may 2025 ISSUE

Analysis from the Center for American Progress and the National Asian Pacific American Women’s Forum finds that AANHPI women, who are often immigrants, have a broad range of intersecting identities that make their labor market experiences unique. Breaking down these aggregates helps break down racial stereotypes too.

This column presents original analysis from the Center for American Progress and the National Asian Pacific American Women’s Forum on the labor market outcomes of AANHPI women. Using averages from the 2019–2023 American Community Survey data,* it highlights five facts that illustrate the varied experiences of AANHPI women across racial and ethnic groups. Many AANHPI women have the greatest wage gaps and are concentrated in low-paid work, and their labor market realities are intertwined with the challenges they may experience as immigrants.

1. Certain groups of AANHPI women face some of the highest wage gaps Among all workers, the typical AANHPI woman makes 83 cents for every $1 made by white, non-Hispanic men. Yet the population of AANHPI women is far from monolithic. Native Hawaiian and Pacific Islander women have a greater gap, at 61 cents for every $1, and Burmese, Nepalese, and Bangladeshi women make about 54 cents, 62 cents, and 72 cents on the dollar, respectively, compared with white, non-Hispanic men. These disparities may be influenced by intersectional and structural factors including historical immigration patterns, unequal educational opportunities, and potential discrimination in the labor market.

2. AANHPI women are more likely to be immigrants Three-quarters of AANHPI adults living in the United States are immigrants, and more than 45 percent are naturalized citizens. (For the purposes of this analysis, the authors define immigrants as people who are foreign born.) Shares are even higher for AANHPI women: 77 percent of AANHPI American women are immigrants, and 49 percent are naturalized citizens. (see Figure 2a) AANHPI immigrants come from different cultural and economic backgrounds and are more likely to be women than men. (see Figure 2b) This has inherent implications for their labor market outcomes, as AANHPI women are navigating the intersection of being women, people of color, and more often than not, immigrants.

The AANHPI community represents the most rapidly expanding racial demographic in the United States. Asian immigrants are also expected to account for the majority of new immigrants in the coming decades. Projections from the Pew Research Center estimate that the U.S. share of Asian immigrants is projected to increase from 29 percent in 2025 to 38 percent by 2065, surpassing the share of Hispanic immigrants by 2055.

3. AANHPI women have unemployment rates comparable to those of white, non-Hispanic men but disproportionately earn less than $30,000 per year and have lower labor force participation

Earnings

Despite unemployment rates that are comparable to those of white men, more than 1 in 3 working AANHPI women earn $30,000 or less annually—roughly the annual earnings of someone making $17 per hour working full time, year round.** To put this number into perspective, $30,000 per year is less than half the mean annual wage across all occupations for the typical full-time, year-round worker in the United States in 2023. This is particularly pronounced among working Bangladeshi, Burmese, and Mongolian women, among whom more than half earn less than $30,000.

Employment

Employment rates among AANHPI women varied by ethnicity from 2019 to 2023. Tongan women had more than double the unemployment rate of white, non-Hispanic men, and for many women of South Asian descent—for example, Bangladeshi and Pakistani women—unemployment rates were about 50 percent higher.

Some groups of AANHPI women have lower unemployment rates than their white, non-Hispanic male counterparts. This may be due to a combination of factors, including the sectors they work in, household structure and child care, immigration status’ relationship to employment, levels of education, and work experience. Naturalized-citizen AANHPI women, for example, had one of the lowest unemployment rates in the ACS data—3.7 percent, significantly lower than any other group. During the COVID-19 pandemic, AANHPI women experienced persistent unemployment and greater difficulty being rehired because of their likelihood of having in-person jobs in service roles such as health care and food preparation and serving.

Labor force participation

Many subgroups of AANHPI women also experience greater rates of economic vulnerability, given significant variation in unemployment rates and labor force participation. Many AANHPI women have lower labor force participation than white, non-Hispanic men, though they outperform women’s overall participation rate. Hmong women had one of the highest participation rates, at 69.4 percent, while Japanese women had the lowest, at 47.5 percent. (see Table 1)

4. Most AANHPI women work in lower-paid service occupations Disaggregating occupational data by racial and ethnic subgroups reveals stark disparities. This is because a key driver of the gender pay gap for AANHPI women is occupational segregation, where many AANHPI women work in lower-wage occupations.


Some AANHPI women are more likely than AANHPI women as an aggregate group to work in service occupations that pay substantially lower wages. For example, the analysis finds Bangladeshi, Cambodian, Vietnamese, and Native Hawaiian women are heavily represented in service-oriented jobs such as cashiers, waitresses, aides, and assemblers. Similarly, the majority of Fijian, Samoan, and Tongan women work as personal care aides. These roles typically have lower wages and limited opportunities for career advancement.

Across the top 3 most common occupations for AANHPI women, regardless of ethnic subgroup, median wages of all women consistently lagged those of all men within the occupation. Many service-oriented jobs had some of the steepest wage gaps. For example, female cashiers earned a median wage of $27,292 compared with $29,991 for their male counterparts—equivalent to 91 cents for every $1. Similarly, personal care aides saw a 10 percent gap, with women earning $32,741 and men earning $36,267.


AANHPI women in health care

While health care roles can generally offer stability and decent wages, AANHPI women tend to work in lower-paid roles that lack the upward mobility of other health care positions, further contributing to wage disparities. For example, the top occupations for Filipino and Nepalese women were registered nurses and nursing/psychiatric aides. Immigrant women can also be particularly vulnerable to exploitation in sectors such as health care. However, the prevalence of AANHPI women working as registered nurses highlights that AANHPI women—and women in general—were critical to ensuring health outcomes during the pandemic and continue to be an integral part of the health care system.


AANHPI women have a higher propensity to work in sectors such as service and care work, which tend to be lower paid than the sectors that white, non-Hispanic men dominate. These sectors also have disproportionately high rates of sexual harassment and workplace discrimination. For AANHPI women in the United States, particularly immigrant women who lack legal status, the fear of retaliation, coupled with the risk of losing employment, can make it even more difficult to speak out against injustices or seek legal recourse.


Some AANHPI women have access to higher-paying professional opportunities for example, Chinese and Indian women are more likely to be employed in professional fields, such as management occupations. Yet even across these occupations, women’s median wages lag men’s. Higher-paying careers such as software development, accounting, and managerial roles tend to exhibit a larger absolute wage gap, which can result in a substantial cumulative economic impact over the lifetime.

5. Education doesn’t explain the wage gap for many AANHPI women For many AANHPI women, education does not always translate into higher-paid jobs, and according to the analysis, educational attainment varies widely across different ethnic groups, from high levels of advanced degrees among Taiwanese and Indian women to lower education levels among Bhutanese, Burmese, Laotian, Samoan, and Tongan women.


Many AANHPI women have higher educational attainment, with a greater likelihood of holding a bachelor’s degree or higher, than white, non-Hispanic men. Fifty-five percent of AANHPI women have a bachelor’s degree or higher, compared with 38 percent of white, non-Hispanic men. Only about 20 percent of Native Hawaiian and other Pacific Islander women held a bachelor’s degree or higher. (see Figure 4)

While higher education is associated with higher-paid employment, advanced qualifications do not guarantee higher-paying or better-skill-matched jobs. Many AANHPI women, despite holding advanced degrees, may still end up in lower-paying jobs, suggesting systemic barriers such as discrimination, lack of networks, or limited access to opportunities. Underemployment and skill underutilization also remain a prevalent issue for many AANHPI women.

Conclusion

Not all AANHPI women experience the success that is often assumed when looking at aggregated data. There are significant differences between groups, and many face low-quality jobs with little advancement opportunity and can become stuck in lower-wage occupations. Across almost every job type, AANHPI women earn less than white, non-Hispanic men. Even in high-paying jobs such as managers or software developers, the wage gap remains wide, highlighting that education alone is not enough to break down barriers.

This analysis underscores the importance of disaggregating racial and ethnic data to understand better the diverse constituencies that aggregated data often mask. Disaggregated data can ensure policy solutions target the specific challenges facing different AANHPI communities and help dispel racial stereotypes about AANHPI women.

* Unless otherwise stated, all facts and figures in this report rely on the authors’ analysis of ACS 5-year data and are therefore averages across the time period.

** Wage gaps were calculated using the median annual earnings for a worker who worked at least 35 hours per week (full time) and at least 50 weeks during the previous calendar year (year round). Based on the proposed $17 per hour minimum wage, this full-time, year-round worker would earn an estimated $29,750 annually (annual average salary = 17×35×50). Using a standard rounding approach, the authors rounded this figure to $30,000 per year, providing a clear benchmark for wage classification and analysis.

Mimla Wardak is Research Associate Center For American Progress

Sydelle Barreto is Policy Manager National Asian Pacific American Women’s Forum

Natalie Baker is Director of Economic Analysis Center For American Progress