There are 2.2 million people in the United States who—in normal times—work in private homes. These domestic workers are the professionals who are caring for children, supporting older individuals and people with disabilities, and helping households stay clean. This chartbook provides a comprehensive look at not only who domestic workers are and where they live but also their economic vulnerability—their wage, income, benefit, and poverty levels relative to workers in other occupations.
We are releasing this chartbook in the midst of the coronavirus pandemic—a crisis that has highlighted the importance of keeping our homes clean, the skills and patience required to provide child care, and the urgency of caring for elderly, sick, and disabled Americans.
Here are just a few key findings:
- The vast majority (91.5%) of domestic workers are women and just over half (52.4%) are black, Hispanic, or Asian American/Pacific Islander women.
- Though most (64.9% of) domestic workers are U.S.-born, they are more likely than other workers to have been born outside the U.S. and they tend to be older than other workers.
- The typical (median) domestic worker is paid $12.01 per hour, much less than other workers (who are paid $19.97 per hour). Even when compared with demographically similar workers, domestic workers on average are paid just 74 cents for every dollar that their peers make.
- Domestic workers are three times as likely to be living in poverty as other workers, and almost three times as likely to either be in poverty or be above the poverty line but still without sufficient income to make ends meet.
- Fewer than one in 10 domestic workers are covered by an employer-provided retirement plan and just one in five receives health insurance coverage through their job.
The coronavirus crisis has laid bare the ways in which this work is undervalued and this workforce is underprotected. As their employers take steps to practice social distancing, many domestic workers have been left without work—and without any indication that they would get their jobs back. 1 At the same time, many domestic workers who are still on the front lines of the pandemic, caring for the sick and keeping homes clean, may lack the protective equipment they need. Although the pandemic serves as the backdrop for this chartbook, only data from before the pandemic was available at the time of our analysis. That means that the charts and data tables here provide a snapshot of domestic workers in the pre-coronavirus period.
In addition to caring for children and helping households stay clean, domestic workers support older people and people with disabilities or illnesses by providing hands-on health care, running errands, making meals, and cleaning homes, allowing their clients to live as independently as possible in their own homes. These services are incredibly valuable to those who receive them and to the other workers who would otherwise be spending their time on this important work. Given continued gender disparities in home responsibilities for unpaid care work, working women in particular are affected by the existence of the domestic workforce.
Although domestic work is vital to everyday life, this chartbook shows that domestic workers face low pay, rarely receive benefits, and have less access to full-time work than other workers. Because they work in private homes, they are outside of public view and isolated from other workers, leaving them particularly vulnerable to exploitation.2 And many groups of domestic workers are explicitly left out of many federal labor and employment protections—a policy decision dating back to the New Deal, when majority-black domestic and farmworkers were excluded from landmark federal labor laws as a concession to racist Southern lawmakers.3
Specifically, domestic workers are excluded from the National Labor Relations Act, enacted in 1935 to guarantee employees the right to form labor unions—or engage in other forms of collective action—to organize for better working conditions. And “live-in” workers are excluded from the overtime protections in the Fair Labor Standards Act, enacted in 1938.
The exclusions for domestic workers carried through to subsequent worker protection statutes. The Occupational Safety and Health Act does not apply to “individuals who, in their own residences, privately employ persons for the purpose of performing…what are commonly regarded as ordinary domestic household tasks, such as house cleaning, cooking, and caring for children.”4 Federal anti-discrimination laws, such as the Civil Rights Act, the Americans with Disabilities Act, and the Age Discrimination in Employment Act, all generally cover only employers with multiple employees, meaning many domestic workers are excluded from these protections. This exclusion is also part of the Family and Medical Leave Act.
A critical first step to providing domestic workers with the same protections as other workers is passing a National Domestic Workers Bill of Rights. In addition to extending basic wage and hour protections to domestic workers, such a measure would include key provisions establishing fair scheduling (i.e, no unexpected shift cancelations or changes without warning or compensation), transparent employment contracts, and access to health care and retirement benefits for domestic workers. Nine states (California, Connecticut, Hawaii, Illinois, Massachusetts, Nevada, New Mexico, New York, and Oregon) and the city of Seattle have already passed Domestic Workers Bills of Rights, and other states and localities should follow suit.
A quick note about the data and definitions
Throughout this chartbook, we distinguish between two types of child care workers: nannies, whose workplace is their employer’s private residence, and child care workers who provide care in their own homes. We also look at two different groups of home care aides: those who are agency-based (i.e., they work in clients’ homes but are paid by an agency such as a Medicare-certified home health agency) and home care aides who are paid directly by clients. Throughout this chartbook we refer to subgroups of domestic workers as “occupations”, although we define these subgroups using industry, occupation, and sector information. Throughout this chartbook we refer to subgroups of domestic workers as “occupations,” although we define these subgroups using industry, occupation, and sector information. For more details on the domestic worker occupations, see “Domestic worker occupations defined” at the end of this chartbook.
The hourly wage measure used throughout this chartbook includes overtime, tips, and commissions for both hourly and nonhourly workers. For more details on the data samples and measures used in this chartbook, see “Technical notes about data and definitions” at the end of this chartbook.
Supplemental tables
In addition to the data available in this chartbook, we have produced supplemental tables with demographic breakdowns and median hourly wages of domestic workers in each state and in selected metropolitan areas.
Home care aides make up the majority of the nation's 2.2 million domestic workers: Employment in domestic worker occupations, 2019
| House cleaners | Nannies | Providers of child care in own home | Non-agency-based home care aides | Agency-based home care aides | |
|---|---|---|---|---|---|
| House cleaners | 343,527 | ||||
| Child care workers | 225,933 | 276,311 | |||
| Home care aides | 141,400 | 1,257,878 |
Note: There were 2,245,047 workers in domestic occupations in 2019. To ensure sufficient sample sizes for the subcategories, this figure draws from pooled 2017–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
T
here are 2.2 million domestic workers in the United States and more than half are agency-based home care aides. Domestic workers do the vital work of cleaning homes, tending to children, and providing daily living and health assistance to people who are elderly, are convalescing from illness, or have disabilities. The data from this chart are also available in Table 1, at the end of the chartbook.
It is highly likely that this 2.2 million estimate is an undercount of domestic workers. First, a significant proportion of domestic workers are paid “under the table,” which makes individuals who participate in surveys less likely to report these jobs. Second, the share of domestic workers who were born outside of the United States is higher than the share of workers overall who are not U.S.-born, and it is believed that immigrants are underrepresented in national surveys.5
Women make up the vast majority of domestic workers: Share of workers who are women or men, for domestic workers, for all other workers, and by domestic worker occupation, 2019
| Women | Men | |
|---|---|---|
| Domestic workers | 91.5% | 8.5% |
| All other workers | 46.3% | 53.7% |
| House cleaners | 95.5% | 4.5% |
| Nannies | 96.8% | 3.2% |
| Child care (in own home) | 97.2% | 2.8% |
| Home care (non-agency) | 86.1% | 13.9% |
| Home care (agency-based) | 88.8% | 11.2% |
Note: To ensure sufficient sample sizes, this figure draws from pooled 2017–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
More than nine in 10 domestic workers (91.5%) are women—a gender imbalance that is even more pronounced for house cleaners (95.5% women) and child care providers (roughly 97% women). By comparison, women make up just under half (46.3%) of the rest of the workforce. While men are somewhat more likely to be home care aides than house cleaners or child care providers, they still account for less than 15% of home care aides.
See Table 2 at the end of the chartbook for a demographic breakdown of domestic workers by gender, race/ethnicity, nativity, education, and age. We have also provided supplemental tables with demographic breakdowns of domestic workers in each state and in selected metropolitan areas.
Black and Hispanic workers make up a disproportionate share of domestic workers: Share of workers who are of a given race or ethnicity, for domestic workers, for all other workers, and by domestic worker occupation, 2019
| White, non-Hispanic | Black, non-Hispanic | Hispanic, any race | Asian American/Pacific Islander | Other | |
|---|---|---|---|---|---|
| Domestic workers | 41.7% | 21.7% | 29.1% | 6.3% | 1.3% |
| All other workers | 62.9% | 11.9% | 17.1% | 6.9% | 1.1% |
| House cleaners | 29.0% | 6.5% | 61.5% | 2.2% | 0.8% |
| Nannies | 64.6% | 7.9% | 23.8% | 3.3% | 0.5% |
| Child care (in own home) | 54.8% | 13.3% | 28.4% | 2.7% | 0.8% |
| Home care (non-agency) | 51.3% | 20.1% | 19.5% | 7.2% | 2.0% |
| Home care (agency-based) | 37.0% | 30.3% | 22.4% | 8.6% | 1.6% |
Note: To ensure sufficient sample sizes, this figure draws from pooled 2017–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Well over half (57.1%) of domestic workers are black, Hispanic, or Asian American/Pacific Islander (AAPI). In contrast, black, Hispanic, and AAPI workers make up 36.0% of the rest of the workforce. House cleaners constitute the domestic worker occupation with the highest share of Hispanic workers (61.5%), while agency-based home care aides constitute the domestic worker occupation with the highest share of black, non-Hispanic workers (30.3%).
See Table 2 for a demographic breakdown of domestic workers by gender, race/ethnicity, nativity, education, and age. We have also provided supplemental tables with demographic breakdowns of domestic workers in each state and in selected metropolitan areas.
Black and Hispanic women make up a disproportionate share of domestic workers: The share of domestic workers who are black, Hispanic, or AAPI women, 2019
| Occupation | Black, non-Hispanic women | Hispanic women, any race | Asian American/Pacific Islander (AAPI) women |
|---|---|---|---|
| Domestic workers | 19.7% | 27.2% | 5.5% |
| All other workers | 6.2% | 7.1% | 3.2% |
| House cleaners | 6.1% | 58.9% | 2.0% |
| Nannies | 7.4% | 22.6% | 3.1% |
| Child care (in own home) | 13.1% | 27.8% | 2.6% |
| Home care (non-agency) | 18.5% | 17.7% | 6.3% |
| Home care (agency-based) | 27.2% | 20.3% | 7.4% |
Note: To ensure sufficient sample sizes for the subcategories, this figure draws from pooled 2017–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
While women of all races and ethnicities are overrepresented in the domestic employee workforce, this overrepresentation is particularly pronounced for Hispanic and black women. A majority (52.4%) of domestic workers are black, Hispanic, or AAPI women—over a quarter (27.2%) are Hispanic women and nearly one in five (19.7%) are black women. Most house cleaners are Hispanic women (58.9%) and more than a quarter (27.2%) of agency-based home care aides are black women.
See Table 3 for a detailed demographic breakdown showing the race/ethnicity and nativity of domestic workers by gender.
Domestic workers are more likely than other workers to have been born outside the U.S.: Share of workers with given nativity status, for domestic workers, for all other workers, and by domestic worker occupation, 2019
| U.S.-born | Foreign-born U.S. citizen | Foreign-born noncitizen | |
|---|---|---|---|
| Domestic workers | 64.9% | 14.8% | 20.3% |
| All other workers | 82.9% | 8.4% | 8.7% |
| House cleaners | 30.7% | 18.5% | 50.8% |
| Nannies | 71.6% | 11.4% | 16.9% |
| Child care (in own home) | 70.9% | 12.3% | 16.8% |
| Home care (non-agency) | 76.7% | 10.6% | 12.6% |
| Home care (agency-based) | 70.4% | 15.4% | 14.2% |
Notes: To ensure sufficient sample sizes, this figure draws from pooled 2017–2019 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
More than a third (35.1%) of domestic workers were born outside of the U.S., compared with just 17.1% of the rest of the workforce. One in five is a foreign-born noncitizen (20.3%), while about one in seven is a U.S. citizen who was born in a different country (14.8%). While noncitizens are overrepresented in all domestic worker occupations, they are particularly overrepresented in the house cleaner workforce, making up half (50.8%) of house cleaners.
See Table 2 for a demographic breakdown of domestic workers by gender, race/ethnicity, nativity, education, and age. Table 3 provides even more detail, showing the race/ethnicity and nativity of domestic workers by gender. We have also provided supplemental tables with demographic breakdowns of domestic workers in each state and in selected metropolitan areas.
Domestic workers tend to be older than other workers: Share of workers by age group, for domestic workers, for all other workers, and by domestic worker occupation, 2019
| Under 23 | 23–49 | 50+ | |
|---|---|---|---|
| Domestic workers (median age 45) | 9.0% | 51.0% | 40.0% |
| All other workers (median age 41) | 8.3% | 58.2% | 33.5% |
| House cleaners (median age 47) | 2.8% | 54.3% | 42.8% |
| Nannies (median age 26) | 35.7% | 46.2% | 18.1% |
| Child care (in own home) (median age 47) | 5.9% | 50.8% | 43.3% |
| Home care (non-agency) (median age 51) | 6.1% | 40.8% | 53.0% |
| Home care (agency-based) (median age 45) | 6.8% | 52.1% | 41.0% |
Note: To ensure sufficient sample sizes, this figure draws from pooled 2017–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Two in five domestic workers are age 50 or older, while just one-third of all other workers are at least 50 years old. Home care aides who aren’t agency-based are the domestic worker occupation with the highest median age (51). The exception to the tendency of domestic workers to skew older is the occupation of nannies, whose median age is 26. Over one-third of nannies are younger than 23 years old, compared with 8.3% of nondomestic workers who are under 23.
These data suggest that domestic work is often an important source of income for older workers. The reliance of some older workers on income from domestic occupations is particularly relevant during the coronavirus pandemic—older workers have a greater risk of severe illness from the virus—and underscores the need to provide domestic workers with access to paid sick leave and adequate protective equipment.
See Table 2 for more detailed age categories and the median ages of domestic workers. We have also provided supplemental tables with demographic breakdowns of domestic workers in each state and in selected metropolitan areas.
How many domestic workers are employed in your state?: Number of domestic workers working in each state, by occupation and compared with all workers, 2019
| State | All other workers | Domestic workers | House cleaners | Nannies | Child care (in own home) | Home care (non-agency) | Home care (agency-based) |
|---|---|---|---|---|---|---|---|
| Connecticut | 1,854,406 | 30,016 | 4,618 | 3,700 | 3,546 | 2,826 | 15,009 |
| Maine | 695,023 | 10,931 | 883 | 869 | 1,760 | 807 | 6,663 |
| Massachusetts | 3,511,411 | 50,085 | 6,267 | 6,390 | 5,588 | 2,971 | 29,386 |
| New Hampshire | 753,295 | 8,011 | 841 | 1,181 | 964 | 516 | 4,536 |
| New Jersey | 4,471,507 | 56,112 | 10,550 | 6,631 | 5,496 | 2,663 | 30,892 |
| New York | 9,360,472 | 258,155 | 30,949 | 17,764 | 24,117 | 8,378 | 190,515 |
| Pennsylvania | 6,340,703 | 74,297 | 6,870 | 6,620 | 5,963 | 4,825 | 54,453 |
| Rhode Island | 554,549 | 5,601 | 585 | 687 | 771 | 233 | 3,345 |
| Vermont | 354,627 | 6,186 | 619 | 521 | 1,187 | 649 | 3,002 |
| Illinois | 6,448,489 | 84,647 | 8,657 | 11,219 | 14,719 | 5,230 | 42,236 |
| Indiana | 3,227,001 | 30,366 | 3,387 | 2,741 | 5,438 | 1,079 | 17,183 |
| Iowa | 1,695,788 | 22,610 | 1,578 | 2,184 | 7,403 | 758 | 8,053 |
| Kansas | 1,490,107 | 22,938 | 1,910 | 3,042 | 5,152 | 705 | 10,843 |
| Michigan | 4,781,699 | 63,973 | 5,066 | 7,350 | 10,895 | 4,053 | 35,789 |
| Minnesota | 2,976,346 | 48,691 | 2,917 | 4,966 | 11,186 | 2,066 | 25,511 |
| Missouri | 3,023,480 | 43,548 | 3,152 | 4,073 | 6,578 | 1,530 | 28,977 |
| Nebraska | 1,020,590 | 12,842 | 1,113 | 1,606 | 4,071 | 461 | 3,976 |
| North Dakota | 394,134 | 5,526 | 286 | 471 | 1,911 | 198 | 1,998 |
| Ohio | 5,762,605 | 74,214 | 7,097 | 7,210 | 10,184 | 2,374 | 48,709 |
| South Dakota | 453,616 | 4,987 | 325 | 499 | 2,010 | 136 | 1,156 |
| Wisconsin | 3,082,812 | 41,105 | 2,409 | 3,867 | 7,207 | 2,165 | 25,492 |
| Alabama | 2,167,013 | 19,429 | 3,988 | 2,291 | 2,183 | 2,174 | 8,264 |
| Arkansas | 1,334,766 | 16,837 | 2,584 | 1,022 | 1,596 | 1,134 | 11,092 |
| Delaware | 451,111 | 4,330 | 438 | 424 | 813 | 268 | 2,266 |
| Washington D.C. | 344,833 | 4,021 | 813 | 899 | 247 | 197 | 1,808 |
| Florida | 9,258,211 | 104,482 | 37,002 | 9,088 | 7,218 | 8,567 | 38,969 |
| Georgia | 4,745,118 | 41,810 | 8,899 | 6,848 | 5,058 | 3,264 | 15,768 |
| Kentucky | 2,009,155 | 18,064 | 3,227 | 1,832 | 2,971 | 1,848 | 7,302 |
| Louisiana | 2,057,857 | 31,380 | 4,921 | 2,566 | 2,817 | 2,780 | 19,113 |
| Maryland | 3,080,645 | 36,947 | 6,766 | 6,992 | 6,726 | 1,961 | 11,292 |
| Mississippi | 1,273,037 | 11,609 | 2,323 | 713 | 1,730 | 1,279 | 5,188 |
| North Carolina | 4,560,543 | 59,710 | 7,041 | 6,288 | 6,235 | 2,842 | 39,024 |
| Oklahoma | 1,789,220 | 20,858 | 3,012 | 1,665 | 2,833 | 1,216 | 12,176 |
| South Carolina | 2,154,162 | 19,569 | 3,136 | 2,098 | 2,308 | 1,517 | 10,434 |
| Tennessee | 3,048,589 | 31,370 | 5,370 | 2,664 | 3,767 | 3,493 | 15,825 |
| Texas | 12,297,893 | 213,896 | 42,267 | 16,876 | 15,865 | 10,914 | 134,434 |
| Virginia | 4,159,587 | 56,406 | 7,752 | 10,434 | 8,526 | 5,238 | 21,542 |
| West Virginia | 788,773 | 13,038 | 887 | 479 | 1,207 | 917 | 10,563 |
| Alaska | 346,681 | 5,713 | 230 | 481 | 1,013 | 252 | 3,802 |
| Arizona | 3,053,357 | 40,736 | 7,390 | 3,905 | 4,130 | 4,662 | 20,558 |
| California | 17,989,336 | 358,013 | 74,374 | 30,359 | 35,743 | 28,994 | 188,209 |
| Colorado | 2,767,754 | 35,900 | 6,025 | 6,698 | 5,395 | 1,539 | 14,306 |
| Hawaii | 662,053 | 5,084 | 842 | 221 | 724 | 547 | 2,714 |
| Idaho | 774,528 | 11,229 | 812 | 1,192 | 2,118 | 1,018 | 5,797 |
| Montana | 508,979 | 6,291 | 572 | 631 | 1,129 | 352 | 3,496 |
| Nevada | 1,335,289 | 9,518 | 2,212 | 1,148 | 1,067 | 850 | 3,915 |
| New Mexico | 915,274 | 20,904 | 1,992 | 650 | 1,587 | 1,509 | 16,872 |
| Oregon | 1,929,241 | 29,320 | 2,777 | 3,342 | 5,017 | 3,086 | 14,311 |
| Utah | 1,413,140 | 11,367 | 1,181 | 2,104 | 2,792 | 376 | 3,783 |
| Washington | 3,449,723 | 49,080 | 4,293 | 8,143 | 6,546 | 3,767 | 25,891 |
| Wyoming | 297,389 | 3,295 | 323 | 292 | 804 | 216 | 1,441 |
Note: To ensure sufficient sample sizes, this map draws from pooled 2010–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
This map is color-coded to show which states have the most domestic workers. You can click on a state to display how many domestic workers total are employed there, and how many are employed in each domestic worker occupation, and compare these with the number of workers in all other occupations. You can access the map data from Table 4, which also shows employment counts by region. Employment counts for selected metropolitan areas are available in Table 5.
We have also provided supplemental tables with demographic breakdowns and median hourly wages of domestic workers in each region and state and in selected metropolitan areas.
There is a wide and persistent gap between domestic workers’ wages and wages of all other workers: Median real hourly wages of domestic workers, by occupation, versus other workers, 2005–2019
| All other workers | Home care (agency-based) | Home care (non-agency) | House cleaners | Nannies | |
|---|---|---|---|---|---|
| 2005 | $19.21 | $11.34 | $11.81 | $11.21 | $10.54 |
| 2006 | $19.05 | $11.35 | $11.97 | $11.13 | $10.42 |
| 2007 | $18.99 | $11.34 | $12.27 | $10.98 | $10.52 |
| 2008 | $18.99 | $11.31 | $12.21 | $11.07 | $10.53 |
| 2009 | $19.12 | $11.32 | $12.07 | $11.39 | $10.66 |
| 2010 | $19.32 | $11.35 | $11.93 | $11.64 | $10.58 |
| 2011 | $19.29 | $11.49 | $11.90 | $11.50 | $10.41 |
| 2012 | $19.07 | $11.36 | $12.15 | $11.37 | $10.27 |
| 2013 | $18.92 | $11.22 | $11.38 | $11.28 | $10.73 |
| 2014 | $18.87 | $11.04 | $11.19 | $10.85 | $10.76 |
| 2015 | $18.98 | $11.01 | $11.11 | $10.76 | $10.82 |
| 2016 | $19.27 | $11.18 | $11.75 | $10.79 | $10.81 |
| 2017 | $19.52 | $11.51 | $11.81 | $11.11 | $11.08 |
| 2018 | $19.72 | $11.67 | $11.84 | $11.41 | $11.87 |
| 2019 | $19.97 | $12.08 | $11.89 | $11.89 | $11.60 |
Notes: Wages include overtime, tips, and commissions and are computed from rolling three-year pooled microdata (i.e., “2019” is pooled 2017–2019 data, “2018” is pooled 2016–2018 data, “2017” is pooled 2015–2017 data, etc.). Since the best wage measure in the Current Population Survey is unavailable for self-employed workers, wages of workers who provide child care in their own homes are not included.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
There is a large “domestic worker wage gap”—a wide gulf between the median hourly wage of domestic workers and the median hourly wage of all other workers. The wage gap for domestic workers is not only large, but it is also persistent. Like other typical workers, domestic workers have seen stagnant wages for decades (since well before 2005, which is the starting point in this chart because it is the first year for which data are available for the domestic worker occupations defined in our analyses). For an in-depth look at the sluggish wage growth of the last 40 years, see EPI’s report State of Working America Wages 2019.6
The pay gap for domestic workers is widest for nannies: Median real hourly wages, domestic workers (all and by occupation) versus other workers, 2019
| Hourly wage | |
|---|---|
| Domestic workers | $12.01 |
| All other workers | $19.97 |
| House cleaners | $11.89 |
| Nannies | $11.60 |
| Home care (non-agency) | $11.89 |
| Home care (agency-based) | $12.08 |
Notes: Wages include overtime, tips, and commissions and are computed from pooled 2017–2019 microdata to ensure sufficient sample size. Data are in 2019 dollars. Since the best wage measure in the Current Population Survey is unavailable for self-employed workers, wages of workers who provide child care in their own homes are not included.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
The typical domestic worker is paid $12.01 per hour, including overtime, tips, and commissions—39.8% less than the typical nondomestic worker, who is paid $19.97. This wide gap between domestic workers’ wages and the wages of all other workers is consistent across domestic worker occupations.
Table 6 shows the median hourly wages of domestic workers, all other workers, and domestic workers by occupation broken out by gender, race/ethnicity, nativity, education, and age. We have also provided supplemental tables with median hourly wages of domestic workers by demographic group for each region and state and for selected metropolitan areas.
Domestic workers who are male, U.S.-born, AAPI, college-educated, or ages 50 and older have the biggest wage gaps relative to their peers in other professions: Median real hourly wages, domestic workers versus other workers, 2019
| Hourly wage | |
|---|---|
| Domestic workers | $12.01 |
| Other workers | $19.97 |
| Domestic workers | $12.85 |
| Other workers | $21.62 |
| Domestic workers | $13.00 |
| Other workers | $24.46 |
| Domestic workers | $13.49 |
| Other workers | $30.09 |
| Domestic workers | $12.04 |
| Other workers | $22.87 |
Notes: This chart pulls the demographic worker categories with the largest percent difference between the hourly wages of all other workers and domestic workers in Table 6. Wages include overtime, tips, and commissions and are computed from pooled 2017–2019 microdata to ensure sufficient sample size. Data are in 2019 dollars.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
W
ithin every demographic category that we analyze, domestic workers are typically paid less than their peers. Male domestic workers face a larger wage gap relative to other men ($8.77, or 40.6%) than do female domestic workers ($6.27, or 34.4%; not shown). Asian American/Pacific Islander domestic workers, older domestic workers, and domestic workers with at least a bachelor’s degree also face particularly large within-group wage gaps.
Table 6 shows the median hourly wages of all domestic workers versus all other workers, and by domestic worker occupation, broken out by gender, race/ethnicity, nativity, education, and age.
Even when controlling for demographics and education, domestic workers are paid less than similar workers: Average domestic worker hourly wages as a share of wages paid to demographically similar workers in other professions, 2019
| Wage share | Wage gap | |
|---|---|---|
| Domestic workers | 74.1% | 25.9% |
| Other workers | 100.0% | |
| House cleaners | 79.1% | 20.9% |
| Nannies | 79.8% | 20.2% |
| Home care (non-agency) | 64.5% | 35.5% |
| Home care (agency-based) | 73.5% | 26.5% |
Notes: All wage gaps are significantly different from zero at the 0.01 level. The regressions control for gender, nativity, race/ethnicity, educational attainment, age, marital status, and census geographical division. To ensure sufficient sample sizes, this figure draws from pooled 2017–2019 microdata. Since the best wage measure in the Current Population Survey is unavailable for self-employed workers, wages of workers who provide child care in their own homes are not included.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
E
ven when we control for demographics and educational background using regressions, domestic workers face a big pay gap: The average domestic worker is paid 74 cents for every dollar that a similar worker would make in another occupation—or 26% less. Home care aides who are not agency-based face the largest wage gap: Their wages are two-thirds the wages of demographically similar workers—a third less. Although the regression-adjusted wage gap is smaller for nannies and house cleaners, they are still paid only about 80 cents for every dollar that a similar worker would make in another occupation.
Table 7 shows regression-adjusted hourly wage gaps for all domestic workers and for each domestic worker occupation, broken out by gender, race/ethnicity, nativity, education, and age.
Domestic workers are more likely to work part time and more than twice as likely to work part time because they can't get full-time hours: Share of workers who work full and part time, for domestic workers, for all other workers, and by domestic worker occupation, 2019
| Full-time | Part-time for economic reasons (i.e., want full-time work) | Part-time for noneconomic reasons | |
|---|---|---|---|
| Domestic workers | 54.8% | 9.7% | 35.6% |
| All other workers | 77.3% | 4.0% | 18.7% |
| House cleaners | 37.0% | 15.0% | 47.9% |
| Nannies | 52.3% | 7.4% | 40.3% |
| Child care (in own home) | 67.4% | 6.2% | 26.4% |
| Home care (non-agency) | 51.7% | 9.3% | 39.0% |
| Home care (agency-based) | 57.6% | 9.4% | 33.0% |
Notes: “Part-time” is defined as usually working less than 35 hours per week on the primary job. Those who say they are working part time because they could only find part-time work or because of slack work or business conditions are categorized by the Bureau of Labor Statistics as part-timers “for economic reasons” and often described as workers who would prefer to work full time. The “part-time for noneconomic reasons” category includes workers who say they work part time to take care of their children or for other family and personal reasons; while they may prefer to work full time if, say, they could afford child care, they are not included in the standard count of part-timers who want full-time work. To ensure sufficient sample sizes, this figure draws from pooled 2017–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
I
n addition to having lower hourly wages, domestic workers tend to work fewer hours than other workers. Nearly half of domestic workers work part time, compared with less than a quarter of all other workers. Much of this difference is at least somewhat “voluntary,” with domestic workers being more likely than other workers to have a part-time job because they want a part-time schedule (or need a part-time schedule to handle child care or other responsibilities). But domestic workers are also more than twice as likely as other workers to want a full-time job but to have to settle for a part-time job because they can’t get full-time hours. The greater likelihood of wanting but being unable to get full-time work is particularly acute for house cleaners, 15% of whom work part time but would like a full-time job. The greater incidence of part-time work among domestic workers is reflected in their average weekly hours on the job (not shown). While workers in other occupations put in just under 40 hours a week on average, domestic workers spend an average of 33.4 hours on the job each week.
Table 8 displays the data from this chart, as well as the average weekly hours of domestic workers.
Domestic workers are paid less in a year than other workers: Median annual earnings, domestic workers versus other workers, 2018
| Median annual earnings | |
|---|---|
| Domestic workers | $15,980 |
| All other workers | $39,120 |
| House cleaners | $14,915 |
| Nannies | $13,558 |
| Home care (non-agency) | $18,111 |
| Home care (agency-based) | $20,337 |
Notes: Earnings include reported annual wage and salary income but exclude income from unemployment insurance, child support, investments, Social Security, etc. To ensure sufficient sample sizes, this figure draws from pooled 2016–2018 microdata. Since the earnings measure we use here does not include earnings from self-employment, earnings of workers who provide child care in their own homes are not included.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
T
he combination of lower average hours and much lower median wages (shown in Table 8 and Figure 9) results in substantially lower annual earnings for domestic workers relative to other workers. The typical domestic worker’s annual earnings are just two-fifths of a typical worker’s in another occupation. While typical agency-based home care aides have higher annual earnings than domestic workers in other occupations, they still are paid just half of what workers outside the domestic workforce are paid in a year.
Table 9 shows the median annual earnings of all domestic workers, domestic worker occupations, and all other workers, broken out by gender, race/ethnicity, nativity, education, and age.
Even when controlling for demographics and education, domestic workers are paid less in a year than similar workers: Average domestic worker annual earnings as a share of earnings paid to demographically similar workers in other professions, 2018
| Earnings share | Earnings gap | |
|---|---|---|
| Domestic workers | 46.2% | 53.8% |
| Other workers | 100% | |
| House cleaners | 33.2% | 66.8% |
| Nannies | 28.7% | 71.3% |
| Home care (non-agency) | 41.7% | 58.3% |
| Home care (agency-based) | 57.2% | 42.8% |
Notes: All earnings gaps are significantly different from zero at the 0.01 level. The regressions control for gender, nativity, race/ethnicity, educational attainment, age, marital status, and census geographical division. To ensure sufficient sample sizes, this figure draws from pooled 2016–2018 microdata. Since the earnings measure we use here does not include earnings from self-employment, earnings of workers who provide child care in their own homes are not included.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
E
ven when we control for demographics and educational background using a regression, domestic workers face a big pay gap as a result of lower hourly wages and fewer hours: The average domestic worker is paid less than half of what a similar worker would make in another profession on an annual basis. Nannies face the largest gap: Their annual earnings are less than one-third the earnings of a demographically similar worker. Although the regression-adjusted earnings gap is smaller for agency-based home care aides, they are still paid 42.8% less annually than a similar worker would be paid in another occupation.
Domestic workers are three times as likely to be in poverty and almost three times as likely to lack enough income to make ends meet: Poverty rates and twice-poverty rates of domestic workers versus other workers, 2018
| Rate | |
|---|---|
| Domestic workers | 16.8% |
| All other workers | 5.0% |
| House cleaners | 25.4% |
| Nannies | 20.1% |
| Child care (in own home) | 13.3% |
| Home care (non-agency) | 14.2% |
| Home care (agency-based) | 15.1% |
| Domestic workers | 44.3% |
| All other workers | 16.9% |
| House cleaners | 54.8% |
| Nannies | 39.0% |
| Child care (in own home) | 32.4% |
| Home care (non-agency) | 36.4% |
| Home care (agency-based) | 45.8% |
Notes: The poverty rate is the share of workers whose family income is below the official poverty line. The twice-poverty rate is the share of workers whose family income is below twice the official poverty line. Since poverty thresholds set in the 1960s have not evolved to reflect changing shares of spending on various necessities by low-income families, researchers often use the twice-poverty rate as a better cutoff for whether a family is able to make ends meet. To ensure sufficient sample sizes, this figure draws from pooled 2016–2018 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
D
omestic workers are much more likely than other workers to be living in poverty, regardless of occupation. They are also much more likely to have incomes that fall below the twice-poverty threshold, which is considered by many researchers a better cutoff for whether a family has enough income to make ends meet. The majority of house cleaners are struggling to make ends meet (their “twice-poverty” rate is 54.8%) and more than a quarter (25.4%) have incomes that put them below the official poverty threshold. Workers who provide child care in their own homes have somewhat lower poverty rates than other domestic workers, although a third of them (32.4%) still do not have enough income to make ends meet—about twice the share of the nondomestic workforce living below the twice-poverty line. Domestic workers who are not U.S. citizens and those without a high school diploma face particularly high poverty rates, as do black and Hispanic domestic workers. (These data are shown at the end of the chartbook in Table 10 and Table 11, which provide poverty and twice-poverty rates for domestic workers and all other workers broken out by gender, race/ethnicity, nativity, education, and age.)
Poverty researchers generally do not consider the poverty rate to be a good measure of the share of families who cannot make ends meet in part because the poverty thresholds were set in the 1960s and have not evolved to reflect changing shares of spending on various necessities by low-income families. That is why “twice poverty” is often used as a cutoff for whether a family is able to make ends meet.
Even when controlling for demographics and education, domestic workers are more likely to live below the poverty line than similar workers: Percentage-point difference between the poverty rate of domestic workers and that of demographically similar workers in other occupations, 2018
| Poverty rate ppt. difference | |
|---|---|
| Domestic workers | 8.5 |
| House cleaners | 14.0 |
| Nannies | 10.8 |
| Child care (in own home) | 6.4 |
| Home care (non-agency) | 7.1 |
| Home care (agency-based) | 7.0 |
| Domestic workers | 17.8 |
| House cleaners | 19.5 |
| Nannies | 11.1 |
| Child care (in own home) | 9.8 |
| Home care (non-agency) | 13.6 |
| Home care (agency-based) | 19.9 |
Notes: All poverty rate differences are significantly different from zero at the 0.01 level. The regressions control for gender, nativity, race/ethnicity, educational attainment, age, marital status, and census geographical division. The “twice-poverty rate” is the share of workers whose family income is below twice the official poverty line, and is often considered a better cutoff for whether a family is able to make ends meet. To ensure sufficient sample sizes, this figure draws from pooled 2016–2018 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
E
ven when we compare domestic workers exclusively with workers in other professions who are demographically similar, domestic workers are still much more likely to be living in poverty. House cleaners on average have a poverty rate that is 14.0 percentage points higher than the poverty rate of similar workers. Along with agency-based home care aides, house cleaners also have twice-poverty rates that are nearly 20 percentage points higher than you would expect these rates to be if these workers were employed in nondomestic occupations. (The twice-poverty rate is the share of workers whose family income falls below the twice-poverty threshold, considered by many researchers a better cutoff for whether a family has enough income to make ends meet.)
Domestic workers are less likely to have health or retirement benefits: Employer-provided health insurance and retirement coverage rates, domestic workers versus other workers, 2018
| Coverage rate | |
|---|---|
| Domestic workers | 19.1% |
| All other workers | 48.9% |
| House cleaners | 7.3% |
| Nannies | 15.1% |
| Child care (in own home) | 6.8% |
| Home care (non-agency) | 17.1% |
| Home care (agency-based) | 25.2% |
| Domestic workers | 9.1% |
| All other workers | 32.8% |
| House cleaners | 2.0% |
| Nannies | 3.5% |
| Child care (in own home) | 2.6% |
| Home care (non-agency) | 6.6% |
| Home care (agency-based) | 13.1% |
Note: To ensure sufficient sample sizes, this figure draws from pooled 2016–2018 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
J
ust under one in five domestic workers has employer-provided health insurance, a shockingly low coverage rate compared with the near-majority of other workers who receive health insurance through their job. Coverage rates are less than 10% for house cleaners and workers who provide child care in their own home. Even agency-based home care aides, the domestic worker occupation with the highest employer-provided health insurance coverage rate, are barely half as likely to be covered as nondomestic workers.
The coverage rates for employer-provided retirement plans are even more dismal—fewer than one in 10 domestic workers are covered. By comparison, about a third of other workers benefit from their employer contributing to their retirement savings.
See Table 12 and Table 13 for variations in employer-provided health insurance and retirement coverage rates for domestic and all other workers by gender, race/ethnicity, nativity, education, and age.
Even when controlling for demographics and education, domestic workers are less likely to have benefits than similar workers: Percentage-point gap between the coverage rates of domestic workers and those of demographically similar workers in other occupations, 2018
| Coverage gap | |
|---|---|
| Domestic workers | 21.4 |
| House cleaners | 26.2 |
| Nannies | 18.4 |
| Child care (in own home) | 34.5 |
| Home care (non-agency) | 24.9 |
| Home care (agency-based) | 17.1 |
| Domestic workers | 17.1 |
| House cleaners | 17.3 |
| Nannies | 17.3 |
| Child care (in own home) | 26.6 |
| Home care (non-agency) | 20.6 |
| Home care (agency-based) | 14.1 |
Note: All coverage gaps are significantly different from zero at the 0.01 level, using heteroskedasticity-robust standard errors. Regressions control for gender, nativity, race/ethnicity, educational attainment, age, marital status, and census geographical division. To ensure sufficient sample sizes, this figure draws from pooled 2016–2018 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
The glaring gaps in health insurance and retirement coverage rates are evident even when we compare domestic workers with demographically similar workers. The share of domestic workers with employer-provided health insurance is 21.4 percentage points lower than the share of all other workers with such coverage. And the share of domestic workers with employer-provided retirement plans is 17.1 percentage points lower than the share of all other workers with such coverage. Agency-based home care aides are more likely than other domestic workers to have employer-provided benefits, but the gap between these workers and nondomestic workers remains enormous even after controlling for demographic characteristics.
Employment in domestic worker occupations is growing faster than the rest of the workforce: Projected employment change, domestic workers versus other workers, 2018–2028
| Projected employment change | |
|---|---|
| Domestic workers | 22.9% |
| All other workers | 6.9% |
| House cleaners | -10.9% |
| Nannies | -10.6% |
| Child care (in own home) | 2.7% |
| Home care (non-agency) | 1.8% |
| Home care (agency-based) | 45.4% |
Notes: All but one of the domestic worker occupations are defined in exactly the same way here as they are defined elsewhere in the chartbook. The only difference is that here, due to data limitations, workers who provide child care in their own homes are defined as any child care workers who are self-employed (either incorporated or unincorporated). In the rest of our analysis, the definition of workers who provide child care in their own homes is somewhat more restrictive: child care workers who work in the child day care services industry who are self-employed but not incorporated.
Source: Economic Policy Institute (EPI) analysis of Bureau of Labor Statistics Employment Projections program public data series
Employment in domestic worker occupations is projected to grow more than three times as fast as employment in other occupations over a decade—22.9% compared with 6.9%. This trend is driven by the expected large increase (45.4%) in agency-based home care aides, who make up about half of the domestic employee workforce.
Home care aides make up the majority of domestic workers: Employment in domestic worker occupations, 2019
| Occupation | Number of workers |
|---|---|
| House cleaners | 343,527 |
| Child care workers | |
| Nannies | 225,933 |
| Provider in own home | 276,311 |
| Home care aides | |
| Non-agency-based | 141,400 |
| Agency-based | 1,257,878 |
| Total domestic workers | 2,245,047 |
Note: To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Demographic characteristics of domestic workers: Shares of domestic workers in different occupations with given characteristic, 2019
| Domestic worker occupations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Percentage-point difference | House cleaners | Nannies | Provider in own home | Non-agency-based | Agency-based | |
| All | 100% | 100% | 100% | 100% | 100% | 100% | 100% | |
| Gender | ||||||||
| Female | 46.3% | 91.5% | 45.2 | 95.5% | 96.8% | 97.2% | 86.1% | 88.8% |
| Male | 53.7% | 8.5% | -45.2 | 4.5% | 3.2% | 2.8% | 13.9% | 11.2% |
| Nativity | ||||||||
| U.S.-born | 82.9% | 64.9% | -18.0 | 30.7% | 71.6% | 70.9% | 76.7% | 70.4% |
| Foreign-born U.S. citizen | 8.4% | 14.8% | 6.4 | 18.5% | 11.4% | 12.3% | 10.6% | 15.4% |
| Foreign-born noncitizen | 8.7% | 20.3% | 11.6 | 50.8% | 16.9% | 16.8% | 12.6% | 14.2% |
| Race/ethnicity | ||||||||
| White, non-Hispanic | 62.9% | 41.7% | -21.3 | 29.0% | 64.6% | 54.8% | 51.3% | 37.0% |
| Black, non-Hispanic | 11.9% | 21.7% | 9.7 | 6.5% | 7.9% | 13.3% | 20.1% | 30.3% |
| Hispanic, any race | 17.1% | 29.1% | 12.0 | 61.5% | 23.8% | 28.4% | 19.5% | 22.4% |
| Asian American/Pacific Islander | 6.9% | 6.3% | -0.6 | 2.2% | 3.3% | 2.7% | 7.2% | 8.6% |
| Other | 1.1% | 1.3% | 0.2 | 0.8% | 0.5% | 0.8% | 2.0% | 1.6% |
| Education | ||||||||
| Not high school graduate | 8.0% | 19.1% | 11.1 | 38.9% | 14.6% | 17.0% | 11.0% | 15.9% |
| High school graduate | 25.8% | 37.6% | 11.8 | 36.9% | 30.8% | 34.1% | 36.2% | 40.0% |
| Some college | 28.0% | 30.1% | 2.1 | 15.4% | 32.9% | 34.5% | 35.4% | 32.1% |
| Bachelor’s degree | 24.3% | 10.7% | -13.6 | 7.7% | 17.9% | 12.1% | 14.2% | 9.6% |
| Advanced degree | 13.8% | 2.4% | -11.4 | 1.2% | 3.8% | 2.2% | 3.2% | 2.4% |
| Age | ||||||||
| Under 23 | 8.3% | 9.0% | 0.7 | 2.8% | 35.7% | 5.9% | 6.1% | 6.8% |
| 23–29 | 15.7% | 12.9% | -2.8 | 5.9% | 25.4% | 10.4% | 9.7% | 13.5% |
| 30–39 | 22.0% | 18.6% | -3.4 | 20.1% | 11.8% | 17.8% | 14.2% | 20.0% |
| 40–49 | 20.6% | 19.5% | -1.1 | 28.3% | 9.0% | 22.6% | 16.9% | 18.6% |
| 50–54 | 10.2% | 11.7% | 1.4 | 13.9% | 4.8% | 12.7% | 12.4% | 12.0% |
| 55–59 | 9.8% | 11.5% | 1.7 | 12.4% | 6.1% | 15.2% | 14.0% | 11.2% |
| 60–64 | 7.2% | 8.3% | 1.1 | 8.6% | 4.6% | 7.7% | 11.4% | 8.7% |
| 65+ | 6.2% | 8.5% | 2.3 | 7.9% | 2.7% | 7.7% | 15.2% | 9.2% |
| Median age | 41 | 45 | 47 | 26 | 47 | 51 | 45 | |
Notes: To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or who lack an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Race/ethnicity and nativity of domestic workers, by gender: Shares of domestic workers in different occupations with given characteristic, 2019
| Domestic worker occupations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Percentage-point difference | House cleaners | Nannies | Provide care in own home | Non-agency-based | Agency-based | |
| All | 100% | 100% | 100% | 100% | 100% | 100% | 100% | |
| Race/ethnicity and gender | ||||||||
| White, non-Hispanic, female | 29.2% | 37.9% | 8.8 | 27.7% | 63.1% | 53.1% | 42.1% | 32.4% |
| Black, non-Hispanic, female | 6.2% | 19.7% | 13.5 | 6.1% | 7.4% | 13.1% | 18.5% | 27.2% |
| Hispanic, any race, female | 7.1% | 27.2% | 20.1 | 58.9% | 22.6% | 27.8% | 17.7% | 20.3% |
| Asian American/Pacific Islander, female | 3.2% | 5.5% | 2.3 | 2.0% | 3.1% | 2.6% | 6.3% | 7.4% |
| Other, female | 0.5% | 1.2% | 0.6 | 0.8% | 0.4% | 0.7% | 1.6% | 1.4% |
| White, non-Hispanic, male | 33.8% | 3.7% | -30.0 | 1.3% | 1.5% | 1.8% | 9.2% | 4.6% |
| Black, non-Hispanic, male | 5.7% | 2.0% | -3.8 | 0.4% | 0.5% | 0.2% | 1.6% | 3.1% |
| Hispanic, any race, male | 10.0% | 1.9% | -8.1 | 2.7% | 1.2% | 0.6% | 1.8% | 2.1% |
| Asian American/Pacific Islander, male | 3.7% | 0.8% | -2.9 | 0.2% | 0.1% | 0.2% | 0.9% | 1.2% |
| Other, male | 0.6% | 0.1% | -0.4 | 0.0% | 0.0% | 0.1% | 0.4% | 0.2% |
| Nativity and gender | ||||||||
| U.S.-born, female | 39.3% | 58.7% | 19.3 | 28.7% | 69.5% | 68.6% | 64.2% | 62.1% |
| Foreign-born U.S. citizen, female | 3.8% | 13.6% | 9.8 | 17.5% | 11.1% | 12.2% | 10.2% | 13.7% |
| Foreign-born noncitizen, female | 3.1% | 19.2% | 16.1 | 49.3% | 16.2% | 16.4% | 11.7% | 13.0% |
| U.S.-born, male | 43.6% | 6.2% | -37.4 | 2.1% | 2.1% | 2.3% | 12.6% | 8.3% |
| Foreign-born U.S. citizen, male | 4.6% | 1.2% | -3.4 | 1.0% | 0.4% | 0.1% | 0.5% | 1.7% |
| Foreign-born noncitizen, male | 5.5% | 1.1% | -4.4 | 1.5% | 0.7% | 0.4% | 0.9% | 1.2% |
Notes: To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Employment in domestic worker occupations, by region and state, 2019
| Domestic worker occupations | |||||||
|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | ||||||
| All other (nondomestic) workers | Domestic workers | House cleaners | Nannies | Provider in own home | Non- agency-based | Agency-based | |
| All | 153,215,916 | 2,245,047 | 343,527 | 225,933 | 276,311 | 141,400 | 1,257,878 |
| Northeast | 27,895,992 | 499,394 | 62,182 | 44,364 | 49,392 | 23,869 | 337,799 |
| Connecticut | 1,854,406 | 30,016 | 4,618 | 3,700 | 3,546 | 2,826 | 15,009 |
| Maine | 695,023 | 10,931 | 883 | 869 | 1,760 | 807 | 6,663 |
| Massachusetts | 3,511,411 | 50,085 | 6,267 | 6,390 | 5,588 | 2,971 | 29,386 |
| New Hampshire | 753,295 | 8,011 | 841 | 1,181 | 964 | 516 | 4,536 |
| New Jersey | 4,471,507 | 56,112 | 10,550 | 6,631 | 5,496 | 2,663 | 30,892 |
| New York | 9,360,472 | 258,155 | 30,949 | 17,764 | 24,117 | 8,378 | 190,515 |
| Pennsylvania | 6,340,703 | 74,297 | 6,870 | 6,620 | 5,963 | 4,825 | 54,453 |
| Rhode Island | 554,549 | 5,601 | 585 | 687 | 771 | 233 | 3,345 |
| Vermont | 354,627 | 6,186 | 619 | 521 | 1,187 | 649 | 3,002 |
| Midwest | 34,356,668 | 455,447 | 37,896 | 49,225 | 86,753 | 20,755 | 249,924 |
| Illinois | 6,448,489 | 84,647 | 8,657 | 11,219 | 14,719 | 5,230 | 42,236 |
| Indiana | 3,227,001 | 30,366 | 3,387 | 2,741 | 5,438 | 1,079 | 17,183 |
| Iowa | 1,695,788 | 22,610 | 1,578 | 2,184 | 7,403 | 758 | 8,053 |
| Kansas | 1,490,107 | 22,938 | 1,910 | 3,042 | 5,152 | 705 | 10,843 |
| Michigan | 4,781,699 | 63,973 | 5,066 | 7,350 | 10,895 | 4,053 | 35,789 |
| Minnesota | 2,976,346 | 48,691 | 2,917 | 4,966 | 11,186 | 2,066 | 25,511 |
| Missouri | 3,023,480 | 43,548 | 3,152 | 4,073 | 6,578 | 1,530 | 28,977 |
| Nebraska | 1,020,590 | 12,842 | 1,113 | 1,606 | 4,071 | 461 | 3,976 |
| North Dakota | 394,134 | 5,526 | 286 | 471 | 1,911 | 198 | 1,998 |
| Ohio | 5,762,605 | 74,214 | 7,097 | 7,210 | 10,184 | 2,374 | 48,709 |
| South Dakota | 453,616 | 4,987 | 325 | 499 | 2,010 | 136 | 1,156 |
| Wisconsin | 3,082,812 | 41,105 | 2,409 | 3,867 | 7,207 | 2,165 | 25,492 |
| South | 55,520,511 | 703,756 | 140,427 | 73,179 | 72,100 | 49,608 | 365,058 |
| Alabama | 2,167,013 | 19,429 | 3,988 | 2,291 | 2,183 | 2,174 | 8,264 |
| Arkansas | 1,334,766 | 16,837 | 2,584 | 1,022 | 1,596 | 1,134 | 11,092 |
| Delaware | 451,111 | 4,330 | 438 | 424 | 813 | 268 | 2,266 |
| District of Columbia | 344,833 | 4,021 | 813 | 899 | 247 | 197 | 1,808 |
| Florida | 9,258,211 | 104,482 | 37,002 | 9,088 | 7,218 | 8,567 | 38,969 |
| Georgia | 4,745,118 | 41,810 | 8,899 | 6,848 | 5,058 | 3,264 | 15,768 |
| Kentucky | 2,009,155 | 18,064 | 3,227 | 1,832 | 2,971 | 1,848 | 7,302 |
| Louisiana | 2,057,857 | 31,380 | 4,921 | 2,566 | 2,817 | 2,780 | 19,113 |
| Maryland | 3,080,645 | 36,947 | 6,766 | 6,992 | 6,726 | 1,961 | 11,292 |
| Mississippi | 1,273,037 | 11,609 | 2,323 | 713 | 1,730 | 1,279 | 5,188 |
| North Carolina | 4,560,543 | 59,710 | 7,041 | 6,288 | 6,235 | 2,842 | 39,024 |
| Oklahoma | 1,789,220 | 20,858 | 3,012 | 1,665 | 2,833 | 1,216 | 12,176 |
| South Carolina | 2,154,162 | 19,569 | 3,136 | 2,098 | 2,308 | 1,517 | 10,434 |
| Tennessee | 3,048,589 | 31,370 | 5,370 | 2,664 | 3,767 | 3,493 | 15,825 |
| Texas | 12,297,893 | 213,896 | 42,267 | 16,876 | 15,865 | 10,914 | 134,434 |
| Virginia | 4,159,587 | 56,406 | 7,752 | 10,434 | 8,526 | 5,238 | 21,542 |
| West Virginia | 788,773 | 13,038 | 887 | 479 | 1,207 | 917 | 10,563 |
| West | 35,442,745 | 586,450 | 103,022 | 59,165 | 68,066 | 47,168 | 305,096 |
| Alaska | 346,681 | 5,713 | 230 | 481 | 1,013 | 252 | 3,802 |
| Arizona | 3,053,357 | 40,736 | 7,390 | 3,905 | 4,130 | 4,662 | 20,558 |
| California | 17,989,336 | 358,013 | 74,374 | 30,359 | 35,743 | 28,994 | 188,209 |
| Colorado | 2,767,754 | 35,900 | 6,025 | 6,698 | 5,395 | 1,539 | 14,306 |
| Hawaii | 662,053 | 5,084 | 842 | 221 | 724 | 547 | 2,714 |
| Idaho | 774,528 | 11,229 | 812 | 1,192 | 2,118 | 1,018 | 5,797 |
| Montana | 508,979 | 6,291 | 572 | 631 | 1,129 | 352 | 3,496 |
| Nevada | 1,335,289 | 9,518 | 2,212 | 1,148 | 1,067 | 850 | 3,915 |
| New Mexico | 915,274 | 20,904 | 1,992 | 650 | 1,587 | 1,509 | 16,872 |
| Oregon | 1,929,241 | 29,320 | 2,777 | 3,342 | 5,017 | 3,086 | 14,311 |
| Utah | 1,413,140 | 11,367 | 1,181 | 2,104 | 2,792 | 376 | 3,783 |
| Washington | 3,449,723 | 49,080 | 4,293 | 8,143 | 6,546 | 3,767 | 25,891 |
| Wyoming | 297,389 | 3,295 | 323 | 292 | 804 | 216 | 1,441 |
Note: To ensure sufficient sample sizes, this table draws from pooled 2010–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Employment in domestic worker occupations, by selected metropolitan area, 2019
| Domestic worker occupations | |||||||
|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | ||||||
| Metropolitan area | All other (nondomestic) workers | Domestic workers | House cleaners | Nannies | Provider in own home | Non- agency-based | Agency-based |
| Boston-Cambridge-Newton, Mass.* | 969,980 | 15,021 | 2,412 | 1,804 | 1,476 | 755 | 8,687 |
| Chicago-Naperville-Elgin, Ill.* | 4,330,297 | 56,210 | 5,719 | 9,038 | 8,776 | 3,546 | 28,081 |
| Houston-Baytown-Sugar Land, Texas | 3,057,343 | 46,201 | 11,334 | 5,840 | 4,121 | 1,645 | 22,962 |
| Los Angeles-Long Beach-Anaheim, Calif. | 2,580,766 | 55,888 | 15,868 | 3,605 | 4,054 | 5,970 | 26,447 |
| Miami-Fort Lauderdale-West Palm Beach, Fla. | 2,931,316 | 54,494 | 27,891 | 3,057 | 2,673 | 2,872 | 16,370 |
| New York, N.Y.* | 6,070,857 | 218,103 | 28,083 | 15,451 | 17,500 | 5,641 | 159,340 |
| Philadelphia, Pa.* | 1,958,882 | 30,551 | 2,740 | 3,143 | 1,805 | 1,930 | 22,301 |
| Phoenix-Mesa-Scottsdale, Ariz. | 2,149,878 | 26,953 | 5,011 | 2,730 | 2,652 | 3,435 | 13,107 |
| San Francisco-Oakland-Fremont, Calif. | 2,417,860 | 43,435 | 7,541 | 7,437 | 5,521 | 2,372 | 19,632 |
| Seattle-Tacoma-Bellevue, Wash. | 1,973,355 | 24,502 | 3,110 | 5,940 | 3,403 | 1,904 | 9,286 |
Notes: To ensure sufficient sample sizes, this table draws from pooled 2010–2019 microdata. *Indicates a metropolitan area that has been restricted to one state.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Median real hourly wages, domestic workers versus other workers, by demographic group, 2019
| Domestic worker occupations | |||||||
|---|---|---|---|---|---|---|---|
| Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Percent difference | House cleaners | Nannies | Non- agency-based | Agency-based | |
| Median hourly wage | $19.97 | $12.01 | -39.8% | $11.89 | $11.60 | $11.89 | $12.08 |
| Gender | |||||||
| Female | $18.23 | $11.96 | -34.4% | $11.93 | $11.59 | $11.62 | $12.01 |
| Male | $21.62 | $12.85 | -40.6% | NA | NA | NA | $12.99 |
| Nativity | |||||||
| U.S. born | $20.16 | $11.86 | -41.2% | $11.91 | $11.57 | $12.14 | $11.88 |
| Foreign-born U.S. citizen | $21.21 | $12.69 | -40.2% | $11.85 | NA | NA | $13.03 |
| Foreign-born noncitizen | $15.86 | $12.09 | -23.8% | $11.88 | NA | NA | $12.44 |
| Race/ethnicity | |||||||
| White, non-Hispanic | $21.95 | $12.17 | -44.5% | $12.25 | $11.66 | $12.41 | $12.25 |
| Black, non-Hispanic | $16.56 | $11.59 | -30.0% | NA | NA | NA | $11.75 |
| Hispanic, any race | $16.06 | $11.86 | -26.2% | $11.67 | $11.67 | NA | $11.93 |
| Asian American/Pacific Islander | $24.46 | $13.00 | -46.9% | NA | NA | NA | $13.13 |
| Other | $17.21 | NA | NA | NA | NA | NA | NA |
| Education | |||||||
| Not high school graduate | $12.27 | $11.14 | -9.3% | $10.99 | NA | NA | $11.28 |
| High school graduate | $16.16 | $11.97 | -26.0% | $12.06 | $11.85 | $11.24 | $12.00 |
| Some college | $17.62 | $12.20 | -30.8% | $13.06 | $11.63 | $11.60 | $12.24 |
| Bachelor’s degree or more | $30.09 | $13.49 | -55.2% | NA | $13.37 | NA | $13.63 |
| Age | |||||||
| Under 23 | $11.29 | $10.74 | -4.9% | NA | $10.45 | NA | $11.16 |
| 23–49 | $20.37 | $12.20 | -40.1% | $11.94 | $12.92 | $12.39 | $12.20 |
| 50+ | $22.87 | $12.04 | -47.4% | $11.93 | NA | $11.64 | $12.03 |
Notes: To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. NA indicates limited sample size. Data are in 2019 dollars. Since the best wage measure in the Current Population Survey is unavailable for self-employed workers, wages of workers who provide child care in their own homes are not included. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. NA indicates limited sample size. Data are in 2019 dollars. Since the best wage measure in the Current Population Survey is unavailable for self-employed workers, wages of workers who provide child care in their own homes are not included. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Hourly wage gaps for domestic workers, by occupation and demographic group, 2019
| Domestic worker occupations | |||||
|---|---|---|---|---|---|
| Home care aides | |||||
| Domestic workers | House cleaners | Nannies | Non-agency-based | Agency-based | |
| All | -25.9%*** | -20.9%*** | -20.2%*** | -35.5%*** | -26.5%*** |
| Gender | |||||
| Female | -25.9%*** | -18.4%*** | -22.4%*** | -34.9%*** | -26.7%*** |
| Male | -35.7%*** | NA | NA | NA | -33.6%*** |
| Nativity | |||||
| U.S.-born | -27.5%*** | -30.8%*** | -15.6%*** | -34.4%*** | -28.0%*** |
| Foreign-born U.S. citizen | -27.3%*** | -19.5%*** | NA | NA | -27.9%*** |
| Foreign-born noncitizen | -15.9%*** | -8.6%*** | NA | NA | -14.1%*** |
| Race/ethnicity | |||||
| White, non-Hispanic | -30.9%*** | -31.6%*** | -15.5%*** | -40.0%*** | -33.6%*** |
| Black, non-Hispanic | -22.2%*** | NA | NA | NA | -20.9%*** |
| Hispanic, any race | -22.8%*** | -15.0%*** | -24.4%*** | NA | -26.1%*** |
| Asian American/Pacific Islander | -31.2%*** | NA | NA | NA | -29.0%*** |
| Other | NA | NA | NA | NA | NA |
| Education | |||||
| Not high school graduate | -8.3%*** | -9.0%*** | NA | NA | -8.5%*** |
| High school graduate | -19.1%*** | -18.1%*** | -7.5%** | -30.3%*** | -19.1%*** |
| Some college | -27.6%*** | -28.4%*** | -17.1%*** | -33.5%*** | -28.4%*** |
| Bachelor’s degree or more | -62.8%*** | NA | -51.8%*** | NA | -62.7%*** |
| Age | |||||
| Under 23 | -5.9%*** | NA | -8.2% | NA | -3.5% |
| 23–49 | -23.5%*** | -20.1%*** | -26.3%*** | -36.3%*** | -22.6%*** |
| 50+ | -31.3%*** | -18.5%*** | NA | -38.0%*** | -32.8%*** |
Notes: All wage gaps are significantly different from zero at the 0.01 level. The regressions control for gender, nativity, race/ethnicity, educational attainment, age, marital status, and census geographical division. To ensure sufficient sample sizes, this figure draws from pooled 2017–2019 microdata. Since the best wage measure in the Current Population Survey is unavailable for self-employed workers, wages of workers who provide child care in their own homes are not included. To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
All wage gaps are significantly different from zero at the 0.01 level. The regressions control for gender, nativity, race/ethnicity, educational attainment, age, marital status, and census geographical division. To ensure sufficient sample sizes, this figure draws from pooled 2017–2019 microdata. Since the best wage measure in the Current Population Survey is unavailable for self-employed workers, wages of workers who provide child care in their own homes are not included.To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Hours worked and share of workers with full- or part-time hours, domestic workers versus other workers, 2019
| Domestic worker occupations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Difference | House cleaners | Nannies | Provide care in own home | Non- agency-based | Agency-based | |
| Average weekly hours | 38.94 | 33.36 | -14.3% | 26.7 | 31.1 | 39.1 | 34.2 | 34.2 |
| All | 100% | 100% | 100% | 100% | 100% | 100% | 100% | |
| Full-time | 77.3% | 54.8% | -22.5 ppt. | 37.0% | 52.3% | 67.4% | 51.7% | 57.6% |
| Part-time | 22.7% | 45.2% | 22.5 ppt. | 63.0% | 47.7% | 32.6% | 48.3% | 42.4% |
| Part-time for economic reasons (i.e., want full-time) | 4.0% | 9.7% | 5.6 ppt. | 15.0% | 7.4% | 6.2% | 9.3% | 9.4% |
| Part-time for noneconomic reasons | 18.7% | 35.6% | 16.9 ppt. | 47.9% | 40.3% | 26.4% | 39.0% | 33.0% |
Notes: “Part-time” is defined as usually working less than 35 hours per week on the primary job. Those who say they are working part time because they could only find part-time work or because of slack work or business conditions are categorized by the Bureau of Labor Statistics as part-timers “for economic reasons” and often described as workers who would prefer to work full time. The “part-time for economic reasons” category also includes those who are not at work but are usually part time. The “part-time for noneconomic reasons” category includes workers who say they work part time to take care of their children or for other family and personal reasons; while they may prefer to work full time if, say, they could afford child care, they are not included in the standard count of part-timers who want full-time work. To ensure sufficient sample sizes, this table draws from pooled 2017–2019 microdata.
Source: Economic Policy Institute (EPI) analysis of Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org
Median annual earnings, domestic workers versus other workers, 2018, by demographic group
| Domestic worker occupations | |||||||
|---|---|---|---|---|---|---|---|
| Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Percent difference | House cleaners | Nannies | Non- agency-based | Agency-based | |
| All | $39,120 | $15,980 | -59.2% | $14,915 | $13,558 | $18,111 | $20,337 |
| Gender | |||||||
| Female | $33,374 | $15,644 | -53.1% | $15,060 | $13,850 | $18,111 | $19,344 |
| Male | $44,797 | $20,362 | -54.5% | NA | NA | NA | $22,160 |
| Nativity | |||||||
| U.S.-born | $40,675 | $15,798 | -61.2% | $12,217 | $13,236 | $17,730 | $19,816 |
| Foreign-born U.S. citizen | $41,717 | $19,344 | -53.6% | NA | NA | NA | $20,859 |
| Foreign-born noncitizen | $29,525 | $15,272 | -48.3% | $13,032 | NA | NA | $20,024 |
| Race/ethnicity | |||||||
| White, non-Hispanic | $42,761 | $15,272 | -64.3% | $14,915 | $11,453 | NA | $20,770 |
| Black, non-Hispanic | $33,026 | $20,362 | -38.3% | NA | NA | NA | $20,859 |
| Hispanic, any race | $29,830 | $14,254 | -52.2% | $13,558 | NA | NA | $16,687 |
| Asian American/Pacific Islander | $47,941 | $18,111 | -62.2% | NA | NA | NA | $19,177 |
| Other | $31,288 | NA | NA | NA | NA | NA | NA |
| Education | |||||||
| Not high school graduate | $19,177 | $12,784 | -33.3% | $12,784 | NA | NA | $16,702 |
| High school graduate | $30,544 | $17,046 | -44.2% | $15,883 | NA | NA | $20,242 |
| Some college | $34,092 | $16,687 | -51.1% | NA | NA | NA | $20,242 |
| Bachelor’s degree or more | $61,087 | $17,939 | -70.6% | NA | NA | NA | $24,405 |
| Age | |||||||
| Under 23 | $10,429 | $8,343 | -20.0% | NA | NA | NA | NA |
| 23–49 | $41,549 | $16,687 | -59.8% | $12,784 | NA | NA | $20,362 |
| 50+ | $44,288 | $17,046 | -61.5% | $17,046 | NA | NA | $20,024 |
Notes: Earnings include reported annual wage and salary income but exclude income from unemployment insurance, child support, investments, Social Security, etc. To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. Since the best income measure in the Current Population Survey is unavailable for self-employed workers, incomes of workers who provide child care in their own homes are not included. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
Earnings include reported annual wage and salary income but exclude income from unemployment insurance, child support, investments, Social Security, etc. To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. Since the best income measure in the Current Population Survey is unavailable for self-employed workers, incomes of workers who provide child care in their own homes are not included. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
Poverty rates, domestic workers versus other workers, 2018, by demographic group
| Domestic worker occupations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Percentage-point difference | House cleaners | Nannies | Provider in own home | Non-agency-based | Agency-based | |
| All | 5.0% | 16.8% | 11.8 | 25.4% | 20.1% | 13.3% | 14.2% | 15.1% |
| Gender | ||||||||
| Female | 5.7% | 17.3% | 11.6 | 24.6% | 20.0% | 13.5% | 15.0% | 16.0% |
| Male | 4.4% | 10.3% | 5.9 | NA | NA | NA | NA | 7.5% |
| Nativity | ||||||||
| U.S.-born | 4.5% | 16.1% | 11.6 | 28.6% | 15.6% | 11.8% | 12.7% | 16.1% |
| Foreign-born U.S. citizen | 4.3% | 12.2% | 7.9 | NA | NA | NA | NA | 14.5% |
| Foreign-born noncitizen | 10.7% | 22.7% | 12.0 | 29.2% | NA | NA | NA | 10.8% |
| Race/ethnicity | ||||||||
| White, non-Hispanic | 3.5% | 12.3% | 8.9 | 24.4% | 23.8% | 7.9% | NA | 9.5% |
| Black, non-Hispanic | 8.2% | 18.5% | 10.3 | NA | NA | NA | NA | 17.6% |
| Hispanic, any race | 8.7% | 23.9% | 15.2 | 27.2% | NA | NA | NA | 23.6% |
| Asian American/Pacific Islander | 4.2% | 9.4% | 5.2 | NA | NA | NA | NA | 9.0% |
| Other | 7.5% | NA | NA | NA | NA | NA | NA | NA |
| Education | ||||||||
| Not high school graduate | 14.4% | 23.6% | 9.2 | 27.6% | NA | NA | NA | 21.0% |
| High school graduate | 7.0% | 17.0% | 10.0 | 25.0% | NA | 15.3% | NA | 15.4% |
| Some college | 5.0% | 16.3% | 11.4 | NA | NA | 8.9% | NA | 16.5% |
| Bachelor’s degree or more | 2.0% | 9.1% | 7.1 | NA | NA | NA | NA | 4.0% |
| Age | ||||||||
| Under 23 | 10.5% | 19.4% | 8.9 | NA | NA | NA | NA | NA |
| 23–49 | 5.6% | 22.1% | 16.5 | 35.1% | NA | 17.7% | NA | 19.8% |
| 50+ | 2.6% | 9.5% | 6.9 | 14.0% | NA | 7.9% | NA | 9.5% |
Notes: To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
Twice-poverty rates, domestic workers versus other workers, 2018, by demographic
| Domestic worker occupations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Percentage-point difference | House cleaners | Nannies | Provider in own home | Non-agency-based | Agency-based | |
| All | 16.9% | 44.3% | 27.4 | 54.8% | 39.0% | 32.4% | 36.4% | 45.8% |
| Gender | ||||||||
| Female | 18.1% | 45.4% | 27.3 | 54.5% | 39.2% | 32.5% | 36.9% | 47.8% |
| Male | 15.8% | 31.0% | 15.2 | NA | NA | NA | NA | 28.7% |
| Nativity | ||||||||
| U.S.-born | 15.0% | 42.3% | 27.3 | 54.4% | 32.8% | 25.1% | 35.9% | 46.8% |
| Foreign-born U.S. citizen | 17.2% | 40.1% | 22.9 | NA | NA | NA | NA | 42.8% |
| Foreign-born noncitizen | 33.7% | 54.3% | 20.6 | 61.7% | NA | NA | NA | 44.2% |
| Race/ethnicity | ||||||||
| White, non-Hispanic | 12.0% | 34.6% | 22.5 | 47.7% | 37.9% | 20.0% | NA | 36.5% |
| Black, non-Hispanic | 25.4% | 53.3% | 27.9 | NA | NA | NA | NA | 54.6% |
| Hispanic, any race | 29.8% | 54.4% | 24.6 | 60.6% | NA | NA | NA | 53.4% |
| Asian American/Pacific Islander | 13.7% | 33.9% | 20.3 | NA | NA | NA | NA | 35.3% |
| Other | 24.9% | NA | NA | NA | NA | NA | NA | NA |
| Education | ||||||||
| Not high school graduate | 40.9% | 55.8% | 14.9 | 59.3% | NA | NA | NA | 55.5% |
| High school graduate | 24.4% | 47.3% | 22.9 | 55.4% | NA | 31.7% | NA | 50.2% |
| Some college | 17.8% | 41.9% | 24.1 | NA | NA | 28.0% | NA | 45.1% |
| Bachelor’s degree or more | 6.7% | 27.0% | 20.3 | NA | NA | NA | NA | 21.2% |
| Age | ||||||||
| Under 23 | 29.7% | 43.7% | 13.9 | NA | NA | NA | NA | NA |
| 23–49 | 18.8% | 52.7% | 33.8 | 65.5% | NA | 41.5% | NA | 54.0% |
| 50+ | 10.4% | 33.9% | 23.5 | 41.8% | NA | 24.1% | NA | 35.0% |
Notes: The “twice-poverty rate” is the share of workers whose family income is below twice the official poverty line, and is often considered a better cutoff for whether a family is able to make ends meet. To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
The “twice-poverty rate” is the share of workers whose family income is below twice the official poverty line, and is often considered a better cutoff for whether a family is able to make ends meet. To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
Employer-provided health insurance coverage rates, domestic workers versus other workers, 2018, by demographic group
| Domestic worker occupations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Percentage-point difference | House cleaners | Nannies | Provider in own home | Non- agency-based | Agency-based | |
| All | 48.9% | 19.1% | -29.7 | 7.3% | 15.1% | 6.8% | 17.1% | 25.2% |
| Gender | ||||||||
| Female | 46.7% | 18.6% | -28.1 | 7.5% | 15.1% | 6.9% | 16.9% | 24.8% |
| Male | 50.8% | 25.0% | -25.8 | NA | NA | NA | NA | 28.3% |
| Nativity | ||||||||
| U.S.-born | 50.2% | 18.9% | -31.3 | 8.7% | 9.4% | 8.0% | 17.0% | 24.0% |
| Foreign-born U.S. citizen | 49.7% | 23.5% | -26.2 | NA | NA | NA | NA | 31.2% |
| Foreign-born noncitizen | 35.3% | 16.4% | -18.9 | 5.0% | NA | NA | NA | 24.1% |
| Race/ethnicity | ||||||||
| White, non-Hispanic | 51.1% | 19.9% | -31.1 | 8.1% | 13.6% | 8.1% | NA | 28.2% |
| Black, non-Hispanic | 49.7% | 22.7% | -27 | NA | NA | NA | NA | 25.8% |
| Hispanic, any race | 39.2% | 14.1% | -25.1 | 7.0% | NA | NA | NA | 19.0% |
| Asian American/Pacific Islander | 52.2% | 22.2% | -29.9 | NA | NA | NA | NA | 25.2% |
| Other | 40.6% | NA | NA | NA | NA | NA | NA | NA |
| Education | ||||||||
| Not high school graduate | 22.5% | 12.6% | -9.9 | 5.0% | NA | NA | NA | 20.2% |
| High school graduate | 42.8% | 19.3% | -23.5 | 9.2% | NA | 4.7% | NA | 23.9% |
| Some college | 46.0% | 20.1% | -25.9 | NA | NA | 9.3% | NA | 25.3% |
| Bachelor’s degree or more | 59.9% | 24.1% | -35.8 | NA | NA | NA | NA | 34.9% |
| Age | ||||||||
| Under 23 | 11.5% | 11.3% | -0.2 | NA | NA | NA | NA | NA |
| 23–49 | 51.8% | 18.8% | -33 | 6.0% | NA | 6.4% | NA | 25.2% |
| 50+ | 52.8% | 21.0% | -31.8 | 9.4% | NA | 7.2% | NA | 26.9% |
Notes: To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
Employer-provided retirement coverage rates, domestic workers versus other workers, 2018, by demographic
| Domestic worker occupations | ||||||||
|---|---|---|---|---|---|---|---|---|
| Child care workers | Home care aides | |||||||
| All other (nondomestic) workers | Domestic workers | Percentage-point difference | House cleaners | Nannies | Provider in own home | Non-agency-based | Agency-based | |
| All | 32.8% | 9.1% | -23.7 | 2.0% | 3.5% | 2.6% | 6.6% | 13.1% |
| Gender | ||||||||
| Female | 32.9% | 8.9% | -24 | 2.1% | 3.5% | 2.6% | 5.5% | 13.3% |
| Male | 32.6% | 10.6% | -22.1 | NA | NA | NA | NA | 11.5% |
| Nativity | ||||||||
| U.S.-born | 34.5% | 9.4% | -25.1 | 3.2% | 2.4% | 3.2% | 6.3% | 12.9% |
| Foreign-born U.S. citizen | 31.2% | 11.1% | -20.1 | NA | NA | NA | NA | 15.1% |
| Foreign-born noncitizen | 18.2% | 6.2% | -12.1 | 1.1% | NA | NA | NA | 12.2% |
| Race/ethnicity | ||||||||
| White, non-Hispanic | 35.8% | 9.6% | -26.2 | 1.8% | 3.0% | 3.7% | NA | 14.7% |
| Black, non-Hispanic | 31.3% | 11.9% | -19.4 | NA | NA | NA | NA | 13.9% |
| Hispanic, any race | 22.8% | 5.6% | -17.2 | 1.0% | NA | NA | NA | 10.0% |
| Asian American/Pacific Islander | 32.4% | 10.4% | -21.9 | NA | NA | NA | NA | 12.3% |
| Other | 29.2% | NA | NA | NA | NA | NA | NA | NA |
| Education | ||||||||
| Not high school graduate | 11.0% | 5.4% | -5.7 | 2.1% | NA | NA | NA | 9.7% |
| High school graduate | 26.5% | 9.5% | -17 | 1.4% | NA | 0.2% | NA | 14.1% |
| Some college | 30.7% | 9.9% | -20.8 | NA | NA | 4.4% | NA | 13.1% |
| Bachelor’s degree or more | 42.6% | 10.2% | -32.4 | NA | NA | NA | NA | 13.5% |
| Age | ||||||||
| Under 23 | 7.7% | 2.6% | -5.1 | NA | NA | NA | NA | NA |
| 23–49 | 33.3% | 11.0% | -22.4 | 2.1% | NA | 3.1% | NA | 15.5% |
| 50+ | 37.9% | 7.9% | -29.9 | 2.1% | NA | 2.4% | NA | 11.2% |
Notes: To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth.
To ensure sufficient sample sizes, this table draws from pooled 2016–2018 microdata. “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as DACA recipients and asylum applicants whose cases are in process).
Source: Economic Policy Institute (EPI) analysis of Current Population Survey Annual Social and Economic Supplement microdata
Technical notes about data and definitions
The figures and tables in this chartbook use data from the Current Population Survey (CPS), a monthly survey of households in the United States sponsored jointly by the U.S. Census Bureau and the U.S. Bureau of Labor Statistics (BLS). Our CPS basic and Outgoing Rotation Group microdata are pulled from the Economic Policy Institute Current Population Survey Extracts, Version 1.0.2 (2020), https://microdata.epi.org.
In our analyses of hourly wages, we use data from the CPS’s Outgoing Rotation Group (ORG), a CPS subgroup of employed adults asked to answer a detailed set of questions about their earnings from work. Our analyses of annual earnings, benefits, and poverty rates come from the CPS’s Annual Social and Economic Supplement (ASEC). To ensure adequate sample sizes for these detailed analyses, we pool several years of CPS, CPS-ORG, or CPS-ASEC microdata. Most data sets are drawn from pooled 2016–2018 or 2017–2019 microdata, whichever microdata set is the most recent available. Data sets that are broken down by geography are drawn from pooled 2010–2019 microdata. Even after pooling years together, we still do not have adequate sample sizes to report statistics for some demographic groups, as indicated in the tables by “NA.”
The CPS asks respondents about both race and ethnicity, so respondents may be categorized as having Hispanic ethnicity and being of any race. To avoid including observations in multiple categories, we create five mutually exclusive categories for race/ethnicity: white (non-Hispanic), black (non-Hispanic), Hispanic (any race), Asian American/Pacific Islander (non-Hispanic; sometimes referred to as “AAPI” in this report), and “other.” Likewise, gender is restricted to the two predominant binary categories: women and men. Note that for clarity, when discussing our findings, we adhere to the category name of “Hispanic,” which is used in official government sources, rather than Latino, Latina, or Latinx.
In our charts, “Foreign-born” refers to anyone who is not a U.S. citizen at birth. “Foreign-born noncitizen” includes foreign-born persons who are either lawful permanent residents, in a nonimmigrant status (migrants with temporary visas), or lacking an immigration status, including both unauthorized immigrants and those with lawful presence (such as Deferred Action for Childhood Arrivals recipients and asylum applicants whose cases are in process).
The data include all public- and private-sector workers ages 16 and older. Due to rounding, in a few cases sums that can be calculated by using the data in tables or figures vary slightly from sums cited in the text.
Domestic worker occupations defined
Using the occupation, industry, and sector classification systems in the Current Population Survey Outgoing Rotation Group data set, we define the domestic worker occupations as follows:
- House cleaners are workers who perform cleaning and housekeeping duties in private households. We define them as workers who are in the occupation “Maids and housekeeping cleaners” (Census occupation code 4230) and in the “Private household” industry (Census industry code 9290).
- Nannies are workers who attend to children—performing a variety of tasks such as dressing, feeding, bathing, and overseeing activities—in the child’s own home. Nannies may either “live in” with employers or live in their own homes, but they work in employers’ private residences. We define them as workers who are in the occupation “Childcare workers” (Census occupation code 4600) and in either the “Private household” industry or the “Employment services” industry (Census industry code 9290 or 7580).
- Providers of child care in their own home provide child care in their own home to the children of one or more families. We define them as workers who are in the occupation “Childcare workers” (Census occupation code 4600) in the industry “Child day care services” (Census industry code 8470) and who are self-employed and unincorporated. We are unable to look at the wages of these workers since the best wage measure in the Current Population Survey is not available for self-employed workers.
- Home care aides include personal care aides and home health aides who assist people in their homes. Personal care aides assist people who are elderly, are convalescing, or have disabilities with daily living activities. The aides’ duties may include keeping house (e.g., making beds, doing laundry, washing dishes) and preparing meals. Home health aides provide hands-on health care such as giving medication, changing bandages, and monitoring the health status of the person they are caring for. They may also provide personal care such as bathing, dressing, and grooming of the patient. We distinguish between the smaller group of home care aides who are paid directly by someone in the household, and the larger group of home care aides who are agency-based.
- Non-agency-based home care aides are workers who are (a) in the occupation “Nursing, psychiatric, and home health aides” (Census occupation code 3600) and in the “Private household” industry (Census industry code 9290), or (b) in the occupation “Personal and home care aides” (Census occupation code 4610) and in either the “Private household” industry (Census industry code 9290) or the “Employment services” industry (Census industry code 7580).
- Agency-based home care aides are workers who are (a) in the occupation “Nursing, psychiatric, and home health aides” (Census occupation code 3600) and in either the “Home health care services” industry (Census industry code 8170) or the “Individual and family services” industry (Census industry code 8370), or (b) in the occupation “Personal and home care aides” (Census occupation code 4610) and in either the “Home health care services” industry (Census industry code 8170) or the “Individual and family services” industry (Census industry code 8370).
We exclude any workers who do domestic work without pay, and instead focus on those who do this work for wages. We also exclude other types of domestic workers such as cooks, gardeners, and chauffeurs.
Acknowledgments
The authors would like to thank EPI Editor Krista Faries for improving the chartbook through her careful editing and preparing of our figures and tables for publication. And we are indebted to EPI’s Online and Creative Director, Eric Shansby, who created the awesome system that makes it possible to design and publish these interactive chartbooks.
Endnotes
1. Julia Wolfe, “Domestic Workers Are at Risk During the Coronavirus Crisis,” Working Economics Blog (Economic Policy Institute), April 8, 2020.
2. Laura Dresser, Valuing Care by Valuing Care Workers: The Big Cost of a Worthy Standard and Some Steps Toward It, Roosevelt Institute, October 2015.
3. Linda Burnham and Nik Theodore, Home Economics: The Invisible and Unregulated World of Domestic Work, National Domestic Workers Alliance, 2012.
4. Occupational Safety and Health Administration, “Policy as to Domestic Household Employment Activities in Private Residences,” Standard Number 1975.6.
5. United States General Accounting Office, Immigration Statistics: Information Gaps, Quality Issues Limit Utility of Federal Data to Policymakers, July 1998.
6. Elise Gould, State of Working America Wages 2019: A Story of Slow, Uneven, and Unequal Wage Growth over the Last 40 Years, Economic Policy Institute, February 2020.
