城市研究所：30年来住房拥有率性别差距的下降【英文版】

HOUSING FINANCE POLICY CENTER RESEARCH REPORT A Three-Decade Decline in the Homeownership Gender Gap What Drove the Change, and Where Do We Go from Here? Jung Hyun Choi URBAN INSTITUTE August 2021 Laurie Goodman URBAN INSTITUTE Jun Zhu INDIANA UNIVERSITY BLOOMINGTON ABOUT THE URBAN INSTITUTE The nonprofit Urban Institute is a leading research organization dedicated to developing evidence-based insights that improve people’s lives and strengthen communities. For 50 years, Urban has been the trusted source for rigorous analysis of complex social and economic issues; strategic advice to policymakers, philanthropists, and practitioners; and new, promising ideas that expand opportunities for all. Our work inspires effective decisions that advance fairness and enhance the well-being of people and places. Copyright © August 2021. Urban Institute. Permission is granted for reproduction of this file, with attribution to the Urban Institute. Cover image by Tim Meko. Contents Acknowledgments iv Executive Summary v The Homeownership Gender Gap 1 Overall Trends 3 How Socioeconomic Characteristics Affect the Homeownership Gender Gap 8 The Homeownership Gender Gap, by Race and Ethnicity 22 Policy Recommendations 42 Appendix 45 Notes 47 References 48 About the Authors 49 Statement of Independence 51 Acknowledgments This report was supported by the Housing Finance Innovation Fund, a group of organizations and individuals that support high-quality independent research that informs evidence-based policy development. We are grateful to them and to all our funders, who make it possible for Urban to advance its mission. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Funders do not determine research findings or the insights and recommendations of Urban experts. Further information on the Urban Institute’s funding principles is available at urban.org/fundingprinciples. We would also like to thank our Urban Institute colleague Monique King-Viehland, associate vice president for metropolitan housing and communities policy, for her invaluable review and comments. iv ACKNOWLEDGMENTS Executive Summary Over the past 30 years, women have made tremendous gains in closing both the income and the education gaps between them and men, and growth in their homeownership rates has become an important manifestation of these trends. In 1990, there were 15.7 million female-headed homeowner households. By 2019, that number had reached 39.2 million. In contrast, the number of male-headed homeowner households decreased from 44.4 million to 43.1 million. In this report, we examine homeownership by the gender of the household head and how it has changed over the past three decades. Our analysis explores factors narrowing the homeownership gender gap, overall and by race and ethnicity. This narrowing can be attributed mostly to gains in household income, followed closely by the fact that more married women are head of household. Although there are real advances to appreciate, it is not a simple picture. When we analyze these trends, we must keep in mind the dynamics of the headship shift coupled with the dominance of economic advantage, historical racial and ethnic barriers to homeownership, and family composition in tenure choice, particularly as those underlying factors play out differently across racial and ethnic groups. Furthermore, the COVID-19 pandemic has had a disproportionate effect on women’s labor force participation, putting these gains at risk. Hence, following our analysis are policy recommendations to ensure that the pandemic, along with persistent racial and ethnic disparities, do not undermine or undo 30 years of progress toward closing the homeownership gender gap. EXECUTIVE SUMMARY v The Homeownership Gender Gap In this report, we examine homeownership by the gender of the household head and how it has changed over the past 30 years. We find that 61 percent of female-headed households owned their homes in 2019, a 10 percentage-point increase from 1990, and that the gap between homeownership rates for male- versus female-headed households closed from 20 percentage points in 1990 to just 6 percentage points in 2019. Our analysis explores the factors narrowing this gap, overall and by race and ethnicity. In 2019, half of all households reported being female-headed compared with just under a third in 1990. In particular, a much larger share of married households identified as female-headed in 2019 compared with 1990, likely driven by women’s gains in economic power. This married-headship shift occurred within each racial and ethnic group, though to differing degrees. As married households represent the largest share of households and have the highest homeownership rates and income levels on average, this marriedheadship shift boosted the homeownership rate among female-headed households. At the same time, the rise in the share of households headed by single or divorced men dampened the homeownership rate for that category. In fact, we find that overall in 2019, once we control for marital status, income, race, ethnicity, and other factors, the impact from the sex of household head on homeownership is smaller. Applying these controls reveals greater gender parity in homeownership in all racial and ethnic groups than looking at the raw gaps. In 2019, whether the household head was male or female had no impact on homeownership among Black households. For white households, the gap is significantly narrower than in 1990. Although the controlled gap narrowed for Hispanic households, female-headed households still lagged in homeownership, and among Asian households, female-headed households had a slight lead over male-headed households. Although there are real advances to celebrate in these findings, it is not a simple picture. When we analyze these trends, we must keep in mind the dynamics of the headship shift coupled with the dominance of economic advantage, historical racial barriers to homeownership, and family composition in tenure choice, particularly as those underlying factors play out differently across racial and ethnic groups. Notably, the increase in Black female-headed homeownership has not been enough to stem the overall drop in Black homeownership, which today stands at a level lower than it did 30 years ago, and the gap between white male-headed homeownership and Black male-headed homeownership is wider than that in 1990. Moreover, our analyses use prepandemic data. The pandemic has had a disproportionate effect on women’s labor force participation, putting these homeownership gains at risk. Women with children have been hit harder by the pandemic’s economic fallout than women without children. In 2019, single women with children, a group that has increased over the past three decades, already had the lowest homeownership rate (25 percent). COVID-19 has also been harder on Black and Hispanic households, creating more stress for families that were already struggling (Neal and McCargo 2020). Hence, we need to ensure homeownership losses do not occur, as COVID-19 is threatening to undo 30 years of progress toward closing the homeownership gender gap. One note: our research used the binary gender designations found in the Census Bureau and American Community Survey data. In addition, the designation of “married” is self-reported and will include same-sex couples if the spouse is the same sex as the household head. 2 THE HOMEOWNERSHIP GENDER GAP Overall Trends Owning a home is at the heart of the American dream. It is one of the primary tools for building wealth. Over the past 30 years, women have made tremendous gains in closing both the income and the education gaps between them and men,1 and growth in homeownership by female-headed households has become an important manifestation of these trends.2 In 1990, there were 15.7 million femaleheaded homeowner households. By 2019, that number had reached 39.2 million. In contrast, the number of male-headed homeowner households decreased from 44.4 million to 43.1 million. The large increase of female-headed homeowning households is the result of two related phenomena. First, the proportion of female-headed households has increased, as more households are self-reporting a female head. Second, the homeownership rate has increased for female-headed households, while it has fallen for male-headed households. Table 1 summarizes the transformation of homeownership along both these dimensions. TABLE 1 The Transformation of Homeownership, 1990–2019 Total number of households Female-headed households (%) Female-headed households among married households (%) Homeownership rate among female-headed households Homeownership rate among male-headed households Number of female-headed homeowner households Number of male-headed homeowner households 1990 93,347,000 32% 8% 51% 71% 15,710,300 44,405,168 Sources: 1990 Decennial Census and the 2019 American Community Survey. 2019 128,579,000 50% 40% 61% 67% 39,216,595 43,073,965 From 1990 to 2019, the share of households with female heads increased from 32 percent to 50 percent. The increase in female households heads is related to women’s increased labor force participation and income. For example, 63 percent of women ages 16 to 65 were working in 1990, and 68 percent were working in 2019. For men, the share decreased from 78 percent to 75 percent. Working women’s 2019 inflation-adjusted median annual income increased from $27,400 in 1990 to $35,000 in 2019. For men, the increase was from $47,000 to $48,000. The rise in employment and income for women is highly correlated with the increase in female headship. In 2019, the share of female household heads among the working-age population was 36 percent for those earning less than $25,000, 50 percent for households earning between $25,000 and $50,000, and 59 percent for those earning $50,000 or more. THE HOMEOWNERSHIP GENDER GAP 3 The greatest increase in the share of female household heads came from married households, where the female share of household heads increased from 8 percent to 40 percent between 1990 and 2019. Thirty years ago, in heterosexual relationships, the male partner was generally the main breadwinner and usually claimed to be the household head, even when the female partner earned more (Agarwal et al. 2018). That dynamic has changed. Given women’s increased labor force participation and greater earning power, it is not surprising that more women are the primary or roughly equal breadwinners in American households. The respondent household can decide who the household head is for the census survey (as long as the household head is one of the people in whose name the unit is owned or rented), but most couples consider the primary breadwinner to be the household head.3 For those households who are not married, the share of female household heads was more than 50 percent in 1990 and did not change much over the past 30 years.4 Table 1 also shows the homeownership trajectory for female-headed households. From 1990 to 2019, the female-headed household homeownership rate has increased from 51 percent to 61 percent, while the male-headed household homeownership rate has dropped from 71 percent to 67 percent. Thus, the homeownership gap narrowed from 20 percentage points in 1990 to 6 percentage points in 2019. Differences by Race and Ethnicity Though women have made substantial gains in both headship and homeownership, those gains vary substantially by race and ethnicity (figure 1). For example, women were the household head in 60 percent of Black households in 2019. That is the highest rate of any group both in 1990 and in 2019, but with the least amount of change over that period. Only 40 percent of Asian households were femaleheaded households in 2019, the lowest of any category. For all racial and ethnic groups, women were far more apt to be household heads in 2019 than in 1990 (17 to 19 percentage points higher for Asian, Hispanic, and white households and 8 percentage points higher for Black households). 4 THE HOMEOWNERSHIP GENDER GAP FIGURE 1 Female Household Heads, by Race or Ethnicity 1990 2019 60% 52% 40% 23% 49% 31% 49% 30% Asian Black Hispanic Sources: 1990 Decennial Census and the 2019 American Community Survey. White URBAN INSTITUTE The homeownership gender gap also closed significantly for all races and ethnicities between 1990 and 2019 (figure 2). In 1990, the gap was 15 to 20 percentage points for each race or ethnicity. By 2019, the gap had closed to between 2 and 6 percentage points, narrowing by 12 to 14 percentage points across all races and ethnicities. In both 1990 and 2019, the gap was the widest for Black and Hispanic families and the narrowest for Asian families. Although the changes in the gap between men and women show similar trajectories, we observe differences in how the gaps narrowed across racial and ethnic groups. Among white households, male-headed households maintained the same homeownership rate as female-headed households gained 13 percentage points. Hispanic and Asian households saw gains in male-headed homeownership but at a slower pace than among female-headed households. But Black male-headed households suffered an 8 percentage-point homeownership rate decline while Black female-headed households saw a 6 percentage-point increase, the smallest gain. In other words, unlike other racial and ethnic groups, a greater portion of the Black homeownership gender gap has narrowed more because of a decline in male homeownership rather than an increase in female homeownership. Part of the explanation for this is the increase in never-married households among Black male-headed households and a significant decline in the proportion of never-married Black male-headed household heads with children, both of which decrease the need of owning a house. THE HOMEOWNERSHIP GENDER GAP 5 FIGURE 2 Homeownership Rates, by Sex and Race or Ethnicity Asian Black Hispanic White 74% 74% 70% 57% 59% 56% 54% 45% 48% 61% 51% 46% 41% 40% 34% 30% 1990 2019 Female-headed households 1990 2019 Male-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. URBAN INSTITUTE We also examined the reasons for the homeownership gender gap narrowing from 20 percentage points in 1990 to 6 percentage points in 2019. Household income gains are the largest contributor, followed closely by the fact that more married women are head of household. Households headed by women have experienced a higher income increase than households headed by men. Although some of this increase is because female labor force participation and income have increased, it also reflects the fact that a greater share of women in married households is head of household. Married households, on average, have higher incomes because they have more earners. If we look across marital status, the homeownership gender gap narrowed less among households with unmarried heads. Our investigation of trends by race or ethnicity revealed that the homeownership gender gap has converged considerably and relatively equally for all races and ethnicities. And the gap becomes even smaller once we control for income, educational attainment, and marital status. The current absolute homeownership gender gap is 2 percentage points for Asian households, 4 percentage points for white households, and 6 percentage points for Black and Hispanic households. Educational attainment helped narrow the gap for all racial and ethnic groups, especially for Blacks households. Although we see improvement in the female homeownership rate over time, that improvement is partially driven by the fact that a greater share of married households reports the woman as head of household. This reflects the gains in women’s social status within households, which can be viewed 6 THE HOMEOWNERSHIP GENDER GAP positively. But the increased homeownership rate disguises the remaining gaps related to gender. Married households are more likely to be homeowners, so if the same married households change their head from male to female, this simple reporting change increases the female homeownership rate and lowers the male homeownership rate, all else unchanged. Among never-married households, femaleheaded households still have a lower homeownership rate—although the gap shrinks once we control for socioeconomic characteristics—and they are more likely to raise children. Single women with children, a group that has increased over the past three decades, have the lowest homeownership rate (25 percent). In the next section, we look at how socioeconomic characteristics affect the homeownership gender gap. We then examine different characteristics by race and ethnicity and conclude with policy recommendations. THE HOMEOWNERSHIP GENDER GAP 7 How Socioeconomic Characteristics Affect the Homeownership Gender Gap In this section, we look at how marital status, presence of children, income, educational attainment, and location affect the homeownership gender gap. These factors play a significant role in explaining differences in homeownership by gender. In 1990, the raw homeownership gender gap was 20 percentage points; after controlling these factors, the gap declined to 2.6 percentage points. The raw homeownership gender gap in 2019 was 6 percentage points; after controlling for these factors, the gap was only 0.3 percentage points. Marital Composition Married households are more likely to be homeowners, as many households pursue greater stability once wed, and household income increases for dual-income couples (Grinstein-Weiss et al. 2011). In 1990, 78 percent of male-headed households were married compared with 14 percent of femaleheaded households (figure 3). This reflects, in part, that for married couples in 1990, the male was considered the de facto household head, while most female-headed households arose from divorce, separation, or widowhood. The marital composition of American households has changed significantly over the past three decades—in 2019, 59 percent of male household heads and 40 percent of female household heads were married. A major part of the increase in female household heads and the decline in male household heads is because of both women’s increased earning power and the change from “the male is generally household head” to “the breadwinner is generally household head” mentality. Moreover, the age at first marriage has increased, increasing the never-married share of households. As a result, the share of households that are never married or are divorced or separated produces a noticeable increase of male household heads. And as the proportion of married female household heads has increased, the nevermarried share has held steady, and both the widowed and divorced or separated household shares have decreased. 8 THE HOMEOWNERSHIP GENDER GAP FIGURE 3 Marital Status among Female- and Male-Headed Households Married Divorced or separated Widowed Never married 11% 22% 23% 21% 9% 15% 15% 33% 23% 78% 31% 59% 40% 14% 1990 2019 Female-headed households 1990 2019 Male-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. URBAN INSTITUTE The homeownership rate for married and widowed male-headed households has stayed relatively constant (figure 4). Those who divorced or separated and those who never married increased their homeownership rate by 9 and 6 percentage points between 1990 and 2019. Consequently, the drop in the male homeownership rate is mainly the result of a shift in marital composition. That is, from 1990 to 2019, there was a significant decline in the number of married households, who have higher homeownership rates, while there was a significant increase in the number of unmarried (never married and divorced or separated) households, who have lower homeownership rates. Remarkably, the homeownership rates for most unmarried men increased from 1990 to 2019, even though these homeownership rates are still far lower than for married men. For female-headed households, the homeownership rate has increased for all marital categories, and the increase was greatest among married households. Both the increase in the share of femaleheaded married households and homeownership rate changes within each marital category have driven the rise in the number of female homeowners and will be a key explanatory factor in closing the THE HOMEOWNERSHIP GENDER GAP 9 homeownership gender gap. Additionally, we observed that the homeownership gender gap has narrowed for all marital categories, except for never-married households.5 FIGURE 4 Homeownership Rates, by Marital Status Married Divorced or separated Widowed Never married 78% 78% 80% 68% 71% 72% 74% 66% 57% 54% 48% 44% 38% 32% 32% 26% 1990 2019 1990 2019 Female-headed households Male-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. URBAN INSTITUTE Presence of Children Households with children are more likely to become homeowners, after controlling for age (Choi, Zhu, and Goodman 2018). In 2019, female-headed households were more likely to be living with children than male-headed households (figure 5). For men, between 1990 and 2019, the share of married households with children declined, while for women, the share stayed constant. Among never-married households, the share of households with children increased for both male-headed households and female-headed households. About one-third of single female-headed households have children living in the home. 10 THE HOMEOWNERSHIP GENDER GAP FIGURE 5 Female- and Male-Headed Households with Children Married Never married 58% 53% 53% 33% 26% 6% 48% 12% 1990 2019 1990 2019 Female-headed households Male-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. URBAN INSTITUTE Figure 6 shows the homeownership rates of married households with and without children and never-married households with and without children by year and sex. If we do not control for age, households without children have a higher homeownership rate because a portion of them are older households with adult children who have moved out. For men, the greatest homeownership changes occurred among single-parent households. These households experienced a 13 percentage-point homeownership rate increase. Single fathers now have a slightly higher homeownership rate than single male household heads with no children. For women, the homeownership rate increased for all four groups. The greatest increase occurred for single-parent households, in both male- and female-headed single households. But the 2019 homeownership rate for single-parent female households, though almost double the 1990 rate, is only 25 percent, the lowest among all groups. THE HOMEOWNERSHIP GENDER GAP 11 FIGURE 6 Homeownership Rates among Households with at Least One Child, by Marital Status Married and has no children Never married and has no children Married and has at least one child Never married and has at least one child 81% 80% 82% 76% 77% 77% 70% 62% 41% 30% 35% 33% 28% 37% 25% 13% 1990 2019 Female-headed households 1990 2019 Male-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. URBAN INSTITUTE Household Income Higher income is associated with higher homeownership rates (Choi et al. 2019). From 1990 to 2019, the household income distribution shifted considerably higher for female-headed households than for male-headed households (figure 7). By 2019, the share of female-headed households with annual incomes of at least $150,000 was 25 percent, 6 percentage points higher than for male-headed households. The share of female-headed households with incomes below $25,000 dropped from 30 percent in 1990 to 19 percent in 2019. On the other hand, incomes among some male-headed households dipped; the share of those with incomes below $25,000 increased slightly.6 Women’s incomes increased faster than men’s between 1990 and 2010. The inflation-adjusted personal incomes of female household heads increased 28 percent, while male household heads’ incomes increased only 2 percent. Changes in marital composition also contributed to the increase of female-headed household income, as married households who have relatively higher incomes are more 12 THE HOMEOWNERSHIP GENDER GAP likely to state they are female-headed households. Between 1990 and 2019, the household income of female household heads increased 64 percent, compared with 5 percent for male-headed households. FIGURE 7 Annual Household Income among Female- and Male-Headed Households < $25,000 $25,000–49,999 $50,000–99,999 $100,000–149,999 7% 11% 11% 25% 17% 29% 16% ≥ $150,000 19% 17% 38% 26% 32% 23% 14% 21% 19% 30% 19% 12% 14% 1990 2019 Female-headed households 1990 2019 Male-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. Note: Income is in 2019 constant dollars. URBAN INSTITUTE For all income categories, male-headed households as a group experienced a homeownership rate decline from 1990 to 2019, while female-headed households experienced an increase. By 2019, femaleheaded households had a slightly lower homeownership rate than male-headed households in the lower income categories, but for the highest two income categories, the male and female homeownership rates became identical (figure 8). THE HOMEOWNERSHIP GENDER GAP 13 FIGURE 8 Homeownership Rates, by Annual Household Income < $25,000 $25,000–49,999 $50,000–99,999 $100,000–149,999 82% 86% 90% 85% 79% 72% 72% 66% 59% 59% 49% 52% 48% 41% 40% ≥ $150,000 86% 79% 68% 55% 42% 1990 2019 Female-headed households 1990 2019 Male-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. Note: Income is in 2019 constant dollars. URBAN INSTITUTE Educational Attainment Higher education generally leads to higher income, and a major reason for the increase in female income is because women’s educational attainment has increased. In 1990, female household heads, on average, were less educated than male household heads. By 2019, there were almost no differences in educational attainment: for both male and female household heads, more than one-third have a bachelor’s degree, and those without a high school diploma account for only 8 percent of households (figure 9). 14 THE HOMEOWNERSHIP GENDER GAP FIGURE 9 Educational Composition of Household Heads No high school diploma High school diploma Some college Four-year degree or higher 17% 35% 25% 25% 32% 32% 26% 8% 1990 2019 Female-headed households 24% 37% 26% 23% 31% 32% 19% 8% 1990 2019 Male-headed households URBAN INSTITUTE Sources: 1990 Decennial Census and the 2019 American Community Survey. As the average level of educational attainment has risen in the United States, the differences in homeownership by education level are more pronounced for both male-headed and female-headed households than they were in 1990. Households with less educational attainment experienced a substantial decrease in their homeownership rate, with larger drops for men (figure 10). For example, the homeownership rate of those without a high school diploma dropped 16 percentage points for maleheaded households versus 6 percentage points for female-headed households. For female-headed households, the greatest increase in the homeownership rate is shown among those with at least a bachelor’s degree. Even though female-headed homeownership rates have generally risen from 1990 levels and male-headed homeownership rates have dropped, there still are homeownership rate gaps within each educational attainment level. The largest gap is among the least educated households, and the smallest gap is among the most educated. Educational attainment has helped women overcome barriers to achieve homeownership. THE HOMEOWNERSHIP GENDER GAP 15 FIGURE 10 Homeownership, by Educationof Household Heads No high school diploma High school diploma Some college 74% 70% 71% 69% 58% 55% 52% 50% 48% 44% Four-year degree or higher 73% 66% 65% 53% 1990 2019 Female-headed households 1990 2019 Male-headed households URBAN INSTITUTE Sources: 1990 Decennial Census and the 2019 American Community Survey. Location From 1990 to 2019, there has been a major population shift in the United States, with a huge movement away from rural areas and toward large cities with higher living costs (measured by house prices). In 1990, 31 percent of male-headed households and 27 percent of female-headed households lived in areas with home prices in the bottom 25 percent of the national home price distribution (figure 11). By 2019, this had contracted to 8 percent for all households. This movement was heavily weighted toward areas with home prices above the 75th percentile of the national average. 16 THE HOMEOWNERSHIP GENDER GAP FIGURE 11 Home Value Percentiles among Female- and Male-Headed Households Bottom 25th percentile 51st to 75th percentile 26th to 50th percentile 76th to 100th percentile 31% 37% 28% 37% 24% 25% 18% 18% 17% 17% 37% 37% 27% 8% 1990 2019 Female-headed households 31% 8% 1990 2019 Male-headed households URBAN INSTITUTE Sources: 1990 Decennial Census and the 2019 American Community Survey. This population shift is important because the highest-cost areas have the lowest homeownership rates. But there have been shifts in the homeownership rate within area home value buckets. In most areas, across home value buckets, male-headed households experienced a homeownership decline. The decline was greatest among male-headed households in the least expensive areas. On the other hand, female-headed households experienced a homeownership increase in all areas, especially in the most expensive areas. These trends are related to the fact that people with higher educational attainment have been increasingly concentrating in high-cost areas (Choi, Green, and Noh 2020). THE HOMEOWNERSHIP GENDER GAP 17 FIGURE 12 Homeownership Rates, by Home Value Percentile Bottom 25th percentile 51st to 75th percentile 26th to 50th percentile 76th to 100th percentile 77% 72% 72% 70% 69% 63% 68% 62% 64% 62% 59% 60% 57% 51% 50% 44% 1990 2019 Female-headed households 1990 2019 Male-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. URBAN INSTITUTE Regression and Oaxaca Decomposition To examine how the concurrent changes in the demographic and socioeconomic characteristics of maleand female-headed households affected the homeownership gap, we conducted regression analyses.7 The dependent variable equals 1 if the household owns a home.8 We controlled for race, ethnicity, age, marital status, presence of children, income, the existence of more than one income earner, immigrant status, and the area median home value. We also ran separate regressions by marital status (appendix table A.1). Once we included the control variables, we found that the homeownership gender gap decreases significantly. In 1990, including the control variables decreases the gap from 20 percentage points 18 THE HOMEOWNERSHIP GENDER GAP (without controls) to 2.6 percentage points (with controls). In 2019, the gap decreases from 6 percentage points to 0.3 percentage points. That is, there is almost no homeownership gender gap in 2019 once we include the observable demographic and socioeconomic variables. We also observed that once we added the control variables, the gap has become smaller in all four groups of marital status (appendix table A.1). For those who are married or have once been married, there is almost no homeownership gender gap by 2019. But for never-married homeowners, there is still a 2.8 percentagepoint gap. TABLE 2 Regression of the Homeownership Gender Gap, 1990 versus 2019 Variables Female Black Hispanic Asian Others Ages 40 to 59 Ages 60 and older Married Divorced or separated Widowed 1 child 2 or more children High school Four-year degree and higher Household income $25,000–49,999 Household income $50,000–99,999 Household income $100,000–149,999 Household income $150,000 and higher (1) 1990 -0.026*** (0.001) -0.116*** (0.001) -0.101*** (0.001) -0.033*** (0.001) -0.062*** (0.002) 0.195*** (0.000) 0.307*** (0.001) 0.255*** (0.001) 0.064*** (0.001) 0.206*** (0.001) 0.029*** (0.001) 0.061*** (0.001) 0.022*** (0.001) 0.024*** (0.001) 0.105*** (0.001) 0.231*** (0.001) 0.333*** (0.001) 0.380*** Total (2) 2019 -0.003*** (0.001) -0.158*** (0.001) -0.078*** (0.001) -0.030*** (0.002) -0.084*** (0.002) 0.198*** (0.001) 0.324*** (0.001) 0.212*** (0.001) 0.055*** (0.001) 0.162*** (0.002) 0.028*** (0.001) 0.051*** (0.001) 0.050*** (0.001) 0.082*** (0.002) 0.106*** (0.001) 0.210*** (0.001) 0.295*** (0.001) 0.338*** THE HOMEOWNERSHIP GENDER GAP 19 Variables Multiearner household Naturalized citizen Noncitizen Log (median home value) Constant Observations R2 (1) 1990 (0.001) -0.015*** (0.000) -0.007*** (0.001) -0.147*** (0.001) -0.115*** (0.000) 1.439*** (0.004) 4,593,342 0.282 Sources: 1990 Decennial Census and the 2019 American Community Survey. *** p < 0.01; ** p < 0.05; * p < 0.1. Total (2) 2019 (0.002) 0.005*** (0.001) 0.016*** (0.001) -0.164*** (0.002) -0.130*** (0.001) 1.699*** (0.010) 1,276,716 0.289 All variables have the expected sign and are of a reasonable order of magnitude. For example, indicators for any race or ethnicity other than white have negative coefficients, indicating that Black, Hispanic, Asian, and other households have lower homeownership rates than white households. Moreover, being married, the presence of children, age, household income, and educational attainment have positive effects on homeownership, while households in more expensive communities are less apt to be homeowners. We also included multiearner households and citizenship status in the regression. In 1990, the coefficient on multiearner households is negative, indicating that compared with single-earner households, multiearner households had lower homeownership rates. But in 2019, multiearner households had a positive coefficient. One potential reason for this difference is that with higher job turnover in the more recent period, the safety net created by two incomes has become more valuable. We also included a variable for citizenship status. In 1990, both naturalized citizens and noncitizens had a negative coefficient that was close to zero, indicating that all else equal, these households were slightly less likely to be homeowners than US citizen households. In 2019, the coefficient on naturalized citizens was positive, indicating that, all else equal, naturalized citizens were slightly more likely to be homeowners than their US-born counterparts. For immigrants, homeownership increases the longer they are in the United States. By 2019, naturalized citizens have caught up with US-born citizens, as a greater share of them have resided in the country for a longer period than in 1990.9 20 THE HOMEOWNERSHIP GENDER GAP Finally, to size how each variable contributed to the homeownership gender gap, we used the Oaxaca decomposition. We included the years 1990, 2000, 2010, and 2019 from the decennial census and the American Community Survey. Figure 13 shows that only 8.5 percent of the homeownership disparities remain unexplained. Household income and marital status explain 83 percent of the gap. Household income and the married share of households have increased substantially among femaleheaded households over the past three decades, which is highly correlated with the convergence of the male-female homeownership rates, as married couples have a much higher homeownership rate than their single counterparts. Educational attainment does not explain much because, during this period, both female and male household heads’ educational composition changed in a similar fashion over the past 30 years. But educational attainment is highly correlated with income, and a substantial increase in women’s educational attainment is associated with their increase in income, which has increased their likelihood of becoming household heads. FIGURE 13 Explaining the Gender Homeownership Gap: Oaxaca Decomposition Household income Marital status Race or ethnicity Median home value Presence of children Educational attainment Immigrant status Age Unexplained -2.1% -5.9% 8.4% 5.9% 1.0% 0.9% 8.5% Sources: 1990 and 2000 Decennial Censuses and the 2010 and 2019 American Community Surveys. 42.5% 40.8% URBAN INSTITUTE THE HOMEOWNERSHIP GENDER GAP 21 The Homeownership Gender Gap, by Race and Ethnicity In this section, we look at the homeownership gender gap by race and ethnicity. We look at homeownership rates, and the variables affecting them, for Asian, Black, Hispanic, and white households. The absolute gap is largest for Black and Hispanic households (6 percent) and is 4 percent for white households and 2 percent for Asian households. We show the results of the regression analysis to understand the disparities across races and ethnicities. We find, after controlling for other factors that affect homeownership, the homeownership gender gap is most pronounced among Hispanic households. Marital Composition Figure 14 shows the distribution of gendered household types by race and ethnicity. Among all races and ethnicities, the share of married female household heads has increased dramatically since 1990. For example, in 2019, 49 percent of Asian female-headed households were married couples, up from 24 percent in 1990. This share is 44 percent among white female-headed households, 41 percent among Hispanic female-headed households, and 22 percent among Black female-headed households. In 1990 and 2019, households headed by Black men and women had the lowest share of married households. 22 THE HOMEOWNERSHIP GENDER GAP FIGURE 14 Marital Status among Female- and Male-Headed Households, by Race or Ethnicity Asian households Black households Never married Widowed Divorced or separated Married 31% 24% 13% 19% 11% 21% 16% 25% 81% 74% 49% 24% 1990 2019 Female-headed households 1990 2019 Male-headed households Hispanic households 15% 31% 41% 33% 15% 23% 12% 19% 25% 35% 22% 11% 1990 2019 Female-headed households 65% 42% 1990 2019 Male-headed households White households 25% 27% 18% 8% 24% 40% 41% 17% 1990 2019 Female-headed households 12% 25% 8% 14% 78% 59% 1990 2019 Male-headed households 20% 17% 17% 36% 22% 30% 44% 14% 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. 10% 19% 8% 16% 79% 61% 1990 2019 Male-headed households URBAN INSTITUTE Homeownership rate changes between 1990 and 2019 differ considerably across gender and race and ethnicity (figure 15). A few observations are worth noting. First, for married households, the homeownership rate over the past three decades for female-headed households increased nearly 25 percentage points for Asian and Hispanic households, 15 percentage points for Black households, and 11 percentage points for white households. Second, never-married female-headed households also increased their homeownership rates between 7 and 9 percentage points across most races and THE HOMEOWNERSHIP GENDER GAP 23 ethnicities. Third, compared with the high growth in homeownership for Black female-headed households, Black male-headed households experienced a much slower homeownership rate increase. For example, single Black male households’ homeownership rate increased 2 percentage points from 1990 to 2019. For married Black male-headed households, the 2019 homeownership rate is 1 percentage point lower than the 1990 level. FIGURE 15 Homeownership Rates, by Marital Status and Race or Ethnicity Asian households Black households Married Divorced or separated Widowed Never married 71% 69% 53% 63% 59% 62% 54% 63% 54% 57% 61% 66% 58% 57% 65% 58% 48% 46% 41% 38% 34% 32% 33% 41% 35% 40% 27% 26% 22% 22% 24% 15% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households 1990 2019 Male-headed households Hispanic households White households 73% 84% 82% 75% 76% 86% 78% 62% 70% 60% 61% 61% 63% 53% 59% 53% 49% 51% 45% 41% 45% 40% 36% 27% 32% 28% 31% 36% 23% 14% 18% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households 1990 2019 Male-headed households URBAN INSTITUTE Sources: 1990 Decennial Census and the 2019 American Community Survey. 24 THE HOMEOWNERSHIP GENDER GAP Presence of Children The presence of children can have a significant impact on the homeownership rate, but the impact is not uniform across races and ethnicities. To illustrate, we separated our data on married couples and single or never-married households into those with children and without children by race and ethnicity. For simplicity, we eliminated divorced and widowed households from this part of the analysis. In 2019, Hispanic households were more apt to have children than any other racial or ethnic group, followed by Asian households and then Black households (figure 16). White households were the least likely to have children living with them. For Hispanic households, 68 to 72 percent of married households had children, 51 percent of never-married female-headed households had children, and 24 percent of never-married male-headed households had children. For white households, 42 to 49 percent of married households had children, as did 20 percent of never-married female-headed households and 8 percent of never-married male-headed households. Interestingly, since 1990, the proportion of never-married Black female household heads with children has declined from 63 percent to 48 percent, while it has increased from 11 percent to 20 percent for never-married white female household heads. The proportions have been roughly constant for Asian households (11 to 12 percent) and Hispanic households (49 to 51 percent). THE HOMEOWNERSHIP GENDER GAP 25 FIGURE 16 Female- and Male-Headed Households with Children, by Race or Ethnicity Asian households Black households Married Never married 75% 65% 63% 63% 68% 68% 63% 55% 53% 48% 11% 12% 3% 5% 14% 15% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households 1990 2019 Male-headed households Hispanic households White households 73% 72% 77% 68% 49% 51% 56% 48% 49% 42% 24% 20% 20% 11% 8% 4% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. 1990 2019 Male-headed households URBAN INSTITUTE Owning a home has been associated with better psychological health and greater stability for children, though there are ongoing debates about causality (Dietz and Haurin 2003; Green and White 1997). All else constant, families with children are more likely to become homeowners than those without children. But the effect of the presence of a child on homeownership differs across races and ethnicities. We can observe a huge effect on Asian households (figure 17). For never-married adults between 1990 and 2019, the homeownership rate increased 25 to 27 percentage points for those with 26 THE HOMEOWNERSHIP GENDER GAP children. For households without children, the homeownership rate increase is only 5 percentage points. For Black households, the homeownership increase is much higher for female-headed households than for male-headed households. For married Black households with children, femaleheaded households had a 15 percentage-point homeownership rate increase, while male-headed households had a 2 percentage-point homeownership rate decrease. Although homeownership rates for single mothers have increased, the rates are still low, especially for Black and Hispanic households. In 2019, the homeownership rate of the female-headed single-parent household was 18 percent for Black households and 21 percent for Hispanic households. These households are likely to face the greatest housing instability under negative economic circumstances and need special attention. THE HOMEOWNERSHIP GENDER GAP 27 FIGURE 17 Homeownership Rates among Households with at Least One Child, by Marital Status and Race or Ethnicity Asian households Black households Married and has no children Married and has at least one child Never married and has no children Never married and has at least one child 74% 72% 67% 67% 65% 65% 64% 64% 65% 63% 58% 50% 53% 53% 52% 44% 43% 43% 28% 18% 33% 26% 31% 21% 27% 26% 18% 21% 28% 23% 12% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households 1990 2019 Male-headed households Hispanic households 41% 33% 21% 8% 61% 58% 54% 26% 21% 18% 14% White households 74% 72% 61% 85% 83% 83% 81% 32% 27% 32% 18% 41% 35% 36% 34% 87% 85% 53% 44% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. 1990 2019 Male-headed households URBAN INSTITUTE Household Income From 1990 to 2019, female-headed household incomes increased significantly for all races and ethnicities (figure 18). If we focus on the share of low-income households (those earning less than $25,000 a year), we see that for Asian households, the share of low-income female-headed households 28 THE HOMEOWNERSHIP GENDER GAP dropped from 45 percent in 1990 to 26 percent in 2019. For Black households, it dropped from 36 percent to 20 percent. For Hispanic households, the share dropped from 49 percent to 34 percent, and for white households, the share dropped from 39 percent to 23 percent. On the other hand, the share of low-income male-headed households is virtually constant from 1990 to 2019: it dropped from 13 percent to 11 percent for Asian households, increased from 23 percent to 24 percent for Black households, decreased from 18 percent to 16 percent for Hispanic households, and increased from 11 percent to 12 percent for white households. THE HOMEOWNERSHIP GENDER GAP 29 FIGURE 18 Annual Household Income among Female- and Male-Headed Households, by Race or Ethnicity Asian households Black households < $25,000 $50,000–99,999 ≥ $150,000 $25,000–49,999 $100,000–149,999 8% 22% 12% 30% 26% 25% 45% 26% 1990 2019 Female-headed households 17% 32% 20% 19% 33% 25% 17% 13% 13% 11% 1990 2019 Male-headed households 7% 15% 25% 15% 29% 27% 21% 36% 20% 1990 2019 Female-headed households 6% 9% 13% 12% 34% 30% 25% 24% 23% 24% 1990 2019 Male-headed households Hispanic households White households 6% 9% 20% 26% 25% 26% 49% 34% 1990 2019 Female-headed households 6% 11% 12% 15% 37% 35% 27% 24% 18% 16% 1990 2019 Male-headed households 7% 13% 24% 14% 29% 27% 22% 39% 23% 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. Note: Income is in 2019 constant dollars. 12% 20% 18% 18% 39% 32% 20% 18% 11% 12% 1990 2019 Male-headed households URBAN INSTITUTE Across all races and ethnicities, for most income categories, female-headed households experienced an increase in homeownership rates. In contrast, male-headed households experienced no increase or even significant decreases for most income categories. For households earning $50,000 to $99,999, the homeownership increase among Asian households was 0 percentage points for maleheaded households but 7 percentage points for female-headed households. For Black households, the homeownership rate dropped 7 percentage points for male-headed households and increased 4 30 THE HOMEOWNERSHIP GENDER GAP percentage points for female-headed households. For both Hispanic and white households, the homeownership rate was flat for male-headed households or decreased slightly, but for female-headed households, it increased for all income buckets by 8 to 10 percentage points. Black male-headed households have had significant homeownership declines across every income category, a sharp contrast to other races and ethnicities, which have seen more modest homeownership declines only in select income buckets. FIGURE 19 Homeownership Rates, by Annual Household Income and Race or Ethnicity Asian households Black households < $25,000 $50,000–99,999 ≥ $150,000 $25,000–49,999 $100,000–149,999 87% 85% 77% 80% 77% 79% 76% 76% 79% 66% 50% 68% 57% 55% 50% 69% 65% 60% 55% 47% 46% 67% 58% 50% 45% 68% 51% 33% 34% 31% 34% 30% 26% 38% 33% 24% 36% 26% 20% 16% 1990 2019 Female-headed households Hispanic households 1990 2019 Male-headed households 1990 2019 Female-headed households White households 1990 2019 Male-headed households 69% 78% 81% 71% 66% 84% 78% 75% 67% 62% 89% 83% 91% 86% 73% 75% 62% 63% 88% 83% 75% 64% 58% 50% 53% 53% 53% 50% 54% 51% 41% 37% 36% 48% 39% 28% 28% 29% 31% 20% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. Note: Income is in 2019 constant dollars. 1990 2019 Male-headed households URBAN INSTITUTE THE HOMEOWNERSHIP GENDER GAP 31 Educational Attainment For every race and ethnicity, female household heads attained slightly less education than their male counterparts. Although educational attainment has increased for both men and women, the gains for women have been more dramatic, and by 2019, women had a slight edge. This is particularly true for Black and Hispanic women. In 1990, 27 percent of Black men and 23 percent of Black women who were household heads had at least some college. By 2019, 52 percent of Black men and 55 percent of Black women who were household heads had at least some college. Similarly, Hispanic women lagged Hispanic men in 1990, but by 2019, a greater percentage of Hispanic women had at least some college (43 percent versus 39 percent). For white households, both men and women had higher educational attainment than other racial and ethnic groups, and they showed improvement over time like other groups. In 2019, the educational attainment distribution between white men and women was identical (figure 20). 32 THE HOMEOWNERSHIP GENDER GAP FIGURE 20 Education Composition of Houshold Heads, by Race or Ethnicity Asian households Black households Four-year degree or higher Some college High school diploma No high school diploma 34% 58% 24% 22% 17% 17% 21% 8% 1990 2019 Female-headed households 45% 64% 23% 14% 19% 16% 13% 1990 2019 Male-headed households 10% 25% 23% 30% 33% 35% 33% 10% 1990 2019 Female-headed households 13% 24% 24% 28% 33% 39% 30% 9% 1990 2019 Male-headed households Hispanic households White households 8% 11% 20% 19% 20% 21% 23% 20% 26% 27% 34% 36% 46% 42% 23% 25% 19% 26% 39% 40% 26% 26% 25% 23% 33% 31% 32% 32% 23% 17% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. 1990 2019 Male-headed households URBAN INSTITUTE While women have increased their homeownership rate regardless of their education level, the gains have been especially significant for those with a bachelor’s degree or equivalent. For all races and ethnicities, we have seen a homeownership increase of 16 to 18 percentage points for female-headed households with a bachelor’s degree or higher, compared with a near-zero increase for men. In contrast, for the least educated group, we see a large divergence for women, with white women who did not complete high school experiencing a small drop in their homeownership rate, while the rate increased THE HOMEOWNERSHIP GENDER GAP 33 for Black, Hispanic, and Asian women who did not complete high school. Black and white male-headed households who did not finish high school experienced a large drop in their homeownership rate, while it was up marginally for Asian and Hispanic male-headed households (figure 21). FIGURE 21 Homeownership Rates, by Education Level of Houshold Head, by Race or Ethnicity Asian households Black households No high school diploma High school diploma Some college Four-year degree or higher 45% 43% 40% 31% 63% 57% 56% 61% 56% 47% 53% 44% 63% 59% 53% 47% 37% 30% 56% 59% 56% 51% 45% 50% 37% 34% 43% 37% 30% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households 1990 2019 Male-headed households Hispanic households White households 76% 75% 75% 72% 78% 73% 57% 58% 60% 59% 58% 68% 67% 66% 53% 46% 46% 53% 49% 56% 56% 45% 53% 41% 43% 43% 33% 38% 29% 27% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. 1990 2019 Male-headed households URBAN INSTITUTE 34 THE HOMEOWNERSHIP GENDER GAP Location Compared with Black households and white households, Asian households and Hispanic households are more likely to live in high-cost areas. Among Asian households in 2019, 71 percent of female-headed households and 67 percent of male-headed households lived in areas with home values in the 76th percentile or above. For Hispanic households, 50 to 51 percent of male- and female-headed households lived in high-cost areas (figure 22). FIGURE 22 Home Value Percentiles, by Race or Ethnicity Asian households 76th to 100th percentile 51st to 75th percentile 26th to 50th percentile Bottom 25th percentile Black households 73% 71% 70% 67% 14% 13% 8% 14% 1990 2019 Female-headed households 16% 15% 9% 15% 1990 2019 Male-headed households Hispanic households 28% 36% 27% 37% 30% 21% 17% 35% 24% 9% 1990 2019 Female-headed households 29% 20% 17% 34% 26% 8% 1990 2019 Male-headed households White households 53% 51% 45% 50% 22% 20% 12% 21% 14% 8% 1990 2019 Female-headed households 25% 21% 13% 22% 17% 7% 1990 2019 Male-headed households 29% 31% 24% 18% 17% 42% 29% 9% 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. 26% 32% 23% 18% 17% 42% 34% 8% 1990 2019 Male-headed households URBAN INSTITUTE THE HOMEOWNERSHIP GENDER GAP 35 In high-cost areas, households with home values in the 76th percentile or above have experienced a significant homeownership increase from 1990 to 2019 (figure 23). The homeownership rate of Hispanic female-headed households increased 18 percentage points, and the homeownership rate of Hispanic male-headed households increased 6 percentage points. We can see a similar pattern for Asian households: the homeownership rate of female-headed households increased 18 percentage points, and the homeownership rate of male-headed households increased 3 percentage points. For both Black and white families, male-headed households had no increase in homeownership in the highest-cost areas, while for female-headed households, the homeownership rate increased 12 and 15 percentage points, respectively, smaller increases than for Asian and Hispanic female-headed households. Among female-headed households, only Black female household heads in the lowest-cost areas (those whose median home values were in the bottom quartile nationally) experienced a homeownership rate decline (7 percentage points), significantly lower than the 19 percentage-point decline for similarly situated men. 36 THE HOMEOWNERSHIP GENDER GAP FIGURE 23 Homeownership Rates, by Home Value Percentile and Race or Ethnicity Asian households Black households Bottom 25th percentile 26th to 50th percentile 51st to 75th percentile 76th to 100th percentile 43% 41% 35% 64% 60% 59% 55% 58% 54% 53% 49% 64% 61% 58% 56% 46% 33% 64% 55% 53% 41% 45% 39% 47% 46% 45% 32% 27% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households 1990 2019 Male-headed households Hispanic households White households 50% 37% 35% 21% 64% 56% 53% 49% 53% 50% 39% 39% 61% 57% 55% 62% 56% 45% 52% 78% 77% 76% 71% 67% 75% 73% 70% 75% 70% 1990 2019 Female-headed households 1990 2019 Male-headed households 1990 2019 Female-headed households Sources: 1990 Decennial Census and the 2019 American Community Survey. 1990 2019 Male-headed households URBAN INSTITUTE Regression Table 3 presents the results of a regression estimation for homeownership, separated by race and ethnicity. For Black, Hispanic, and white households, the coefficient on the female variable is smaller in 2019 than it was in 1990, indicating that the homeownership gender gap has declined. For Asian THE HOMEOWNERSHIP GENDER GAP 37 households, the female coefficient turned positive in 2019, indicating that, after including control variables, women have a higher homeownership rate than men. In 1990, female-headed white households had a homeownership rate that was 2.2 percentage points lower than for male-headed white households. By 2019, that gap had declined to 0.3 percentage points, closing the gap by 1.9 percentage points. The gains have been larger for female-headed households of color. For Black female-headed households, the homeownership rate in 1990 was 3.2 percentage points lower than for male-headed households; the gap had declined to 0.3 percentage points by 2019, a 2.9 percentage-point improvement. For Hispanic households, the gap has declined 2.4 percentage points, from 3.7 percentage points to 1.3 percentage points. In 2019, Asian female-headed households were more likely than Asian male-headed households to own homes, all else equal—a 2.4 percentage-point improvement. The rest of the control variables show reasonable coefficients. For example, consistent with life cycle theory, older household heads are more likely than younger ones to own their house. All racial and ethnic groups have effects of similar magnitude. Likewise, being married significantly increases the probability of becoming a homeowner. But the marginal effects are different across races and ethnicities. Marriage has the strongest effect on homeownership for white households, followed by Black and Hispanic households. Marriage has the least effect for Asian households, about half the magnitude of the effect for white households. We found a strong education effect for Black households, especially in 2019. Black households with at least a bachelor’s degree have a homeownership rate 15.8 percentage points higher than those with a household head who did not complete high school. The marginal effect is 10 percentage points for Asian households, 8.2 percentage points for white households, and 6.4 percentage points for Hispanic households. Higher income plays a significant role in homeownership. Higher income is associated with increased home affordability and a higher homeownership rate. Income’s impact on homeownership is highest for Hispanic households, followed by Black households, Asian households, and then white households. That white homeownership rates increase less with income is worth noting. As white households, on average, have more wealth and are more likely to receive parental support, they have a homeownership rate in the lowest income bucket that is significantly higher than other racial and ethnic groups (McCargo and Choi 2020). This indicates that low-income households of color would need greater financial support, such as down payment assistance, to achieve similar homeownership rates. 38 THE HOMEOWNERSHIP GENDER GAP Having multiple earners in a household increased homeownership rates significantly for Asian and Black households, but it had no impact on Hispanic or white homeownership rates. Noncitizens have a uniformly lower homeownership rate across all races and ethnicities for both 1990 and 2019. In 2019, Asian and Hispanic naturalized citizens had significantly higher homeownership rates than their US-born counterparts. For Black households, the homeownership rate for naturalized citizens was insignificantly higher, and for white households, naturalized citizens had a lower homeownership rate than their US-born counterparts. Noncitizens have significantly lower homeownership rates. On average, naturalized citizens have spent more years in the United States than noncitizens, and research shows that the homeownership gap between immigrants and US-born citizens declines with the number of years the immigrant has resided in the country (Myers, Megbolube, and Lee 1998). THE HOMEOWNERSHIP GENDER GAP 39 TABLE 3 Regression of the Homeownership Gender Gap, by Race or Ethnicity, 1990 versus 2019 Variables Female Ages 40 to 59 Ages 60 and older Married Divorced or separated Widowed 1 child 2 or more children High school Four-year degree and higher Household income $25,000–49,999 Household income $50,000–99,999 Household income $100,000–149,999 Household income $150,000 and higher Multiearner household Naturalized citizen Asian (1) (2) 1990 2019 -0.001 0.023*** (0.004) (0.004) 0.135*** 0.193*** (0.003) (0.004) 0.209*** 0.284*** (0.005) (0.006) 0.130*** 0.133*** (0.005) (0.005) 0.031*** 0.067*** (0.006) (0.007) 0.142*** 0.110*** (0.008) (0.009) 0.044*** 0.051*** (0.004) (0.005) 0.073*** 0.088*** (0.004) (0.005) 0.069*** 0.076*** (0.004) (0.007) 0.082*** 0.099*** (0.005) (0.007) 0.092*** 0.109*** (0.005) (0.007) 0.273*** 0.183*** (0.005) (0.006) 0.434*** 0.265*** (0.005) (0.007) 0.504*** 0.360*** (0.006) (0.007) 0.008** 0.053*** (0.003) (0.004) 0.001 0.030*** (0.004) (0.005) Black (3) (4) 1990 2019 -0.031*** -0.003 (0.002) (0.003) 0.212*** 0.187*** (0.002) (0.003) 0.360*** 0.348*** (0.002) (0.004) 0.202*** 0.186*** (0.002) (0.004) 0.042*** 0.043*** (0.002) (0.004) 0.165*** 0.160*** (0.003) (0.005) 0.025*** 0.021*** (0.002) (0.003) 0.023*** -0.003 (0.002) (0.004) 0.036*** 0.070*** (0.002) (0.005) 0.091*** 0.158*** (0.003) (0.005) 0.106*** 0.091*** (0.002) (0.004) 0.229*** 0.204*** (0.002) (0.004) 0.367*** 0.332*** (0.003) (0.005) 0.449*** 0.395*** (0.004) (0.006) 0.017*** 0.024*** (0.002) (0.003) -0.000 0.009* (0.005) (0.005) Hispanic (5) (6) 1990 2019 -0.037*** -0.013*** (0.002) (0.002) 0.189*** 0.160*** (0.002) (0.003) 0.330*** 0.307*** (0.003) (0.004) 0.173*** 0.177*** (0.003) (0.003) 0.031*** 0.040*** (0.003) (0.004) 0.164*** 0.160*** (0.004) (0.006) 0.024*** 0.022*** (0.002) (0.003) 0.062*** 0.050*** (0.002) (0.003) 0.045*** 0.033*** (0.002) (0.003) 0.051*** 0.064*** (0.003) (0.004) 0.103*** 0.097*** (0.002) (0.004) 0.256*** 0.214*** (0.003) (0.004) 0.418*** 0.335*** (0.003) (0.005) 0.500*** 0.427*** (0.005) (0.006) -0.022*** 0.002 (0.002) (0.003) 0.000 0.057*** (0.002) (0.003) White (7) (8) 1990 2019 -0.022*** -0.003*** (0.001) (0.001) 0.196*** 0.207*** (0.001) (0.001) 0.300*** 0.324*** (0.001) (0.001) 0.276*** 0.232*** (0.001) (0.001) 0.072*** 0.059*** (0.001) (0.001) 0.216*** 0.166*** (0.001) (0.002) 0.030*** 0.030*** (0.001) (0.001) 0.068*** 0.062*** (0.001) (0.001) 0.017*** 0.057*** (0.001) (0.002) 0.015*** 0.082*** (0.001) (0.002) 0.106*** 0.112*** (0.001) (0.001) 0.227*** 0.207*** (0.001) (0.001) 0.319*** 0.279*** (0.001) (0.002) 0.361*** 0.309*** (0.001) (0.002) -0.021*** -0.004*** (0.001) (0.001) -0.016*** -0.019*** (0.001) (0.002) 40 THE HOMEOWNERSHIP GENDER GAP Variables Noncitizen Log (median home value) Constant Observations R2 Asian (1) (2) 1990 2019 -0.209*** -0.198*** (0.004) (0.005) -0.040*** -0.085*** (0.003) (0.003) 0.542*** 1.100*** (0.032) (0.043) 90,182 59,339 0.318 0.277 Sources: 1990 Decennial Census and the 2019 American Community Survey. *** p < 0.01; ** p < 0.05; * p < 0.1. Black (3) (4) 1990 2019 -0.098*** -0.160*** (0.004) (0.007) -0.196*** -0.124*** (0.001) (0.003) 2.234*** 1.453*** (0.015) (0.040) 420,005 111,993 0.282 0.261 Hispanic (5) (6) 1990 2019 -0.107*** -0.112*** (0.002) (0.003) -0.175*** -0.196*** (0.001) (0.002) 2.045*** 2.471*** (0.017) (0.030) 275,426 133,600 0.278 0.246 White (7) (8) 1990 2019 -0.126*** -0.195*** (0.002) (0.004) -0.100*** -0.113*** (0.000) (0.001) 1.264*** 1.491*** (0.005) (0.012) 3,772,344 941,361 0.246 0.241 THE HOMEOWNERSHIP GENDER GAP 41 Policy Recommendations Over the past three decades, the number of female-headed homeowner households increased by 23.5 million, closing the homeownership gender gap considerably. The 20 percentage-point gap in the homeownership rate between male- and female-headed households in 1990 shrunk to 6 percentage points by 2019. In fact, once we control for income, race, and other factors, the overall gender gap largely disappears. But understanding these data as a simple victory for women would be a mistake. The gain for Black female-headed households has been much less than the gain for Asian, white, and Hispanic femaleheaded households, and Black male-headed households lost ground. As a result, the homeownership gap between Black female-headed households and white female-headed households increased from 23 percentage points in 1990 to 30 percentage points in 2019, while the gap between Black male-headed households and white male-headed households increased from 20 percentage points in 1990 to 28 percentage points in 2019. We highlight three important and interrelated implications: ◼ Women have made gains in homeownership and economic standing over the past 30 years. But the COVID-19 pandemic threatens to erase this progress, particularly among the most vulnerable and families with children. The labor force participation rate for women with children decreased 3.5 percent from January 2020 to March 2021, while the participation rate was 1 percent lower for men with children.10 The labor force participation decline for single women with children was 5 percent for the same 14-month period. Black women with children have a larger labor force participation decline than white, Asian, or Hispanic women with children.11 The labor market instability has been exacerbated by the unstable housing many of these women face. ◼ Income, education, race or ethnicity, and household composition, rather than gender, are the key determinants of who owns a home. This report illustrates that opportunity is unevenly distributed across race and ethnicity and across gender by race and ethnicity, reflecting longstanding patterns of systemic racism. Homeownership can increase housing stability and provide the opportunity to build wealth, as homeownership and housing wealth transfer from parents to children (Choi, Zhu, and Goodman 2018). These findings point to the need for solutions that support financial and homebuying opportunities for households of color, many of whom have been locked out for generations. 42 THE HOMEOWNERSHIP GENDER GAP ◼ Although the homeownership gender gap has narrowed, a greater share of women than men are still renters. In particular, the share of female-headed single-parent households has increased, and single women with children have the lowest homeownership rate and have been disproportionately affected by the COVID-19 crisis. In 2019, the homeownership rate of the female-headed single-parent household was 18 percent for Black households and 21 percent for Hispanic households. These households are likely to face the greatest housing instability under negative economic circumstances and need special attention. Although some of the indicated measures are outside the scope of housing, specific steps can increase access to homeownership for households with less economic advantage and can support female homeowners, especially those with low incomes and less wealth: ◼ Increase the visibility, access, and types of down payment assistance programs for femaleheaded households. Lack of funds for a down payment is one of the major barriers to homeownership, especially for households of color (Goodman et al. 2018). A well-designed and targeted down payment assistance program, such as for first-generation or single-parent homebuyers, would help low- and moderate-income families access homeownership. Such programs should include efforts to increase awareness and access among the target households. Many renters have misconceptions about the homebuying process (Goodman et al. 2018). Empowered with facts, more women would have the confidence to step into homebuying. Corresponding investments in expanding housing counseling and outreach would increase the likelihood that less advantaged households could avail themselves of such programs. ◼ Consider flexibility on mortgage applications. Most mortgages require that the borrower has spent two years in the same job or in the same field. Because child care responsibilities during the pandemic caused many parents (mostly mothers) to drop out of the labor force, it is going to take a while for some households to rebuild this history. Policies could allow flexibility when a woman currently has a job or a long prepandemic job history but shows intermittent employment or an employment break during the pandemic. Similarly, both alimony and child support count as payments, even though the borrower needs to document that they have uninterruptedly received these for the past six months and can expect to do so for the next three years. Supportive policy would allow for more flexibility on these payments when the coparent has a long history of paying and is currently paying but may have missed payments during the pandemic. Furthermore, more flexibility is needed on including the income of family members not on the mortgage. For the approximately 60 percent of single female borrowers, THE HOMEOWNERSHIP GENDER GAP 43 33 percent have additional sources of household income, but those additional earners will not be a party to the mortgage. Counting this income would, in many cases, make a difference. ◼ Ensure the stable housing of women with children in rental units because it is the point of entry to homeownership. Although the gap has narrowed, more women than men are still renters. Without achieving housing and financial stability, most renters will not be able to save for homeownership. In particular, single women with children have the lowest homeownership rate, and women have been disproportionately affected by the COVID-19 crisis; Black and Hispanic women have even lower homeownership rates than their white counterparts and have been disproportionately affected by COVID-19. Once the forbearance and eviction moratoriums expire, renters are likely to face greater challenges staying housed. Many are still unaware of the emergency rental assistance they can receive. Those who are aware find it confusing to apply. In the short term, quickly reaching out to renters who are financially struggling will be critical. In the long term, expanding housing choice vouchers and other policies that make it affordable to rent high-quality housing can increase renters’ financial stability. 44 THE HOMEOWNERSHIP GENDER GAP Appendix TABLE A.1 Regression of the Homeownership Gender Gap, by Marital Status, 1990 versus 2019 Variables Female Black Hispanic Asian Others Ages 40 to 59 Ages 60 and older 1 child 2 or more children High school Four-year degree or higher Household income $25,000–49,999 Household income $50,000–99,999 Household income $100,000–149,999 Never married (1) (2) 1990 2019 -0.041*** -0.028*** (0.001) (0.002) -0.078*** -0.148*** (0.002) (0.002) -0.047*** -0.057*** (0.002) (0.003) 0.048*** -0.014*** (0.004) (0.005) 0.013** -0.072*** (0.006) (0.005) 0.251*** 0.237*** (0.002) (0.002) 0.357*** 0.381*** (0.002) (0.003) 0.006*** 0.041*** (0.002) (0.003) 0.010*** 0.043*** (0.002) (0.003) 0.020*** 0.069*** (0.002) (0.004) -0.001 0.097*** (0.002) (0.004) 0.096*** 0.105*** (0.001) (0.002) 0.243*** 0.234*** (0.002) (0.003) 0.383*** 0.335*** (0.002) (0.004) Married (3) (4) 1990 2019 -0.046*** 0.004*** (0.001) (0.001) -0.126*** -0.163*** (0.001) (0.002) -0.117*** -0.083*** (0.001) (0.002) -0.055*** -0.029*** (0.002) (0.002) -0.085*** -0.080*** (0.003) (0.003) 0.180*** 0.171*** (0.001) (0.001) 0.305*** 0.290*** (0.001) (0.001) 0.021*** 0.022*** (0.001) (0.001) 0.064*** 0.058*** (0.001) (0.001) 0.008*** 0.029*** (0.001) (0.002) 0.010*** 0.055*** (0.001) (0.002) 0.080*** 0.073*** (0.001) (0.002) 0.215*** 0.169*** (0.001) (0.002) 0.317*** 0.253*** (0.001) (0.002) Divorced or separated (5) (6) 1990 2019 0.014*** -0.001 (0.001) (0.002) -0.112*** -0.159*** (0.002) (0.003) -0.094*** -0.090*** (0.002) (0.003) -0.015*** 0.001 (0.005) (0.007) -0.061*** -0.095*** (0.006) (0.006) 0.178*** 0.172*** (0.001) (0.003) 0.280*** 0.311*** (0.002) (0.003) 0.035*** 0.016*** (0.002) (0.003) 0.049*** 0.014*** (0.002) (0.003) 0.050*** 0.065*** (0.002) (0.004) 0.077*** 0.120*** (0.002) (0.004) 0.121*** 0.122*** (0.002) (0.003) 0.247*** 0.229*** (0.002) (0.003) 0.354*** 0.318*** (0.003) (0.004) Widowed (7) (8) 1990 2019 -0.023*** -0.009*** (0.002) (0.003) -0.122*** -0.148*** (0.002) (0.004) -0.096*** -0.073*** (0.003) (0.005) -0.053*** -0.039*** (0.006) (0.008) -0.050*** -0.083*** (0.008) (0.009) 0.154*** 0.162*** (0.005) (0.012) 0.193*** 0.277*** (0.004) (0.012) 0.034*** 0.062*** (0.002) (0.004) 0.004 0.045*** (0.003) (0.007) 0.036*** 0.065*** (0.001) (0.004) 0.046*** 0.082*** (0.002) (0.004) 0.120*** 0.124*** (0.001) (0.003) 0.186*** 0.187*** (0.002) (0.003) 0.244*** 0.238*** (0.003) (0.006) APPENDIX 45 Variables Household income $150,000 and higher Multiearner household Naturalized citizen Noncitizen Log (median home value) Constant Observations R2 Never married (1) (2) 1990 2019 0.487*** 0.378*** (0.003) (0.004) -0.059*** -0.045*** (0.001) (0.002) -0.009*** 0.063*** (0.003) (0.004) -0.079*** -0.097*** (0.003) (0.004) -0.118*** -0.145*** (0.001) (0.002) 1.469*** 1.857*** (0.012) (0.025) 583,288 232,984 0.182 0.191 Sources: 1990 Decennial Census and the 2019 American Community Survey. Married (3) (4) 1990 2019 0.358*** 0.301*** (0.001) (0.002) -0.018*** 0.038*** (0.001) (0.001) -0.007*** -0.001 (0.001) (0.002) -0.183*** -0.217*** (0.001) (0.002) -0.103*** -0.125*** (0.000) (0.001) 1.598*** 1.908*** (0.005) (0.013) 2,716,803 675,930 0.192 0.213 Divorced or separated (5) (6) 1990 2019 0.421*** 0.362*** (0.003) (0.005) -0.004*** 0.016*** (0.001) (0.002) 0.028*** 0.037*** (0.003) (0.004) -0.080*** -0.090*** (0.003) (0.005) -0.139*** -0.140*** (0.001) (0.002) 1.714*** 1.863*** (0.012) (0.029) 701,202 233,980 0.130 0.138 Widowed (7) (8) 1990 2019 0.283*** 0.236*** (0.005) (0.006) 0.046*** 0.021*** (0.002) (0.004) -0.028*** -0.012** (0.003) (0.005) -0.159*** -0.139*** (0.005) (0.008) -0.136*** -0.108*** (0.001) (0.003) 1.969*** 1.636*** (0.014) (0.036) 592,049 133,822 0.085 0.094 46 APPENDIX Notes 1 In 1990, 17 percent of women and 24 percent of men had a bachelor’s degree or higher, a 7 percentage-point gap. By 2019, 35 percent of women and 37 percent of men had a bachelor’s degree or higher. 2 The household head refers to the person (or one of the people) in whose name the housing unit is owned or rented (maintained) or, if there is no such person, any adult member, excluding roomers, boarders, or paid employees. If the house is owned or rented jointly by a married couple, the head may be either partner and is designated as the “reference person” to whom the relationships of all other household members, if any, are recorded. 3 In 2019, for married couples with a female head and two earners, the median woman’s income was 53.4 percent of total household income. The ratio was higher in 1990. 4 For those who are not married, we observe smaller changes in the share of female household heads. For nevermarried households, the share increased from 50 percent to 51 percent between 1990 and 2019. For divorced or separated households, the share decreased from 63 percent to 60 percent, and for widowed households, the share decreased from 84 percent to 76 percent. 5 Even in 2019, female-headed households still had a lower homeownership rate than male-headed households in all marital categories. For example, the homeownership rate for never-married female-headed households was 32 percent, lower than the rate for never-married male-headed households (38 percent). But if we combine divorced and separated, widowed, and never-married households into one category (i.e., “single” households), single women have a slightly higher homeownership rate than single men in 2019, consistent with previous findings (see Odeta Kushi, “For Single Women, Homeownership Increasingly Comes First,” First American, June 11, 2020, https://blog.firstam.com/economics/for-single-women-homeownership-increasingly-comes-first). This is because the homeownership rate is higher for widowed households or divorced households than for never-married households, and female-headed households have a larger share of widowed or divorced households than male-headed households. We decided to separate these households because divorced, separated, and widowed households are likely to differ from never-married households in multiple dimensions, including, age, income, and wealth. 6 All incomes are in 2019 constant dollars. 7 The sample size for 1990 is larger than the sample size for 2019 because we used decennial census data for 1990 but used American Community Survey annual data for 2019. 8 Although our dependent variable is binary, we used the ordinary least squares regression because of the ease of interpretation of the coefficients. Studies, including Angrist and Pischke (2009), suggest that the difference between marginal effects calculated from the linear probability model and logit or probit models is minor when the mean of the dependent variable ranged between 0.2 and 0.8. In both years of our estimation, the mean value of the homeownership rate falls within this range. 9 Jung Hyun Choi and Daniel Pang, “More Asian Americans Are Becoming Homeowners, but They Still Face Barriers in the Housing Market,” Urban Wire (blog), Urban Institute, June 17, 2021, https://www.urban.org/urban-wire/more-asian-americans-are-becoming-homeowners-they-still-face-barriershousing-market. 10 Lauren Bauer, “Mothers Are Being Left Behind in the Economic Recovery from COVID-19,” Up Front (blog), Brookings Institution, May 6, 2021, https://www.brookings.edu/blog/up-front/2021/05/06/mothers-are-beingleft-behind-in-the-economic-recovery-from-covid-19/. 11 Tyler Atkinson and Alex Richter, “Pandemic Disproportionately Affects Women, Minority Labor Force Participation,” Federal Reserve Bank of Dallas, November 10, 2020, https://www.dallasfed.org/research/economics/2020/1110. NOTES 47 References Angrist, Joshua D., and Jörn-Steffen Pischke. 2009. Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton, NJ: Princeton University Press. Agarwal, Sumit, Richard Green, Eric Rosenblatt, Vincent W. Yao, and Jian Zhang. 2018. “Gender Difference and Intra-Household Economic Power in Mortgage Signing Order.” Journal of Financial Intermediation 36 (October): 86–100. https://doi.org/10.1016/j.jfi.2018.01.001. Choi, Jung Hyun, Jun Zhu, and Laurie Goodman. 2018. Intergenerational Homeownership: The Impact of Parental Homeownership and Wealth on Young Adults’ Tenure Choices. Washington, DC: Urban Institute. Choi, Jung Hyun, Jun Zhu, Laurie Goodman, Bhargavi Ganesh, and Sarah Strochak. 2019. Millennial Homeownership: Why Is It So Low, and How Can We Increase It? Washington, DC: Urban Institute. Choi, Jung Hyun, Richard K. Green, and Eul Noh. 2020. “Wage Trickle Down versus Rent Trickle Down: How Does an Increase in College Graduates Affect Wages and Rents?” Journal of Regional Science. https://doi.org/10.1111/jors.12516. Dietz, Robert D., and Donald R. Haurin. 2003. “The Social and Private Micro-level Consequences of Homeownership.” Journal of Urban Economics 54 (3): 401–50. https://doi.org/10.1016/S0094-1190(03)00080-9. Goodman, Laurie, Alanna McCargo, Edward Golding, Bing Bai, and Sarah Strochak. 2018. Barriers to Accessing Homeownership: Down Payment, Credit, and Affordability–2018. Washington, DC: Urban Institute. Green, Richard K., and Michelle J. White. 1997. “Measuring the Benefits of Homeowning: Effects on Children.” Journal of Urban Economics 41 (3): 441–61. https://doi.org/10.1006/juec.1996.2010. Grinstein-Weiss, Michael, Pajarita Charles, Shenyang Guo, Kim Manturuk, and Clinton Key. 2011. “The Effect of Marital Status on Home Ownership among Low-Income Households.” Social Service Review 85 (3): 475–503. https://doi.org/10.1086/662166. McCargo, Alanna, Jung Hyun Choi, and Edward Golding. 2019. “Building Black Homeownership Bridges: A FivePoint Framework for Reducing the Racial Homeownership Gap.” Washington, DC: Urban Institute. McCargo, Alanna, and Jung Hyun Choi. 2020. Closing the Gaps: Building Black Wealth through Homeownership. Washington, DC: Urban Institute. Myers, Dowell, Isaac Megbolugbe, and SeongWoo Lee. 1998. “Cohort Estimation of Homeownership Attainment among Native-Born and Immigrant Populations.” Journal of Housing Research 9 (2): 237–69. https://doi.org/10.1080/10835547.1998.12091939. Neal, Michael, and Alanna McCargo. 2020. How Economic Crises and Sudden Disasters Increase Racial Disparities in Homeownership. Washington, DC: Urban Institute. 48 REFERENCES About the Authors Jung Hyun Choi is a senior research associate in the Housing Finance Policy Center at the Urban Institute. She studies urban inequality, focusing on housing, urban economics, real estate finance, and disadvantaged populations in the housing market. Before joining Urban, Choi was a postdoctoral scholar at the University of Southern California Price Center for Social Innovation, where her research examined innovative housing and social policies to enhance quality of life for low-income households. Choi holds a PhD in public policy and management from the Price School of Public Policy at the University of Southern California. Laurie Goodman is vice president for housing finance policy and the founder of the Housing Finance Policy Center. The center provides policymakers with data-driven analyses of housing finance policy issues that they can depend on for relevance, accuracy, and independence. Before joining Urban, Goodman spent 30 years as an analyst and research department manager at several Wall Street firms. From 2008 to 2013, she was a senior managing director at Amherst Securities Group LP, a boutique broker-dealer specializing in securitized products, where her strategy effort became known for its analysis of housing policy issues. From 1993 to 2008, Goodman was head of global fixed income research and manager of US securitized products research at UBS and predecessor firms, which were ranked first by Institutional Investor for 11 straight years. Before that, she held research and portfolio management positions at several Wall Street firms. She began her career as a senior economist at the Federal Reserve Bank of New York. Goodman was inducted into the Fixed Income Analysts Hall of Fame in 2009. Goodman serves on the board of directors of MFA Financial, Arch Capital Group Ltd., Home Point Capital Inc., and DBRS Inc. and is a consultant to the Amherst Group. She has published more than 200 journal articles and has coauthored and coedited five books. Goodman has a BA in mathematics from the University of Pennsylvania and an AM and PhD in economics from Stanford University. Jun Zhu is a visiting assistant professor with the finance department at Indiana University Bloomington and a nonresident fellow in the Housing Finance Policy Center (HFPC) at the Urban Institute. Before joining Indiana University, she was a principal research associate with HFPC, where she provided timely and rigorous data-driven research of key housing policy issues, designed and conducted quantitative studies of housing finance market, and managed and explored housing and mortgage databases. Before that, Zhu was a senior economist in the Office of the Chief Economist at Freddie Mac, where she ABOUT THE AUTHORS 49 conducted research around mortgage and housing, including issues about default, prepayment, and house price appreciation. While at Freddie Mac, she served as a consultant to the US Department of the Treasury. Zhu has published more than 50 research articles on topics such as the financial crisis and the government-sponsored enterprises, mortgage refinance and modification, mortgage default and prepayment, housing affordability and credit availability, and affordable housing and access to homeownership. Her research has been published in leading real estate and finance academic and professional journals, such as Real Estate Economics, the Journal of Real Estate Finance and Economics, and the Journal of Fixed Income. Zhu holds a BS in real estate and a minor in computer science from Huazhong University of Science and Technology, an MS in real estate from Tsinghua University, and a PhD in real estate and a minor in economics from the University of Wisconsin–Madison. 50 ABOUT THE AUTHORS STATEMENT OF INDEPENDENCE The Urban Institute strives to meet the highest standards of integrity and quality in its research and analyses and in the evidence-based policy recommendations offered by its researchers and experts. We believe that operating consistent with the values of independence, rigor, and transparency is essential to maintaining those standards. As an organization, the Urban Institute does not take positions on issues, but it does empower and support its experts in sharing their own evidence-based views and policy recommendations that have been shaped by scholarship. Funders do not determine our research findings or the insights and recommendations of our experts. Urban scholars and experts are expected to be objective and follow the evidence wherever it may lead. 500 L’Enfant Plaza SW Washington, DC 20024 www.urban.org