The health, well-being, and quality of life of sexual and gender diverse (SGD) populations are significantly affected by the economic systems in which they live, develop, and work. Socioeconomic status and educational, employment, and housing opportunities are important measures of well-being. They are also connected to family, health, community, and other aspects of well-being addressed elsewhere in this report. This chapter explores what is known and not known about the economic well-being of SGD populations, and it identifies essential economics research needs. It examines how specific SGD populations fare with respect to economic well-being, focusing on individuals’ and families’ economic security and access to necessary resources that sustain and enhance life. In the United States, most of those resources or goods and services come from the marketplace, requiring purchases using income acquired through earnings from employment, benefits from a public assistance program, or income derived from sources of wealth. Accordingly, this chapter addresses what is known about income, wealth, and poverty, looking at differences based on sexual orientation and gender identity.
The chapter also discusses several factors that are likely to affect income and wealth. As a complement to the discussion of education in Chapter 9 and the discussion of health in Chapter 11—two areas that contribute to the skills and knowledge that an individual has to offer in the labor market, known as human capital (Goldin, 2016)—this chapter adds a discussion of individual occupational attainment. It considers the dynamics of SGD families and households (one or more adults with or without children living together), the attainment of an adequate or equal standard of living
for SGD people in comparison with heterosexual and cisgender people, and barriers to that attainment, such as discrimination.
Overall, studies that measure socioeconomic status as earnings, household income, poverty, and occupational attainment reveal a complex picture of the economic well-being of SGD populations. The research primarily compares people who identify as lesbian, gay, or bisexual with those who identify as heterosexual, or it compares transgender people with those who are cisgender. Much evidence suggests that bisexual and transgender people have lower incomes and higher poverty than lesbian, gay, and cisgender heterosexual people (Badgett, 2018; Badgett, Choi, and Wilson, 2019; Carpenter, Eppink, and Gonzales, 2020). Lesbian women and gay men may have mitigated some of the effects of discrimination on earnings and household income through adaptive strategies in education, occupations, and family decisions, but they still face discrimination in the labor force (Valfort, 2017).
Individual Income from Earnings
Research on individual earnings suggests that, after controlling for differences in income-related characteristics, gay and bisexual men earn less than heterosexual men and that lesbian and bisexual women earn less than heterosexual men but more than heterosexual women (Klawitter, 2015; Valfort, 2017). Recent research suggests that the lower earnings of bisexual men might be driving those general patterns for men, but the research is not conclusive on this point (Carpenter, 2005; Mize, 2016; Sabia, 2014). Some evidence suggests that the wage gap for men might be diminishing over time, but these observations are preliminary and have not been confirmed.
These general findings have been made possible by the growing availability of datasets that have measures of income along with measures of sexual orientation or gender identity, thus improving researchers’ ability to analyze income differences. Some datasets have behavioral measures of sexual orientation (the sex of one’s sexual partners), and others have measures of self-identity (gay, lesbian, bisexual, or transgender). Many datasets that lack sexual orientation questions do contain household rosters that allow the identification of people with same-sex partners, as in the U.S. census, the American Community Survey (ACS), and the Current Population Survey (U.S. Census Bureau, n.d.). Those datasets expand researchers’ ability to compare economic outcomes between people in same-sex couples and people with different-sex partners, but they do not include single people. Other significant data gaps remain. Some samples of older SGD populations are too small for analysis or for detailed comparisons by race or ethnicity.
In addition, no probability-based surveys with individual income measures include questions on transgender status or people with intersex traits, so less is known about the economic status of those groups.
Making comparisons of income among sexual orientation and gender identity categories is a complex task. For example, a recent study of incomes in the 2013–2015 National Health Interview Survey (NHIS) reported average annual earnings; they were $39,903 for heterosexual women but $38,803 for bisexual women and $47,026 for lesbian women. Earnings were $57,033 for heterosexual men, $49,766 for bisexual men, and $59,618 for gay men (Carpenter and Eppink, 2017). However, such simple comparisons of average earnings may be misleading, as differences in the characteristics of groups, such as a higher average education level or different ages, confound observed earnings differences across groups. Accordingly, the rest of this section reviews research from economics and sociology that accounts for other influences on earnings, such as race, sex, age, education, and experience.
Earnings differences by sexual orientation were examined in a recent meta-analysis of 31 studies conducted through 2012, of which 69 percent were from the United States (Klawitter, 2015). After adjusting for key factors that influence earnings, these studies found that, on average, gay and bisexual men earn 11 percent less than comparable heterosexual men, with ranges of 11–16 percent lower wages in the United States and 0–30 percent lower for all countries. The biggest gaps were seen in studies using data on same-sex couples. Earnings for lesbian and bisexual women were nine percent higher than those for heterosexual women on average (the “lesbian premium”). The range of estimates for women was wider than for men, partly because the studies analyzed only full-time workers: differences in earnings between lesbian and bisexual women and heterosexual women ranged from 5 to 15 percent higher earnings for lesbian and bisexual women in the United States and from 25 percent lower earnings to 43 percent higher earnings in studies from all countries.
In general, recent studies continue to find negative earnings gaps for gay and bisexual men (Burn, 2019; Valfort, 2017). However, one U.S. study found a different earnings pattern for gay men in comparison with heterosexual men. An analysis of data from the 2013–2015 NHIS, including more than 1,300 self-identified lesbian, gay, and bisexual people (Carpenter and Eppink, 2017), found that, after controlling for race, age, education, partnership, children, region, and job characteristics, both lesbian women and gay men earned more than their heterosexual counterparts. One possible reason for the unusual finding for men is that the NHIS data did not include a variable for living in an urban area. That variable is important, since urban areas have higher wages and more gay men (Denier and Waite, 2019). More recent studies on earnings differences for lesbian and bisexual
women show mixed results: some studies report higher earnings for them than for heterosexual women (Burn, 2019; Valfort, 2017); other studies report lower earnings (Curley, 2018; Martell, 2019; Martell and Hansen, 2017). For example, one study using data from the ACS found that women under 45 who have female partners have lower earnings than women with male partners, while women over 45 with female partners have the lesbian “earnings premium” (Martell, 2019).
While most studies reviewed by Klawitter (2015) and Valfort (2017) combined gay or lesbian people with bisexual people and compared the combined group to heterosexual men or women, some studies have been able to estimate separate effects for being bisexual and lesbian or gay people. Two such studies found that bisexual men and women (but not gay men or lesbian women) appear to earn less than heterosexuals and less than gay or lesbian people (Carpenter, 2005; Mize, 2016). In contrast, two other studies found either small or insignificant earnings differences for bisexual men and women compared with heterosexuals (Carpenter and Eppink, 2017; Sabia, 2014).
Some researchers have considered specifically whether the sexual orientation effects on income have fallen over time in the United States. Findings from these studies are inconclusive due to design weaknesses, including confounding, small sample sizes, and failure to report the statistical significance of reported differences (Clarke and Sevak, 2013; Cushing-Daniels and Yeung, 2009; Elmslie and Tebaldi, 2014; Klawitter, 2015; Martell and Hansen, 2017).
Interpretations of Earnings Data
The interpretation of reported wage differences by sexual orientation or gender identity is challenging for several reasons: LGBT people are a heterogeneous population, and the effects may be subgroup specific; studies have used different data sources; time periods vary; and the study designs limit extrapolations.
One possible interpretation is that discrimination accounts for some of the observed wage gaps for gay and bisexual men (Badgett, 1995; Blandford, 2003). A recent study found that the wage gap is larger for men in same-sex couples who live in states with more people who are prejudiced against homosexuals (Burn, 2019). Another study argued that discrimination was an unlikely explanation for the observed pay gap among some bisexual people because they are unlikely to be known as bisexual, such as bisexual men with female partners (Sabia, 2014). Finally, a few studies have estimated the effect of statewide employment nondiscrimination laws on wage gaps, finding some evidence that states with those laws have lower earnings gaps for gay men (Burn, 2018; Klawitter, 2011).
A second potential interpretation of earnings differences relates to the household division of labor, or how families, particularly couples, divide up paid work and household work responsibilities. Those decisions directly affect how much time an individual devotes to hours worked in the paid labor market and to earnings, as well as how much individuals invest in building the human capital that may increase earnings over time (Becker, 1991). People who are partnered with or expect to partner with a person of the same sex might make different decisions about education, training, experience, and careers than those who plan to partner with a different-sex partner (Antecol and Steinberger, 2013; Badgett, 1995; Black, Sanders, and Taylor, 2007).
Some analysts have argued that gay men will not expect to support a partner and children, so they will invest less in labor market–specific human capital than heterosexual men, reducing gay men’s earnings (Black et al., 2003). However, as noted in Chapter 9, measures of actual investment in education do not support this argument.
The thesis about the household division of labor may better fit the common, although not universal, pattern of higher earnings for lesbian and bisexual women. Lesbian and bisexual women might expect not to have a higher earning (male) partner who might be expected to provide for them. This expectation might result in greater investment in their own education, training, and experience, thereby raising their wages above those of heterosexual women (Badgett, 2001; Black et al., 2003). However, although studies that report a lesbian premium did control for education, they did not directly measure labor market experience, requiring researchers to use a proxy (age minus years of education minus five). It is possible that researchers might be underestimating the gap in actual experience between lesbian and heterosexual women, which would make lesbian women look like they have higher earnings. The lack of inclusion of measures of sexual and gender diversity in longitudinal surveys has prevented more detailed comparisons of earnings at different stages of life for SGD people, as well as better insight into measuring labor market experience.
Given the gaps and weaknesses in the available data, studies use novel strategies to approximate the sexual orientation difference in labor market experience and explore whether the lesbian premium is related to greater commitment to and experience in the paid labor market. Two studies showed that the return on one year of potential experience is higher for lesbian women than for heterosexual women (Daneshvary, Waddoups, and Wimmer, 2008; Jepsen, 2007), supporting the idea that lesbian women have more unmeasured human capital than heterosexual women. Also, the wage premium is largest for lesbian women who do not have a bachelor’s degree, and it disappears for those with higher levels of education, perhaps because heterosexual women with higher levels of education are also more
committed to the labor market (Daneshvary, Waddoups, and Wimmer, 2008). Notably, the premium is higher for women in same-sex couples who were never married to men (Daneshvary, Waddoups, and Wimmer, 2009). Overall, it appears plausible that lesbian women have higher earnings because of a greater commitment to the paid labor force, an adaptation that might also counteract a potential negative effect of discrimination on lesbian women’s wages.
Overall, making generalizations about the individual earnings of LGBT people is very difficult, and future research is warranted to understand the causes of earnings differences. While the first generation of wage gap studies found a consistent penalty in the United States (and other countries) for gay and bisexual men, more recent studies are less consistent and occasionally find that only bisexual men earn significantly less than heterosexual men. Studies for lesbian and bisexual women have always found a wide range of values, with most U.S. studies showing higher earnings than heterosexual women but lower earnings than gay, bisexual, and heterosexual men, demonstrating the complexity of interpreting wages in the context of a highly gendered labor market.
The wage effects of sexual orientation and gender identity may not be uniform across gender, race, and ethnicity, immigration status, or disability status given the intersecting effects of those personal characteristics, although there has been little research on intersectionality in economic outcomes. Three studies provide direct evidence that cisgender women and SGD people of color are worse off in terms of income than are their male or white counterparts. Two of these three studies used data on same-sex and different-sex couples from the ACS, which has the largest sample sizes of people presumed to be lesbian, gay, or bisexual (del Río and Alonso-Villar, 2019a; Douglas and Steinberger, 2015). Other sources of data have samples too small to support detailed comparisons by race and ethnicity.
Four perspectives demonstrate the variation in the effects of sexual orientation by gender, race, and ethnicity. First, one study showed that white LGB people earned more than Black, Hispanic, and Asian LGB people with the same characteristics, except for Asian lesbian women and Hispanic gay men (del Río and Alonso-Villar, 2019a; Douglas and Steinberger, 2015). Second, lesbian and bisexual women of all races earn less than their same-race male counterparts (del Río and Alonso-Villar, 2019a). Third, all lesbian women earn more than their same-race heterosexual female counterparts, but studies vary in findings about which group of lesbian women has the largest wage premium (Carpenter and Eppink, 2017; del Río and
Alonso-Villar, 2019a; Douglas and Steinberger, 2015). Fourth, a sexual orientation penalty consistently exists for white, Hispanic, and Asian gay men compared with same-race heterosexual men, but the relative earnings of Black gay men vary by study (del Río and Alonso-Villar, 2019a; Douglas and Steinberger, 2015). Relative to white heterosexual men, Black gay men have the largest earnings gap, followed by Hispanic, Asian, and then white gay men (del Río and Alonso-Villar, 2019a).
Because members of households or families are likely to share income, it is useful to know how household income compares across sexual orientation or gender identity. However, there are only a few studies of LGBT household income that control for other predictors of income, which is important for making appropriate comparisons.
Studies of same-sex couples suggest that the gender composition of couples matters greatly. Married different-sex couples and male same-sex couples have the highest household incomes, while female same-sex couples and unmarried different-sex couples have the lowest (Black, Sanders, and Taylor, 2007; Klawitter, 2011). One recent study found that bisexual men had lower household incomes than heterosexual men (Chai and Maroto, 2019). Among couples in which one or both partners were 65 or older, female same-sex couples had significantly lower levels of income than either older male same-sex couples or older married different-sex couples (Goldberg, 2009).
Only one study assessed household income differences by gender identity (Carpenter, Eppink, and Gonzales, 2020). After taking into account differences in the number of adults in the household, health, education, age, race, and other characteristics, transgender women’s household income was 17 percent lower and transgender men’s income 9 percent lower than cisgender people’s household income. However, the income difference was only statistically significant for the transgender women.
Poverty and Economic Insecurity
In the United States, people are classified as poor if their household income falls below the official poverty line for their family size and age configuration (Semega et al., 2019). A growing body of research suggests that at least some groups in the LGBT population—notably, transgender people and bisexual people—have a higher risk of poverty than heterosexual cisgender people. On average, lesbian women and gay men appear to be equally likely to be poor as heterosexuals, although some groups show a higher risk of poverty. In addition to these and similar measures of
poverty, this section also addresses food insecurity and other markers of having insufficient income to provide for human needs that suggest a higher level of economic insecurity for LGBT people.
The findings on relative poverty differ somewhat between studies using data on couples and those using data on self-identity among individuals. First, couple comparison studies have mostly found higher poverty rates for female same-sex couples than for women in married different-sex couples, but lower poverty rates for male same-sex couples than for men in married different-sex couples (Albelda et al., 2009; Badgett, 2018; Badgett, Durso, and Schneebaum, 2013; Prokos and Keene, 2010; Schneebaum and Badgett, 2019). However, studies using ACS or census data also found that, after controlling for other predictors of being poor, such as education, employment, region, residence in a rural area, and race, both male and female same-sex couples are at greater risk of being poor than married different-sex couples.
Second, data on self-identified LGBT people show that bisexual and transgender people are more at risk and lesbian women and gay men at equal risk of poverty compared with heterosexual-identified people. One study pooled 2013–2016 NHIS data that included 2,600 self-identified LGB people (Badgett, 2018); the poverty rate was 14.3 percent for heterosexual women, 13.8 percent for lesbian women, and 27.3 percent for bisexual women; and the poverty rate was 11.0 percent for heterosexual men, 11.7 percent for gay men, and 22.9 percent for bisexual men. After controlling for other predictors, lesbian women and gay men were as likely to be poor as heterosexual people, but bisexual women and men were significantly more likely to be poor than heterosexuals with the same demographic, health, education, and other characteristics.1 A recent study of data from the Behavioral Risk Factor Surveillance System (BRFSS) also found a similar risk of poverty for lesbian women, gay men, and bisexual men compared with their heterosexual counterparts and a significantly higher risk of poverty for bisexual women (Badgett, Choi, and Wilson, 2019).
Transgender people are much more vulnerable to poverty than are cisgender heterosexual, lesbian, and gay people according to two analyses of BRFSS data (Badgett, Choi, and Wilson, 2019; Carpenter, Eppink, and Gonzales, 2020). The poverty rate for transgender men was 33.7 percent, for transgender women 29.6 percent, and for gender-nonconforming people 23.8 percent; in comparison, the rate for cisgender heterosexual men was 13.4 percent, and for cisgender heterosexual women it was 17.8 percent
1 It is important to note, however, that the public-use NHIS dataset used in this study does not include a measure of urban residence, where wages are higher. As a result, the greater urban concentration of gay men than heterosexual men, in particular, could bias the poverty difference for gay men in the multivariable analysis.
(Badgett, Choi, and Wilson, 2019). After controlling for predictors of poverty, transgender people (combined) had 70 percent higher odds of being poor than cisgender heterosexual men and 38 percent higher odds of being poor than cisgender heterosexual women. Similarly, the 2015 U.S. Transgender Survey (USTS), which is a large, purposive, community-based sample, found that one-third of transgender and gender-nonconforming adult respondents were living in poverty (James et al., 2016).
In addition to disaggregating the LGBT population, some research provides insights into subgroups of the LGBT population who are at greater or lesser risk of poverty.
- LGB people in couples, especially married couples, are less likely to be poor than single LGB people, based on 2013–2016 NHIS data (Badgett, 2018). These differences by marital status could reflect selection into marriage or the poverty-reducing effects of marriage.
- Same-sex couples and lesbian and bisexual women with children are more likely to be poor than childless couples or LGB women (Badgett, 2018; Brown, Manning, and Payne, 2016; Schneebaum and Badgett, 2019). Also, the poverty rates for same-sex couples raising children were twice as high as the rates for married different-sex couples raising children (Albelda et al., 2009; Badgett, Durso, and Schneebaum, 2013).
- Blacks who identify as LGBT or are in same-sex couples have higher poverty rates than white LGBT people or same-sex couples and higher rates than non-LGBT Blacks (Badgett, Choi, and Wilson, 2019; Badgett, Durso, and Schneebaum, 2013).
- People whose sex assigned at birth is female—women in same-sex couples and lesbian women generally, as well as transgender men—have higher rates of poverty than do all groups of cisgender men (Badgett, Choi, and Wilson, 2019).
- Among LGBT people, 26 percent living in rural areas are poor, compared with 21 percent of those living in urban areas (Badgett, Choi, and Wilson, 2019).
- In data from Washington state, LGB people 50 and older are as likely as heterosexuals to have incomes that are less than or equal to 200 percent of the poverty level (Fredriksen-Goldsen et al., 2013). Almost half (47 percent) of transgender people 50 and older had similarly low incomes in a recent survey (Fredriksen-Goldsen et al., 2014).
Relatedly, several characteristics that are more common for LGB people may provide some protection from poverty, most notably higher levels of education and labor force participation, a lower probability of having chil-
dren, and living in urban areas (Badgett, Choi, and Wilson, 2019; Schneebaum and Badgett, 2019). Each of those factors tends to reduce the risk of poverty in general and therefore contributes to reducing the potential gap between LGB and heterosexual poverty rates.
The research on poverty is corroborated by other measures that indicate economic insecurity. An analysis from the National Longitudinal Study of Adolescent to Adult Health found that female sexual minorities were more likely than heterosexual women to have personal incomes in the near-poverty range (100–199 percent of the poverty level); both sexual minority women and men were more likely than heterosexuals to have experienced economic hardship in the past 12 months (such as unpaid rent or utility bills) (Conron, Goldberg, and Halpern, 2018).
Receiving means-tested benefits is another marker of economic insecurity. Same-sex couples are more likely to receive cash or cash-like public assistance benefits (such as Temporary Assistance to Needy Families and the Supplemental Nutrition Assistance Program [SNAP, food stamps]) than are married different-sex couples (Badgett, Durso, and Schneebaum, 2013). Using several population-based surveys between 2011 and 2014, one study found that LGBT adults are more likely to report food insecurity and more likely to participate in the SNAP program than are non-LGBT adults (Brown, Romero, and Gates, 2016). Disparities were higher among bisexual people, women, young adults, and people of color. Other data also suggest that LGBT people overall have higher rates of use of Medicaid and SNAP than non-LGBT people (Rooney, Whittington, and Durso, 2018). Little is known about how low-income SGD populations are treated when seeking services and public assistance, but given the existence of bias in other economic settings, it is possible bias would also exist in public services. Policy simulations suggest that raising the minimum wage and reducing gender and racial wage gaps would reduce LGBT poverty (Badgett and Schneebaum, 2015, 2016).
These research studies have focused on economic insecurity, but many related topics are either mostly or completely unexplored (Burwick et al., 2014). For example, only a few studies have attempted to identify economic issues for aging LGBT people. Surveys show that the LGBT population is young and growing among younger cohorts (see Chapter 3), but older cohorts have faced different historical contexts and might have diminished social and financial resources in retirement, requiring particular policies and services (Fredriksen-Goldsen, 2016). In addition, very little is known about the pathways into poverty or the barriers to leaving poverty for SGD populations. Higher take-up rates for means-tested programs might also disguise differences in treatment and experiences of LGBT people: exploring this issue would require administrative data and other research efforts. No research has focused on how inclusive or effective human services and
programs are for LGBT adults, nor have studies assessed the effectiveness of other services that are more directly targeted to low-income LGBT people. There has also been little systematic research about the interactions between poverty and the criminal justice system (Hunter, McGovern, and Sutherland, 2018). Finally, one in five respondents to the USTS reported that they had worked in the underground economy at some time in their lives, particularly in the sex or drug trades (James et al., 2016). A small body of available research links participation in survival economic work with arrests and incarceration (Fitzgerald, Elspeth, and Hickey, 2015; James et al., 2016) and social services discrimination (Bakko, 2019).
Occupational Attainment and Segregation
People’s occupations provide an additional indicator of socioeconomic status. Only a few studies have directly addressed this issue, finding that LGB people have different occupational patterns than do heterosexuals (del Río and Alonso-Villar, 2019a, 2019b; Pearson and Wilkinson, 2017; Tilcsik, Anteby, and Knight, 2015; Ueno, Peña-Talamantes, and Roach, 2013; Ueno, Vaghela, and Nix, 2018). These differing patterns of occupational attainment by an ascribed status, like gender identity and sexual orientation, are generally called occupational segregation. Occupational segregation matters because occupation is an important determinant of earnings, and it also reflects the inclusiveness of labor markets for SGD populations.
The studies of earnings discussed above usually controlled for occupation in their analyses, and several of them also highlighted that LGB people are overrepresented or underrepresented in particular occupational categories when compared with non-LGBT people (Antecol, Jong, and Steinberger, 2008; Badgett, 1995; Baumle, Compton, and Poston, 2009). One study analyzing detailed occupational data for same-sex partners and different-sex partners in the ACS found clear patterns of occupation segregation: 22.5 percent of people in same-sex couples would have to change their occupations in order to have the same occupational distribution as the overall economy, compared with only 9 percent of people in different-sex couples who would have to change (del Río and Alonso-Villar, 2019b).
Researchers are divided about whether occupational segregation by sexual orientation is a positive or negative outcome. For example, one consistent finding across studies is that gender plays a smaller role in the sorting of LGB individuals into occupations than it does for heterosexual people (Badgett and King, 1997; Baumle, Compton, and Poston, 2009; del Río and Alonso-Villar, 2019b; Ueno, Roach, and Peña-Talamantes, 2013). More specifically, lesbian and bisexual women are in occupations with a
higher percentage of men than are heterosexual women; gay and bisexual men are in occupations with a higher percentage of women than are heterosexual men. These patterns might be seen as positive if LGB people feel less constrained by early socialization or by gendered expectations about appropriate occupations than do heterosexual men and women. However, stereotyping and discrimination may also generate gendered barriers that shape those patterns. For instance, gay and bisexual men are less likely to be hired into jobs requiring stereotypically masculine characteristics (such as being assertive or aggressive), and lesbian and bisexual women are less likely to be hired when employers seek stereotypically feminine characteristics (such as being cheerful or gentle) (Ahmed, Andersson, and Hammarstedt, 2013; Drydakis, 2015; Tilcsik, 2011).
Stigma may also shape occupational choices of sexual and gender minorities in other ways. Compared with heterosexual people, LGB people are found in occupations that involve more task independence and social perceptiveness, which might protect them against discrimination and harassment if they were to disclose their sexual orientation (Martell, 2018; Tilcsik, Anteby, and Knight, 2015). Also, some evidence from Australia and the United States suggests that LGB people seek out occupations where they will have more tolerant coworkers (Badgett and King, 1997; Plug and Webbink, 2014).
One way to assess whether occupational segregation is benign would be to see its effect on earnings, and two studies suggest that this relationship is complicated by the role of education in both occupational attainment and income. The occupational patterns of men in same-sex couples tend to raise their earnings relative to the average for people in different-sex couples, while women in same-sex couples get only a tiny bump in earnings from their occupational patterns (del Río and Alonso-Villar, 2019b). However, those gains are largely because of individuals’ relatively high education levels. After controlling for education and other relevant characteristics, the gains from occupations shrink for men in same-sex couples and are negative for women of all races in same-sex couples. Also, those gains are not the same across race, and it is mainly white and Asian people in same-sex couples who gain from occupational sorting, while Black and Hispanic people in same-sex couples are in occupations that tend to reduce their earnings relative to all earners (del Río and Alonso-Villar, 2019a). A study of one young cohort found that young women who had sexual contact with women in young adulthood had lower status occupations (measured by education and income in occupations) than those with early sexual contact or no sexual contact with women, at least partly because of lower levels of education (Ueno, Peña-Talamantes, and Roach, 2013). In contrast, young men who had dating relationships with men in young adulthood were in higher status occupations than men without same-sex
dating or those with early same-sex dating, at least partly because of their higher education levels.
In sum, research has established differences in occupational patterns across sexual orientation. But the research on how and why sexual and gender diversity shape occupational segregation is at an early stage. Further research will be necessary to distinguish the extent to which occupational segregation reflects stigma-related stereotyping and barriers or reflects greater freedom from gender stereotypes.
Research conducted over several decades has found that SGD populations face stigma and unequal treatment in the workforce. Assessments of discrimination toward SGD employees come in a variety of forms, but there are as yet no studies in the United States of discrimination against people with intersex traits. Self-reports of discrimination show that many LGBT people perceive that they have been treated unequally in the workforce. For example, findings from a 2017 survey using a national probability sample of more than 3,400 LGBT adults showed that one in five reported experiencing discrimination associated with their LGBT status when applying for a job (National Public Radio, 2017). A 2017 study of federal agencies in the fields of science, technology, engineering, and mathematics found that LGBT employees reported more negative workplace experiences than their non-LGBT colleagues (Cech and Pham, 2017). More than 9,000 people filed charges of employment discrimination based on either sexual orientation or gender identity discrimination with state and federal nondiscrimination agencies over the 2013–2016 period (Baumle, Badgett, and Boutcher, 2019).
The 2015 USTS includes substantial self-reporting of workplace discrimination by transgender and gender-nonconforming people: 19 percent report being fired, denied a promotion, or not getting hired due to their gender identity or expression (James et al., 2016). Other studies of nonrandom samples of transgender people reveal a range of workplace experiences when transitioning (Brewster et al., 2014; Dietert and Dentice, 2010; Lombardi and Malouf, 2001; Ruggs et al., 2015). In some cases, transgender workers report having supportive workplaces and positive experiences, while others have more negative experiences, including coworkers’ refusal to use proper pronouns and negative treatment for deviating from gender norms. One study compared non-binary transgender people to transgender men and transgender women, finding that transgender women often reported the worst workplace outcomes in terms of unemployment, underemployment, and discrimination (Davidson, 2016).
Several audit studies that consider employer responses to resumes provide additional evidence of employment discrimination. These studies involve carefully constructed experiments to see if applicants who are sexual and gender minorities, as indicated primarily by activities on a resume, are treated differently than cisgender heterosexual applicants. A large U.S. study found that openly gay men in many states were less likely to be invited to a first-round interview than otherwise identical straight men (Tilcsik, 2011). That study implied that a gay man would have to apply to 14 jobs to get an interview while a heterosexual man would have to apply for only 9. A similar result was found for LGBT women in the United States (Mishel, 2016). A third experiment found evidence that racial and sexual stereotypes might interact in unexpected ways: Black gay male job applicants were seen as less threatening and as deserving of higher salaries than Black heterosexual male job candidates (Pedulla, 2014). However, transgender people in New York City who applied in person for jobs were significantly less likely to receive job offers for retail sales positions than cisgender applicants with comparable fictionalized resumes (Make the Road New York, 2010). Studies in other countries also find potentially discriminatory hiring practices for gay men and lesbian women in Sweden and the United Kingdom and for transgender people in four Asian countries (Ahmed, Andersson, and Hammarstedt, 2013; Drydakis, 2015; Winter et al., 2018). A challenge associated with experimental designs that focus on reaction to resumes is that they are generally limited to entry-level positions; assessments of discrimination at later career stages are limited.
Other possible evidence of employment discrimination comes from disparities in the probability of unemployment, defined as being available and searching for a job. Analyses of population-based data from Gallup show that 9 percent of LGBT-identified adults report being unemployed compared with 5 percent of non-LGBT adults. The 2015 USTS found that 15 percent of transgender and gender-nonconforming adult respondents said they were unemployed (James et al., 2016), and another study shows that, after controlling for other predictors of unemployment in BRFSS data, transgender people were more likely than cisgender men to be unemployed (Carpenter, Eppink, and Gonzales, 2020). In general, the research base is too thin to draw conclusions about unemployment disparities.
Many important research topics are understudied related to the experiences of LGBT people in the workplace. Expanding the research base will be necessary to better identify the sources of disadvantage and to design and evaluate interventions to reduce discrimination. Such research might include analyzing variation in the experiences of SGD populations by other important characteristics, such as race and ethnicity; variation by geographic location, in relation to policy and attitudes; and varia-
tion by industry and occupation. Research that studies the attitudes and behaviors of supervisors and coworkers of LGBT people might provide additional insights.
SGD populations experience compensation discrimination in the workplace, which includes unequal treatment between same-sex and different-sex couples regarding health insurance benefits and parental leave and access to transition-related care for transgender populations. Prior to the national legalization of marriage for same-sex couples in 2015, several studies documented disparities in access to health insurance among same-sex couples and their children (Ash and Badgett, 2006; Buchmueller and Carpenter, 2010, 2012; Heck, Sell, and Gorin, 2006; Ponce et al., 2010), with larger disparities for Hispanic men, Black women, and Native American and Alaskan women (Gilbert and Ortiz, 2015; Gonzales and Blewett, 2013). Both qualitative and quantitative studies have shown that LGBT employees in some firms formed “employee resource groups” that were influential in convincing employers to offer domestic partner benefits to employees with same-sex partners (Badgett, 2001; Raeburn, 2004; Briscoe and Safford, 2008; Creed, Douglas, and Scully, 2000), and unions sometimes bargained for these benefits (Boris, 2010; Holcomb, 1999). Access to the right to marry appears to have reduced disparities in health insurance among same-sex couples (Carpenter et al., 2018), although the research is too preliminary to draw strong conclusions.
More generally, several studies have documented changes in access to insurance coverage among SGD populations in relation to passage of the Affordable Care Act (ACA). In 2013, prior to the full implementation of the ACA, 34 percent of a nationally representative sample of LGBT people making less than $45,000 per year were uninsured (Baker, Durso, and Cray, 2014). Uninsurance among LGBT people in this income bracket dropped to 26 percent in 2014 and to 22 percent in 2017 (Baker and Durso, 2017). Data from the Health Reform Monitoring Survey similarly indicated that the share of LGB adults without health insurance across all income ranges decreased from 21.7 percent to 11.1 percent between 2013 and 2015 (Karpman, Skopec, and Long, 2015). Still, a 2017 analysis of Gallup data found that LGBT-identified adults remained less likely to report having health insurance than their non-LGBT counterparts (15 percent and 12 percent, respectively), though this finding did not account for age differences in the two populations: LGBT-identified individuals were younger.2 (See more detailed discussion in Chapter 12 on health care access.)
For transgender people, insurance exclusions for transition-related care have historically been a common problem in employer plans. In 2012, the Corporate Equality Index began to require self-insured employers to remove these exclusions from their employee benefits in order to receive a full score. By 2019, 62 percent of Fortune 500 employers, representing a 16-fold increase since 2010, had eliminated transgender exclusions from the coverage they offer their employees (Human Rights Campaign, 2019). The Federal Employees Health Benefits Program required participating carriers to eliminate transgender exclusions in 2016 (U.S. Office of Personnel Management, n.d.), and at least 17 state governments and the District of Columbia also offer employee benefits that include transition-related care (Movement Advancement Project, 2020). In a related trend, several courts have found that transgender exclusions in employer-sponsored insurance violate Title VII of the federal Civil Rights Act, which bans sex discrimination in employment, as well as Section 1557 of the ACA, which bans sex discrimination in health care and insurance (Glasser and Labbees, 2018).
Access to Military Service
Research suggests that military service can be a route to better economic outcomes, especially for marginalized populations, and the military is a large employer of SGD people (Martorell et al., 2014; Routon, 2014). Estimates from a 2010 study suggested that 2.2 percent of active and reserve forces in the U.S. military were lesbian, gay, or bisexual (Gates, 2010). A 2014 study estimated that 0.6 percent of U.S. active and reserve forces are transgender. The lifting of the “don’t ask, don’t tell” policy in 2010 meant that lesbian, gay, and bisexual individuals could serve openly in the U.S. military, but transgender individuals are currently banned from military service. The economic effects on individual LGBT people of both the lifting of the “don’t ask, don’t tell” policy and the continuation of the ban on transgender people are unknown. Given the research suggesting positive economic benefits of military service among marginalized populations, it seems reasonable to assume that the ban on transgender military service effectively closes an avenue for economic advancement for this already economically disadvantaged population.
Workplace Disclosure of Sexual Orientation and Gender Identity
Another important factor in assessing the effects of workplace discrimination is the degree to which SGD populations are “out” in their workplace environments. A 2013 population-based survey of LGBT adults conducted by the Pew Research Center found that, even though one-half of employed LGBT adults think their workplace is accepting of LGBT employees, only
one-third say they are open to most of their work colleagues about their sexual orientation or gender identity. Openness about sexual orientation is much higher among lesbian women and gay men (50 percent and 48 percent, respectively) than bisexual individuals (11 percent). Notably, LGBT adults are more out to family and friends than to their work colleagues. More than half of respondents said they were out to all or most of the important people in their lives. However, like the responses about the workplace, lesbian women and gay men were far more likely to be out (71 percent and 77 percent, respectively) than their bisexual counterparts (28 percent). However, the research base on workplace disclosure and its relationship to economic outcomes is very thin, at least in part because large-scale surveys that include sexual orientation and gender identity questions do not also include questions on workplace disclosure. Future research could approach disclosure as both an outcome variable that measures the workplace climate and as an explanatory variable that may predict other outcomes, such as experiencing discrimination, wage gaps, job turnover, and productivity.
Employment discrimination against public-sector workers is prohibited by the Equal Protection Clause of the Fourteenth Amendment. Until the Supreme Court’s Bostock vs. Clayton County decision in 2020, the status of protection against private-sector discrimination was uncertain, even though coverage had been extended by federal agencies and some federal courts (see Chapter 5). Between 2013 and 2016, more than 9,000 people filed charges of employment discrimination with state and federal nondiscrimination agencies on the basis of either sexual orientation or gender identity discrimination (Baumle, Badgett, and Boutcher, 2019). Enforcement agencies might increase the likelihood of a charge being filed when employees believe they face discrimination by making filing methods more transparent and accessible, as some European human rights agencies have attempted (Organization for Economic Cooperation and Development [OECD], 2020).
Evidence suggests that laws banning workplace discrimination based on sexual orientation have positive economic effects for sexual minority populations. Studies prior to 2020 found that gay men and men in same-sex couples saw lower wage gaps in locations where there was a state anti-discrimination law (Klawitter, 2011). An audit study of resumes found lower levels of discrimination toward gay men in states with antidiscrimination laws (Tilcsik, 2011). A more recent study also found that state anti-discrimination laws are associated with increased wages for gay men, but it also found an association with decreased employment among lesbian women (Burn, 2018). Additional research is needed into the policy
effects on other economic outcomes, as well as exploring more directly the effects of nationwide nondiscrimination laws on transgender people and on groups within LGBT populations. Early research on the effects of marriage equality suggests that such a policy change may be linked to higher rates of employment, more mortgage applications, and more health insurance coverage (Carpenter et al., 2018; Downing and Cha, 2020; Miller and Park, 2018; Sansone, 2019).
Some businesses and other private-sector employers have implemented their own sexual orientation and gender identity nondiscrimination protections that cover employees regardless of state of residence. In some cases, qualitative research suggests those changes in policy emerged because of direct pressure from the employer’s own employees (Badgett, 2001; Raeburn, 2004) or from unions, as noted above. As of the writing of this report, 93 percent of Fortune 500 companies have sexual orientation nondiscrimination policies, and 91 percent of Fortune 500 companies had gender identity protections (Human Rights Campaign, 2020). Other “best practices” by employers in the United States and globally include equal benefits, internal training on employer policies, prejudice-reduction trainings, clear guidelines for gender transitions, and employee resource groups (Human Rights Campaign, 2020; OECD, 2020).
Private-sector workplaces that have policies that affirm the inclusion of SGD people and prohibit discrimination based on sexual orientation and gender identity are associated with positive outcomes for both the businesses and their employees. A review of 36 studies using nonprobability samples found that LGBT-supportive policies and affirming workplace climates are often associated with greater job commitment, improved workplace relationships, increased job satisfaction, and improved health outcomes among LGBT employees (Badgett et al., 2013). LGBT employees also reported an association between LGBT-affirming organizations and less discrimination and more openness. Comparisons of companies with and without LGBT-inclusive policies show that more inclusive companies report higher stock prices, return on assets, productivity, and more patents (Gao and Zhang, 2016; Johnston and Malina, 2008; Li and Nagar, 2013; Pichler et al., 2018; Shan, Fu, and Zheng, 2017; Wang and Schwarz, 2010).
Access to housing is another measure of economic well-being. This topic has received much less research attention than issues of employment, but it is important for several reasons. First, housing is a necessary resource to sustain life, and evidence of high rates of homelessness for LGBT young people indicates a pressing social and individual problem. Second, home ownership is both a means to obtain housing and an asset that makes up a
significant part of wealth for people in the United States, and evidence of disparities in home ownership between same-sex couples and different-sex couples have implications for differences in the wealth of SGD populations. Third, because of stigma, SGD populations may face barriers in the markets for credit and rental housing. Data on housing outcomes with measures of sexual orientation and gender identity (or other SGD markers) are limited, so the body of research reviewed in this section includes existing studies of population-based data, but it relies heavily on nonprobability samples and experiments to study disadvantages related to housing.
Existing studies show an elevated risk of homelessness among LGBT youth. An analysis of data from eight states using the population-based Youth Risk Behavior Survey found that LGB youth were twice as likely as their non-LGB counterparts to experience homelessness (Cutuli, Treglia, and Herbers, 2019). Surveys of homeless youth service providers also indicate elevated risks of homelessness among LGBTQ youth, with a higher risk among youths of color. Providers have reported that LGBTQ youth experience longer periods of homelessness than their non-LGBTQ counterparts, and service patterns suggest particular increases in transgender youth accessing services for homelessness (Choi et al., 2015). A systematic review of literature identified four main themes associated with LGBTQ+ homelessness: stigma, discrimination, and exclusion; mental health issues and substance use; sexual risks and vulnerability; and interventions and supports (McCann and Brown, 2019).
Studies of adult homelessness among the LGBT population reveal that adult LGBTQ+ people are also vulnerable to homelessness. In one recent study based on nationally representative samples, 3 percent of sexual minority and 8 percent of transgender adults reported having experienced homelessness in the previous 12 months, compared with only 1 percent of cisgender heterosexual adults (Wilson et al., 2020). A recent systematic literature review found that many homeless LGBT adults have challenges associated with HIV and substance use (Ecker, Aubry, and Sylvestre, 2019).
Evidence suggests that adult homelessness may be particularly acute among transgender and gender-nonconforming populations. In the USTS, nearly one-third of respondents reported having ever experienced homelessness, and 12 percent reported being homeless within the past year (James et al., 2016). The New York state 2015 LGBT Health and Human Services Needs Assessment, a community survey of nearly 3,800 people, found that transgender respondents were substantially more likely to report housing insecurity (50 percent), defined as having difficulty paying for housing accommodation, than they were to report having ever been homeless
(31 percent) (Frazer and Howe, 2015). The New York study highlights a potential gap in the literature addressing homelessness issues among SGD populations, which focuses on a limited assessment of variation in forms of homelessness (e.g., sleeping outdoors, group shelters, “couch surfing” with friends or acquaintances) and rarely considers the extent or effects of housing insecurity. Transgender and gender-nonconforming adults in homelessness systems have reported experiencing frequent concerns regarding safety and gender-affirming supports. One study found that most shelters were not willing to house a transgender homeless woman in accordance with her gender identity (Rooney, Durso, and Gruberg, 2016).
Home Ownership and Wealth
Home ownership is both a source of housing services and an important source of wealth. Some research finds that LGBT populations have lower home ownership rates than cisgender heterosexual people. The 2015 USTS found only 16 percent of transgender and gender-nonconforming adult respondents indicated that they owned their homes, compared with more than 60 percent of all U.S. adults (James et al., 2016). Same-sex couples and sexual minorities are less likely to be homeowners than are heterosexuals after controlling for income and demographic factors (Conron, Goldberg, and Halpern, 2018; Jepsen and Jepsen, 2009; Leppel, 2007). More recent analyses still find lower home ownership rates among married same-sex couples than their married different-sex counterparts, but unmarried cohabiting same-sex couples are more likely to own their homes than unmarried different-sex couples (Gates, 2015). A 2016 study suggests that the introduction of legal marriage for same-sex couples has led to increases in mortgage applications among same-sex couples (Miller and Park, 2018).
Differences in home ownership can be associated with a wide array of possible disparities related to sexual and gender diversity. A gap in ownership rates can be a sign of discrimination in mortgage lending practices. Evidence suggests that same-sex couples experience mortgage discrimination. In a large-scale study of mortgage lending data, same-sex couples were 73 percent more likely than different-sex couples to be denied a mortgage, and they were charged up to 0.2 percent higher fees or interest rates. Also, a neighborhood’s higher same-sex couple population density adversely affects both same-sex and different-sex borrowers’ lending experiences (Sun and Gao, 2019). A gap could also be a sign of housing insecurity, meaning that SGD populations are more likely than others to lack sufficient resources to buy a home. Finally, differences in home ownership rates offer evidence of differences and possible disparities in asset and wealth accumulation.
Research that considers disparities in asset accumulation and wealth associated with SGD populations is rare. Population-based data resources to
comprehensively assess these issues do not exist. Although home ownership is occasionally measured, no major U.S. national population-based survey that measures assets and wealth includes measurements of sexual orientation and gender identity, creating a large knowledge gap that requires further research. This gap in knowledge about wealth is particularly problematic for assessing the economic well-being of aging SGD populations, who may receive fewer transfers of wealth from unsupportive families of origin and may have fewer children to count on for unpaid assistance with their needs in old age.
Discrimination in Rental Housing
Research shows that rental-related housing discrimination associated with sexual orientation and gender identity exists, but the extent of that discrimination is not well documented. Findings from the 2011 National Transgender Discrimination Survey (NTDS) and the 2015 USTS show substantial self-reporting of housing discrimination. The NTDS found that 19 percent of respondents reported having ever been refused a home or apartment, and 11 percent reported being evicted because of their gender identity or expression (Grant, Mottet, and Tanis, 2011). Nearly one-quarter (23 percent) of USTS respondents said they had experienced housing discrimination in the past year, which included evictions and being denied a home or apartment because of their transgender or gender-nonconforming status (James et al., 2016). Findings from an internet-based U.S. probability sample of lesbian, gay, and bisexual adults showed that 10 percent reported experiencing housing discrimination, with gay men and lesbian women reporting more discrimination than their bisexual counterparts (Herek, 2009).
In studies other than self-reports, researchers have found differential treatment of LGBT people in experiments that compare responses to LGBT people to those of non-LGBT people at key stages of the rental process, particularly in the initial response to a rental ad. Using telephone and in-person paired testing, two fair housing organizations found differential treatment between LGBTQ individuals and their heterosexual cisgender counterparts (Equal Rights Center, 2014; Fair Housing Centers of Michigan, 2007). A study sponsored by the U.S. Department of Housing and Urban Development (HUD) found that same-sex male couples were significantly less likely than their different-sex couple counterparts to receive email responses from housing providers (Friedman et al., 2013). A separate academic study of email responses to inquiries about rental listings on Craigslist found discrimination against male same-sex couples, with the largest amount of discrimination against Black and Hispanic male couples (where race was designated through names) (Schwegman, 2019). The treatment of Black
male couples was less unequal in states that ban discrimination against sexual orientation in housing. The Black male couples also received fewer positive responses from property owners. Studies in Sweden and Canada have also found differential treatment between same-sex male and different-sex couples (Ahmed and Hammarstedt, 2009; Lauster and Easterbrook, 2011). One audit study of senior housing in 10 states found that same-sex couples experienced adverse differential treatment in comparison with different-sex couples in almost half of the tests conducted (Equal Rights Center, 2014).
The Urban Institute used in-person, telephone, and email testing to conduct one of the most recent and largest studies of LGBT-related housing discrimination in three metropolitan areas: Dallas-Fort Worth, Los Angeles, and Washington, D.C. (Levy et al., 2017). Their paired-testing study (funded by HUD) assessed differences between same-sex and different-sex couples and differences between transgender and genderqueer individuals compared with their cisgender counterparts. As with other studies, this study found more evidence of differential and discriminatory treatment among men in same-sex couples than among women in same-sex couples. Providers told gay men about fewer available rental units and were slightly less likely to schedule an appointment with them. Gay men were also quoted higher average yearly costs than were heterosexual men. Treatment of same-sex couples, regardless of gender, did not differ much by race or city. Relative to cisgender testers, transgender testers were told about fewer units. Of note, the Urban Institute study was considered a pilot test of methodologies used to assess differential treatment based on sexual orientation and gender nonconformity. The study included several tests of different approaches with regard to selection of testers, disclosure of sexual orientation or gender identity, and a comparison of email and in-person assessments of discrimination.
The social science research on the economic well-being of SGD populations has focused mainly on comparisons of lesbian, gay, and bisexual people with heterosexual people. More recently, data on transgender people have allowed for some comparisons with cisgender populations. The research, which has analyzed earnings, household income, poverty, education, and occupational attainment, reveals a picture of economic inequality for LGBT people. Some research is at an early stage or is limited by currently available data. Accordingly, this chapter notes many unmet data needs and research opportunities. In particular, interventions that may currently exist to enhance well-being and to reduce inequality for SGD groups in these economic contexts are inadequate and untested. However, several general findings on economic well-being emerge from the existing research.
Evidence suggests that transgender people—and possibly bisexual people—have lower incomes and higher poverty than lesbian, gay, and cisgender heterosexual people. Lesbian women and gay men may have mitigated some of the effects of discrimination on earnings and household income through adaptive strategies in education, occupations, and family decisions, but they still face discrimination in the labor force. Research on individual earnings suggests that, after controlling for differences in income-related characteristics, gay and bisexual men earn less than heterosexual men, while lesbian and bisexual women earn less than heterosexual men but more than heterosexual women.
These general findings have been made possible by the growing availability of datasets that have measures of income as well as measures of sexual orientation or gender identity, thus improving the ability to analyze income differences by sexual orientation and gender identity. However, significant data gaps remain. Some samples are too small for analysis of older SGD populations or for detailed comparisons by race or ethnicity. In addition, no probability-based surveys with individual income measures include questions on transgender people or people with intersex traits. Some researchers have asked specifically whether sexual orientation effects on income have fallen over time in the United States. Findings from these studies are inconclusive.
Poverty and economic insecurity are more common among LGBT people than among cisgender, heterosexual people. Poverty rates are higher for female same-sex couples and lower for male same-sex couples than for married different-sex couples, which at least partly reflects the gender composition of the couple. But after adjusting for other predictors of being poor, both male and female same-sex couples are at greater risk of being poor than married different-sex couples. Among self-identified single and coupled LGBT people, bisexual and transgender people are more at risk of poverty and lesbian and gay people are at equal risk of poverty than self-identified heterosexual cisgender people of the same sex. Some groups within the LGBT population are at greater risk of poverty or low-income status: unmarried people, people with children, Black people, people living in rural areas, and people over age 50. Some studies suggest that food and housing insecurity are greater among LGBT people than among cisgender heterosexual people.
In the workforce, lesbian and bisexual women are in occupations with a higher percentage of men than are heterosexual women; gay and bisexual men are in occupations with a higher percentage of women than are heterosexual men. These patterns might be seen as positive if LGB people feel less constrained by gendered expectations about appropriate occupations than do heterosexual men and women. However, stereotyping and discrimination may also generate gendered barriers that shape those patterns. Access to the right to marry appears to have reduced disparities in health insurance among same-sex couples, and changes in access to insurance coverage among SGD populations in relation to passage of the ACA have improved conditions for previously uninsured individuals.
Studies based on self-report data show that many LGBT people perceive that they have been treated unequally in the workforce. Many individual employers have created their own voluntary nondiscrimination policies. SGD populations have also experienced compensation and benefit discrimination in the workplace. In 2020, the Supreme Court held that discrimination based on sexual orientation or gender identity is prohibited by Title VII, the federal law that is part of the 1964 Civil Rights Act (Bostock v. Clayton County). The efficacy of this clarity about nationwide anti-discrimination protections will depend on how well federal and state agencies and courts carry out its mandate.
Access to housing is another measure of economic well-being for sexual and gender diverse populations, but data on housing outcomes with measures of sexual orientation and gender identity are somewhat limited. Those limited data show significant disparities for SGD people.
There is a greater risk of homelessness among LGBTQ youth, with elevated risk for LGBTQ youth of color, than other youth. Adult homelessness may be particularly acute among transgender and gender-nonconforming populations. There are four main factors associated with LGBTQ homelessness: stigma, discrimination, and exclusion; mental health issues and substance use; sexual risks and vulnerability; and a lack of access to interventions and supports.
Some research finds that LGBT populations have lower home ownership rates than cisgender heterosexual people. Differences in home ownership can be associated with a wide array of possible disparities related to
sexual and gender diversity and can point to discrimination in mortgage lending practices. Differences in home ownership rates offer evidence of possible disparities in asset and wealth accumulation, but there are no population-based data that comprehensively assess these issues.
Because of stigma, SGD populations may also face barriers in the markets for credit and rental housing. Nearly a quarter of respondents to the 2015 U.S. Transgender Survey said they had experienced housing discrimination in the past year, and there is evidence of more differential and discriminatory treatment among men in same-sex couples than among women in same-sex couples.
Many outstanding questions about the economic well-being of SGD people can be addressed with enhanced research that addresses known disparities and data gaps. For instance, research on lifetime workforce experience could measure the effects of labor force participation and human capital differences on income differences for SGD populations. Research on the influences on occupational attainment could address the roles of gender and sexuality stereotypes, preferences, barriers, and workplace characteristics. As access to health care is a critical component of well-being, it is important to also study how the provision of LGBT-relevant health care benefits, including same-sex partner benefits and transition-related care benefits, affect SGD communities.
Much more research is needed to assess the economic well-being of transgender people, non-binary people, and people with intersex traits. From wealth and asset accumulation to homelessness and housing insecurity, there is much more to be understood about how certain economic conditions affect SGD populations, particularly for groups identified as having bigger economic challenges, such as people in rural areas, older SGD people, and SGD people of color.
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