How Asian Americans Fare in the Labor Market: The Intersection of Education, Gender, and Ethnicity

INTERSECTIONALITY, STEREOTYPES OF ASIAN AMERICANS, AND EARNINGS IN THE LABOR MARKET

A large and growing body of literature under the conceptual umbrella of intersectionality has sought to document and explain how multiple aspects of an individual or group “operate not as unitary, mutually exclusive entities, but as reciprocally constructing phenomena that in turn shape complex social inequalities” (Collins 2015, 2). For example, Kimberlé Crenshaw (1989) highlights several employment discrimination lawsuits concerning Black women in which courts interpreted race- and gender-based discrimination in unidimensional fashion, overlooking the ways in which Black women’s labor market experiences are distinct from those of Black men and White women. Similarly, Peggy Li (2014) critiques the “single-axis” framing offered by the “glass ceiling” and the “bamboo ceiling,” labor market metaphors that respectively focus on gender and race, as obscuring the experiences of Asian American women.

To better understand some of the ways in which race, class, and gender intersect to shape the labor market experiences of contemporary Asian Americans, we draw on what Yoko Kawai (2005) describes as the ambivalence of Asian American stereotypes, in which they are seen contradictorily as both a “Yellow Peril” and a “Model Minority.” Both depictions are closely linked to economic concerns. Early Asian labor migrants to the US, for example, were seen as cheap and pliant—a peril to White workers in their numbers and willingness to tolerate subpar working and living conditions (Dhingra and Rodriguez 2014; Saito 1997). More modern portrayals of Asian Americans see them as highly educated and hardworking—a model minority—but lacking the requisite qualities to be leaders in the workplace (Chin 2020; Li 2014). In the contemporary labor market, these perceptions may result in classed experiences for Asian Americans. Asian Americans without college degrees run counter to model minority stereotypes and may be viewed as especially deviant cases suitable at best for particular types of menial labor. Asian Americans with college degrees, on the other hand, might be considered competent technical workers in a narrow sense, restricting their opportunities for advancement (Chin 2020; Li 2014), or as “forever foreigners” whose loyalties are suspect (Dhingra and Rodriguez 2014), thus rendering them unsuitable for high-level positions.

Indeed, studies that control for or disaggregate by educational attainment show no earnings advantage for Asian Americans (Kim and Sakamoto 2010; Zeng and Xie 2004) or even an Asian American earnings disadvantage when compared with Whites (Covarrubias and Liou 2014; Kim and Sakamoto 2010). A study using US census data from 2000 to 2007 finds that native-born Asian American men who did not complete high school and those with only a high school diploma earn significantly less than their White counterparts, especially at the lower end of the earnings distribution (Kim and Sakamoto 2014). Two studies using data from the 2003 National Survey of College Graduates, one comparing the annual earnings of college-educated men (Kim and Sakamoto 2010) and the other of college-educated women (Kim and Zhao 2014), find that native-born Asian Americans do not have an earnings advantage over Whites once field of study and college selectivity are taken into account.

Stereotypes of Asian Americans also have strongly gendered implications. The historical relegation of Asian American men to domestic jobs in laundering and housekeeping and strict immigration policies that led to Asian “bachelor societies” have sustained stereotypes of Asian American men as lacking in masculinity (Dhingra and Rodriguez 2014). In the contemporary labor market, such stereotypes may block Asian American men from masculine-coded blue-collar work, such as occupations in construction, and Asian American men in white-collar jobs may be evaluated less favorably on traits deemed necessary for career advancement (for example, leadership and charisma). Historical depictions of Asian American women, in addition to being highly exoticized and sexualized, painted them as either vulnerable or cunning (Dhingra and Rodriguez 2014; Li 2014). These tropes, alongside model minority stereotypes, might play out in classed fashion in the labor market. Working-class Asian American women may be seen as ideal menial workers, given their supposed docility, whereas highly educated Asian American women might be judged as more aggressive and competent relative to other women.

Research offers evidence for the intersection of race and gender in shaping Asian American experiences in educational and workplace settings. Amy Hsin (2018) argues that the model minority stereotype is more harmful for Asian American boys than girls because it runs counter to hegemonic ideals of masculinity. Hsin finds that Asian American boys perform academically as well as Asian American girls in elementary school but fall behind in adolescence. The salience of gender thus grows over time for Asian Americans. In a recent study using data from the Census Bureau’s Current Population Survey Annual Social and Economic Supplement, averaged across more than a quarter century, researchers find that the gender gap in predicted income favoring men is smaller among Asian American workers than among White workers (Vo et al. 2023). Earlier research also finds a similar pattern of smaller gender gaps in earnings for Asian American and other non-White women (Greenman and Xie 2008). On the whole, a deeper look at the ways in which stereotypes of Asian Americans are classed and gendered suggests possible disadvantages for Asian American men and advantages for Asian American women in earnings, with the caveat that any advantages for the latter may stem from harmful stereotypes and do not preclude an overall female disadvantage in the labor market.

LABOR SUPPLY AND OCCUPATIONAL STRATIFICATION

We focus on two potential avenues through which Asian Americans experience work in simultaneously racialized, classed, and gendered ways that result in differences in earnings compared with their White counterparts: labor supply and occupations. Reports of time spent at work either omit Asian Americans entirely (Wilson and Jones 2018) or else offer a monolithic and unidimensional view of them. For example, a Bureau of Labor Statistics statistical table shows similar average hours worked for Asian American and White men and women (aged sixteen and older) but does not provide estimates based on level of education or nativity. Studies of occupations tend to focus on specialized or elite jobs requiring high levels of education (Chin 2020; Greenman 2011), with much less focus on the types of occupations available to Asian Americans without college degrees. The amount of time spent at work and occupations worked also represent a combination of employer and employee needs and preferences, both of which are shaped by the varying social locations of Asian American men and women, with and without college degrees.

Early work on Asians in the US labor market alludes to their longer working hours, though it is not always clear whether this holds across immigrant generations and levels of education (Chun 1980; Hirschman and Wong 1981; Hurh and Kim 1989). For example, Charles Hirschman and Morrison G. Wong (1981) briefly mention the “long hours and low pay” associated with jobs commonly held by immigrant Chinese men. Yet simply accepting that all Asian Americans are predisposed to working longer hours, whether out of necessity or choice, risks turning a finding for a particular segment of the population into a stereotype of all Asian Americans with little empirical basis. In fact, ChangHwan Kim and Arthur Sakamoto (2014) find that native-born Asian American men typically work less than White men, both in terms of hours per week and weeks over the year, with differences generally larger among men without college degrees. Two other studies find evidence of greater labor supply among highly educated Asian American women. Emily Greenman’s (2011) study of women scientists and engineers finds that both prior to and after having a child, Asian American women are more likely than White women to be working full-time. ChangHwan Kim and Yang Zhao’s (2014) findings show that greater labor supply accounts for some of the earnings differences college-educated Asian American women have with White women across immigrant generations. However, whether such findings apply to Asian American women without college degrees remains a question.

Family factors also shape labor supply in significantly racialized and gendered ways. Emily Greenman and Yu Xie’s (2008) analysis of Census 2000 data finds that among married mothers with young children, nearly all groups of non-White mothers are more likely than White mothers to work full-time, year-round. The authors suggest that White families are most likely to engage in “gender role specialization,” in which men engage in “market” production and women in “domestic” production. Elsewhere, Greenman (2011) argues that a mix of structural and cultural factors—ranging from immigration trends to family composition to cultural perspectives on mothering—contributes to Asian American women’s greater participation in the labor market, even after becoming mothers. Greenman suggests that immigrant and highly educated Asian American women are likely to have a “strong work commitment” but the study’s focus on elite workers (scientists and engineers) and lack of analysis by nativity again calls for greater attention to be paid to the intersection of race, class, and gender.

Differences in earnings between Asian Americans and Whites might also be due to occupations. Some scholars have argued that, given their “newcomer” and minority status in the US, Asian Americans tend to strategically aim for occupations that require “hard” skills, credentials, and training because they believe evaluations for such positions are more objective and less susceptible to bias and discrimination. Thus, technical occupations in science, engineering, law, and medicine are seen as ideal (Chun 1980; Lee and Zhou 2015; Xie and Goyette 2003). Such occupations, because of the specialized skill sets required, also typically command higher pay. To the extent that college-educated Asian Americans are more highly concentrated in such occupations, they may enjoy an overall earnings advantage. However, because such occupations conform to model minority stereotypes of Asian Americans as technically competent but otherwise unexceptional workers, they might not outearn their White peers within similar occupations. Preferences and strategies for occupations may also be gendered. For example, Asian American women, but not Asian American men, are generally more likely to select college majors with greater earnings potential compared to their White counterparts (Song and Glick 2004). In professional fields where women remain underrepresented, such as in many science, technology, engineering, and mathematics (STEM) occupations, Asian American overrepresentation may advantage Asian American women. In such occupations, gender, if not race, can set Asian American women apart, marking them as exceptional or more capable workers, whereas neither gender nor race sets Asian American men apart in STEM occupations, casting them as typical workers.

For Asian Americans without high levels of education, earnings may depend on what types of occupations are open to them in the low-wage sector. The Bureau of Labor Statistics lists jobs in construction, maintenance, and transportation as among the better-paying jobs for those without college degrees (Farrell and Lawhorn 2022). As we argued earlier, such occupations are strongly coded as masculine in ways that disadvantage Asian American men, an argument some earlier research supports (Hirschman and Wong 1981). This suggests that Asian American men may not have access to the same types of occupations with lower educational requirements as their White peers and may instead be concentrated in service work with lower pay. However, we think it unlikely that stereotypes about Asian Americans disadvantage Asian American women in the same way in the low-skill, low-wage labor market. This is because employers may view Asian American women in such jobs as especially hardworking and compliant, in other words, as ideal workers for the types of jobs commonly open to women without high levels of education.

To summarize, we have argued that the ambivalent nature of Asian American stereotypes— ranging from yellow peril to model minority tropes—has distinct implications for the labor market experiences of Asian Americans across class and gender. We theorize that the racialized experiences of Asian American workers by class and gender may manifest in differences in both the amount of time spent at work and in the kinds of work done, ultimately resulting in differences in earnings. Our analyses build on these ideas by examining the labor supply, occupations, and earnings of Asian Americans in comparison with their White counterparts and with particular attention paid to similarities and variations in such comparisons across educational attainment and gender. Comparisons with White Americans, as well as with Black Americans, offer insight into the broader racialized experiences of Asian Americans, while patterns by educational attainment, for men and women, speak to the extent to which Asian American experiences are classed and gendered in ways that have largely been understudied in the extant literature. Our analytic strategies allow us to assess the extent to which differences in labor supply (time spent working) and occupations account for earnings differences between Asian American men and women and their White peers across levels of education.

DATA AND METHODS

In the following sections, we describe the data upon which this study relies, including sample restrictions and composition. We also provide descriptions of study measures before outlining the analytic strategy.

FINDINGS

We first present descriptive analyses of wage differences, labor supply, and occupations. Next, we present findings from multivariate models that examine the relationships between labor supply, occupations, and wage income.

Wage Differences

Figure 1 plots gross differences from Whites in logged wage income by gender and education. These estimates control for background and demographic variables but not labor supply or occupation. Among men without a bachelor’s degree, Asian American men across all represented ethnic groups earn significantly less than comparably educated White men, with wage incomes ranging from about 11–21 percent lower.⁴ For reference, Black men without bachelor’s degrees earn about 24 percent less in wage income than their White counterparts. As shown in figure 1, the wage incomes of Chinese, Indian, and Vietnamese American men without bachelor’s degrees are closer to the wage income of Black men than to the wage income of White men.

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Figure 1.

Gross Differences in Logged Wage Income from Whites by Gender and Educational Attainment (Ages 25–54)

Source: IPUMS American Community Survey five-year file (Ruggles et al. 2024).

Note: CHN = Chinese, FIL = Filipino, IND = Indian, KOR = Korean, VIET = Vietnamese, BLK = Black. Whites, represented as vertical lines, are the reference group. Estimates are weighted and control for demographic variables, including additional educational categories (associate’s degree or graduate degree), marital status, child in household, age, and commuting zone. BA = bachelor’s degree.

Among men with a bachelor’s degree, we find somewhat less consistent evidence of an Asian American disadvantage. College-educated Filipino and Vietnamese American men earn less than comparably educated White men (by about 20 percent and 10 percent, respectively). For Filipino men with bachelor’s degrees, the wage income disadvantage relative to Whites is even larger than corresponding comparisons among their counterparts without bachelor’s degrees. This places their earnings closer to that of college-educated Black men, who earn about 28 percent less than college-educated White men. College-educated Chinese and Korean American men are at a slight disadvantage (p < .10) and college-educated Indian American men are at a clear advantage, earning nearly 14 percent more than similarly educated White men.

For women, we find a pattern of Asian American parity among those without a bachelor’s degree and an advantage among those with at least a bachelor’s degree relative to their White counterparts. Filipina Americans without a bachelor’s degree earn about 5 percent more in wage income, while Chinese, Indian, Korean, and Vietnamese American women without a bachelor’s degree earn about the same as comparably educated White women. Among women with at least a bachelor’s degree, all Asian American groups shown in figure 1 have a wage income advantage, with the advantage being largest for Chinese and Indian American women, who earn about 16–17 percent more than comparably educated White women. These patterns contrast with the experiences of Black women, who have lower wage incomes than White women across levels of education.

Baseline wage income comparisons provide evidence that Asian American earnings are strongly patterned by the intersection of class (via educational attainment) and gender. While Asian American men are largely at a disadvantage relative to White men, there is variability in this overall pattern among the college-educated. Asian American women do not experience the same earnings disadvantage as men, but any earnings advantage they may have is restricted to the college-educated. Here, we examine the potential of labor supply and occupations in helping to understand these differences in earnings.

Labor Supply Differences

Figure 2 presents differences from Whites in hours worked over the past year, approximated by taking the product of the number of weeks worked in the past year and the usual hours worked per week. A clear division is seen between Asian American and White men in that nearly all of the former, across levels of education, work fewer hours than the latter. Among men without a bachelor’s degree, the largest gap is seen between Chinese American and White men, with the former having worked about 169 fewer hours (roughly five fewer full-time work weeks) than the latter over the past year.⁵ For other Asian American men without a bachelor’s degree, differences range from 100 to 137 fewer hours worked over the past year (about three to four fewer full-time work weeks). This places the labor supply of Asian American men without college degrees in the range of their Black counterparts, who worked about 147 fewer hours than White men over the past year.

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Figure 2.

Differences in Labor Supply from Whites by Gender and Educational Attainment (Ages 25–54)

Source: IPUMS American Community Survey five-year file (Ruggles et al. 2024).

Note: CHN = Chinese, FIL = Filipino, IND = Indian, KOR = Korean, VIET = Vietnamese, BLK = Black. Whites, represented as vertical lines, are the reference group. Estimates are weighted. BA = bachelor’s degree.

This pattern is also mostly present for men with a bachelor’s degree or higher. The difference is especially stark for college-educated Filipino Americans, who worked about 200 fewer hours (nearly six fewer full-time work weeks) than college-educated White men over the past year. College-educated Vietnamese American men likewise worked about 159 fewer hours than White men (more than four fewer full-time work weeks). Both these groups have even lower labor supply than college-educated Black men. The lower labor supply of Korean and Chinese American men with at least a bachelor’s degree is more modest—about two fewer full-time work weeks. Once again, the exception is college-educated Indian American men, who worked about thirty-three more hours over the past year than comparably educated White men.

Unlike the generally consistent pattern of lower labor supply among Asian American men, Asian American women typically work about the same or more hours than White women. Among women without bachelor’s degrees, Chinese, Indian, and Korean American women’s labor supply is no different from that of their White counterparts, while Filipina Americans and Vietnamese American women, like Black women, work more hours. For Filipina Americans, the difference is a modest twenty-nine more hours worked over the past year, while for Vietnamese American women, the difference is larger at just over seventy more hours worked (about two more full-time work weeks). Among the college-educated, Chinese and Indian American women, like Black women, work more than White women, while Korean and Vietnamese American women work about the same amount. Only college-educated Filipina Americans work slightly less than White women.

Patterns of labor supply differences largely map onto the differences in earnings seen in figure 1. Of course, we would expect the amount of time spent at work to correspond to earnings. Our focus, however, lies in the racialized, classed, and gendered ways in which these differences emerge. Moreover, the role labor supply plays in explaining earnings differences is likely to be stronger among those without college degrees, as the jobs available to such individuals are typically of the hourly pay type. Labor supply may play a lesser role in explaining earnings differences among the college-educated, who are more likely to work in jobs that pay a salary and where time spent at work has a less direct connection to pay. For such workers, occupations may play a larger role, as we discuss in the following section.

Occupational Differences

To understand how occupations might account for differences in wage income, we present two descriptive measures: occupational segregation (figure 3) and occupational concentration (figures 4 and 5). To measure occupational segregation, we estimate the dissimilarity index D for each Asian American group and for Blacks relative to Whites by gender and educational attainment using OCC2010, an IPUMS measure that captures over 400 occupations. The dissimilarity index indicates the extent to which the distribution of Asian Americans across occupations differs from the corresponding distribution of Whites. To gauge occupational concentration, we depict the top three most common occupational categories for each racial and ethnic group, by gender and educational attainment. In other words, we aim to show how much occupations differ between Asian Americans and Whites as well as what types of occupations are most common for each group.

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Figure 3.

Occupational Dissimilarity to Whites by Gender and Educational Attainment (Ages 25–54)

Source: IPUMS American Community Survey five-year file (Ruggles et al. 2024).

Note: Estimates are weighted. BA = bachelor’s degree.

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Figure 4.

Common Occupational Categories for Men by Educational Attainment (Ages 25–54)

Source: IPUMS American Community Survey five-year file (Ruggles et al. 2024).

Note: Estimates are weighted. The three most common occupational categories for each subgroup are depicted, with respective median wage incomes (based on gender and educational attainment) also provided. The optimal way to view this figure is in color. We refer readers of the print edition of this article to https://www.rsfjournal.org/content/12/3/76 to view the color version.

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Figure 5.

Common Occupational Categories for Women by Educational Attainment (Ages 25–54)

Source: IPUMS American Community Survey five-year file (Ruggles et al. 2024).

Note: Estimates are weighted. The three most common occupational categories for each subgroup are depicted, with respective median wage incomes (based on gender and educational attainment) also provided. The optimal way to view this figure is in color. We refer readers of the print edition of this article to https://www.rsfjournal.org/content/12/3/76 to view the color version.

Occupations Among Men

Figure 3 depicts estimates of occupational dissimilarity from Whites, which can be interpreted as the proportion of each group that would need to change occupations in order to have a distribution across occupations similar to that of Whites. For example, more than one-third of Chinese, Indian, Korean, and Vietnamese American men without a bachelor’s degree would have to change occupations in order to be distributed in a manner similar to that of their White counterparts. The occupational dissimilarity scores for Filipino and Black men are somewhat lower (30 and 28, respectively). From this perspective, Asian American men without bachelor’s degrees are more dissimilar to Whites than Black men are in the occupations they hold. Levels of occupational dissimilarity among college-educated men are generally lower, but racial and ethnic patterns remain similar. Anywhere from one-quarter to one-third of Asian American men would have to change occupations in order to have distributions like that of their White counterparts. This level of occupational dissimilarity between college-educated Asian American and White men is generally higher than that seen between college-educated Black and White men.

Figure 4 shows the three most common occupational categories for men with and without bachelor’s degrees, alongside the median wage income for men with the respective level of educational attainment in the occupational category. For example, among Chinese American men without bachelor’s degrees, the most common occupational category is office and administrative support (13 percent) and the median wage income for all men without bachelor’s degrees in the analytic sample working in such occupations is $35,600 (rounded to the nearest hundred). The levels of occupational dissimilarity seen in figure 3 are reflected in figure 4. Whereas construction and production occupations are common among White men without bachelor’s degrees, such occupations are not consistently seen among comparably educated Asian American men. For the latter, occupations in office and administrative support, as well as sales, are more common. There is also ethnic variation among Asian American men without bachelor’s degrees. For example, occupations in food preparation and serving are common among Chinese Americans, transportation and moving occupations among Filipino Americans, and management positions among Indian and Korean Americans. Figure 3 shows that among men with at least a bachelor’s degree, levels of occupational dissimilarity between Asian Americans and Whites are generally lower. Likewise, figure 4 shows that management and computer and mathematical occupations are common among both Asian American and White men. However, while anywhere from 10 to 19 percent of college-educated Asian American men work as health-care practitioners and technicians, such occupations do not rank among the most common for college-educated White men.

Occupations Among Women

Compared with their male counterparts, Asian American women without bachelor’s degrees exhibit less occupational dissimilarity from Whites (figure 3). About one-quarter of Chinese, Indian, and Korean American women without bachelor’s degrees would need to change occupations to achieve distributions across occupations like that of comparably educated White women. This level of occupational dissimilarity is on par with that of Black women without bachelor’s degrees. Filipina Americans show the lowest dissimilarity scores to Whites, while Vietnamese American women show the highest (18 and 34, respectively). Whereas among men, Asian American occupational dissimilarity was generally lower among the college-educated, the opposite appears to be the case for some groups of Asian American women. College-educated Chinese and Indian American women, as well as Filipina Americans, show noticeably higher levels of occupational dissimilarity from their White counterparts compared to levels among women without bachelor’s degrees.

Women show greater occupational concentration compared to men in that the top three occupations typically account for about half of each group (figure 5). Moreover, among women without college degrees, some occupational categories are fairly common regardless of race and ethnicity: anywhere from 20 to 29 percent of Asian American, Black, and White women work in office and administrative support, and another 10 to 15 percent work in sales. One notable outlier is Vietnamese American women without bachelor’s degrees, nearly a quarter of whom work in personal care and services. This is likely a reflection of the prevalence of Vietnamese American women in the US who work as manicurists (Eckstein and Nguyen 2011), an economic niche that is highly racialized, classed, and gendered.

College-educated women also tend to work in similar occupations. Roughly equal shares of Asian American, Black, and White women with at least a bachelor’s degree are in management occupations (15–17 percent). Office and administrative support occupations are also common for college-educated women. Occupations such as health-care practitioners and technicians are common for college-educated Asian American and White women, albeit to varying degrees. For example, about 28 percent of prime working-age Indian American women with at least a bachelor’s degree work in such occupations, almost double the 15 percent of White women who do so. Nearly one-fifth of college-educated White women work in education, but such occupations are not common among most Asian American women, with the exception of Korean American women, though their share is about half that of White women. Indian American women with at least a bachelor’s degree are the only group for whom occupations as business operations specialists are relatively common.

Before turning to multivariate models, we sum up the descriptive findings presented thus far. Among prime working-age adults, there is no consistent earnings advantage for Asian Americans relative to Whites. Instead, patterns vary by educational attainment and gender. Among workers without bachelor’s degrees, Asian American men experience a consistent wage income disadvantage relative to Whites while Asian American women do not. Among college-educated workers, Asian American women experience an earnings advantage relative to Whites while only Indian American men have a noticeable earnings advantage. Both labor supply and occupations may account for some of the above patterns. The lower labor supply of Asian American men without bachelor’s degrees, as well as their concentration in occupations with lower median wage incomes, may account for their earnings disadvantage relative to Whites. For college-educated men, their concentration in higher-paying occupations such as health-care practitioners and technicians and in computer and mathematical fields is likely to matter for their earnings. Labor supply and occupational differences are less prominent among women and thus may have less explanatory power when it comes to earnings. However, where wage income advantages exist for Asian American women, we typically also find corresponding greater labor supply or greater concentrations in occupational categories with higher median wage incomes.

DISCUSSION AND CONCLUSION

This study makes a number of contributions to research on contemporary Asian American experiences in the labor market. We examine wage incomes for an ethnically diverse sample of prime working-age Asian Americans relative to their White peers across intersecting dimensions. Because our sample of Asian Americans is restricted to the native-born and those who arrived as younger children, our study is well-suited to examining the role of race and its impact on Asian Americans in the labor market. Moreover, based on our focused literature review, we identify labor supply and occupations as two important factors that are subject to ambivalent stereotypes about Asian Americans and that potentially explain differences in earnings between Asian Americans and Whites across levels of education and by gender. In doing so, we highlight the ways in which Asian American experiences in the labor market are simultaneously racialized, classed, and gendered. This approach provides a broader comparative perspective than is found in most existing research on Asian American labor market experiences.

Our empirical analysis aligns closely with our theoretical framework, which focuses on the ways in which stereotypes about Asian Americans impact their labor market experiences. We show that the disadvantages in wage income among Asian American men without bachelor’s degrees are explained in large part by their lower labor supply and different occupations held relative to White men. Our study cannot determine if these differences reflect employer discrimination. However, such findings accord with broader classed and gendered stereotypes about Asian American men in a number of ways. First, as 1.5 and later generation Asian Americans educated in the US but who do not hold bachelor’s degrees, these men do not conform to model minority stereotypes, potentially making employers wary of their potential as workers. Second, both yellow peril and model minority stereotypes might serve to funnel these men into low-wage service occupations (akin to the launderers and houseboys of the past) and hinder their entry into traditionally masculine blue-collar occupations in construction and production, which are among the higher-paying jobs for men without college degrees. Our findings suggest that Asian Americans should not be overlooked in research on the low-wage labor market for men. Their experiences are essential to understanding the potential harm of stereotypes about Asian Americans beyond educational experiences.

The finding that college-educated Asian American men would be at an even greater earnings disadvantage relative to White men were it not for their occupations also brings to mind model minority stereotypes of Asian Americans as particularly suited for certain occupations. We show that larger shares of college-educated Asian American men do indeed work in computer and mathematical jobs and as health-care practitioners and technicians, both higher-paying occupational categories. To be sure, individual agency and preferences play a role, but the set of occupational choices college-educated Asian American men select from may be constrained by group-based definitions of success (Lee and Zhou 2015), “playbooks” that prescribe limited tactics for getting ahead (Chin 2020), and beliefs about opportunities for upward mobility (Sue and Okazaki 1990). Some might construe these as part of the culture of Asian Americans, though we would argue such strategies reflect a sense of precariousness about their position within the US racial and socioeconomic hierarchy. Controlling for occupations, many college-educated Asian American men actually earn less than their White peers. Again, stereotypes may play a role—whether in viewing Asian American workers as virtually identical to one another (and thus interchangeable and replaceable), in assumptions of their supposed foreignness, or in doubts about their suitability for leadership roles.

Our comparison of earnings among women further underscores the racialized, classed, and gendered nature of Asian American labor market experiences. We show that Asian American women, unlike Asian American men, do not have an earnings disadvantage relative to White women and, at the upper end of educational attainment, even have a small advantage. Unlike their male counterparts, Asian American women without a bachelor’s degree work similar or sometimes greater hours than their White counterparts, and they do so in largely similar occupations. This suggests a gendered dimension to how Asian American workers in the low-wage labor market are perceived. Whereas Asian American men without a bachelor’s degree may be seen as unsuitable for masculine-coded occupations, Asian American women without bachelor’s degrees appear to have access to the same types of occupations as other women. While such women may not embody the stereotype of a highly educated model minority, they do fit long-established, strongly gendered depictions of Asian women in subservient roles.

College-educated Asian American women are the only group of Asian Americans for whom we find clearer evidence of an earnings advantage. As with their male counterparts, occupational concentration plays a larger role than labor supply in explaining earnings differences. College-educated Asian American men and women may adhere to similar strategies for achieving upward mobility, such as greater investments in education and the selection of particular occupations. But the contrast between model minority stereotypes of Asian Americans as exceptionally skilled in math and science and gender stereotypes of women as lacking skills in such fields may also serve to advantage college-educated Asian American women over other women in some occupational settings. Notably, our findings do not suggest that college-educated Asian American women are advantaged over their male counterparts. For all groups, men retain an advantage over women in average wage incomes (see table A.2). As college-educated Asian American women consider their labor market experiences, they may come to view gender rather than race as of greater salience (Huang 2021), given that they appear to earn as much, if not more, than other women but not as much as men.

In explaining patterns of Asian American earnings relative to Whites by level of education and gender, we have focused on the role of labor supply and occupations. However, our study also yields results that speak to a need for more research on family dynamics, ethnic variations, and disparate mechanisms driving racial differences. For example, we find that Asian American women are at parity or outearn White women net of controls for marital status and the presence of children in the household. We recognize that this strategy does not fully capture the complicated ways in which family dynamics and decision-making matter for Asian American women’s labor market experiences; see Sojung Lim and Wonjeong Jeong (2026, this issue) for a focus on how family composition shapes labor force participation for Asian American women. We instead highlight how stereotypes about Asian American workers have a highly gendered element that is not often articulated when drawing on simple descriptions of model minority stereotypes and believe this framework can be expanded to incorporate family dynamics.

Throughout, we also noted instances in which specific ethnic groups exhibited different baseline patterns—for instance, that college-educated Indian American men have an earnings advantage over White men whereas other Asian American men do not. Even among 1.5- and later generation Asian Americans, ethnic niches can persist in the labor market (such as the concentration of Vietnamese American women in personal services and Filipina Americans in health care). The framework we have offered of Asian American stereotypes as concurrently racialized, classed, and gendered can be applied to studies focused on particular ethnic groups. We note also that our study shows labor supply and occupations have similar classed and gendered impacts on earnings across Asian American ethnic groups, even though baseline earnings differ.

Lastly, including Black Americans as an additional point of reference proved illuminating in a number of ways. First, some Asian American men without bachelor’s degrees have labor market experiences that are startlingly similar to those of Black Americans, in terms of labor supply and earnings disadvantages. Not only does this run completely counter to model minority stereotypes, it also suggests pockets of Asian American disadvantage that have been largely overlooked in the literature. Second, while differences in labor supply and occupations are key to explaining differences in earnings experienced by Asian American workers, they appear to play a smaller role for understanding the experiences of Black American workers. This has implications for future research on mechanisms that drive racial differences in earnings. We have argued that stereotypes about Asian Americans may undergird decisions made by workers and employers that manifest in differences in labor supply, occupations, and ultimately, earnings. Stereotypes about other racial groups might also result in differences in earnings but through different channels.

Overall, our results reveal that the intersection of race, class, and gender offers a much more nuanced story of Asian American earnings that is consistent with literature on the power of stereotypes in shaping Asian American experiences. A compelling theoretical framework—one that moves beyond simply critiquing the harmfulness of stereotypes about Asian Americans and instead moves toward understanding how such stereotypes differentially impact Asian Americans—remains elusive. We have endeavored to articulate ways in which contradictory but often simultaneously held stereotypes about Asian Americans—as yellow peril threats or competent but faceless model minorities—might operate in classed and gendered fashion to produce differences in the labor supply, occupations, and earnings of Asian American men and women workers with and without college degrees. Future research can further explore mechanisms that might be contributing to differences in time spent at work and occupational concentrations among Asian American men and women, which we have shown are key to understanding differences in earnings. We hope also that future work on Asian Americans, in the spirit of intersectional scholars, pays attention to those on the “margins” (Crenshaw 1991), including Asian Americans who, whether for reasons related to their level of education, the types of occupations they hold, or other characteristics, do not fit common perceptions of Asian American success and advantage. Without attending to their experiences, we cannot continue to advance in our understanding of the contemporary and future well-being of Asian Americans.