified for high-level corporate positions ( Cohen et al. 2009 ).

Because marriage may increase the likelihood that both men and women will have one percent status at the household level, it follows that marrying a partner with good earnings prospects (i.e., with a higher education level, self-employed) will be particularly beneficial. Both men and women are likely to benefit from marrying a high earner. Women, however, may benefit more than men from their spouse’s characteristics, because their husband’s income potential is likely higher than their own potential (this is likely not the case for men). Even men who marry women with poor financial prospects may still be part of a one percent household because men’s elite household status is less dependent on their partner’s characteristics. Nevertheless, for men, marrying a highly educated or self-employed spouse may still be associated with increased odds of having household one percent status. Qian’s (2017) recent work suggests that highly educated women (who likely have high incomes themselves) marry men with higher incomes, on average, suggesting that men who marry highly educated women may be especially successful themselves. This suggests the following hypotheses:

For women, marriage may be associated with membership in the one percent at the household level because their spouse’s income may determine whether the couple exceeds the one percent threshold. Importantly, relationships are still characterized by strong income hypergamy patterns, with women more likely to marry up in income and men more likely to marry down ( Qian 2017 ). Given such disassortative mating patterns with respect to income, marriage is likely to be more strongly associated with women’s household one percent status than with men’s. We still, however, expect a positive association between marriage and household one percent status for men, but for different reasons for men than for women. Characteristics positioning men to earn elite-level incomes may also make them especially likely to marry ( Ludwig and Brüderl 2018 ), and men’s own income likely dictates top one percent household status. This leads to the following hypotheses:

Selection effects may also contribute to who marries and stays married, but these effects likely differ for men and women. Men who are positioned to earn exceptionally high incomes may be the most likely to marry and stay married, because high achievement increases desirability in the marriage market and enables them to meet masculine breadwinning expectations ( Fisman et al. 2006 ; Ludwig and Brüderl 2018 ). Successful, ambitious women may be similarly likely or less likely to marry (compared with less-ambitious women), but they may be more likely to divorce because their success disrupts gendered marital expectations ( Fisman et al. 2006 ; Ly, Seabury, and Jena 2015 ). Accordingly, we expect the following:

Marriage is likely to be positively associated with personal one percent status for men but not for women for two key reasons. First, women tend to perform the majority of housework, childcare, and eldercare, particularly in male-breadwinning households, thereby freeing men’s time to devote to paid work ( Chesley and Flood 2017 ; Morgan et al. 2016 ; Yavorsky et al. 2015 ). Even when women are the household breadwinners, their male partners typically do not perform the majority of unpaid family labor ( Chesley and Flood 2017 ). Second, a couple may make major life decisions that favor men’s careers. For example, partnered men and women who have comparable incomes are more likely to relocate for men’s jobs, often to the detriment of women’s careers and incomes ( Cooke et al. 2009 ; Sorenson and Dahl 2016 ). Thus, marriage may increase men’s income while offering little to no benefits to women’s income.

Given that couples share resources, marriage is likely to be a route to the one percent for both spouses; however, marriage may matter differently for women and men because of entrenched relationship gender dynamics ( England 2010 ). Marriage could increase a person’s likelihood of one percent status either by increasing the effect of their own characteristics (education or self-employment) or by increasing access to rewards that stem from their partner’s individual characteristics.

Because women may be less likely to earn enough income to qualify for one percent status, they may be more reliant than men on education and self-employment to reach this elite position even if their overall likelihood of being in the one percent is lower. Indeed, Hout (2012) and DiPrete and Buchmann (2013) found that women receive higher returns from a bachelor’s degree than do men, likely because men have other pathways to earning high income outside of earning a degree. This gendered pattern could also play out at the very top: women may need an advanced degree or may need to be self-employed to be a member of the one percent on their own, whereas the association between education/self-employment and membership in the personal one percent may be more variable for men. Thus, we expect the following:

Although higher education and self-employment may increase women’s likelihood of having personal one percent status compared with less-credentialed women, several factors suggest that women’s individual characteristics may be less predictive of personally reaching top income status. First, women earn less income than men at every education level ( Hout 2012 ), and significant income gaps persist between men and women in otherwise highly paid professions, such as medicine and law ( Dinovitzer et al. 2009 ). Second, women may have more limited access to positions associated with exceptionally high incomes due to discrimination, as Rivera and Tilcsik (2016) found in elite law firms. Third, considerable gender gaps exist in leadership positions that may contribute to gender differences in the association between individual characteristics and income. As the concept of a glass ceiling implies, women experience significant obstacles in climbing organizational hierarchies that often intensify over their careers ( Cotter et al. 2001 ; Maume 1999 ). However, research on obstacles to career advancement may underestimate the extent of inequality between men and women because it focuses on gender differences in reaching top organizational positions. A glass ceiling may extend beyond the occupational level to include membership in the more expansive elite group defined by the one percent.

Self-employment is also likely to be associated with personal one percent status for both men and women, although this may be less straightforward for women. More women are starting businesses than in the past, but they still face significant barriers to entry into entrepreneurship and, critically, to securing financial capital to grow their businesses ( Saurav, Goltz, and Buche 2013 ). Moreover, many women start businesses to create greater work-family flexibility, in contrast to men who are more likely to start a business to advance their careers ( Jennings and Brush 2013 ). However, the work profiles and reasons for self-employment of highly educated, professional women—the women who are perhaps the most likely to earn exceptionally high income—more closely resemble those of comparable self-employed men ( Budig 2006 ). Thus, becoming self-employed by starting a successful business may offer a route to the personal one percent for women who would otherwise have few opportunities to advance in a corporation ( Maume 1999 ; Smith 2012 ; Warner 2014 ).

Higher education (particularly professional degrees) is strongly associated with higher earnings ( Hout 2012 ; Quadrini 2000 ), and scholars have shown that women’s income gains in recent decades result in large part from increases in their educational and occupational attainment ( DiPrete and Buchmann 2013 ; England 2010 ; Goldin 2006 ). Higher education is also required for many, if not most, high-earning professions (e.g., lawyer, medical doctor). Thus, education likely increases men’s and women’s chances of earning sufficient income to qualify for the personal one percent, relative to their same-gender peers who have less education.

Finally, the Federal Reserve provides sample weights for each survey to adjust for sampling design. We use the sample weights for our descriptive analyses and the calculation of the one percent threshold to estimate descriptions of the population. In our regression analysis, because the analytic goal is to use survey data to see whether the relationship between personal/household one percent status and individual/spousal attributes differs between men and women, we account for important survey design features by controlling for homeownership and race, instead of weighting, when fitting models (as recommended in the SCF codebook and by Winship and Radbill 1994 ).

In addition to our main strategies, two other important considerations are worth noting. The Federal Reserve uses multiple imputation to address missing values in all survey years and stores the imputed values as five successive replicates of each data record ( Kennickell 1998 ). We follow standard procedure and the Federal Reserve’s recommendation (see SCF codebook) and use Rubin’s rule (1987) to adjust our standard errors to ensure that the multiple imputations do not inflate statistical significance. We implement Rubin’s rule using the mi estimate command in Stata (for further discussion on using Rubin’s procedure with SCF data, see Kennickell 2003 ; Lindamood, Hanna, and Bi 2007 ).

To evaluate Hypothesis 1, we use descriptive statistics to examine whether the woman’s income is necessary or sufficient for married households to qualify for one percent status. For analyses assessing how individual characteristics and marital status shape one percent status (testing Hypotheses 2 through 5) and whether women have made any progress in having personal one percent status over time relative to men (Hypothesis 6), we use logistic regression. 5 For Hypotheses 2 through 5, we first run gender-specific models ( Tables 3 , 4 , and 5 ) to assess whether our independent variables are positively associated with one percent status for men and women, separately. We then conduct post-estimation tests (using the mysuest command in Stata) to formally evaluate whether coefficient differences are statistically significant for men and women ( Cañette and Marchenko 2018 ). Such tests allow us to examine whether the relationship between predictors and one percent status differs between men and women. Notably, the post-estimation tests use the full interaction model and produce the same coefficient estimates as running a model with gender interacted with every covariate. Finally, to test whether women have made progress in earning personal one percent status relative to men, we run a regression model that includes interactions between period and gender using a pooled sample of men and women. 6 This model assesses whether the gender gap in having personal one percent status has converged over time (through the 2000s), compared with the mid-to-late 1990s.

Our analyses also include multiple control variables. We control for the number of children under age 18 residing in the household, because having children is significantly associated with lower incomes for women and higher incomes for men ( Weeden et al. 2016 ); thus, it is important to compare men and women with a similar number of children. We also control for an individual’s age, because longer tenure in one’s career is tightly linked to higher income, particularly for those earning elite income ( Willson 2003 ; Wolff 2010 ). Additionally, we control for the SCF respondent’s race, given stark income disparities between white and racial minority groups ( Bloome 2014 ). Because the SCF asked the race of only SCF respondents who completed the survey, we can use only respondents’ own race to capture the race of both spouses in couple households. This approach has been used in prior research with similar data limitations (see, e.g., Qian 2018 ). We code race as a binary variable (nonwhite [1] versus white [0]). 4 Finally, we include a dichotomous variable for homeownership status (1 = yes, 0 = no) to help account for features of the survey, as explained in the following section.

Finally, we include survey year as a predictor to assess whether the association between gender and personal one percent status has changed over time. We use a set of dummy variables indicating time periods: 1995 to 1998 (reference category), 2001 to 2007, and 2010 to 2016. Because we are interested in progress since the 1990s, we include 1995 and 1998 in one category. 3 Note that the period ranges are not continuous; because SCF is administered every three years, the variables consist of only the years that follow a three-year increment. For example, 2001 to 2007 includes the years 2001, 2004, and 2007.

Our main independent variables are individuals’ own characteristics, marital status, spousal characteristics, and time period. Individuals’ own characteristics include (1) highest educational level, measured as less than a bachelor’s degree (reference group), bachelor’s degree, or advanced degree; and (2) self-employment, a proxy for entrepreneurship ( Cagetti and De Nardi 2006 ). Marital status is a dummy variable indicating whether individuals are married (including those who were married or cohabiting) or single (i.e., unpartnered individuals, including those who were never married, divorced, or widowed; reference category). We use two variables to measure spousal characteristics: (1) spouse’s highest educational level; and (2) a dichotomous measure indicating whether the spouse is self-employed.

For the remaining analyses, we use two dichotomous measures of income as our dependent variables; both rely on the aforementioned income thresholds. First, for analyses examining whether individual characteristics (Hypothesis 2), marriage (Hypothesis 3), and time period (Hypothesis 6) are associated with personally earning elite income, we use a dummy variable indicating whether an individual earns sufficient income for personal one percent status (similar to the variable “woman’s income is sufficient for one percent status”). This dummy variable indicates whether a woman’s or man’s personal income sufficiently meets or exceeds the household one percent income threshold on their own. Personal income includes salary/wage and business income because these can be attributed to specific individuals rather than to the household overall. Second, for analyses examining whether marriage (Hypothesis 4) and spousal characteristics (Hypothesis 5) are associated with household one percent status , we use a dummy variable indicating whether a person is part of a household with total income that ranks in the top one percent of households. Total household income is included in the SCF data and includes respondent reports of gross, pretax income from salaries/wages, businesses, investments, government transfers, alimony, and other sources in the previous calendar year. Thus, both spouses’ incomes are included in household one percent status for married households.

For Hypothesis 1, which addresses the importance of women’s income for a household to qualify for the top one percent, we use two measures: (1) woman’s income is necessary for one percent status , indicating that the household would not be in the top one percent without her income; and (2) woman’s income is sufficient for one percent status , indicating that the woman’s income alone pushes the household over the one percent threshold, regardless of her husband’s income contribution. In both cases, income includes salary/wages and business income, because these can be attributed to each member of a couple. In 2016 dollars, the income threshold for a household to qualify for one percent status ranges between $394,000 and $859,000 (depending on the year, 1995 to 2016). 2 If a woman’s income reaches this threshold on her own, then her income is considered sufficient for one percent status.

In our regression analysis, our unit of analysis is the individual. The observations of men in our analysis are based on either interviews of male respondents or female respondents’ reports of spousal information; the observations of women were similarly obtained. Accordingly, our analytic sample consists of 26,089 men and women living in households with different-sex couples, 5,524 single men, and 8,805 single women.

Cohabiting couples in the one percent may eventually transition to marriage, given that cohabitation is frequently a stepping stone before marriage for individuals with high income prospects ( Sassler, Michelmore, and Qian 2018 ). The small number of cohabiting cases prevents us from examining marriage and cohabitation separately: in the different-sex couples belonging to the top one percent households, only 2.4 percent are headed by cohabiting couples, whereas 97.6 percent are headed by married couples. 1 For simplicity, we use “married” to refer to both married and cohabiting hereafter; likewise, our use of the term “spouse” refers to both marital and cohabiting partners.

We start with the full sample of 40,727 households. Because we are interested in partnered men and women in the one percent, we exclude 309 households headed by same-sex couples. Our sample includes 40,418 households: 26,089 were headed by a different-sex married/cohabiting couple (23,445 married and 2,644 cohabiting), and 14,329 were headed by an unmarried/unpartnered person. In our analyses, we include cohabiting-couple households in married-couple households because the SCF assumes that couples who live together, regardless of marital status, are financially interrelated and treats them as a primary economic household unit.

Most of the SCF data represent a household’s financial characteristics, but the 1995 to 2016 surveys contain separate questions about respondents’ and their spouse’s (or cohabiting partner’s) income, allowing us to assess each partner’s economic contribution to the household. The 1995 to 2016 SCF datasets also include information on income, age, education, and employment characteristics of respondents and their partners (if married or cohabiting).

We use data from the 1995 to 2016 Survey of Consumer Finances (SCF) to evaluate these hypotheses. The Federal Reserve Board’s SCF is a repeated cross-sectional survey conducted every three years and is widely considered the best source of information on top-income households. The SCF is designed to provide financial and economic profiles of U.S. households and, importantly, includes both a multistage national area probability sample of households and a sample of high-income households selected from tax files to accurately measure the distribution of income across U.S. households. Given that high-income households receive disproportionate amounts of total salary, wages, and other income, it is critical to ensure they are included in a survey intended to represent the income distribution. In addition, the SCF sampling method is effective at drawing sufficient numbers of high-income households ( Kennickell 2007 ), whose response rates are typically lower than those of other households. The oversample of high-income households is identified with Internal Revenue Service data and is calibrated against other known data to ensure accurate representation of affluent households ( Bricker et al. 2014 ). The oversample also ensures that the unique income profile of top households (e.g., business income, investment income) is represented ( Kennickell and Woodburn 1999 ). Other survey datasets that contain information on income (e.g., Panel Study of Income Dynamics, Survey of Income and Program Participation, National Longitudinal Survey of Youth [1979], and Current Population Survey) do not include sufficient numbers of high-income households to analyze.

Women are clearly disadvantaged in having personal one percent status, but has this female disadvantage lessened over time? To explore this possibility, we add interaction terms between gender and period indicators in Model 2. Coefficients for both interaction terms are small in magnitude and insignificant ( b 2001–2007 × female = .100, p > .05); ( b 2010–2016 × female = .047, p > .05), suggesting a lack of significant change in women’s lower likelihood, relative to men’s, of having personal one percent status across periods. As suggested by Mood (2010) , we calculated average marginal effects of gender by period to confirm these interaction results and also found insignificant change in gender difference over time ( p > .05). Thus, results are consistent with Hypothesis 6: women have not made any gains over the past 20 years in closing the gender gap in having personal one percent status.

Our final analysis assesses whether women have made significant progress in recent decades in closing the gender gap in the likelihood of having personal one percent status ( Table 6 ). Before adding interaction terms in the pooled sample of men and women, we confirm in Model 1 what the descriptive results in Figure 1 suggest: women’s chances of having personal one percent status are significantly lower than men’s chances. Specifically, women are 84 percent less likely than men to have personal one percent status ( b female = −1.849, exp( b ) = .16, p < .001), with other variables held constant.

Our post-estimation tests (column 3, Table 5 ) show that the relationships between spousal characteristics (such as education and self-employment) and household one percent status are significantly stronger for women than for men. These results provide support for Hypothesis 5b and are compelling when compared with gender differences between men’s and women’s own characteristics and household one percent status. Here, the positive relationship between individual characteristics and household one percent status is significantly stronger for men than for women (coefficients for bachelor’s degree, advanced degree, and self-employment are, respectively, 1.134, 1.394, and 1.575 for men versus .627, .694, and .066 for women; all significant gender differences at p < .05). These findings suggest that household one percent status for men is tied more strongly to their own individual characteristics, whereas household one percent status for women is linked more strongly to their spouse’s characteristics.

Consistent with Hypothesis 5a, having a highly educated spouse is positively associated with having household one percent status for both married men and women, compared with having a lower-educated spouse (when individuals’ own education and other attributes are controlled for). Compared with their same-gender peers who have a spouse without a bachelor’s degree, women whose husbands have a bachelor’s or advanced degree are 211 and 312 percent, respectively, more likely to have household one percent status ( b spouse’s bachelor’s degree = 1.134, exp( b ) = 3.11, p < .001; b spouse’s advanced degree = 1.417, exp( b ) = 4.12, p < .001). Likewise, men whose spouses have a bachelor’s or advanced degree are 95 and 111 percent, respectively, more likely to have household one percent status ( b spouse’s bachelor’s degree = .666, exp( b ) = 1.95, p < .001; b spouse’s advanced degree = .746, exp( b ) = 2.11, p < .001). In addition, married women who have a self-employed spouse are 385 percent more likely to be in a one percent household than are married women with a non-self-employed spouse ( b spouse’s self-employment = 1.580, exp( b ) = 4.85, p < .001). However, men who have a self-employed spouse are not significantly more likely to be in a one percent household than are men with a non-self-employed spouse ( b spouse’s self-employment = .072, p >.05). In contrast to the role self-employment plays for women personally earning elite income, men appear to receive few benefits from their partner’s self-employment at the household level. This follows from our finding that household one percent status is largely determined by men’s own characteristics.

What remains unknown is whether our marriage-related findings are driven by a subsample of women who are married to men with good prospects. In the next set of analyses ( Table 5 ), we examine married persons only to test whether marriage to partners with good prospects (highly educated or self-employed partners) is positively associated with household one percent status for both men and women (Hypothesis 5a) and whether this positive association is stronger for women than for men (Hypothesis 5b).

These contrasting gendered explanations gain further support when we consider gender differences in the relationship between individual characteristics and household one percent status (third column, Table 4 ). Here, we find that an individual’s own higher education and self-employment is more strongly associated with household one percent status for men than for women (coefficients for bachelor’s degree, advanced degree, and self-employment are, respectively, 1.384, 1.757, and 1.613 for men versus 1.240, 1.461, and .590 for women; all significant gender differences at p < .05). Although we do not include a hypothesis related to these gender differences, they are useful in understanding the broader story of how individual characteristics and marriage differentially matter for women’s and men’s pathways to household one percent status. Taken together, these findings suggest that although marriage is more strongly associated with women’s household one percent status, individuals’ own educational and employment characteristics are more strongly associated with men’s household one percent status.

Given that women’s income is necessary for household one percent status only 15 percent of the time (at its peak, in 2016; see Figure 1 ), our results indicate that marriage is a key pathway to one percent status for women, and they speak to relationship norms in which women are more likely than men to marry up in income ( Qian 2017 ). In contrast, the positive association between marriage and household one percent status for men is likely indicative of selection effects (married men are more likely to have household one percent status because of advantageous characteristics that make them more likely to marry and succeed in the workplace) or the benefits that married men receive from a wife prioritizing the man’s career and performing the majority of household/family work.

Whereas Table 3 shows that marriage is not significantly associated with women’s likelihood of having personal one percent status, Table 4 indicates that marriage is significantly associated with women’s likelihood of having household one percent status, when other variables are held constant. Married women are 992 percent more likely than single women to have household one percent status ( b marriage = 2.391, exp( b ) = 10.92, p < .001). Married men, too, are more likely than single men to have household one percent status (71 percent more likely) ( b marriage = .535, exp( b ) = 1.71, p < .001). Thus, we find support for Hypothesis 4a: marriage positively predicts household one percent status for both genders. Consistent with the stark disparity in the coefficient for marriage between women and men (2.391 versus .535), the post-estimation test confirms Hypothesis 4b: the positive association between marriage and household one percent status is significantly stronger for women than for men ( p < .05).

Table 4 shows analyses similar to those in Table 3 but changes the dependent variable to reflect whether a respondent has household one percent status based on total family income. This strategy allows us to examine whether marriage is a key pathway for one percent status at the household level, as we expect it to be for women. Specifically, we test whether marriage is positively associated with having household one percent status for both men and women (Hypothesis 4a) and whether this positive association is stronger for women than for men (Hypothesis 4b).

Next we test Hypothesis 3, which states that the positive association between marriage and personal one percent status is stronger for men than for women. As shown in Table 3 , married men are 31 percent more likely than single men to have personal one percent status ( b marriage = .269, exp( b ) = 1.31, p < .01), whereas the likelihood of earning sufficient one percent income is similar for single and married women ( b marriage = .146, p > .05), with other variables held constant. This suggests that the positive association between personal one percent status and marriage may be stronger for men. However, our formal post-estimation test indicates that the difference in the male and female marriage coefficients is not statistically significant at the .05 level (as shown by the third column in Table 3 ; men: b marriage = .269; women: b marriage = .146; nonsignificant gender difference at p > .05).

Next, we conducted post-estimation tests to evaluate whether higher education and self-employment effects are stronger for women than for men (Hypothesis 2b). Results are shown in the third column of Table 3 . As predicted, the positive association between self-employment and personal one percent status is stronger for women than for men (women: b self-employment = 3.405; men: b self-employment = 2.228; significant gender difference at p < .05). This finding suggests that, compared to men, self-employment is more important for women to earn exceptionally high income. In contrast to Hypothesis 2b, we find that having a bachelor’s degree is a better predictor of having personal one percent status for men than for women (women: bbachelor’s degree = .730; men: bbachelor’s degree = 1.256; significant gender difference at p < .05). Notably, the post-estimation test shows that an advanced degree is a similarly important route for both men and women (as indicated in Figure 1 ).

Higher education and self-employment are also positively associated with having personal one percent status for men. With other variables held constant, men with an advanced degree are 386 percent more likely to have personal one percent status than are men who have less than a bachelor’s degree ( b advanced degree = 1.581, exp( b ) = 4.86, p < .001), and self-employed men are 828 percent more likely than non-self-employed men to have this status ( b self-employment = 2.228, exp( b ) = 9.28, p < .001). Results provide support for Hypothesis 2a: education and self-employment are associated with an increased likelihood of having personal one percent status for both men and women.

Our descriptive results suggest that education and self-employment are important for personal one percent status for both genders, but these effects may be confounded by other factors that are associated with membership in top income positions. Next, we test our hypotheses using multivariate models. Table 3 shows results of logistic regression models testing whether higher education and self-employment are positively associated with having personal one percent status for both men and women (Hypothesis 2a). We find support for this hypothesis. Compared with women without a college degree, women with an advanced degree are 453 percent more likely to have personal one percent status ( b advanced degree = 1.710, exp( b ) = 5.53, p < .001), and women with a bachelor’s degree are 108 percent more likely to have personal one percent status ( b bachelor’s degree = .730, exp ( b ) = 2.08, p < .001). Importantly, self-employment appears to be an especially influential pathway to personal one percent status for women. With other variables held constant, the odds of having personal one percent status are 30 times higher for self-employed women than for non-self-employed women ( b self-employment = 3.405, exp( b ) = 30.11, p < .001). Such high odds may also reflect the fact that women who are not self-employed have very low odds of having personal one percent status, as intimated by Figure 1 , which shows that the probability of having personal one percent status approximates zero for non-self-employed women regardless of their marital or educational status.

Although women’s income alone rarely meets or exceeds the one percent threshold, perhaps their income could still be necessary in pushing a household over the one percent threshold. Figure 2 shows that women’s income was necessary in about 9.6 and 7.4 percent of married one percent households in 1995 and 1998, respectively; in 2016, the percentage was 15 percent. Although the percentage of married women in the household top one percent is comparable to that of married men (as previously shown in Figure 1 ), women’s income, in most cases, is inconsequential for moving a household into this elite position (as predicted by Hypothesis 1).

Consistent with Hypothesis 1, Figure 2 shows that only in a minority of cases is women’s income sufficient for membership in the one percent (i.e., women’s income alone moved a household into the one percent), regardless of the year. In 1995, women’s income was sufficient for one percent status for 1.7 percent of elite households, and the corresponding figure was 4.5 percent in 2013 and 2016. These findings align with the results in Figure 1 showing that women in every marital, self-employment, and education subgroup have lower probabilities than men of earning sufficient income to qualify for personal one percent status.

Importantly, Figure 1 (the bottom portion) shows there are fewer gender differences for married people in the household top one percent. That is, when income for both spouses is considered, the probability of women having one percent status is comparable to that of men. For example, in the full sample of married persons, an equal percentage of married men and women have one percent status (1.6 percent). Moreover, compared with only two subgroups for personal one percent status, six detailed subgroups of women now have probabilities of top one percent household status of at least 1 percent. Although women’s probabilities are lower than men’s in most subgroups, women have higher probabilities of household one percent status than do men in three subgroups (married; non-self-employed; and education less than a bachelor’s degree, a bachelor’s degree, or an advanced degree). This pattern likely emerges because women at every educational level are more likely to marry men with higher incomes than themselves ( Qian 2017 ). Not surprisingly, large gender gaps remain for household one percent status for single men and women; this follows because single women do not have spousal income to bolster their chances of being in a top income household. Whereas .1 percent of single women in the full sample have household one percent status, .5 percent of single men do. One of the largest disparities exists between single men and women who are self-employed and have an advanced degree: 11.7 percent of these men have household one percent status, compared with only 1.6 percent of comparable women.

However, there are stark gender differences in personal one percent status. For every subgroup included in Figure 1 , men have higher probabilities of being in the personal one percent. 8 In the full sample (not stratified by education or self-employment status), .01 percent of single women and .05 percent of married women have personal one percent status, compared with .3 percent of single men and .6 percent of married men. In five male subgroups, at least 1 percent of men have personal one percent status; comparatively, only two subgroups of women meet this criterion. For example, about 1.8 percent of women who are married, are self-employed, and have an advanced degree have personal one percent status; yet, 7.4 percent of men with these same characteristics have sufficient income to qualify for this status. Even self-employed married men who have a lower education status (bachelor’s degree) have a probability of being in the personal one percent that is almost double that of women who have similar characteristics but have an advanced degree (3.4 versus 1.8 percent).

Because we are interested in how individual characteristics are associated with who has one percent status, we compare mean percentages of personal and household one percent status for various marital, self-employment, and education subgroups in Figure 1 . The top portion of Figure 1 underscores that higher education and self-employment are both positively associated with being in the personal one percent. Both men and women who have high education levels, especially when combined with self-employment, have higher representation in the personal one percent than do other subgroups of the same gender. In most same-gender subgroups, married persons are also more likely than their single counterparts to be in the personal one percent.

Many demographic differences between individuals in one percent households and the full sample are also evident. For example, married and single men and women in one percent households between 1995 and 2016 are older, on average, than the general population. Single women are particularly older than both the general population and other subgroups in the one percent. In fact, the average age for single women (63) is 9 to 12 years older than others in the one percent, suggesting that earning elite-level income requires longer employment tenure for single women. Also, households in the top one percent are less racially diverse than households in the general population. Indeed, only 7 percent of married households in the one percent had respondents who identified as nonwhite, with an even lower percentage for single women (3 percent).

Table 2 includes weighted descriptive statistics for variables used in the analyses, including separate estimates by gender and marital status. We compare people living in top one percent households (the lower panel) with the full sample (the upper panel). Table 2 shows that a higher percentage of both married and single men and women in top one percent households are highly educated, compared with those in the full population. For example, 53 percent of married men and 35 percent of married women in one percent households have an advanced degree, compared with only 13 and 11 percent of married men and women, respectively, in the full population. Individuals in top one percent households also have higher rates of self-employment, particularly for men. Whereas only 14 percent of married men and 11 percent of single men in the general population are self-employed, about half of married men (48 percent) and single men (52 percent) living in top one percent households are self-employed. Similarly, only 7 percent of married women and 5 percent of single women are self-employed, compared with 17 percent of married women and 40 percent of single women for those in one percent households.

Discussion

In this article, we studied the characteristics associated with men’s and women’s membership in the top one percent of income earners, positions that have become increasingly important given growth in income concentration in the past 40 years (Keister and Lee 2014). This study takes seriously the call by McCall (2011) and England (2011) to study economic inequality according to intersecting gender and class structures and is among the first to dissect gender patterns within the one percent. Our findings reveal that top one percent households are anything but gender-neutral. Our analyses add a critical dimension to conceptualizations of the glass ceiling and identify another economic measure on which gender progress has stalled in recent decades.

Importantly, we found that married households rarely qualify for one percent status based on women’s income alone. In 2016, women’s income was sufficient for one percent status in only 1 in 20 elite households. We also found that women’s income is not necessary for the vast majority of married households to meet the one percent threshold. That is, most households would have one percent status without women’s income, because this status is largely determined by men’s income. These findings suggest a persistent male dominance of income resources in elite families.

Personal achievement is associated with membership in the one percent for a minority of women, and we find that higher education and self-employment are two critical pathways in this regard. In fact, self-employment carries a higher return for women than for men in having personal one percent status. This, of course, does not imply that self-employed women have higher rates of personal one percent status than do self-employed men (they do not, as results in Figure 1 show); instead, it implies that the proportionate gain for self-employment is greater for women than it is for men. Such findings may stem from the fact that the probability of having personal one percent status for women who are not self-employed approximates zero. Self-employment (via starting a successful business) may free some ambitious and capable women from blocked pathways of upward mobility in the corporate world, despite the reality that women still face gender-based challenges related to business startup and growth (Jennings and Brush 2013; Saurav et al. 2013). Given that men occupy most corporate leadership positions (Warner 2014), men have routes other than self-employment to earning elite-level incomes (even though self-employment is still an important route for men as well).

The greater return to self-employment for women may also reflect gendered selection into self-employment. Relative to men with similar characteristics, women hold themselves to stricter standards of competence before considering entrepreneurial activity (Thébaud 2010), activity that could result in high income returns. Thus, for women looking to advance their careers through self-employment (and not just to resolve family–work conflict) (Budig 2006), perhaps only the most competent, confident, and highly educated women start their own businesses. In contrast, men of more diverse abilities may pursue entrepreneurial activity. It follows that the women who pursue self-employment may be exceptionally qualified and likely to succeed relative to women who are not self-employed, because women may need more markers of validation than men to start a business.

In addition, we find that in the gender-specific models, the relationship between marriage and personal one percent status appears to differ for men and women. For similarly positioned women, we find no significant differences between married and single women’s likelihood of having personal one percent status. In contrast, married men have increased likelihoods of having personal one percent status relative to comparable single men. Although we are unable to identify causality, one explanation for this finding is that married men, unlike married women, are more likely to have partners who perform the majority of unpaid labor in their household (Sayer et al. 2009; Yavorsky et al. 2015) and are willing to compromise their own careers to favor their spouse’s ambitions (Cooke et al. 2009). This may be particularly true for highly successful men and women, given that high-achieving women tend to marry other high-achieving men, whereas high-achieving men tend to have more economically diverse spouses (Pearce and Gambrell 2016).

Alternatively, the finding that marriage is strongly associated with men’s personal one percent status but not women’s may indicate that men who are likely to earn high incomes are more inclined to marry (Ludwig and Brüderl 2018). This possibility would provide support for the notion that the characteristics that position men to succeed at high career levels (e.g., competitiveness, authority, leadership, long work hours) do not counter their desirability as marital mates (Fisman et al. 2006; Qian 2017). Yet, for women, those same characteristics may decrease their likelihood of finding a spouse (Fisman et al. 2006) or remaining married if they do find a spouse (Ly et al. 2015). Thus, marriage may be less compatible for women than for men with earning personal one percent status. Note that we caution against over-interpretation of this finding, because according to our post-estimation test, the gender difference in the relationship between marriage and personal one percent status does not reach statistical significance at the .05 level. Although perhaps counterintuitive, the difference between a significant and nonsignificant coefficient may not necessarily be statistically significant, as we found in our study. Gelman and Stern (2006:329) advise that scholars focus on “the statistical significance of the difference rather than the difference between their significance levels.” Therefore, additional research is needed to provide more definitive answers when more recent data with larger sample sizes become available.

Our findings suggest that marriage benefits women by giving them access to their spouse’s income and one percent status at the household level. That is, women who are married to high-income men have a significantly higher likelihood of being in a one percent household than do similar single women. However, not all married women have similar chances of making it to a one percent household; rather, there are clear differences among married women. In particular, women who have spouses with good prospects (a highly educated or self-employed spouse) are best positioned to attain this top status. Given that household one percent status is mostly determined by men’s income, wives’ characteristics are less important for men’s membership in a top one percent household. Ultimately, this analysis highlights the different and unequal pathways associated with men’s and women’s access to these elite positions.

Although women still encounter barriers to membership in top income groups, their access, relative to men’s, may have improved in recent decades. Our period analysis addresses this potential, but we largely find that women have not made any progress over time in closing the gender gap in personal one percent status. That is, the patterns we find when comparing recent periods (2001–2007 and 2010–2016) with the mid- to late-1990s differ little between men and women with comparable characteristics.

Theoretical Implications The notion of a glass ceiling suggests that invisible barriers prevent women from rising to top leadership positions (Cotter et al. 2001; Maume 1999; Smith 2012). Our findings suggest that these barriers are more pervasive than previous research has demonstrated. Whereas previous work focused almost exclusively on occupational barriers, we provide evidence that women experience difficulty accessing all top personal income positions. This implies that the glass ceiling extends to a broader measurement of elite status: the top one percent of income earners. Some may argue that the question of how women break into the one percent is less consequential than whether women occupy top positions. However, gender differences in how individuals access top income positions may have important implications for power and status. It is reasonable to infer that because men’s income is primarily responsible for a household’s one percent status, they have greater political influence outside the household than do their spouses who earn less income or whose income is inconsequential to the household’s overall status. This factor is important in itself, but given studies showing that economic elites have substantial influence on government policy (see Gilens and Page 2014), this influence likely reflects men’s interests rather than women’s. In fact, evidence suggests that women use political power differently than men. For example, high-income women are more likely than high-income men to donate to PACs that promote and lobby for more liberal and progressive policies, such as EMILY’s List, MoveOn PAC, and Hollywood Women’s PAC (Heerwig and Gordon 2018). More liberal stances may also emerge because women who make it into the one percent have high levels of education and likely have consistent labor force participation over the course of their careers. Women with these characteristics have higher rates than men of voting Democratic and of holding more progressive social and civil rights attitudes (Cotter, Hermsen, and Vanneman 2011). In addition to these external benefits, men likely gain additional internal household advantages, such as greater decision-making power in the household (Davis and Greenstein 2013) and the ability to retain these income streams in the event of a divorce (depending on prenuptial agreements and divorce filings) (Kurz 2013). Taken together, these findings suggest that scholars should be more explicit about who the one percent is because these individuals likely hold most of the substantive status within these groups. That is not to say that women in elite households are disempowered or marginalized. Rather, our findings suggest that men likely hold qualitatively different positions in these households and that this difference has important social implications. Our findings also have implications for understanding income inequality. It is widely documented that most U.S. income gains since the late 1970s have gone to the top one percent of households (Feller and Stone 2009; Keister 2014; Piketty and Saez 2003). However, if women’s income is inconsequential in 85 percent of these households, rising inequality is largely due to a small group of men’s income disproportionately rising compared with all others. Thus, it is critical that future research consider gender in work on both elites and the general population.

Limitations Although our study has many strengths, a few limitations are worth noting. Ideally, we would have longitudinal data, but no currently available data include longitudinal information on incomes and sufficiently large samples of high-income households to explore how these patterns change for the same individuals over time. In addition, the SCF asks respondents to disclose information regarding their pretax income and government transfers. As Nau (2013) notes, this way of disclosing information could potentially understate the importance of investment income to post-tax income because wages are often taxed at a higher rate. Like any other survey capturing household financial information, the SCF may be subject to inaccurate or incomplete financial information if respondents do not fully report their finances. However, due to the care the Federal Reserve takes in sampling, surveying, and calibrating data prior to releasing them, the SCF is considered the most accurate source of information on income and related financial traits and behaviors (Bricker et al. 2014). Finally, because cohabiting couples represent only 2.4 percent of all different-sex partnered households, we do not have a sufficiently large sample size to examine married and cohabiting persons separately. More detailed conceptualization and analyses on differences between these two types of couples in one percent households await future research.