Education-Occupation Linkage in the Highly-Educated Workforce: Patterns and Sources of Difference by Race/Ethnicity

Abstract

The present study investigates education-to-occupation linkage by race/ethnicity in the increasingly diverse educated workforce of the United States. We use a recently introduced linkage approach and identify two dimensions of linkage between educational credentials and occupation (vertical and horizontal linkage). Using data from the 2014 –2018 American Community Survey, we find notable differences in the total strength of education-occupation linkage by race/ethnicity. Highly-educated Black workers experience weaker vertical and horizontal linkage than their white counterparts; this is also true for Hispanic workers, though to a lesser extent. Ethnoracial differences in vertical linkage are stronger and more consistent than those in horizontal linkage. We decompose group differences in linkage strength and find that differences in occupational distributions and the composition-invariant structural component account for a large part of the overall difference in linkage strength. Separate analyses by degree levels show that, while the linkage is generally stronger for advanced degree holders than bachelor’s degree holders, ethnoracial differences remain similar between the two groups of highly-educated workers.

Keywords

education linkage mismatch occupation race and ethnicity

Introduction

Globally, higher education expansions have increased the number of college graduates and have also contributed to the diversification of college and advanced degree holders. A prime example of this trend is the United States, given its pace of educational expansion and racial/ethnic diversification (Craig et al., 2018; Jensen et al., 2021). Unprecedented numbers of ethnoracial minorities have entered the labour market with college or graduate degrees in the United States. Between 1980 and 2015, the percentage of Black workers¹ aged 25 and above with at least a bachelor’s degree increased from 7.9% to 22.9%; the corresponding growth for Hispanic workers was from 7.6% to 15.5% (compared to an increase from 18.4% to 36.2% for white workers; Snyder et al., 2018). The conventional wisdom holds that higher education is a great equaliser that reduces labour market inequality by social class origin (Hout, 2012; Torche, 2011).

However, in the United States wage inequality by race and ethnicity has been stubbornly persistent; this inequality is larger and has even expanded for highly-educated workers (Autor et al., 2006; Cheng et al., 2019; Daly et al., 2017). Specifically, the wage disparity between white and Black college graduates has risen from 8.8% in 1980 to 18% in 2015 (Wilson and Rodgers, 2016). A similar pattern has been found for Hispanic college graduates (Mora and Dávila, 2018).

An important yet underexplored question is why higher education falls short of narrowing racial/ethnicity inequality in the labour market. The conventional wisdom of the equalising role of higher education is premised on the assumption that collegiate credentials are closely linked to commensurate positions in the labour market. The persistent inequality among highly-educated workers suggests that the linkage may be uneven among college graduates and may differ by race/ethnicity.

In the present study, we conceptualise that the connection between higher education and the labour market is captured by the linkage between educational credentials and occupational positions. We operationalise the strength of education-occupation linkage across different racial/ethnic groups by measuring the extent to which college graduates work in occupations that are typically associated with their educational credentials. We expect that the education-occupation linkage is structured differently and exhibits different strength for college graduates of different races and ethnicities. Given that a stronger linkage strength generally leads to higher labour market rewards (Bol et al., 2019), we expect the education-occupation linkage to be weaker for minority groups than white workers.

We distinguish between two facets of the linkage, which are rarely studied in a unified framework. The first facet is the vertical linkage between workers’ educational levels and occupations typically associated with that level of education. The second facet is the horizontal linkage between workers’ fields of study and the occupations that typically require that type of education.

The first key question we examine is whether the overall education-occupation linkage strength differs by race/ethnicity. Do college-educated ethnoracial minority workers experience weaker education-occupation linkage than their white counterparts? If so, is the racial/ethnic difference found in vertical linkage, horizontal linkage, or both? The existing research on this topic has not distinguished between different dimensions of the education-occupation linkage and has largely focused on comparing two racial groups, especially white and Black workers. We address this issue by measuring and comparing the strength of both vertical and horizontal linkage across all four main racial/ethnic groups (white workers, Black workers, Hispanic workers, and Asian workers).

Specifically, we follow the linkage strength approach introduced by DiPrete et al. (2017), which builds on entropy-based segregation indices (Mora and Ruiz-Castillo, 2011). This approach allows for the analysis of group-level association between two categorical variables, such as educational and occupational categories. The method was originally developed for cross-country comparison of education-occupation linkages. We extend this method to capture the linkage strength across subpopulations (along ethnoracial lines) within one country (the United States). In such a setting, total linkage for a given racial/ethnic group measures the strength of the association between that group’s educational credentials and occupational distribution. We calculate the vertical and horizontal linkage strengths separately for each racial/ethnic group. A higher linkage strength indicates a greater degree of clustering in occupations for a specific educational background, which in turn reflects the typically travelled education-to-occupation pathways for people with specific educational credentials, such as college-level occupations for bachelor’s degree holders and occupations closely related to a specific field of study. Taken together, the total linkage strength reflects the extent to which college graduates secure college-level jobs (vertical linkage) and jobs typically related to their field of study (horizontal linkage).

The second key question of our study focuses on the underlying sources of ethnoracial differences in education-occupation linkage strength. The entropy-based segregation measures that we use have the desirable property of being decomposable. We use a procedure developed by Elbers (2021) to decompose group differences in total linkage strength into compositional and structural components. This allows us to identify the extent to which racial/ethnic differences in overall linkage emerge from unequal educational distributions, unequal occupational distributions, or unequal structural association between education and occupation.

The analysis uses data from the 2014–2018 American Community Survey. In general, we find notable differences in the total strength of education-occupation linkage by race/ethnicity, with traditionally disadvantaged groups (i.e., Black and Hispanic workers) experiencing weaker vertical and horizontal linkages than their white peers. Decomposition analysis further suggests that differences in occupational distributions and the composition-invariant structural component account for a large part of the overall difference in linkage strength.

Vertical and horizontal education-occupation linkage

Vertical and horizontal linkage represent distinct processes by which educational credentials translate into occupational positions. Vertical linkage refers to the extent to which highly-educated workers (those with at least a college degree) work in typical occupational destinations (i.e., occupations that typically require a college degree). The lower the linkage, the more likely that college graduates are employed in non-college jobs (e.g., retail sales), which on average have lower wages. Vertical linkage is shaped by the relative balance between labour market supply and demand. The expansion of higher education, accompanied by a decline in demand for skilled workers (Beaudry et al., 2016; Shierholz, 2014), has resulted in a relative oversupply of college graduates, forcing some to diverge from the typical pathways and take non-college level occupations.

Horizontal linkage characterises the extent to which highly-educated workers are employed in occupations that are closely related to their field of study. The weaker the linkage, the more likely that college graduates are employed in occupations that are not strongly related to their fields (e.g., STEM majors working in non-STEM occupations). Horizontal linkage is shaped by supply-demand balance as well as the occupational specificity of fields of study, with vocationally-oriented fields (e.g., engineering) presenting clearer occupational pathways than generally-oriented fields (e.g., social sciences) (Roksa and Levey, 2010). Weak horizontal linkage generally indicates that a notable share of college graduates deviate from frequently travelled pathways from specific fields of study to typical occupations associated with these fields.

One key question is whether ethnoracial minority workers are more likely to deviate from the typical pathways than their white peers and whether the ethnoracial differences in vertical and horizontal linkage strength are similar or differ. Another question is what mechanisms drive ethnoracial differences in vertical and horizontal linkage strength, which we turn to next.

Race/ethnicity and education-occupation linkage

Race and ethnicity continue to structure educational and career opportunities in the United States. There are several reasons to expect ethnoracial differences in education-occupation linkage, including differences in educational composition, occupational composition, and the structure of the relationship between education and occupation. The discussion below integrates theories of human capital, occupational segregation, and labour market discrimination to understand how these different social processes may ultimately produce group differences in education-occupation linkage in the aggregate. The conceptual framework is summarised in Figure 1.

Differences in educational composition

From the supply side, ethnoracial differences in education-occupation linkage strength may result from differences in the educational composition: that is, a lower representation of minorities in the college-graduate workforce and in certain fields of study. This is consistent with human capital theory, which attributes racial differences in labour market outcomes to unequal human capital investments and endowments (Roscigno, 1998; Tomaskovic-Devey et al., 2005). Although minority workers have made tremendous gains in educational attainment, Black and Hispanic workers remain less likely to receive a college or advanced degree than their white counterparts. For example, 35% of white workers aged 25 and older hold at least a bachelor’s degree, compared to 21% Black workers and 15% Hispanic workers (de Brey et al., 2019). Asian workers are the most educated group, with 52% having at least a college degree. Tertiary education instils advanced and complex skills and is thus connected to a narrower set of high-skilled occupations; in comparison lower levels of education tend to lead to a wider range of unskilled and semi-skilled jobs (DiPrete et al., 2017). It follows that an advanced degree tends to lead to an even smaller set of occupations and thus higher linkage strength than a bachelor’s degree (DiPrete et al., 2017; Forster and Bol, 2018).

The literature also illustrates complex ethnoracial differences in fields of study. Minorities are found to be similarly, if not more, likely than white peers to select a vocationally-oriented major (such as engineering, education, health and business) for better job prospects, after taking account of socio-economic background and academic preparation (Dickson, 2010; Xie and Goyette, 2003). White workers, by contrast, are more likely to choose generally-oriented fields such as social sciences and humanities. However, Black and Hispanic college students have a higher propensity to switch majors (especially leaving STEM) and lower graduation rates (Adelman, 2006). The actual level of Black and Hispanic college graduates with technical and vocational degrees is comparable or lower to white workers (Beasley and Fischer, 2012). Because vocational and technical fields are more strongly linked with occupation (Bol et al., 2019), ethnoracial differences in linkage strength may be partly attributed to minority graduates’ lower representation in these fields.

Differences in occupational composition

Ethnoracial differences in education-occupation linkage strength may also result from differences in the occupational composition. This reflects demand-side processes that give rise to occupational segregation by race/ethnicity. Racial occupational segregation has been a persistent source of the racial wage gap (Stainback and Tomaskovic-Devey, 2012; Weeden, 2019). Minority workers, especially Black and Hispanic workers, tend to concentrate disproportionately in low and semi-skilled service and production occupations with loosely defined educational requirements and are less likely to hold managerial and professional positions that link more strongly with educational credentials (Kaufman, 2002). This pattern is mitigated but nonetheless holds even among highly-educated workers (Queneau, 2009). Such segregation weakens education-occupation linkage for minority college graduates as they are steered toward racially-segregated occupations that have weak links with collegiate educational credentials (Heiniger and Imdorf, 2018). Taken together, minority workers may have lower education-occupation linkage partly because they are overrepresented in lower-level, segregated occupations.

Differences in structural association between education and occupation

Even after controlling for differences in educational and occupational composition, racial/ethnic differences may exist in the structural association between education and occupation – that is, how educational credentials lead to occupational placement. This component illuminates important labour market sorting mechanisms. The theory of labour market discrimination posits widespread implicit bias and unequal treatment on the basis of race/ethnicity (Birkelund, 2016; Blommaert et al., 2014; Pager et al., 2009), even among college graduates (Gaddis, 2015). Employers may be subject to taste-based discrimination or statistical discrimination (Lippens et al., 2022). The former refers to discrimination that stems from preferences. The latter scenario occurs when employers face ambiguous information about a worker’s productivity and seek to rely on their perceptions about the average qualifications of the worker’s social group (Fiske, 1998). This activates widely-held racial stereotypes, in which highly-educated minority workers are perceived as less competent and committed and thus less suitable for desired college-level and high-skilled positions than similarly-educated white workers (Moss and Tilly, 2001; Pager et al., 2009).

The processes outlined above mean that minority college graduates may be disproportionately channelled into non-college jobs (below their educational level) and jobs not closely related to their qualifications (outside their fields of study). This manifests in minority college graduates being placed across a wider range of occupations that include many non-college jobs and jobs less related or unrelated to their fields of study. Such process implies weaker structural linkage between education and occupation. By contrast, white workers with similar educational qualifications are likely to end up in a narrower set of occupations that are disproportionately college-level jobs or jobs closely related to their training. It is worth noting that the structural component is more pronounced for vertical linkage than horizontal linkage. Horizontal linkage may stem in part from personal preferences and choices, in which workers trade off a high horizontal linkage for other occupational amenities such as flexibility and other working conditions and benefits.

Heterogeneity by race and ethnicity

The foregoing discussion is based largely on the experience of traditionally disadvantaged groups, namely Black and Hispanic workers. Extensive research demonstrates that Black workers, even with a college degree, are subject to negative stereotypes regarding competence and commitment (Kornrich, 2009; Lee and Fiske, 2006; Moss and Tilly, 2001; Neckerman and Kirschenman, 1991; Waldinger and Lichter, 2003). Hispanic workers tend to be viewed as more hardworking and motivated than Black workers (Waldinger and Lichter, 2003), but less productive than comparable white workers (Moss and Tilly, 2001; Telles and Ortiz, 2008). These stereotypes weaken education-occupation linkage for Black workers and, to a lesser degree, Hispanic workers. Employers perceive Asian workers more favourably than Black and Hispanic workers (Woo et al., 2012; Xie and Goyette, 2004), which leads to stronger linkage strength for Asian workers than other minority groups. Overall, these processes point to a possible racial hierarchy among similarly-educated skilled workers, with white workers and (to a lesser degree) Asian workers enjoying favourable occupational outcomes, Black workers experiencing the most disadvantage, and Hispanic workers occupying an intermediate position.

The foregoing discussion leads to the following hypotheses:

Hypothesis 1: There are racial/ethnic differences in education-occupation linkage strength, with white and Asian graduates enjoying a higher linkage and Hispanic and especially Black graduates having a lower linkage.

Hypothesis 2: Considering occupational segregation and structural labour market constraints facing ethnoracial minorities, differences in the linkage strength is driven by both compositional and structural components.

Data, variables and methods

Data and sample

We used data from the American Community Survey (ACS) to measure education-occupation linkage strength across ethnoracial groups. ACS is an annual survey of about 1% of the US population and contains information on occupation, educational level, and field of study (since 2009). We pooled five years of ACS data from 2014 to 2018, which provided a sample size of 9,343,756 workers with occupation information. The large sample size allowed us to examine highly-educated workers across the four main ethnoracial groups, as well as highly-detailed occupational categories and fields of study. Specifically, we distinguished highly-educated workers according to three-digit census occupations (452 categories), three educational levels, and 22 fields of study.

To estimate linkage strength, we restricted the sample to employed individuals with at least a bachelor’s degree (33%) who worked full time and were aged 22 to 65 in ACS 2014–2018. We kept to four main ethnoracial groups (white worker, Black worker, Hispanic worker, and Asian worker) and excluded 0.88% of the sample in other racial groups. The main analysis included workers in a wide age spectrum. We conducted additional analysis restricting the sample to workers within 10 years of graduation (from the highest degree) and obtained similar results. We pooled men and women in the analyses to increase the sample size. This decision was also informed by our analysis that showed no gender difference in the ethnoracial variations of education-occupation linkage. These analyses are presented in the appendices.

The final analytic sample contained 2,745,841 college graduates. About 76.6% of the sample were white workers, followed by 9.5% Asian workers, 6.4% Black workers, and 7.4% Hispanic workers.

Measuring group-level education-occupation linkage strength

To provide an overall picture of the linkage strength by race/ethnicity (Hypothesis 1), we drew on the approach introduced by DiPrete et al. (2017). This approach is based on an entropy-based multigroup segregation measure, specifically the Mutual Information Index M (Mora and Ruiz-Castillo, 2011; Theil, 1972). The method operationalises the linkage strength as the expected gain in information (i.e., reduction in entropy) about workers’ occupational position from knowing their education. This gain corresponds to improved predictability of occupational outcome conditional on educational background and thus higher linkage strength.

The linkage strength approach gives systematic attention to both the macro and granular linkage structure between educational credentials and occupational positions (Bol et al., 2019; DiPrete et al., 2017; Elbers et al., 2021). At the macro level, it takes account of the occupational distribution of individuals across different educational credentials (total linkage). A stronger linkage indicates a higher degree of clustering in occupations conditional on educational background. At the granular level, the linkage strength approach allows us to examine how strongly a specific educational credential is linked to occupational outcomes (local linkage).

Specifically, $M {(e d u)}_{e}$ , the local linkage strength of an educational credential, is formulated as:

M {(e d u)}_{e} = \sum_{o} p_{o | e} l o g (\frac{p_{o | e}}{p_{o}})

(1)

where e denotes an educational credential (level or field) and o represents occupation. $M {(e d u)}_{e}$ measures the extent to which the occupational distribution of workers in a given educational category e (conditional probability, p_o|e) deviates from the unconditional occupational distribution of all workers (marginal probability, p_o). The greater the deviation (i.e., the higher the ratio between p_o|e and p_o), the higher the local linkage strength between that specific educational credential and occupation: that is, workers in a given educational level or field of study cluster in a relatively small set of occupations that represent the typical pathways. In contrast, if workers with a certain educational background disperse across many different occupations (including non-college jobs and jobs not closely related to their field), it indicates a weak linkage. The deviation is then aggregated over all occupations to obtain the local linkage for a specific educational credential.

The local linkage strength can be further aggregated to obtain M (total linkage strength), as in equation (2). This is done by summing the local linkage strength across all educational credentials using weights equal to the relative size of each educational category.

M = \sum_{e} p_{e} M {(e d u)}_{e}

(2)

We calculated M separately by the level of education (vertical linkage) and field of study (horizontal linkage) for each racial/ethnic group. Higher values of M indicate stronger linkages between educational credentials and occupational outcomes for that racial/ethnic group. We used bootstrapping to estimate standard errors for both the M calculations and decomposition procedures.

Total linkage strength decomposition

The M has the useful property of being decomposable in theoretically meaningful ways. This decomposability property allows for a deeper understanding of the source of group difference in overall education-occupation linkage strength ( M ). Specifically, we investigated the extent to which M is driven by group differences in the educational and occupational composition (i.e., marginal differences) and in the (composition-invariant) structural association between education and occupation (i.e., structural differences) (Hypothesis 2).

We adopted a procedure first proposed by Karmel and Maclachlan (1988) and extended by Elbers (2021). This procedure is based on the insight that the odds ratios of the contingency table are the only measure of association that does not change when the margins are transformed. Consider two $g \times j$ contingency matrices for two different groups, $k_{1}$ and $k_{2}$ . To make a margin-free comparison, we adjusted the margins of the contingency matrix $k_{1}$ to be identical to those for $k_{2}$ . This is achieved by the use of iterative proportional fitting (IPF), where first the row margins of $k_{1}$ are scaled toward those of $k_{2}$ , and then the column marginals of the resulting table are scaled toward those of $k_{2}$ . Repeating this process several times would transform the marginals of $k_{1}$ to approach the marginals of $k_{2}$ , while preserving the odds ratios of $k_{1}$ . The process was repeated until the marginals are within 0.001% of the marginals of $k_{2}$ . We call the resulting counterfactual matrix $k'_{1}$ . We then repeated the IPF procedure the other way around, starting from the matrix $k_{2}$ and yielding a counterfactual matrix $k'_{2}$ . These two scenarios differ in the choice of the original matrix: one adjusts from $k_{1}$ forward toward $k_{2}$ , while the other adjusts in a backward direction from $k_{2}$ to $k_{1}$ .

The counterfactual matrices can then be used to compute the size of marginal and structural differences between $k_{1}$ and $k_{2}$ (Elbers, 2021). The full decomposition is given by:

M_{k_{1}} - M_{k_{2}} = Δ_{m a r g i n a l - e d u} + Δ_{m a r g i n a l - o c c} + \sum_{e \in k_{1} \cap^{} k_{2}} Δ_{e, s t r u c t u r a l}

(3)

where we decompose the group difference in M into group difference in the marginal distribution of educational categories ( $Δ_{m a r g i n a l - e d u}$ , or ΔE), group difference in the marginal distribution of occupational categories ( $Δ_{m a r g i n a l - o c c}$ , or ΔO), and group difference in margin-invariant association ( $\sum_{e \in k_{1} \cap^{} k_{2}} Δ_{e, s t r u c t u r a l}$ , or ΔS), also referred to as the structural component. The structural component captures the association between education and occupation net of the effects of the educational and occupational distribution or, in other words, how effectively educational credentials are translated into occupational position. We conducted the decomposition for each pair comparison, using white workers as the reference group. More details of the decomposition procedures are in Appendix A.

Variables

We distinguished between four ethnoracial categories: non-Hispanic white worker, non-Hispanic Black worker, Hispanic worker, and Asian worker. This variable was constructed using two questions in ACS (whether the respondent is of Hispanic, Latino, or Spanish origin; and the race of the respondent).² For education, we used three levels of education (bachelor’s degree, master’s degree, and doctoral degree). For field of study, we followed the International Standard Classification of Education 1997 (ISCED) and used 22 fields of study related to the respondents’ highest level of education (teaching/education, arts, humanities, social and behavioural science, journalism and information, business and administration, law, life sciences, physical sciences, mathematics and statistics, computing, engineering/engineering trades, architecture and building, agriculture/forestry/fishery, health, social service, personal services, transport services, environmental protection, security services, not known or unspecified, and no fields). ACS collects information on the field of study for the bachelor’s degree. We adopted an imputation procedure used in DiPrete et al. (2017) to obtain the field information for advanced degree holders (Appendix B).

For occupation, we used the detailed 3-digit Census 2018 classification, which included 452 occupations derived from the 2018 Standard Occupational Classification SOC system. We conducted an expected value test presented in Elbers (2021) to check if the M indices may be biased due to sparse cells. The test results show that the expected values under random segregation are close to zero, which indicates that the indices are not biased.

Results

Descriptive statistics

The raw ethnoracial differences in education credentials and occupations among people with at least a bachelor’s degree are presented in Table 1. White and Asian graduates tended to have higher educational attainment and are more likely to hold doctoral and professional degrees than Black and Hispanic graduates. With respect to fields of study and occupations, we used aggregated categories in descriptive statistics for parsimony; the refined categories were used in the linkage strength calculation and decomposition. The results show that Black and Hispanic workers were overrepresented in certain fields such as social sciences, business, law, and health and welfare. White workers, in comparison, were overrepresented in humanities and education. Asian workers were disproportionately concentrated in STEM fields.

Table 1.

Descriptive results (percentages) of education credentials and occupations by race/ethnicity among workers with at least a bachelor’s degree (ACS 2014–2018).

	Race/Ethnicity
	Whitegraduates	Blackgraduates	Hispanicgraduates	Asiangraduates
Level of education
Bachelor’s degree	63.24	62.74	68.26	56.06
Master’s degree	26.34	29.38	22.79	29.10
Doctoral/professional degree	10.41	7.88	8.95	14.84
Field of study
Education	12.85	10.52	10.50	4.44
Humanities and Arts	12.38	8.75	11.63	8.15
Social sciences, Business, and Law	37.69	43.15	40.27	30.49
Science	10.08	10.32	9.43	19.82
Engineering, Manufacturing, and Construction	8.64	5.74	10.49	20.36
Agriculture	1.23	0.43	0.61	0.44
Health and Welfare	11.75	14.50	10.81	13.58
Services	3.92	4.99	4.49	1.48
Not known or unspecified	1.46	1.60	1.77	1.24
Occupation
Management, Business, and Financial Occupations	27.08	24.02	22.86	24.23
Professional and Related	45.66	41.64	41.90	50.96
Service Occupations	5.77	8.64	9.47	5.76
Sales and Office	16.19	18.34	17.67	14.09
Natural Resources, Construction, and Maintenance	1.78	1.52	2.77	0.92
Production, Transportation, and Material Moving	3.02	4.87	4.47	3.25
Military Specific Occupations	0.50	0.97	0.86	0.79
N	2,104,272	176,522	203,788	261,259
Total sample size	2,745,841

As for occupation, white graduates were overrepresented in management, business and finance, and professional jobs. Asian graduates were overrepresented in professional occupations, especially STEM jobs. Both groups were less likely to find employment in sales, service, and production. The converse was true for Black and Hispanic graduates, who were overrepresented in these occupations.

Differences in patterns of education-occupation linkage

Table 2 presents estimates of total linkage strength ( M index) for the overall sample and for each racial/ethnic group. M ranges between zero (when the occupational distribution for each educational category is the same as the overall occupational distribution) and the logarithm of the number of educational categories (when all workers in each educational category are concentrated in one occupation). The absolute value of M is not easily interpretable, so we interpret M in relative terms by comparing M across groups.

Table 2.

Vertical and horizontal education-occupation linkage strength among workers with at least a bachelor’s degree (ACS 2014–2018).

	Vertical	% relative to reference group	Horizontal	% relative to reference group
Overall Linkage Strength	0.176		0.621
Linkage Strength by Race/ethnicity
Non-Hispanic white graduate	0.184	100%	0.643	100%
Non-Hispanic Black graduate	0.127	69%	0.492	77%
Hispanic graduate	0.141	77%	0.580	90%
Asian graduate	0.202	109%	0.590	92%
N	2,745,841		2,745,841

Note: The reference group for percentage calculation is white workers.

Results in Table 2 show that among bachelor-degree holders, Asian graduates had the highest vertical education-occupation linkage strength, followed by white workers, Hispanic workers, and Black workers. Specifically, Black and Hispanic graduates had, respectively, 31% and 23% lower vertical linkage strength than their white peers, while Asian graduates had 9% higher strength. The pattern was similar for horizontal linkage strength. Highly-educated white workers and, to a lesser extent, Asian workers enjoyed higher linkage strength. Black workers and Hispanic workers had, respectively, 23% and 10% lower linkage strength than their white peers.

Overall, these results suggest that white and Asian graduates were more likely to follow typically education-occupation pathways for college graduates than the other two ethnoracial groups and that Hispanic graduates were less disadvantaged than Black graduates. These results are consistent with Hypothesis 1. Also, ethnoracial differences in vertical linkage seemed to be more pronounced than those for horizontal linkage.

Differences in source of linkage strength: Decomposition results

Table 3 displays decomposition results by race/ethnicity. The row “Difference” shows the raw group difference in total linkage strength (white graduates as the reference group). The other rows sum to the raw difference. The rows “Marginal-occupation” (ΔO) and “Marginal-education” (ΔE) refer to the extent to which group differences in total linkage strength arise from group differences in the occupational and educational composition, respectively. The row “Structural” (ΔS) displays the contribution of composition-invariant structural association between education and occupation, holding constant the marginal distributions of education and occupation. Note that the bootstrapping standard errors are very small, suggesting that group difference in overall linkage and the contribution of the marginal and structural components are all statistically significant.

Table 3.

Total linkage decomposition by race/ethnicity among workers with at least a bachelor’s degree (ACS 2014–2018).

	Vertical Linkage		Horizontal Linkage
	Estimation	Bootstrap S.E.	Estimation	Bootstrap S.E.
Non-Hispanic white graduate	0.184	0.000	0.643	0.001
Non-Hispanic Black graduate	0.126	0.001	0.491	0.003
Difference	-0.058	0.001	-0.152	0.003
Marginal-occupation (ΔO)	-0.031	0.001	-0.084	0.001
Marginal-education (ΔE)	-0.004	0.000	-0.006	0.001
Structural (ΔS)	-0.023	0.001	-0.061	0.003

Non-Hispanic white graduate	0.184	0.000	0.643	0.001
Hispanic graduate	0.140	0.001	0.581	0.003
Difference	-0.043	0.001	-0.063	0.003
Marginal-occupation (ΔO)	-0.018	0.001	-0.061	0.001
Marginal-education (ΔE)	-0.005	0.000	-0.020	0.001
Structural (ΔS)	-0.020	0.001	0.018	0.002

Non-Hispanic white graduate	0.184	0.000	0.643	0.001
Asian graduate	0.202	0.001	0.590	0.002
Difference	0.018	0.001	-0.053	0.003
Marginal-occupation (ΔO)	0.024	0.001	0.033	0.001
Marginal-education (ΔE)	0.004	0.001	-0.056	0.001
Structural (ΔS)	-0.010	0.001	-0.030	0.002
N	2,745,841		2,745,841

The results show that both the marginal and structural components played a role, which support Hypothesis 2. For the white-Black gap in vertical linkage, a large proportion of the difference, about 53%, was explained by Black-white differences in the occupational distribution. In other words, highly-educated Black workers had lower vertical linkage largely because they were disproportionately placed in occupations that were relatively weakly linked with educational levels (i.e., non-college occupations). In comparison, the contribution of the educational margins was smaller (7%). About 40% of the Black-white difference was attributed to the composition-invariant structural component. That is, highly-educated Black workers were disproportionately steered into a wider range of occupations than similarly-educated white workers, which exposed them to many non-college jobs. Put differently, if highly-educated white workers and Black workers had the same association between education and occupation, the disparity in linkage strength would be reduced by 40%. These decomposition results are more clearly shown in Figure 2.

As for the white-Hispanic difference in vertical linkage, the structural component appeared to play the greatest role. About 42% of the gap was explained by occupational margins and another 12% by education margins, whereas 46% is driven by the structural component. This suggests that Hispanic graduates were more concentrated in less strongly linked occupations and, to a smaller extent, less strongly linked educational levels. They were also especially likely to experience a weaker association between education and occupation.

For the white-Asian difference in vertical linkage, we found an advantage for highly-educated Asian workers. This was largely explained by educational and occupational composition such that Asian workers were concentrated in educational levels and occupations with stronger links to the other entity (e.g., as shown in Table 1, Asian workers were overrepresented in professional and technically-oriented fields of study and occupations). However, their compositional advantage was partly offset by the structural disadvantage. Among similarly-educated Asian and white workers, the association between educational levels and occupations was tighter for white workers.

Turning to horizontal linkage, the most pronounced source of Black-white difference was occupational composition (55%): Black graduates were overrepresented in occupations that were more loosely related to fields of study. The composition-invariant structural component accounted for 40% of the lower horizontal linkage for Black graduates. For the white-Hispanic difference, occupational composition again constituted the most important component, followed by field of study composition. Interestingly, highly-educated Hispanic workers experienced a stronger structural component. This suggests that among college graduates trained in the same field, Hispanic workers were more likely than white workers to find employment in closely related occupations.

The pattern of Asian graduates was different. They experienced lower horizontal linkage than white graduates, which was explained by the educational composition and the structural component. Although Asian graduates were overrepresented in fields such as science, the local linkage strength for certain majors was quite low. However, this difference was counteracted by their occupational composition, which gravitated toward occupations with close connections to fields of study (e.g., professional and technical occupations; Table 1).

Results by bachelor’s and advanced degree holders

One important question is whether an advanced degree can reduce group differences in education-occupation linkage strength. Conventional wisdom points to an equalising effect of postgraduate education. In this view, the high-skilled labour market is more meritocratic than that for lower-educated workers (Breen and Jonsson, 2007; Hout, 1988). Graduate schools also provide more specialised skills and professionalisation, which facilitates connections with the labour market and a strong linkage strength, especially for traditionally disadvantaged groups. However, the alternative view contends that the equalising effect of graduate education is limited (Posselt and Grodsky, 2017; Witteveen and Attewell, 2020). Ascriptive factors such as social origin continue to stratify occupational destinations among postbaccalaureate degree holders (Torche, 2011). A similar pattern may also apply to race and ethnicity.

To answer this question, we conducted separate analyses for terminal bachelor’s degree (BA) holders and advanced degree holders (master’s and doctoral, or MA+), as displayed in Table 4. Note that for this analysis, we focused on horizontal linkage because the separate BA and MA+ samples have too few educational levels to render the analysis of vertical linkage meaningful.

Table 4.

Total horizontal linkage for BA only and MA+ (ACS 2014–2018).

	BA only	% relative to reference group	MA+	% relative to reference group
	Horizontal	% relative to reference group	Horizontal	% relative to reference group
Overall Linkage Strength	0.451		0.915
Linkage Strength by Race/ethnicity
Non-Hispanic white graduate	0.470	100%	0.938	100%
Non-Hispanic Black graduate	0.381	81%	0.784	84%
Hispanic graduate	0.444	94%	0.979	104%
Asian graduate	0.461	98%	0.808	86%
N	1,727,153		1,018,688

For BA holders, we found a racial/ethnic hierarchy, with white workers having the highest horizontal linkage, followed by Asian workers, Hispanic workers, and then Black workers. For advanced degree holders, the horizontal linkage strength was systematically stronger, almost doubling that of bachelor’s degree holders. Hispanic workers with advanced degrees had the tightest link between field of study and occupations, followed by white workers and Asian workers. Black workers remained the group with the lowest linkage. The results for Hispanic college graduates required further investigation. This could partly reflect the variations in perceptions toward Hispanic workers by socio-economic background. The labour market disadvantage of Hispanic workers largely reflected the experience of low-skilled immigrant workers who bore notable ethnoracial dissimilarity to white workers. On the other hand, highly-educated Hispanic workers, who were often native-born, shared greater affinity to white workers in characteristics such as language and culture (Tienda and Lii, 1987; Zong and Batalova, 2018). The blurring ethnic boundaries for this group may result in favourable labour market outcomes for highly-educated Hispanic workers.

We also conducted several additional analyses. To conserve space, they are presented in Appendices C through F (by gender, cohort, period, etc.). The results from these analyses are largely consistent with the main findings.

Conclusion and discussion

The present study provides a systematic investigation of education-occupation linkage by race/ethnicity within the increasingly diverse highly-educated American workforce. We adopt a linkage strength approach and specifically distinguish between vertical and horizontal education-occupation linkage. We further decompose group differences in overall linkage strength into compositional and structural components.

Our study provides insights into two main research questions. First, does the overall education-occupation linkage strength differ by race/ethnicity? The findings demonstrate notable racial/ethnic variations that generally favour white workers, which is consistent with Hypothesis 1. There is also some evidence of a racial hierarchy, with Black college graduates consistently experiencing the weakest linkage strength, Hispanic college graduates occupying an intermediate position, and Asian graduates attaining similar positions as white graduates. Hence, Black and Hispanic college graduates disperse across a wider range of occupations including many non-college and out-of-field jobs. These results highlight the greater difficulty these workers face in finding employment in occupations commensurate with their educational credentials.

Second, what are the underlying sources of ethnoracial differences in education-occupation linkage strength? The results show that differences in linkage strength stem from both compositional and structural differences across groups (in line with Hypothesis 2). Minority workers’ lower linkage is partly attributed to different occupational distributions, which may stem from occupational segregation. Another important explanation is the structural effect (i.e., a looser association between education and occupations net of educational and occupational distributions). The structural component is suggestive of differential treatment based on race in the labour market, which channels equally-qualified minorities disproportionately into non-college level or out-of-field jobs. In comparison, the educational distribution plays a smaller role. This is in line with recent studies that document diminishing ethnoracial differences in education attainment and fields of study among highly-educated workers (Bloome and Western, 2011; Snyder et al., 2018). Taken together, the decomposition analysis brings together theories of human capital, occupational segregation, and labour market discrimination to understand how these forces combine to produce group differences in education-occupation linkage.

The main findings hold for both workers with a terminal bachelor’s degree and an advanced degree. Whereas the linkage strength is systematically stronger for advanced degree holders than for bachelor’s degree holders, the ethnoracial differences in linkage strength (i.e., relative position) and underlying sources are generally similar. These findings highlight the importance of advanced degrees in facilitating education-occupation linkage across the board, but also point to the limited potential of postgraduate education for narrowing racial inequality.

Our main analyses combined individuals across different age groups. In additional analyses (Appendix D), we separately investigated highly-educated workers who entered the labour market 10 years, 20 years, and 30 years prior to the survey. The results show no clear change in vertical and horizontal linkage strength across the three cohorts. Importantly, the racial/ethnic gap in both dimensions of linkage remained highly stable across cohorts. Moreover, to assess the change in linkage patterns over time in general, we replicated our main analysis with the 2009–2013 ACS data and reached a similar conclusion (Appendix E). Over time, the linkage strength has declined slightly across all groups. But the lower linkage facing ethnoracial minorities has persisted in the past decade.

A few limitations warrant discussion. Despite the large sample size of ACS, it is not large enough to disaggregate the analysis by master’s and doctoral degree. In addition, we do not have information on class, which may confound the observed differences by race and ethnicity. Future research should control for class when investigating racial/ethnic differences in education-occupation linkage. We also lack information on other forms of horizontal educational stratification, such as the type (i.e., selectivity) of educational institutions, which may be another reason for the lower linkage of minority workers. We are not aware of large-scale national data that would allow us to study refined educational and occupational categories while also providing information on institutional type. This topic is worth investigating in future research. Another fruitful direction of research is to examine how the linkage process plays out at the individual level and how it varies by race and ethnicity. Doing so will allow us to further distinguish different qualities of horizontal linkage. Theoretically, horizontal linkage is particularly complex because it may reflect personal priorities and preferences. A low horizontal linkage may originate from two different scenarios. One is horizontal undermatch, which occurs when workers are linked to out-of-field occupations that represent a downgrade (in terms of economic rewards or occupational prestige). The other scenario is horizontal overmatch, which transpires when individuals go outside their field of study and pursue occupations that offer greater economic or social rewards than in-field occupations. These different scenarios deserve further research.

Notwithstanding these limitations, our study highlights the analytical value of the linkage approach in providing a useful summary about the relationship between education and occupation across groups within a single country. Whereas our focus is on race and ethnicity, this analytic approach can be applied to investigating education-occupation linkage along other social categories (e.g., class, gender, nativity). Moreover, the present study demonstrates vertical and horizontal linkage as distinct phenomena, with ethnoracial differences for vertical linkage stronger and more consistent than for horizontal linkage. This highlights the need to distinguish these two axes of mismatch in future research.

The current study represents a step toward a fuller understanding of the sources of racial/ethnic inequality among the increasingly diverse skilled workforce. The results suggest that, amid the expansion of higher education, highly-educated minorities are more vulnerable to deviating from the typical education-occupation pathways for college graduates and, as such, disproportionately holding non-college and out-of-field occupational positions. Whereas education-occupation linkage is an important indicator of inequality in its own right, it represents a central mechanism for other forms of inequality (e.g., economic inequality). Existing cross-country comparative research has demonstrated important economic effects of linkage strength: workers in tightly-linked occupations receive higher remuneration (Bol et al., 2019; DiPrete et al., 2017). In this respect, racially differentiated patterns of linkage strength can contribute to racial wage inequality in the high-skilled labour market.

Our results suggest that racial inequality cannot be eliminated simply through educational choice, for example, obtaining a college degree, choosing more vocationally-oriented fields of study, or even pursuing postgraduate education. These choices have not fully levelled the playing field for minorities. Our findings underscore the importance of addressing both compositional and structural elements of group differences in education-occupation match among highly-educated workers. This requires facilitating occupational desegregation and effective school-to-work pathways, as well as enforcing equal opportunity regulations in labour market allocation processes, even for the highly educated.

Our study was conducted in the United States but is emblematic of the broader issue of suboptimal education-occupation linkage worldwide. Many societies have undergone a higher education expansion, which is accompanied by a misalignment between the supply and demand of highly-educated workers. As such, challenges in education-to-work transition among college graduates have been documented outside the United States (Bol et al., 2019; Noelke et al., 2012; Salas-Velasco, 2007). In the meantime, many of these societies have become more racially diverse. An overlooked yet pressing question is whether the linkage process differs by race and ethnicity in these countries. A broadly similar pattern of racial/ethnic difference may be observed, given widespread occupational segregation and racial/ethnic discrimination across contexts. Equally important is the role of education and labour market institutions in shaping the linkage process. To the extent that some countries (e.g., Germany) have a tighter connection between higher education and the labour market (DiPrete et al., 2017; Raffe, 2011), we may observe lower racial/ethnic variation in the linkage strength in these settings.

Supplemental Material

sj-docx-1-wes-10.1177_09500170221133714 – Supplemental material for Education-Occupation Linkage in the Highly-Educated Workforce: Patterns and Sources of Difference by Race/Ethnicity

Supplemental material, sj-docx-1-wes-10.1177_09500170221133714 for Education-Occupation Linkage in the Highly-Educated Workforce: Patterns and Sources of Difference by Race/Ethnicity by Yao Lu, Xiaoguang Li and Benjamin Elbers in Work, Employment and Society

Footnotes

Acknowledgements

The authors are grateful for constructive comments from the reviewers. Yao Lu gratefully acknowledges support from the Columbia Population Research Center and the Institute for Social and Economic Research and Policy at Columbia University. Xiaoguang Li gratefully acknowledges the support from the Institute for Empirical Social Science Research at Xi’an Jiaotong University.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and publication of this article: Yao Lu gratefully acknowledges support from the National Institute of Child Health and Development (K01HD073318), the Washington Center for Equitable Growth, and the Columbia Population Research Center with funding from the National Institute of Child Health and Human Development (P2CHD058486). Xiaoguang Li gratefully acknowledges the support from National Natural Science Foundation of China (72204196).

ORCID iDs

Yao Lu

Xiaoguang Li

Benjamin Elbers

Supplemental material

Supplemental material for this article is available online.

Notes

Yao Lu is Professor of Sociology at Columbia University. Her research lies at the intersection of inequality, demography, and politics. One line of her current work investigates the sources of labour market inequality among highly-educated workers in the United States. Her other research projects include studies of the influence of demographic forces on political processes and the impact of COVID-19 on racial attitudes. Her recent publications have appeared in Proceedings of the National Academy of Sciences, American Journal of Sociology, Demography and Social Forces.

Xiaoguang Li is Assistant Professor of Sociology at Xi’an Jiaotong University. His research focuses on social stratification and inequality in China and the United States. He is currently investigating how education-occupation mismatch intersects with demographic processes to shape wage inequality, and how social capital and social networks reproduce inequality, especially for ethnic minorities in China. His recent research also examines dynamics of change and negative effects of social capital. Recent articles have appeared in Social Forces, Social Networks, and Research in Social Stratification and Mobility.

Benjamin Elbers is a postdoctoral prize research fellow in Sociology at Nuffield College, University of Oxford. He received his PhD from the Department of Sociology at Columbia University. His work focuses on inequality and stratification, with a special interest in segregation and the connection between educational systems and labour markets. He works on segregation measures, and he is the author of a couple of R packages. He is interested in computational methods and reproducible research. Recent articles have appeared in Social Forces, and Sociological Methods & Research.

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