MexicanAncestry,ImmigrantGeneration, …socweb.soc.jhu.edu/faculty/morgan/papers/Morgan... · 2014-10-06 · comparative devaluation of bilingualism, strained ... the pace of incorporation.2

Mexican Ancestry, Immigrant Generation,and Educational Attainment in the United StatesStephen L. Morgan,a Dafna Gelbgiserb(a) Johns Hopkins University and Cornell University, (b) Cornell University

Abstract: After introducing alternative perspectives on assimilation and acculturation, we use the 2002-2012 waves ofthe Education Longitudinal Study to model differences in educational attainment for students sampled as high schoolsophomores in 2002. We focus on patterns observed for the growing Mexican immigrant population, analyzing separatelythe trajectories of 1st, 1.5th, 2nd, and 3rd+ generation Mexican immigrant students, in comparison to 3rd+ generationstudents who self-identify as non-Hispanic whites and students who self-identify as non-Hispanic blacks or AfricanAmericans. The results suggest that the dissonant acculturation mechanism associated with the segmented assimilationperspective is mostly unhelpful for explaining patterns of educational attainment, especially for the crucial groups of1.5th and 2nd generation Mexican immigrant students. Instead, standard measures of family background can account forlarge portions of group differences in bachelor’s degree attainment, with or without additional adjustments for behavioralcommitment to schooling, occupational plans, and educational expectations. The broad structure of inequality in theUnited States, as well as the rising costs of bachelor’s degrees, should be the primary source of concern when consideringthe prospects for the incorporation of the children of recent Mexican immigrants into the mainstream.

Keywords: college degrees; schooling; assimilation; immigrantsEditor(s): Jesper Sørensen, Olav Sorenson; Received: June 19, 2014; Accepted: July 15, 2014; Published: September 29, 2014

Citation: Morgan, Stephen L. and Dafna Gelbgiser 2014. “Mexican Ancestry, Immigrant Generation,and Educational Attainment in the United States.”Sociological Science 1: 397-422. DOI: 10.15195/v1.a23

Copyright: c� 2014 Morgan and Gelbgiser. This open-access article has been published and distributed under a Creative Commons Attribution License,which allows unrestricted use, distribution and reproduction, in any form, as long as the original author and source have been credited.cb

For scholars concerned about the relative stand-ing of recent immigrants to the United States

and their children, three common observationspose grave concerns, each of which is supportedby enough literature to now constitute receivedwisdom in the social sciences. First, incorpo-ration into the mainstream is typified by thestandard of living associated with those who holdmiddle-class jobs. Second, middle-class jobs arereserved frequently for those who obtain bache-lor’s degrees. Third, the direct costs of bachelor’sdegrees are escalating sharply, making college anincreasingly expensive investment.

Although some immigrant groups have fam-ily resources to meet the steep direct costs ofhigher education, the largest and fasting growinggroup—recent immigrants from Mexico and theirchildren—are resource constrained. The gen-eral literature on educational attainment showsthat many students from families with limitedresources are unaware of available financial aidprograms. Immigrants from Mexico and their

children are unlikely to be any more aware offinancial aid programs than students of otherwisesimilar socioeconomic standing.

Alongside consideration of these present re-alities, scholars of immigrant incorporation con-tinue to debate the validity of more specializednarratives, most prominently the segmented as-similation prediction first proposed by Portes andZhou (1993) and later developed in full form byPortes and Rumbaut (2001).1 In brief, this line ofargument maintains that groups such as Mexicanimmigrants face a hostile reception and are insuffi-ciently supported by ethnic enclaves. In response,many adolescents and young adults engage in “dis-sonant” patterns of acculturation, typified by a

1Portes and his colleagues have continued to de-velop the segmented assimilation perspective in morerecent work (see Portes and Rumbaut 2006; Portes andFernández-Kelly 2008; Portes and Rivas 2011; Haller,Portes, and Lynch 2011a, 2011b), but we regard the artic-ulation offered first in Portes and Zhou (1993) and thendeveloped in full detail in Portes and Rumbaut (2001) tobe the subject of ongoing debate.

sociological science | www.sociologicalscience.com 397 September 2014 | Volume 1

Morgan and Gelbgiser Mexican Ancestry and Educational Attainment

comparative devaluation of bilingualism, strainedrelationships with their Spanish-speaking parents,a faltering commitment to schooling in adoles-cence, and an emergent interest in deviance dur-ing the transition to adulthood. As a result, asubstantial proportion of the children of Mexi-can immigrants can be expected to assimilatedownward to a subordinate status, approachingstandards of living more typical of those whoself-identify as black or African American.

The persuasiveness, and even the basic form,of the segmented assimilation prediction contin-ues to be vigorously debated, with its currentproponents focusing on results from the Childrenof Immigrants Longitudinal Study, which sam-pled students typically aged 14 in Ft. Lauderdaleand San Diego in the early 1990s, with a follow-up survey 10 years later (see Haller et al. 2011a,2011b; Portes and Fernández-Kelly 2008; Portesand Hao 2002; Portes and Rumbaut 2006; Portesand Rivas 2011). Opponents of the predictionhave considered broad historical patterns, na-tional demographic data, and also local samplesfrom other areas, such as a comprehensive setof results on children of immigrants resident inthe New York City metropolitan area (see Alba,Kasinitz, and Waters 2011; Alba and Nee 2003;Perlmann 2005, 2011; Waldinger and Feliciano2004; Waters et al. 2010).

Beyond the dissonant acculturation conjec-ture about the children of Mexican immigrants,a second stream of literature highlights an addi-tional mechanism that impedes the acquisitionof higher education among many prospective col-lege students who self-identify as Hispanic orLatino/Latina (i.e., not just those who claim Mex-ican ancestry). Turley (2006, 2009) and Desmondand Turley (2009) argue that familism amongHispanic adolescents and young adults may dis-courage them from taking advantage of availablefour-year college opportunities and predisposethem to enroll in local community colleges fromwhich comparatively few students then transi-tion to and complete bachelor’s degree programs.Ovink and Kalgorides (2014) challenge this con-clusion, with more recent results using the samedata source we also consider in this article. Ovink(2014a, 2014b) makes the case, based on resultsfrom in-depth interviews, that familism operatesin gender-differentiated fashion, such that His-panic young women benefit from extra social sup-

port that encourages them to obtain bachelor’sdegrees.

In this article, we analyze the 2002 to 2012waves of the Education Longitudinal Study (ELS)to model patterns of high school graduation andpostsecondary education for students sampled ashigh school sophomores in 2002. We first offerresults for the full cohort of students, estimatingeducational attainment patterns for 20 distinctgroups of students formed by a constrained cross-classification of self-identified race-ethnicity andimmigrant generation. We then focus on patternsobserved for the growing Mexican immigrant pop-ulation, analyzing separately the trajectories of1st, 1.5th, and 2nd generation Mexican immigrantstudents, in comparison to three specific groupsof students who are neither recent immigrantsnor the children of recent immigrants. So-called3rd+ generation students, we consider separatelystudents who self-identify as Mexican by ancestry,students who self-identify as non-Hispanic whites,and students who self-identify as non-Hispanicblacks or African Americans.

One point of contention when consideringMexican immigrants and their children is how tofit into ongoing debates any results that are ob-served for 3rd+ generation Mexican immigrants,operationalized as those who claim Mexican an-cestry but also report that both of their biologicalparents were born in the United States. Thisheterogeneous group includes a substantial num-ber of individuals with ancestors who lived inthe area bounded by the current borders of theUnited States before they were demarcated assuch. Unfortunately, very few studies allow forany subdivision of this 3rd+ generation, and wewill not be able to do so in this article. Accord-ingly, our main conclusions will be weighted to-ward the evidence we present on recent Mexicanimmigrants—especially 1.5th and 2nd generationMexican immigrants—because no scholars appearto question their relevance to the dissonant ac-culturation conjecture or current concerns aboutthe pace of incorporation.2 We report results for3rd+ generation Mexican immigrants as well but

2Telles and Ortiz (2008) and Jiménez (2010) explainthat generation effects are particularly difficult to parsefor Mexican immigrants when widely dispersed cohorts aremixed together. Feliciano (2005) presents evidence on theselectivity of cohorts of Mexican immigrants, suggestingthat the particular pattern of selection that has unfoldedin recent decades has decreased rates of college entry since



then offer conclusions that are conditional on howone chooses to regard this group’s relevance toongoing debates.

Methods

Data

Data are drawn from the ELS, 2002 to 2012. Thebase-year ELS sample is representative of all U.S.10th-grade students enrolled in public and privateschools in spring 2002. Unlike its predecessor theNational Education Longitudinal Study of 1988,students with limited English proficiency were in-cluded in the sampling frame. Sampled studentswere judged eligible to take the achievement testsand complete the student questionnaire if theyhad received three years of instruction primarilyin English or, according to the ELS base-yearuser’s guide, if the school staff “judged or deter-mined that they were capable of participating.”For the base year, 17,591 students were sampled,and 87 percent of these students completed thestudent questionnaire. Only 44 sampled studentswere excluded from participation based on theseverity of their limited English proficiency.

Analytic Sample

The ELS incorporates an oversample of Hispanicstudents and Asian students to enable more pre-cise estimation. Among the original 2002 base-year students, 84 percent participated in the 2012third follow-up. Our models include the 10,895respondents for whom third follow-up educationalattainment data are available, weighted to adjustfor base-year participation, attrition across thewaves, and item-specific nonresponse for educa-tional attainment.

Measurement of Immigrant

Generation

A parent questionnaire was completed by 85 per-cent of students’ parents or legal guardians. Therespondent, usually a parent (and most com-monly the student’s mother), was asked, “Was

the 1960s. For these reasons, we confine our analysis to asingle cohort (with most students born in 1986).

your tenth grader’s mother born in the UnitedStates (that is, any of the fifty states or the Dis-trict of Columbia), in Puerto Rico, or in anothercountry or area?” Respondents who selected “inanother country or area” or “in Puerto Rico” werethen asked, “How many years ago did she cometo the United States to stay?” After answer-ing these questions, respondents to the parentquestionnaire were then asked the same ques-tions about the 10th grader’s biological father andabout the 10th grader. Standard indicators of im-migrant generation can be constructed from theseresponses. Across the full ELS sample, 2,838 stu-dents had mothers born outside of the UnitedStates, 2,794 students had fathers born outsideof the United States, and 1,388 students werethemselves born outside of the United States.

If both parents were born inside the UnitedStates, we coded the student as a 3rd+ generationimmigrant. If either parent was born outsideof the United States, but the student was borninside the United States, we coded the studentas a 2nd generation immigrant. If the studentand one or more parents was born outside ofthe United States, we coded the student as a1.5th generation immigrant if the student enteredthe United States by the age of six and as a 1stgeneration immigrant if the student entered theUnited States after the age of six.

For the 15 percent of the sampled studentsfor whom a parent questionnaire was not com-pleted, the ELS also includes a series of questionsposed to students that can be used to separatestudents into those who are more and less likelyto be themselves immigrants or the children ofimmigrants. On their own surveys, students wereasked, “Is English your native language (the firstlanguage you learned to speak when you werea child)?” along with a follow-up question forthose who answered “yes”: “What is your nativelanguage?” (20 response categories with Spanishfirst, followed by 18 other languages or languagegroups, and an “other” category). Although thisquestion is indirect, we use it, as explained in theresults section, to develop an exhaustive codingof immigrant generation by race-ethnicity for asubset of our results, mindful that what is deemeda “native language” may be a poor indicator ofimmigrant status.



Measurement of Race-Ethnicity

Self-identified race-ethnic categories are compara-tively extensive for the ELS, introduced by a filterquestion: “Are you Hispanic or Latino/Latina?”Students who answered yes to this question werethen asked, “If you are Hispanic or Latino/Latina,which one of the following are you? (Mark oneresponse)”: (1) Mexican, Mexican American, Chi-cano; (2) Cuban; (3) Dominican; (4) Puerto Ri-can; (5) Central American (Guatemalan, Salvado-ran, Nicaraguan, Costa Rican, Panamanian, Hon-duran); and (6) South American (Colombian, Ar-gentinian, Peruvian, etc.). All students were thenasked, “Please select one or more of the followingchoices to best describe your race. (Mark all thatapply)”: (1) White, (2) Black/African American,(3) Asian, (4) Native Hawaiian or Other Pacific Is-lander, and (5) American Indian or Alaska Native.This question generated 64 distinct combinationsof responses.3

Given the range of response possibilities, wecoded race-ethnicity by imposing a hierarchy thatreflects the focus of this article as well as the struc-ture of the questionnaire. Students who indicatedthat they were “Hispanic or Latino/Latina” werecoded as Hispanic, regardless of any other sub-sequent responses to the racial self-identificationquestion that follows it.4 If students selected“Black/African American” and had not been des-ignated Hispanic by their responses to prior ques-tions, we coded them as black, regardless ofwhether they expressed a multiracial identity byselecting additional categories. We made analo-gous decisions for all non-Hispanics who subse-quently selected Asian, Native Hawaiian or Pa-

3An ethnicity question for Asians was offered as afollow-up to the race question: “If you marked Asianin Question 17, which one of the following are you?(MARK ONE RESPONSE)”: (1) Chinese, (2) Filipino, (3)Japanese, (4) Korean, (5) Southeast Asian (Vietnamese,Laotian, Cambodian/Kampuchean, Thai, Burmese), and(6) South Asian (Asian Indian, Bangladeshi, Sri Lankan).We did not use these responses in this article becauseAsian immigrants are not the focus of our analysis. Inaddition, we include the small number of Native Hawaiianand Other Pacific Islanders in our “Asian” category, mind-ful that this decision is reductive but more reasonablethan other possibilities.

4Many of these students, in fact, declined to an-swer the race question that followed the Hispanic eth-nicity/ancestry questions (see Supplementary AppendixTable S1).

cific Islanders, or American Indian or AlaskanNative.

Although we use broad categories of race-ethnicity in this article, Supplementary AppendixTable S1 (available on the journal website andthe authors’ personal websites), provides a break-down across more specific racial-ethnic identitiesfor our focal groups. For example, of the 265students we categorized as 2nd generation im-migrants who claimed Mexican ancestry, 144 de-clined to choose a subsequent racial category (and,thereby, implicitly accepted “Mexican, MexicanAmerican, Chicano” as their only racial-ethnicidentity when forced to choose from among thoseoffered to them). Of the remaining students, 86selected the racial category of “White,” 18 chose“American Indian or Alaskan Native,” and 17were spread across eight additional multiracial–multiethnic categories. The distributions in TableS1 make it clear that each of the categories forrace-ethnicity that we utilize in this article shouldbe interpreted as internally heterogeneous butalso consistent with other broad categorizationsadopted in this literature.

Additional Variables

Our outcome variables are standard measuresused in the literature on educational attainment:timely high school graduation, enrollment at anypostsecondary educational institution, and re-ceipt of a bachelor’s degree. We introduce thedetails of most of our additional measures as weutilize them in the subsequent analysis. Thesevariables include 32 separate measures of behav-ioral commitment to schooling (in three scalesbased on independent reports from teachers, stu-dents, and parents) as well as family structureand the five standard dimensions of socioeco-nomic status. In our extended models, we willuse standardized test scores from the 10th and12th grades, cumulative grade point average bythe 12th grade, and educational expectations inboth the 10th and 12th grades.

Two predictor variables are unique to this ar-ticle and others produced by our research group.For both the 10th- and 12th-grade questionnaires,students were presented with a traditional open-ended occupational plans prompt: “Write in thename of the job or occupation that you expect



or plan to have at age 30.” In this article, weeschew two typical codings of these plans. Forthe first, which is produced by contractors to theU.S. Department of Education, the complexityof these free-form responses is reduced to a cat-egorization of 17 broadly defined occupationalgroups (typically close to what are known as cen-sus “major” occupational groups). For the secondcoding, the verbatim responses are converted intoa score on a unidimensional metric that reflectseither the occupational prestige of one of the oc-cupations listed or the average combined incomeand education of present incumbents of one ofthe occupations listed. In the status attainmenttradition, this latter coding of occupational planshas typically been considered an operationaliza-tion of either latent achievement motivation orstatus aspirations tempered by realism (see Hallerand Portes 1973; Sewell, Haller, and Portes 1969;Spenner and Featherman 1978).

Instead, we code occupational plans in a waythat allows us to capture their inherent uncer-tainty and their relationship to modal patternsof educational requirements for specific jobs. Asexplained in Morgan et al. (2013a, 2013b) andMorgan, Gelbgiser, and Weeden (2013), verbatimresponses to the plans prompt, when extractedfrom restricted-access data records, can be codedto 1,220 occupational categories to capture de-tailed information (specific job titles), extendedinformation (the listing of multiple jobs), andcontradictory information (the listing of multiplejobs with divergent characteristics). After per-forming this coding of the verbatim responses,we matched all jobs listed to the educational re-quirements of detailed jobs, as specified in theU.S. Department of Labor’s O*NET database.For the 10th grade, this procedure yielded a five-category variable, which we label EducationalRequirements of Expected Jobs (see Table 2 inthe results section for the categories). For the12th grade, we created an analogous five-categorymeasure of occupational plans, which we thenelaborated using a measure only available for the12th-grade student questionnaire: students’ ownperceptions of the educational requirements oftheir planned jobs, which were elicited in responseto a follow-up question posed immediately afterthey provided their verbatim occupational plans.For the 12th grade, we then have a seven-categoryvariable labeled Beliefs about the Educational Re-

quirements of Expected Jobs (see Table 2 in theresults section for the categories).

Results

Patterns of Educational Attainment

by Immigrant Generation and

Race-Ethnicity

Table 1 presents patterns of educational attain-ment for all 10,895 respondents in the analyticsample, separately for 19 groups defined by im-migrant generation and race-ethnicity (as well asa small 20th group of respondents with missingrace-ethnicity). As shown in the final row of thetable, 88 percent of 2002 10th graders graduatedhigh school on time in 2004. By 2012, 85 percenthad enrolled in some form of postsecondary ed-ucation, including trade schools, certificate pro-grams, and traditional two-year and four-yearcolleges. Rates of bachelor’s degree receipt weremuch lower. Only 35 percent of 2002 high schoolsophomores had received a bachelor’s degree 10years later (i.e., within 8 years of on-time highschool graduation).

Patterns of educational attainment are stronglyrelated to immigrant generation and race-ethnicity.The 19 row labels indicate the specific compo-sition of each group, and our six focal groupsin this article are placed in boldface type. Werefer to these six groups with simplified labelsin the remainder of the article. For example, re-spondents classified by the full label as “Mexican,Mexican American, or Chicano, 1st generation”are referred to as “1st generation Mexicans” here-after, as is common in this literature.

Notice that the four focal groups of Mexicanimmigrants (groups 1 to 4) are separated fromfive other Hispanic immigrant groups differenti-ated by ancestry and generation (groups 5 to 8and 11). Two additional groups were formed forall Hispanic students with missing parent reportsof immigrant generation. These groups in rows 9and 10, which include some students who claimMexican ancestry, are differentiated by whetherstudents report that Spanish is their native lan-guage. Without making what might be regardedas an arbitrary allocation assumption, we cannotsort members of these two small groups into 1st,1.5th, or 2nd immigrant generations relative to



Table 1: Educational Attainment Patterns by Race-Ethnicity and Immigrant Generation

Proportion Proportion ProportionHigh School Ever Enrolled Bachelor’sCompleted Post-secondary Degree Raw Weightedon Time Education by 2012 N Percentage

1. Mexican, Mexican-American, 0.72 0.64 0.13 115 1.36or Chicano, 1st generation (0.04) (0.04) (0.03)

2. Mexican, Mexican-American, 0.76 0.71 0.14 78 0.97or Chicano, 1.5th generation (0.05) (0.05) (0.04)

3. Mexican, Mexican-American, 0.78 0.82 0.19 265 3.11or Chicano, 2nd generation (0.03) (0.02) (0.02)

4. Mexican, Mexican-American, 0.81 0.79 0.21 408 4.21or Chicano, 3rd+ generation (0.02) (0.02) (0.02)

5. Puerto Rican, Cuban, or Domini- 0.74 0.88 0.16 43 0.47can, 1st or 1.5th generation (0.07) (0.05) (0.06)

6. Puerto Rican, Cuban, or Domini- 0.79 0.87 0.31 84 0.75can, 2nd generation (0.04) (0.04) (0.05)

7. South and Central American, 0.85 0.89 0.23 84 0.761st or 1.5th generation (0.04) (0.03) (0.05)

8. South and Central American, 0.77 0.92 0.30 64 0.512nd generation (0.05) (0.03) (0.06)

9. Hispanic ethnicity of any type, 0.66 0.81 0.15 66 0.78generational status missing but (0.06) (0.05) (0.04)Spanish is the student’s nativelanguage

10. Hispanic ethnicity of any type, 0.67 0.73 0.15 88 0.92generational status missing but (0.05) (0.05) (0.04)Spanish is not the student’s nativelanguage

11. Hispanic ethnicity other than 0.81 0.86 0.19 151 1.35Mexican, Mexican-American or (0.03) (0.03) (0.03)Chicano, 3rd+ generation

12. Asian or NHOPI non-Hispanic, 0.94 0.94 0.48 407 1.611st or 1.5th generation (0.01) (0.01) (0.02)

13. Asian or NHOPI non-Hispanic, 0.92 0.93 0.54 565 2.242nd generation or generational (0.01) (0.01) (0.02)status missing but English is notthe student’s native language

14. Asian or NHOPI non-Hispanic, 0.86 0.81 0.42 243 1.343rd+ generation or generational (0.02) (0.03) (0.03)status missing but English isthe student’s native language

15. Black or African-American non- 0.89 0.95 0.34 156 1.42Hispanic 1st, 1.5th, 2nd generation (0.03) (0.02) (0.04)or generational status missing butEnglish is not the student’s nativelanguage

16. Black or African-American 0.83 0.82 0.20 1,335 13.81non-Hispanic, 3rd+ genera- (0.01) (0.01) (0.01)tion or generational statusmissing but English is thestudent’s native language

17. American Indian or Alaskan 0.79 0.72 0.18 219 2.45Native non-Hispanic, All (0.03) (0.03) (0.03)generations

18. White non-Hispanic, 1st, 1.5th, or 0.92 0.92 0.49 294 2.522nd generation or generational (0.02) (0.02) (0.03)status missing but English isnot the student’s native language

19. White non-Hispanic, 3rd+ 0.92 0.87 0.41 6,166 58.90generation or generational (< 0.01) (< 0.01) (0.01)status missing but English isthe student’s native language

20. Missing race, all generations 0.88 0.82 0.37 64 0.52(0.04) (0.05) (0.06)

Total 0.88 0.85 0.35 10,895 100.00

Notes: Standard errors in parentheses. Data are weighted by the panel weight constructed by the datadistributors (f2pnlwt), which adjusts for base-year nonparticipation and subsequent attrition, multiplied byan adjustment weight that we created to account for missing data on educational attainment.



the 3rd+ immigrant generation, which is oftenreferred to as “native.” Instead, we have decidedto focus on six groups that we can precisely defineand measure.5

We have selected two 3rd+ generation groupsfor comparison: white and black non-Hispanicstudents (groups 16 and 19). These two groupsrepresent alternative comparison groups for thesegmented assimilation literature, against whichthe incorporation of alternative immigrant groupsare evaluated. Black 3rd+ generation studentshave levels of bachelor’s degree receipt that areless than half as high as those of whites, withsimilar but less substantial differences in on-timehigh school graduation and overall rates of post-secondary enrollment of any type.

Now consider the four focal groups of stu-dents who claimed Mexican ancestry. Studentsin the broad and heterogeneous 3rd+ generationhave educational profiles very similar to the fo-cal comparison group of 3rd+ generation non-Hispanic blacks. Any variation between thesetwo groups (4 and 16) is consistent with samplingerror, as revealed by the standard errors reportedin parentheses. A prudent interpretation of 2ndgeneration Mexican immigrants is that they toohave patterns of educational attainment that areequivalent to the comparison group of black stu-dents, even though the point estimates of on-timehigh school graduation and bachelor’s degree re-ceipt are lower. Finally, 1st and 1.5th generationMexican immigrants have educational attainmentpatterns that suggest lower levels of attainmenton each of the three measures (although becausethese groups are smaller, sampling variation ismore of a concern, as reflected in the compara-tively large estimated standard errors).

Overall, all four groups of Mexican immi-grants as well as the non-Hispanic black com-parison group have lower levels of educational

5Nonetheless, we should note that both of these groupshave low levels of reported educational attainment thatare closer to those of 1st and 1.5th generation Mexicanimmigrants than to any other group of Hispanic students.Given that the majority of these two groups do in factclaim Mexican ancestry, it would be tempting to allocatethem across immigrant generations based on student re-ports of socioeconomic status. We have decided not todo so, in part because a later claim—that socioeconomicstatus is the most important predictor of between-grouppatterns of bachelor’s degree attainment—would be com-promised in the eyes of a fair critic by allocating in thisfashion.

attainment, and especially bachelor’s degree at-tainment, than the non-Hispanic white compari-son group. Before carrying on to directly modelbachelor’s degree attainment in the remainder ofthis article, we should note one additional patternin the table. Notice that for many comparisons byimmigrant generation within categories of race-ethnicity, recent immigrants attain higher levelsof education (e.g., groups 12 and 13 vs. 14, group15 vs. 16, and group 18 vs. 19). As shown byFarley and Alba (2002) and Crosnoe and Turley(2011; see also Crosnoe 2005, 2006), this patternis less pronounced for Mexican immigrants to theUnited States. And for Hispanic respondents tothe ELS, the pattern is found only for a compari-son of South and Central American immigrants(i.e., group 7 vs. 8). For both Mexican immi-grants and immigrants in the category of “PuertoRican, Cuban, or Dominican,” this pattern isreversed, although again sampling variation asso-ciated with the group estimates is substantial.

Models of Bachelor’s Degree

Attainment

For the remainder of this article, we focus on thereceipt of bachelor’s degrees. Group differencesare clearly demarcated at this level of educationalattainment, which is also a common life courseevent after which individuals destined for middle-class jobs enter the labor force. Our primaryquestion in this section is the following: can wepredict, based on observed characteristics mea-sured in high school, why the bachelor’s degreeattainment rate of Mexican immigrants lags therate of non-Hispanic whites and instead resemblesthe rate of non-Hispanic blacks?

Group differences in predictors. Table 2 pre-sents group differences in two sets of measuresthat the literature suggests determine subsequentpatterns of educational attainment, first behav-ioral commitment and engagement with schoolingand second forward-looking beliefs about tra-jectories through the educational system andinto occupations. The first three rows presentgroup-specific means of behavioral commitmentto schooling, reported separately by teachers, stu-dents, and parents at baseline data collection inthe 10th grade. Each of these scales is basedon underlying items, presented in Table 3, thatare then factor scored. Each scale is internally



Table 2: Commitment and Beliefs about the Educational Requirements of Expected Jobs for Six FocalGroups Defined by Race-Ethnicity and Immigrant Generation

Mexican Ancestry Black WhiteNon-Hisp. Non-Hisp.

Generation: 1st 1.5th 2nd 3rd+ 3rd+ 3rd+

Commitment (10th grade)Teacher-reported (12 indicators) �0.27 �0.29 �0.14 �0.30 �0.39 0.15Student-reported (13 indicators) 0.05 �0.26 �0.09 �0.34 �0.21 0.10Parent-reported (7 indicators) �0.28 �0.31 �0.20 �0.25 �0.32 0.13

Educational requirements ofexpected jobs(10th grade)

College or more 0.21 0.31 0.35 0.36 0.42 0.45High school or less 0.07 0.21 0.09 0.14 0.11 0.12High school and college 0.01 0.03 0.02 0.03 0.05 0.04Don’t know occupation 0.40 0.29 0.38 0.35 0.25 0.31Missing 0.32 0.16 0.16 0.12 0.18 0.08

Beliefs about the educationalrequirements of expected jobs(12th grade)

Certain and correctCollege or more 0.28 0.39 0.38 0.33 0.41 0.43High school or less 0.04 0.05 0.03 0.04 0.03 0.02

Uncertain but specificHigh school and college 0.02 0.05 < 0.01 0.03 0.03 0.02

UncertainDon’t know occupation 0.37 0.28 0.33 0.31 0.27 0.29

Certain but possibly incorrectExpected job requires a high 0.15 0.12 0.12 0.17 0.12 0.14school degree or less, but thestudent believed college isrequired

Expected job requires a college 0.05 0.07 0.09 0.10 0.11 0.08degree or more, but thestudent believed only a highschool degree is required

Missing 0.09 0.04 0.05 0.03 0.04 0.03

Unweighted N 115 78 265 408 1,335 6,166

Note: See Table 1.

consistent—with interitem estimated reliabilitiesof 0.77, 0.70, 0.79, respectively—and is scaled tohave a mean of 0 and standard deviation of 1 forthe full analytic sample.6

6The scales are substantially left skewed—teacher re-ported (min –3.5, max 1.7), student reported (min –3.5,max 1.7), and parent reported (min –7.4, max 0.6). Thescales are strongly related but sufficiently distinct to spec-ify separately. The pairwise product-moment correlationsare 0.48 for teacher–student, 0.45 for teacher–parent, and0.39 for student–parent.

Table 2 shows that all four groups of thosewho claim Mexican ancestry have levels of mea-sured commitment that are closer to the observedlevels of commitment of 3rd+ generation non-Hispanic blacks rather than 3rd+ generation non-Hispanic whites. This pattern is consistent withthe dissonant acculturation conjecture. In otherwords, the ELS does not provide direct measuresof the strength of available enclaves to which stu-dents have access, any apparent devaluation of



Table 3: Indicators of Commitment in the 10th Grade

Teacher reports of commitment (12 items with inter-item scale reliability of 0.77)Does this student usually work hard for good grades in your class? (English and Math Teacher)How often does this student complete homework assignments for your class? (English and Math Teacher)How often is this student attentive in class? (English and Math Teacher)Has this student fallen behind in school work? (English and Math Teacher)How often is this student absent from your class? (English and Math Teacher)How often is this student tardy to your class? (English and Math Teacher)

Student reports of commitment (12 items with inter-item scale reliability of 0.70)How many times did the following things happen to you in the first semester or term of this school year?

I was late for school.I cut or skipped class.I got in trouble for not following school rules.I was transferred to another school for disciplinary reasons.

How often do you spend time on the following activities outside of school?Visiting friends at a hangoutDriving or riding around

How much do you like school?How often do you come to class without these things?

Pencil/pen or paperBooksHomework done

How many times did the following things happen to you in the first semester or term of this school year?I was absent from school.I was put on in-school suspension.I was suspended or put on probation.

Parent reports of commitment (7 items with inter-item scale reliability of 0.79)Has your 10th grader ever been considered to have a behavior problem at school?Since your 10th grader’s school opened last fall, how many times have you or your spouse/partner

contacted the school about the following?Your 10th grader’s problem behavior in schoolYour 10th grader’s poor attendance record at schoolYour 10th grader’s poor performance in school

Since your 10th grader’s school opened last fall, how many times have you or your spouse/partnerbeen contacted by the school about the following?Your 10th grader’s problem behavior in schoolYour 10th grader’s poor attendance record at schoolYour 10th grader’s poor performance in school

Notes: Scale reliabilities are reported for the 10,895 individuals in the full sample presented in Table 1.

bilingualism, overt parent–child conflict, interestin deviance, and so forth. Yet, if the stipulatedmechanisms are at work, they will produce differ-ences in everyday behavior in school, as measuredby the commitment and engagement indicatorsavailable for the ELS. The reasoning for the link-age is suggested by Portes and Zhou (1993: 88)as follows:

Seeing their parents and grandpar-ents confined to humble menial jobsand increasingly aware of discrimina-

tion against them by the white main-stream, U.S.-born children of earlierMexican immigrants readily join a re-active subculture as a means of pro-tecting their sense of self-worth. Par-ticipation in this subculture then leadsto serious barriers to their chancesof upward mobility because schoolachievement is defined as antitheti-cal to ethnic solidarity. Like Haitianstudents at Edison High, newly ar-



rived Mexican students are at riskof being socialized into the same re-active stance, with the aggravatingfactor that it is other Mexicans, notnative-born strangers, who convey themessage.

Our measurement assumption is that studentsjoining a reactive subculture for which schoolachievement is antithetical to ethnic solidarityshould demonstrate less commitment to behaviorsthat promote short-term school achievement andlong-term educational attainment. The observedcommitment differences in Table 2, which aretypically between one-quarter and one-half of astandard deviation, follow the pattern implied bythe dissonant acculturation prediction.7

Table 2 also shows that all four groups ofthose who claim Mexican ancestry were less likelythan 3rd+ generation non-Hispanic whites andblacks to list verbatim occupational plans thatincluded only jobs that typically required col-lege degrees. With the exception of 1.5th genera-tion immigrants, they were also more likely thanwhites and blacks to offer a response of “Don’tknow” to the occupational plans prompt. Thesedifferences are again present in the 12th grade,perhaps strengthening very slightly.

Overall, the patterns presented in Table 2 areconsistent with possible dissonant acculturation.Regardless of their source, the patterns suggestconcern that the trajectory toward lower levelsof postsecondary attainment among those whoclaim Mexican ancestry, as shown in Table 1, waswell developed already in high school. Whetherthese differences have been shaped by a “reactivestance” that is embedded in more general patternsof dissonant acculturation cannot be determinedwith these data.

Table 4 presents group differences in an al-ternative set of potential causes that are, con-ceptually at least, distinct from those that arepurported to generate dissonant acculturation:family structure and socioeconomic status. Herethe pattern is stark, and the comparison to both3rd+ generation non-Hispanic whites and non-

7The CILS data set that has been analyzed heavily byproponents of the segmented assimilation prediction doesnot contain such measures; the CILS survey instrumentwas not focused on direct measures of school outcomesand did not include a teacher questionnaire.

Hispanic blacks is more complex. First, respon-dents who claim Mexican ancestry are more likelythan non-Hispanic blacks to be living in familieswith two parents, although 3rd+ generation Mex-ican immigrants have rates of “mother-only” par-enthood that are higher than for non-Hispanicwhites. Second, for family income, 1st, 1.5th,and 2nd generation Mexican immigrants havesubstantially lower family income than all 3rd+generation groups. Among these latter groups,3rd+ generation Mexicans have higher family in-come than non-Hispanic blacks but still have sub-stantially lower family income than non-Hispanicwhites. Third, all four groups of those who claimMexican ancestry have lower average levels ofparental education, with the average education of1st, 1.5th, and 2nd generation Mexicans between1.5 to 2 years lower than that of the other threegroups. Fourth, these differences in family in-come and parental education are then reflected inthe Socioeconomic Index (SEI) scores of parents’occupations, with, for example, 3rd+ generationMexican immigrants having higher levels of occu-pational attainment than all but 3rd+ generationnon-Hispanic whites.

Taken together, the family background dif-ferences presented in Table 4 suggest that thegroup differences in bachelor’s degree attainmentreported in Table 1 may reflect a more basicnarrative of socioeconomic disadvantage, ratherthan or in addition to an alternative mechanismof dissonant acculturation. To assess the relativepredictive power of the differences presented inTables 2 and 4, we must offer models that assessthe capacity of these characteristics of studentsand their families to account for patterns of bach-elor’s degree attainment. Before we do so, wemust be clear about our aims. We assume thatour estimates are generated by causal effects, butthese are not causal effects that we can directlyestimate. Instead, our models attempt to discernthe trace of such effects in estimated associationsone or two steps removed from the genuine prefer-ences and choices of individuals, as structured byopportunities and cost constraints. Our readingof the extant literature on segmented assimilationis that all empirical research should be regardedas equally (or more limited) than what we canoffer here. Too few of the quantitatively orientedpieces in this tradition have conceded these limi-tations.



Table 4: Family Background Measures for the Six Focal Groups

Mexican Mexican Mexican Mexican Black, White,Ancestry Ancestry Ancestry Ancestry Non-Hisp. Non-Hisp.1st Gen. 1.5th Gen. 2nd Gen. 3rd+ Gen. 3rd+ Gen. 3rd+ Gen.

Family structureLiving with two parents 0.73 0.75 0.82 0.69 0.50 0.80Mother only 0.19 0.16 0.15 0.23 0.43 0.15Father only 0.03 0.05 0.03 0.03 0.02 0.03Other 0.01 0.02 0.00 0.01 0.02 0.01

Socioeconomic statusFamily income (10th grade) 30,820 23,970 35,600 48,910 42,160 69,520Mother’s education (years) 11.5 11.0 11.3 13.0 13.4 13.9Father’s education (years) 11.6 11.4 11.7 13.0 13.3 14.1Mother’s occupation (SEI) 34.9 34.0 37.7 44.2 43.1 47.2Father’s occupation (SEI) 35.8 36.7 37.7 42.4 41.7 46.2

Unweighted N 115 78 265 408 1,335 6,166

Note: See Table 1.

With this caveat clearly stated, we carry on toestimate logit models of bachelor’s degree receipt,using alternative prediction sets. To simplifymodel specification by eliminating groups not ofcentral interest, we narrow the estimation sampleto the 8,367 students who are members of the sixfocal groups placed in boldface type in Table 1and subsequently examined in Tables 2 and 4.

Table 5 reports predicted rates of bachelor’sdegree attainment (with standard errors), calcu-lated from five logit models with different setsof predictors. Fit statistics for the underlyingmodels are provided at the bottom of each col-umn, and full sets of parameter estimates for eachmodel are offered in Supplementary Appendix Ta-bles S2 and S3.

Unadjusted rates. For model 1, bachelor’s de-gree attainment was regressed on five indicatorvariables for group, one main effect for gender,and five cross-product interactions between groupand gender. The group estimates reported in thefirst column of Table 5 are standardized to thegender composition of non-Hispanic whites forconsistency with subsequent models. Given thatgender varies only with group because of sam-pling variability (as well as some very small dif-ferences that may be attributable to patterns ofhigh school dropout before the sophomore year),we consider these estimates as our baseline un-adjusted group estimates of the proportions ofstudents who obtain bachelor’s degrees. They

are almost exactly equivalent to the nonparamet-ric, unstandardized rates presented in the thirdcolumn of Table 1.8

Rates adjusted by indirect measures of disso-nant acculturation. For model 2, we added thethree commitment scales to the set of predictors.The likelihood ratio statistic summarized at thebottom of the second column indicates that, for aloss of three degrees of freedom, the change in thelog-likelihood between models 1 and 2 is large.The sample-size-scaled and parameter-penalizedBayesian Information Criterion (BIC) values alsoclearly favor model 2 relative to model 1.

The values in the six rows of the second col-umn are properly interpreted as adjusted grouprates of bachelor’s degree receipt, calculated ina targeted way. Each rate is standardized to themarginal distribution of commitment that char-acterizes 3rd+ generation non-Hispanic whites,which is an appropriate reference group when an-alyzing modal patterns of educational attainmentand considering the segmented assimilation pre-diction. Accordingly, each value is an estimatedrate that, according to the parameters of the un-derlying estimated model, would be observed if

8The logit coefficients presented in Table S2 indicatethat young men of all groups are less likely to obtainbachelor’s degrees and that this effect is larger for allgroups of students who claim Mexican ancestry. We willnot focus on this gender difference in this article and will,hereafter, continue to marginalize over the distribution ofgender without comment.



Table 5: Unadjusted and Adjusted Proportions of Students Enrolled in the 10th Grade in 2002 WhoObtained a Bachelor’s Degree by 2012, Where the Adjustments Are Standardized to the Distributionsthat Characterize 3rd+ Generation Non-Hispanic Whites

(1) (2) (3) (4) (5)

Mexican ancestry1st generation immigrant 0.12 0.19 0.14 0.15 0.21

(0.02) (0.03) (0.03) (0.03) (0.08)1.5th generation immigrant 0.13 0.19 0.14 0.14 0.50

(0.04) (0.05) (0.04) (0.04) (0.12)2nd generation immigrant 0.19 0.24 0.20 0.20 0.39

(0.03) (0.03) (0.03) (0.03) (0.05)3rd+ generation immigrant 0.21 0.29 0.22 0.23 0.30

(0.03) (0.03) (0.03) (0.02) (0.03)

Black, non-Hispanic3rd+ generation immigrant 0.20 0.31 0.20 0.21 0.27

(0.01) (0.02) (0.01) (0.01) (0.02)

White, non-Hispanic3rd+ generation immigrant 0.41 0.41 0.41 0.41 0.41

(0.01) (.01) (0.01) (0.01) (0.01)

Adjustment variablesCommitment (10th grade) XEducational requirements of expectedjob (10th grade) XBeliefs about requirements of expectedjob (12th grade) XSocioeconomic status and family structure XLikelihood ratio test

Model for comparison Intercept Model 1 Model 1 Model 1 Model 1only

�2 statistic for change in log-likelihood 127,983 439,186 66,554 279,319 375,987Change in degrees of freedom 11 3 4 6 36p-value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001BIC 3,075,819 2,636,660 3,009,301 2,796,554 2,700,157

Notes: See Table 1. All models include regressors for gender and gender-by-group interactions, as discussedin the main text.

all groups had the same distribution of commit-ment as 3rd+ generation non-Hispanic whites.9For this reason, the adjustment has no effect onthe rate for 3rd+ generation non-Hispanic whites,

9For comparison, adjusted group estimates from thesame five models are offered in the Supplementary Ap-pendix with alternative choices of reference distributionsof the predictors. The adjusted group differences aremarginalized to the pooled distribution of predictorsacross all six groups in Table S5 and then to the dis-tribution of predictors that characterize 2nd generationMexicans in Table S6.

which remains at 0.41. The rates for all othergroups move closer to this value because of theadjustment.

Model 2 suggests that the unadjusted groupdifferences estimated by model 1 would narrowsomewhat if all groups were given the same com-mitment levels.10 For the most crucial compar-

10Models that represent commitment as 32 separatepredictor variables in an alternative to model 2 yieldednearly identical adjusted group estimates of 0.18, 0.19,0.24, 0.29, 0.31, and 0.41 reading from top to bottom (and



ison, the gap between the rates of 2nd genera-tion Mexicans and 3rd+ generation non-Hispanicwhites would narrow by 27 percent (by a raw 6percentage points from 0.22 to 0.16). Other dif-ferences decline similarly, with the gap shrinkingby 24 percent and 21 percent, respectively, for1st and 1.5th generation Mexicans.

The decline is more substantial for 3rd+ gen-eration Mexicans, with the difference of 0.20 de-creasing to 0.12, which is a 40 percent decline.Again, it is hard to interpret mean values of anytype for this very heterogeneous group of 3rd+generation Mexicans (and which, as a result, hasan unclear position in debates over the dissonantacculturation mechanism). Still, it is notablethat the pattern observed for this group is verysimilar to the pattern for 3rd+ generation non-Hispanic blacks. In addition to the similarityof their unadjusted rates of bachelor’s degree re-ceipt, which are 0.21 and 0.20, the adjustmentfor commitment increases their estimated ratessimilarly to 0.29 and 0.31 (but with the increaseslightly larger for non-Hispanic blacks, at leastas judged by the point estimates).

Models 3 and 4 offer alternative adjustments,first for the educational requirements of expectedjobs reported in the 10th grade and second forbeliefs about the educational requirements of ex-pected jobs reported in the 12th grade. As withmodel 2, these adjustment variables predict bach-elor’s degree receipt, as reflected in the likelihoodratio tests and the improved fits summarized byBIC values for models 3 and 4 in comparison tomodel 1. However, the adjusted group differencesreported in the first six rows are only very slightlysmaller in comparison to the unadjusted differ-ences from the baseline model 1, decreasing bybetween 0.01 and 0.03 for all four of the groupsthat claim Mexican ancestry.

Taken together, models 2 through 4 suggestthat the group differences summarized in Table2 that are consistent with the dissonant accul-turation conjecture explain only a modest pro-portion of group differences for 1st, 1.5th, and2nd generation Mexican immigrants. However,for 3rd+ generation Mexicans, commitment is a

with corresponding standard errors equal through the sec-ond decimal place). The BIC value favored the elaboratemodel, but we see no compelling rationale for heedingit (given the near-invariance of the group estimates andthe value of having interpretable dimensions and shortertables in the Supplementary Appendix).

more substantial predictor, narrowing the gap by40 percent. Note, furthermore, that these changesin adjusted rates are upper-bound estimates ofthe extent to which the adjustment variables canaccount for group differences in bachelor’s degreereceipt. From a variety of theoretical perspectives,it would be reasonable to argue that an analysisof how these variables narrow group differencesshould be undertaken only after first adjustingfor differences in family background. We exploresuch models later; for now, we allow these indi-rect measures of dissonant acculturation to havetheir largest possible effects on attainment rates.

One could argue, and we would expect noless from proponents of segmented assimilationpredictions, that the ELS measures deployed foradjustment in models 2 through 4 are too indirectto inform the prediction. Although not an unrea-sonable position, this is not our position. Moresupportive of the conjecture, we believe, wouldbe an argument based on the pattern observedfor 3rd+ generation Mexicans when an adjust-ment for commitment is offered. This patterndoes provide some support for the segmentedassimilation prediction if this group is declaredrelevant for the dissonant acculturation mecha-nism. Furthermore, it must be conceded thatany such support is “behind the backs” of thesestudents, because models 3 and 4 show that ad-justments for students’ own expected trajectoriesthrough the educational system and into occupa-tions can account for only a very small portion ofthe gap between 3rd+ generation Mexicans and3rd+ generation non-Hispanic whites.

Rates adjusted by measures of family back-ground. Model 5 offers rates adjusted by familystructure and socioeconomic status. These es-timates suggest that differences in family back-ground can account for a large portion of unad-justed group differences for 1.5th and 2nd gener-ation Mexicans, and about the same amount ascommitment for 1st and 3rd+ generation Mexi-cans. In particular, when all groups are given thefamily background distributions of 3rd+ genera-tion whites, the gap observed for 2nd generationMexicans narrows, in a comparison of model 1 tomodel 5, from 0.22 to 0.02. The gap estimated for1.5th generation Mexican immigrants reverses di-rection from 0.28 to –0.09 (although the standarderror for the adjusted rate for the 1.5th gener-ation is comparatively large in model 5). The



decline in the gap for 1st generation Mexican im-migrants is less substantial, moving from 0.29 to0.20 (but now the standard error is large, mak-ing it difficult to assess the size of the remainingadjusted difference). The gap for 3rd+ genera-tion Mexicans declines slightly more in responseto an adjustment for family background thanan adjustment for commitment, declining from0.20 to 0.11 rather than 0.13. Overall, familybackground always explains more for each groupthan does commitment, and a great deal morefor the crucial groups of 1.5th and 2nd generationMexicans.

Before carrying on to subsequent analysis andinterpretation, we should explain the specificationchoice for model 5, which represents family struc-ture and socioeconomic status with regressorsthat collectively absorb 36 degrees of freedom.In the course of analysis, we first decided thatbecause of the sample size, we needed to reducethe parameterization of family structure to a sin-gle indicator variable for “mother-only” family.We then fit a model that constrained the con-ditional associations between the variables forfamily background and bachelor’s degree attain-ment to be the same across all six groups. Wethen reestimated the model, allowing these asso-ciations to vary by group. Model 5 in Table 5 isbased on the latter unconstrained specification,which we favored for two reasons.

First, according to the fit statistics, the inter-actions were justified by a likelihood ratio test,with a chi squared test statistic of 12,570 and fora difference of 30 degrees of freedom. Given thelarge sample size, we used a BIC value compar-ison, which yielded the same conclusion (basedon a decline from 2,712,456 to 2,700,157 for theunconstrained model). Nonetheless, as shownby a comparison of models 5-C in Table S2 andmodel 5 in Table S3, most of the interactions arenonsignificant by conventional standards. Thisis a combined result of the small cell sizes forsome of these groups but also the well-knownconsequence of fitting parameters across manydimensions that are related to each other. Thedata do not contain sufficient numbers of unusualcombinations of students in each group to pre-cisely estimate all of the conditional associationsfor the six family background variables.

Second, the direction of the coefficients forthe interactions aligned with concerns often ex-

pressed in this literature and could not be dis-counted based on substantive size. Althoughthe coefficients for the interactions of group withmother’s occupation and father’s occupation werevery small, the coefficients for the interactionsbetween group and the other four main effectswere not. For example, net of all else, being ina “mother-only” family had a negative associa-tion with bachelor’s degree attainment for 3rd+generation African American students but a netpositive association for both 2nd and 3rd+ gener-ation Mexican students.11 The net associationsof parental education with bachelor’s degree at-tainment were slightly smaller for 1st, 1.5th, and2nd generation Mexican immigrants, sometimesfor mother’s education and sometimes for father’seducation. At the same time, the net associationsof logged family income with bachelor’s degreeattainment were largest for 2nd and 3rd+ genera-tion Mexican immigrants.

Although one should be careful in trying tointerpret conditional associations when they areso heavily parameterized and the cell sizes for thegroups are small, the point estimates for thesecoefficients are consistent with ad hoc interpre-tations of the challenges of using socioeconomicstatus to adjust for differences between groupssuch as these. In particular, it is not surprisingthat the relevance of educational certification,often received in the “home” country, is less pre-dictive of outcomes of all types in the UnitedStates. In addition, family income may be espe-cially predictive of bachelor’s degree receipt forimmigrant families that must pay college tuitionfrom current income, having comparatively lowerstocks of wealth to borrow against and, perhaps,fewer kin with resources to help defray costs. As-suming that coefficients for parents’ educationand family income are invariant by group wouldsuppress narratives of this sort, opening up ouradjusted estimates to the claim that adjustmentfor these variables has generated misleading esti-mates of group differences.12

11“Mother-only” family had a zero net association, orthe statistical equivalent thereof, because of impreciseestimation, for all other groups. These associations, how-ever, are net of simultaneous within-group adjustmentsfor mother’s level of education and family income.

12This concern notwithstanding, the overall conse-quence of adopting the unconstrained specification is notconsequential for the main interpretations and conclusions.For the constrained model (model 5-C in Table S2), the



The overall implication of model 5 is that fam-ily background is a strong predictor of bachelor’sdegree receipt, which is consistent with abundantextant research. Even when allowed to have dif-ferential associations across groups, family back-ground can account for large portions, and per-haps all, of the gaps in attainment observed for1.5th and 2nd generation Mexican students. Theprecise mechanisms by which differences in familybackground produce differences in bachelor’s de-gree attainment are not revealed by the analysisreported in Table 5. The literature on collegeentry and persistence suggests many mechanisms,and three are especially important to note now.First, the children of recent Mexican immigrantsare more likely to have attended K to 12 schoolsthat did not adequately prepare them for post-secondary education. Abundant research showsthat the mean of parental socioeconomic statusis strongly related to all observed measures ofquality across schools, even after adjustments fordifferences in the racial and ethnic compositionof schools. There is no basis for arguing that thechildren of recent immigrants are exempt fromthis broad pattern of educational opportunity inthe United States. Second, the children of re-cent Mexican immigrants are more likely to haveparents who are resource constrained and cannotprovide college tuition assistance comparable towhat the parents of non-Hispanic whites can, onaverage, furnish. Third, parents without collegedegrees have less information and fewer personalexperiences that enable them to effectively guidetheir children into and through postsecondaryeducational institutions. Table 4 shows that theparents of ELS students we have coded as 1st,1.5th, and 2nd generation Mexicans have the low-est levels of parental education and, furthermore,have comparatively little experience with highereducation in the United States.

Extended Results for Models of

Bachelor’s Degree Attainment

In this section, we offer three additional piecesof analysis. First, we consider an alternative

adjusted rates would be slightly higher for the 1st gen-eration (0.32 instead of 0.21), the 2nd generation (0.40instead of 0.39), and 3rd+ generation blacks (0.29 insteadof 0.27). The adjusted rates would be slightly lower forthe 1.5th generation (0.35 instead of 0.50) and the samefor 3rd+ generation Mexicans (0.30).

set of measurement assumptions, substitutingeducational expectations for our measures of oc-cupational plans. Second, we consider modelsthat simultaneously adjust for the covariates inmodels 2 through 5 as well as additional predic-tors. Third, we consider predictive simulationsthat assess the sensitivity of our conclusions tothe possibility that a disproportionate number ofstudents who claim Mexican ancestry droppedout of the sample before the 2002 base-year datacollection.

Alternative models that adjust for educationalexpectations. Here we place the foregoing set ofmodels and interpretations in the context of theoriginal literature on the segmented assimilationprediction, where some related measures are usedin quite different ways. To ground this discus-sion, consider first the group means reported inTable 6 for educational expectations in the 10thand 12th grades. Consistent with group differ-ences in our coding of occupational plans as theeducational requirements of expected jobs, stu-dents who claim Mexican ancestry are less likelyto report that they expect to obtain bachelor’sdegrees. They are more likely to expect lowerlevels of education and to express uncertainty byselecting the response option of “Don’t know.”

Yet, all students are very optimistic abouttheir likelihood of obtaining bachelor’s degrees,relative to subsequent outcomes (see Table 1).The educational expectations of students declinesubstantially between the 10th and 12th grades,reflecting greater realism about likely trajectories.But, even in the spring of what is typically senioryear for these respondents, many more studentsstill expect to obtain bachelor’s degrees than will.We interpret these patterns as consistent with theposition that reported educational expectationsare now contaminated by a pervasive “collegefor all” culture that has dominated secondaryschooling in the United States since the early1990s. At the time the Wisconsin model was de-veloped (see Sewell et al. 1979; Haller and Portes1973) and these measures became widely used insocial science research, educational aspirationsand expectations were not subject to this up-ward response bias, which reflects a type of socialdesirability context effect on survey responses.

To motivate the alternative models that wepresent in this section, we need to briefly recon-sider how proponents of the segmented assimila-



Table 6: Educational Expectations for the Six Focal Groups

Mexican Mexican Mexican Mexican Black, White,Ancestry Ancestry Ancestry Ancestry Non-Hisp. Non-Hisp.1st Gen. 1.5th Gen. 2nd Gen. 3rd+ Gen. 3rd+ Gen. 3rd+ Gen.

Educational expectations,10th gradeBachelor’s degree or higher 0.62 0.66 0.63 0.62 0.72 0.74Some college 0.08 0.13 0.13 0.14 0.11 0.10High school diploma or lower 0.12 0.08 0.12 0.13 0.09 0.07Don’t know 0.18 0.13 0.12 0.11 0.08 0.09

Educational expectations,12th gradeBachelor’s degree or higher 0.42 0.49 0.53 0.53 0.62 0.68Some college 0.26 0.30 0.26 0.24 0.19 0.19High school diploma or lower 0.14 0.11 0.08 0.07 0.08 0.05Don’t know 0.18 0.10 0.13 0.15 0.11 0.08

Unweighted N 115 78 265 408 1,335 6,166

Note: See Table 1.

tion literature have used variables for educationalaspirations and expectations. A good startingpoint is the overview piece of Haller and Portes(1973: 68), in particular the key passage wherethey summarize the rationale for the central roleof aspirations in the Wisconsin model of statusattainment:

It is the last set of variables [educa-tional and occupational aspirations]which constitutes the strategic centerof the model. Aspirations mediatemost of the influence of antecedentfactors on status attainment. Evenwhen educational attainment is takeninto account, occupational aspirationsstill exercise a significant direct effecton occupational attainment.The execution of occupational andeducational aspirations appears to bea central process in early adult sta-tus attainment, not only because itrepresents a clear expressive orienta-tion toward desirable goals but alsobecause it is likely to involve a realis-tic appraisal of possibilities conveyedto ego by significant others and hisown self-evaluations. The hypothe-sized impact of aspirations on statusattainment does not mean that all or

most specific goals must be fulfilledbut, more generally, that initial plansset limits to the range where even-tual attainment levels are likely to befound.

Many of the core features of this older argumentwere adopted by Portes and Rumbaut (2001),even while the segmented assimilation conjec-ture was elaborated with ideas drawn from theliterature on oppositional culture that was inascendance in the 1990s.13

Consider first the survey instruments for theCILS, on which the primary results of Portes andRumbaut (2001) are based (as well as some ofthe early results in Portes and Zhou [1993]). Forthe 1991 CILS base-year student questionnaire,educational and occupational aspirations wereelicited with a variety of questions, the first three

13There are important pieces that link these traditionsas well, perhaps most important being Portes, McLeod,and Parker (1978), which offered a comparison of the edu-cational, occupational, and income aspirations of Mexicanand Cuban adult immigrants, sampled at ports of entry.Portes et al. (1978) concluded that occupational aspira-tions are modest and rational and that many of the typicalstatus attainment characteristics have the expected as-sociations with elicited aspirations. Past education andoccupation were the strongest determinants of the occupa-tional aspirations of Mexican immigrants, with mother’slevel of education following next. Feliciano (2006) offers asimilar result for the educational expectations of childrenof immigrants who participated in the CILS.



of which were as follows: (1) “What is the highestlevel of education you would like to achieve?” (2)“And realistically speaking, what is the highestlevel of education that you think you will get?”and (3) “What job would you like to have asan adult? (Please write clearly).” The follow-up questionnaire for the CILS included similarquestions, often exact replicates (see Portes andRumbaut 2001, Appendix A). Similarly, the par-ent questionnaire of the CILS elicited status at-tainment predictors, including the aspirations ofparents for students.14

It is notable that occupational aspirations re-ceived very little attention in any of the corepieces that proposed the segmented assimilationprediction, even though they were measured bythe CILS.15 Yet the data were analyzed, and onecan find small references to some of their pat-terning. Portes and Zhou (1993, Table 2) reporthigh levels of occupational aspirations for thegroups they analyze from the Florida componentof the CILS, which does not include those whoclaim Mexican ancestry. Portes and Rumbaut(2001:219) indicate that, in results “not shown,”18 percent of all CILS respondents aspired to

14Beyond these status attainment items, the CILS alsocollected extensive information on immigration histories,patterns of language usage, social psychological indica-tors of depression and self-esteem, as well as attitudestoward bilingualism, attitudes about other features of theassimilation process, and attitudes about the opportunitystructure of the United States. Similar attitudinal itemson the parent questionnaire then allowed for measures ofparent-child agreement on these attitudes. The CILS didnot, however, measure everyday commitment to school-ing, nor did it have a teacher component like the ELS.In fact, it is remarkably devoid of measures that wouldallow one to directly model oppositional modes of behav-ior that are consistent with the dissonant acculturationthat is purported to be unfolding in adolescence and earlyadulthood.

15One exception is Feliciano and Rumbaut (2005), whichoffers models of occupational expectations for the SanDiego portion of the third wave of the CILS. They showthat young women who are identified as the childrenof Mexican immigrants have lower expectations, net ofsocioeconomic status and schooling (although these arethe occupational expectations of 24–25 year-olds, lookingforward to expected occupations at age 30). Movingbeyond the CILS, Portes et al. (2010) align their analysisof immigrant generational effects in Spain squarely withthe status attainment tradition, offering a figure (see page768) that includes a latent “ambition” variable. Theylater use occupational-prestige-type PRESCA scores toscale occupational aspirations, which is very similar tothe original Level of Occupational Aspiration concept andSEI-scored operationalization of the Wisconsin model.

be physicians but that young women were morelikely to be found among aspiring physicians“across almost all nationalities.”

Although attention to occupational aspira-tions is scarce, educational aspirations and expec-tations feature prominently, usually motivateddirectly by status attainment research. For exam-ple, Portes and Rumbaut (2001:226) write that“in modeling determinants of educational aspira-tions and expectations, we follow past theories ofthe status attainment process.” At the conclusionof their analysis, they conclude that “the bearingof the history and negative modes of incorpora-tion of Mexican immigrants on the adaptationof their young is evident in these findings where,independent of other factors, Mexican origin re-duces educational aspirations and expectations byalmost 10 percent” (Portes and Rumbaut 2001).We read this conclusion as a direct claim that neg-ative modes of incorporation, which are a sourceof dissonant acculturation, decrease educationalaspirations and expectations.16 These declinesare then accentuated by patterns of interaction inschools, where a generalized oppositional cultureto school achievement emerges, as first articu-lated in Portes and Zhou (1993:88) for Mexicanimmigrants as a “reactive stance.”

Our perspective on the origins and measure-ment features of the analysis of Portes and Rum-baut (2001) suggests a reasonable objection to ourresults: we have ignored a measure of ambitionthat the originators of the segmented assimilationprediction would insist be in the foreground. Weagree that we have indeed done this for the mod-els reported in Table 5, but our goal was not at alldriven by a desire to invalidate the segmented as-similation prediction. Rather, for reasons statedwhen presenting models 2 through 5, and fordeeper theoretical reasons detailed in Morganet al. (2013a, 2013b), we think any decision toyoke a set of models of educational attainmentto status attainment predictors conceptualizedin the 1960s is a poor analysis choice, especiallywhen direct measures of commitment and every-day engagement with schooling are now available.Even so, we should also note that we do not en-tirely discount models of forward-looking beliefselicited in high school but rather that we favor

16It is also notable that the ten percent difference high-lighted in this claim is consistent with what we observedfor the ELS in 2002 and 2004 (see Table 6).



ones that represent uncertainty and that are tiedto forecasts about labor market position whichthemselves imply specific educational trajecto-ries. These measures, we maintain, are far lessafflicted by social desirability bias attributable tothe “college for all” ethos of secondary schoolingin the United States.

Still, what would happen if we were to fullyembrace a status attainment rationale for usingeducational expectations as a realistic measureof ambition that, through adaptation to negativemodes of incorporation, generates dissonant ac-culturation? Doing so would bring the designof our analysis into closer alignment with thatof Portes and Rumbaut (2001), but additionalresults show that our conclusions from the lastsection would remain unaltered:

1. If we were to substitute into model 3 the ed-ucational expectations variable in the 10thgrade (see Table 6 for categories) insteadof our variable for the educational require-ments of students’ expected jobs, the corre-sponding adjusted rates reported in Table5 would be 0.14, 0.14, 0.21, 0.25, 0.21, and0.41 rather than 0.14, 0.14, 0.20, 0.22, 0.20,and 0.41.

2. If we were to then substitute into model 4the educational expectations variable in the12th grade instead of our variable for be-liefs about the educational requirements ofstudents’ expected jobs, the correspondingadjusted rates reported in Table 5 would be0.14, 0.14, 0.22, 0.25, 0.21, and 0.41 ratherthan 0.15, 0.14, 0.21, 0.23, 0.21, and 0.41.

In other words, our measures of the educationalrequirements of expected jobs capture the same,quite low, capacity of forward-looking beliefs toaccount for the group differences of interest. Wedo not believe, therefore, that our decision to usean alternative measure of forward-looking beliefsis consequential for our main conclusions, eventhough they generate a mismatch with how theoriginators of the segmented assimilation predic-tion operationalized forward-looking beliefs.

Additional models with simultaneous adjust-ment. To show how simultaneous adjustmentdoes not change our main conclusions, we offertwo final models in Table 7. Model 6 adds the ad-justment variables from models 2 through 4 to the

family background variables specified for model 5.The fit statistics, now for a comparison of model6 to model 5, indicate that these variables aresubstantial predictors of bachelor’s degree attain-ment, net of simultaneous adjustment for familybackground. Forcing the distributions for the pre-dictors in model 6 for all groups to be the sameas the observed distributions for 3rd+ generationnon-Hispanic whites, we obtain some further nar-rowing of the gaps of interest in adjusted ratesof bachelor’s degree attainment.

Model 7 is then a “kitchen sink” model thatadds to the variables specified for model 6 theeducational expectations variables presented inTable 6 along with four measures of high schoolacademic achievement. Group differences in thesemeasures of academic achievement follow expectedpatterns (and are presented in SupplementaryAppendix Table S4). They are ordered consis-tently across measure by year and in the samepattern as socioeconomic status. Non-Hispanic3rd+ generation whites have the highest levels ofachievement, followed by 3rd+ generation Mexi-cans, 3rd+ generation non-Hispanic blacks, 2ndgeneration Mexicans, 1.5th generation Mexicans,and, finally, 1st generation Mexicans. We in-terpret these differences as consistent with thenarratives offered for the effects of socioeconomicstatus on bachelor’s degree receipt, supplementedby two additional rich literatures on K to 12 edu-cation in the United States: (1) how the home en-vironment structures achievement in elementaryand secondary schooling and (2) how differencesin school quality tend to reproduce, rather thanmoderate, these differences.17

For model 7 in Table 7, the additional 10parameters further improve the model fit, as in-dicated by the likelihood ratio test and the BICvalues for the comparison of model 7 to model 6.If we again impose the observed distributions ofthe predictors that characterize 3rd+ generationnon-Hispanic whites, we can produce a new setof adjusted rates of bachelor’s degree attainmentthat differ little across groups. The point esti-mates of these adjusted rates continue to vary

17We also believe, consistent with Morgan et al. (2013a,2013b), that these performance levels are endogenouswith respect to beliefs about likely trajectories throughthe educational system, as picked up by our measures ofthe educational requirements of expected jobs. Any sucheffects may be small relative to those that flow from themechanisms mentioned in the main text.



Table 7: Additional Adjusted Proportions for Bachelor’s Degree Receipt by 2012

(6) (7)

Mexican ancestry1st generation immigrant 0.27 0.36

(0.10) (0.10)1.5th generation immigrant 0.48 0.55

(0.08) (0.07)2nd generation immigrant 0.43 0.43

(0.04) (0.04)3rd+ generation immigrant 0.36 0.40

(0.03) (0.02)

Black, non-Hispanic3rd+ generation immigrant 0.36 0.43

(0.02) (0.02)

White, non-Hispanic3rd+ generation immigrant 0.41 0.41

(0.01) (0.01)

Adjustment variablesCommitment (10th grade) X XEducational requirements of expected job (10th grade) X XBeliefs about requirements of expected job (12th grade) X XSocioeconomic status and family structure X XEducational expectations (10th grade and 12th grade) XReading test (10th grade) XMath test (10th and 12th grade) XCumulative GPA XLikelihood ratio test

Model for comparison Model 5 Model 6�2 statistic for change in log-likelihood 456,168 312,297Change in degrees of freedom 13 10p-value < 0.001 < 0.001BIC 2,244,107 1,931,900

Note: See Table 1.

slightly, but the level of variation is consistentwith sampling error.

The tougher question is how to interpret theadjusted rates from model 7, given the lack ofconsensus in this literature on which variablescan be interpreted as baseline confounders, whichvariables can be interpreted as measures of factorswithin causal mechanisms, and which variablesare neither of these two. Our decisions on thesematters are the following. Models 2 through 5convey what is our major conclusion: socioeco-nomic status alone can account for large portionsof unadjusted group differences. Model 6 is aninteresting model because, as we show in the nextsection, it can be a basis for evaluating alterna-

tive predictions that may be more consistent withthe dissonant acculturation conjecture. Model 7,however, is of less interpretive value for models ofbachelor’s degree attainment because of the ex-tent to which performance in the final two years ofhigh school strongly reflects realistic anticipationof bachelor’s degree attainment itself.

Predictive simulations and sensitivity of re-sults. We recognize that some readers will regardour embrace of model 5, and the conclusion thatsocioeconomic status can account for most groupdifferences, as incomplete (and perhaps even self-serving). We have one nontypical defense to offer.We concede that we had hoped that the mea-sures of forward-looking beliefs and commitment



that we showed were predictive in Morgan et al.(2013a, 2013b) would show their mettle in thiscontext too, lending support to the segmentedassimilation prediction that many scholars hadgood reason to doubt. Instead, while they are pre-dictive and in the same pattern as expected (seethe coefficients in Tables S2 and S3), only com-mitment appears to account for any substantialportion of the between-group differences. Givenour expectations, we were genuinely surprised bythis result.

Nonetheless, it is worthwhile to consider setsof alternative analysis assumptions that can givethese predictors more capacity to account forbetween-group differences. To show what wemean, consider model 6, which we regard as areasonable model between what we favor (model5) and the model that we regard as overfit (model7). For model 6, family structure, socioeconomicstatus, commitment, and the educational require-ments of expected jobs, as well as beliefs aboutthem, are all given a chance to account for groupdifferences in receipt of bachelor’s degrees.

Table 8 presents a set of adjusted group ratesthat we characterize as predictive simulationsbecause most are entirely synthetic (i.e., basedon combinations of distributions that are not ob-served for any real groups of ELS respondents).If we had confidence that our model 6 identi-fied specific causal effects, we would have labeledthese simulations “counterfactual.” Instead, wesee these simulations as an alternative way ofexploring patterns in the results, providing a firstapproximation to genuine what-if scenarios. Inaddition, for this final piece of analysis, we con-sider only what we regard as the comparison mostrelevant for evaluating the prospects that Mexi-can immigrants will join the mainstream in thecoming decades: the gap in bachelor’s degree at-tainment between 2nd generation Mexicans and3rd+ generation non-Hispanic whites.

For the first panel of Table 8, we use the samedistribution of family background that we usedto standardize the group estimates for models 5through 7. For the second panel, we use the distri-bution of family background that is observed for2nd generation Mexicans (and that correspondsto alternative adjusted rates for models 5 through7 that are presented in Supplementary AppendixTable S6).

The group estimate in the top right corner ofthe table, 0.41, is in fact the same unadjustedgroup estimate for 3rd+ generation non-Hispanicwhites from Table 5, which we include in Table8 for comparison purposes. Just below it, thevalue of 0.27 is the predicted rate of bachelor’s de-gree receipt for a synthetic group of respondentswho have the family structure and socioeconomicstatus distributions of 3rd+ generation whitesbut the lower levels of commitment and beliefsabout expected jobs that characterize 2nd gen-eration Mexicans. For this estimated rate, wepass this synthetic group through the coefficientsfor model 6 that apply to 3rd+ generation non-Hispanic whites. Accordingly, we can interpretthe resulting estimate of 0.27 as the rate of bache-lor’s degree attainment that applies to a syntheticgroup of students who are given the high socioe-conomic status characteristics of 3rd+ generationnon-Hispanic whites but not the commitment andbeliefs associated with higher levels of socioeco-nomic status. This adjusted rate is a reasonableprediction for 2nd generation Mexican studentswho are seized by an unshakeable pattern of dis-sonant acculturation that would not respond tohypothetical interventions in family background.In this case, their rate of bachelor’s degree attain-ment would increase only from values between0.19 and 0.21 (depending on the model) to 0.27under such a hypothetical intervention.18 Thisvalue is considerably lower than the adjusted rateof 0.39 reported for model 5 in Table 5.

Now consider an alternative simulated pre-diction. Assume that the ELS sample does notinclude many of the 2nd generation Mexican stu-dents who are most prone to dissonant accul-

18Some of the gap between 0.27 and 0.41 reflects thedifferent way in which the group estimate is calculated.The value of 0.41 is based on the mean of marginal pre-dictions across the sample of 3rd+ generation whites andhence matches our baseline rate from model 1. The valueof 0.27 is a conditional prediction based on setting thevalues of commitment and educational requirements ofexpected jobs at the mean values observed for 2nd gener-ation Mexicans. Using the same procedure at all of themeans of 3rd+ generation whites yields a prediction of0.36, not 0.41, which is not the desired unadjusted ratefor 3rd+ generation whites. The prediction at the meansis not equal to the means of the predictions. Our analysisdecisions for the results in Table 8 are favorable to thesegmented assimilation position so as to give it the bestpossible chance to emerge as a convincing alternative toour chosen interpretations.



Table 8: Simulated Group Differences from Model 6 for Alternative Assumptions That Predisposetoward Acceptance of the Dissonant Acculturation Conjecture for 2nd Generation Mexican Students

Distribution of Model 6 Estimated Proportions For:Family Structure and At Means of Commitment and 2nd Generation 3rd+ GenerationSocioeconomic Status: Beliefs about Expected Jobs: Mexican White, non-Hispanic

3rd generation non-Hispanic 0.43 0.41(0.04) (0.01)

2nd generation Mexican 0.31 0.27(0.06) (0.01)

3rd generation Below the means of 2nd generation 0.24 0.20White non-Hispanics Mexicans by an amount equivalent to (0.05) (0.01)

the observed difference between2nd generation Mexicans and3rd+ generation white, non-Hispanics

3nd generation non-Hispanic 0.19 0.18(0.03) (0.01)

2nd generation Mexican 0.19 0.19(0.02) (0.01)

2nd generation Below the means of 2nd generation 0.10 0.09Mexican Mexicans by an amount equivalent to (0.02) (0.01)

the observed difference between2nd generation Mexicans and3rd+ generation white, non-Hispanics

Note: See Table 1.

turation (e.g., students who dropped out beforethe 10th grade or sampled students who refusedto participate but for whom nonresponse adjust-ments performed by the data distributors wereineffective). As a consequence, suppose that theobserved mean commitment levels and beliefsabout expected jobs are artificially and mislead-ingly high for 2nd generation Mexicans in theELS. If we pick lower reasonable values—in ourcase, by shifting to values below the observedmeans for 2nd generation Mexicans by an amountequal to the observed difference between 3rd+generation non-Hispanic whites and 2nd genera-tion Mexicans—we can use these lower means togenerate a new synthetic prediction. Taking theselower levels, but still giving these synthetic stu-dents the family background distributions charac-teristic of 3rd+ generation non-Hispanic whites,as well as the coefficients from model 6 that applyto these whites, we obtain a predicted bachelor’sdegree attainment rate of only 0.20. Given thatthe unadjusted rate is between 0.19 and 0.21 de-pending on the method of calculation, we haveeffectively undone what we assumed we could

accomplish by eliminating group differences infamily background.

We do not believe that 0.20 is a reasonableprediction, given our judgment about the qual-ity of the ELS sample and our belief, consistentwith extant research, that shifts in family back-ground would be expected to produce changesin everyday behavior as well as beliefs about fu-ture educational and occupational trajectories.In other words, even if dissonant acculturationexists for these students, we do not believe thatit would be entirely unresponsive to changes infamily background. Proponents of segmentedassimilation may not agree.

For completeness, Table 8 presents additionalpredictions for alternative combinations of fam-ily background distributions, means of commit-ment and beliefs, passed through the coefficientsthat pertain alternatively to 3rd+ generation non-Hispanic whites and 2nd generation Mexicans. Al-though differences emerge across these other ninepredictions, they follow the same basic patternsdescribed for our comparison of the predictions inthe upper-right corner of Table 8. The lowest pre-



diction we generate is at the bottom-right cornerof Table 8, where we assume that 2nd generationMexicans keep their family background distribu-tion, have lower than observed levels of commit-ment, and yet move through the coefficients for3rd+ generation non-Hispanic whites, thereby re-ceiving the largest possible penalty for having lowlevels of socioeconomic status. Only 9 percent ofsuch simulated students obtain bachelor’s degrees.Although this value is far too pessimistic, accord-ing to our judgment, it does provide a usefulconclusion. Our best guess is that we could stilldouble the bachelor’s degree rate from 0.09 to0.20 if, as shown in the third cell above it in Table8, we gave these simulated students a distribu-tion of family background that characterizes 3rd+generation non-Hispanic whites.19 Altogether,we conclude that, regardless of whether dissonantacculturation is present, the socioeconomic statusdisadvantage that characterizes the lives of recentMexican immigrants and their children is a strongpredictor, and likely the most important cause, oftheir low levels of bachelor’s degree attainment.

Conclusions

Consistent with abundant research on broad pat-terns of educational achievement and attainment,we have shown that measures of socioeconomicstatus can account for group differences in bach-elor’s degree attainment between 1.5th and 2ndgeneration Mexican immigrant students in com-parison to 3rd+ generation non-Hispanic whitestudents.20 The capacity of socioeconomic status

19And we could do better, pushing the rate up to 0.24, ifwe assume that they passed through the logit coefficientsthat apply to them, as estimated under their observeddistributions.

20Although we have not developed our article in a waythat makes it directly comparable to the following studies,it bears noting that other scholars have reached similarconclusions with national data sets. Pong and Hao (2007),for example, in an analysis of the National LongitudinalStudy of Adolescent Health, show that the difference be-tween the grade point averages of non-Hispanic whitesand Mexican immigrant students can be accounted for bydifferences in measured characteristics of families, schools,and neighborhoods. Relatedly, Bohon, Johnson, and Gor-man (2006) show that the lower educational aspirationsand expectations of Mexicans in the National Longitu-dinal Study of Adolescent Health can be accounted forby socioeconomic status. More directly related to ourresult, Ovink and Kalgorides (2014) show, with the ELS

to adjust for the differences observed for 1st gen-eration and 3rd+ generation Mexican immigrantstudents is lower, but here imprecise estimationand inherent heterogeneity, respectively, degradethe capacity of the ELS data to assess the effec-tiveness of adjustment by socioeconomic status.

While developing this primary result, we alsoused two sets of detailed measures of individualorientations to schooling and beliefs about thefuture: (1) behavioral commitment to schooling,reported directly by students, their parents, andtheir teachers, and (2) detailed forward-lookingmeasures of occupational plans and their impliededucational requirements. Results utilizing thesemeasures offered little or no support for the dis-sonant acculturation mechanism that casts 1.5thand 2nd generation Mexican immigrants as groupslikely to experience downward assimilation in partbecause of the behavioral orientations of studentsthemselves. With or without baseline adjust-ments for socioeconomic status, these student-level measures can account for only a modestportion of group differences in bachelor’s degreeattainment for these two groups. In possible sup-port of the dissonant acculturation conjecture,observed commitment did account for 40 percentof the bachelor’s degree gap for 3rd+ generationMexican immigrant students, even though beliefsabout the future continued to have little or noexplanatory power.

We also assessed the sensitivity of these con-clusions by simulating the consequences of 2ndgeneration Mexican students having much lowerlevels of commitment to schooling than measuredfor the ELS, as would perhaps be the case if wehad firm evidence (which we do not have) thatstudents engaged in behavior consistent with dis-sonant acculturation are embedded in an unob-served group of respondents who either refused toparticipate in the ELS or dropped out of schoolbefore they could have been sampled in the springof the 10th grade. We showed that one could in-deed undo the support for some of our main con-clusions by making assumptions that, althoughnot implausible, are ones that we regard as fartoo pessimistic. These results, however, may be

2002 to 2006 waves, that family background can accountfor apparent negative effects of familism on rates of col-lege application and college entry, when considering allHispanic ethnic groups together (i.e., not separating outthose who claim Mexican ancestry from others).



encouraging to those who wish to find support inour analysis for alternative conclusions.

Discussion

Sociologists of education cannot be surprised bythe main conclusion of this article, given howfrequently basic differences in family backgroundhave been shown to be of paramount importancein the literature they have built over the past fivedecades. For most immigration scholars, thesepatterns may not be surprising either, althoughthey may not be as welcome. Here a primaryinterest of some scholars is the discovery of knowl-edge that can be used to design an institutionalframework that promotes a swift incorporation ofimmigrants into the economic mainstream. High-lighting what appear to be persistent effects ofparental socioeconomic status does not directlycontribute to such knowledge, and it implies thatinterventions that target the reduction of disso-nant acculturation among adolescents will havemodest impact on patterns of incorporation.

Nonetheless, in this case, a generalized policyresponse is available: lowering the costs of ob-taining a bachelor’s degree. Because family back-ground interventions are difficult to realize, an al-ternative approach is to reduce the consequencesof having been born into a resource-constrainedfamily. Although we cannot of course providedirect evidence of the future benefits that couldflow from reducing the cost of bachelor’s degrees,the ELS data do clearly suggest that the childrenof recent Mexican immigrants are responsive tocosts.

According to the College Board, in the 2001 to2002 academic year, when most ELS respondentswere first sampled as high school sophomoresand entertaining the possibility of pursuing bach-elor’s degrees, the average tuition and fees to-taled $4,956 and $2,116 at public four-year andtwo-year colleges, respectively (both expressed in2013 dollars; see the College Board 2013:Table2). For the 2011 to 2012 academic year, whichcorresponds to the last wave of ELS data collec-tion, tuition and fees had increased by 73 percentat public four-year colleges and 45 percent atpublic two-year colleges (to $8,557 and $3,074 in2013 dollars, respectively). Thus, while tuitionincreased dramatically for both types of insti-

tutions, the relative cost of a bachelor’s degreeincreased as well.

Examining the ELS data closely, one can seethe likely consequences of these changes. First,among ELS respondents who enrolled in at leastone postsecondary institution, 2nd generationMexicans were much more likely than 3rd+ gen-eration non-Hispanic whites and non-Hispanicblacks to first enter two-year or certificate-offeringpostsecondary institutions (54 percent comparedto 34 and 39 percent for 3rd+ generation non-Hispanic whites and non-Hispanic blacks, respec-tively). Second, among those who began theirpostsecondary education at these types of two-year (or less) institutions, 2nd generation Mex-icans were less likely to subsequently enroll infour-year colleges by 2012 (29 percent comparedto 34 and 32 percent, respectively).

The results offered in this article support theposition that the increasing costs of bachelor’sdegrees since the 1990s have worked against in-corporating the children of recent Mexican immi-grants into the economic mainstream. When thesegmented assimilation prediction was developed,these dramatic increases in the costs of collegecould not have been foreseen. Nonetheless, theseare the costs that prospective college studentsnow face as they age into young adulthood. Ifthe children of recent Mexican immigrants cannotfind a way to cover these costs, then access tomiddle-class jobs is not within reach, regardlessof their behavior in adolescence. Accordingly, seg-mented assimilation would appear to be a veryreal threat in the coming decades, but not pri-marily because of dissonant acculturation.

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http://dx.doi.org/10.1111/j.1747-7379.2010.00825.x

http://dx.doi.org/10.1111/j.1747-7379.2010.00825.x

http://dx.doi.org/10.1177/0002716208322577

http://dx.doi.org/10.1177/0002716208322577

http://dx.doi.org/10.1073/pnas.0403418101

http://dx.doi.org/10.1073/pnas.0403418101

http://dx.doi.org/10.2307/2112363



http://dx.doi.org/10.1177/0002716293530001006

http://dx.doi.org/10.1177/0002716293530001006

http://dx.doi.org/10.2307/2092789

http://dx.doi.org/10.2307/2092789

http://dx.doi.org/10.1146/annurev.so.04.080178.002105

http://dx.doi.org/10.1146/annurev.so.04.080178.002105

http://dx.doi.org/10.1007/s11162-006-9017-4

http://dx.doi.org/10.1007/s11162-006-9017-4

http://dx.doi.org/10.1177/003804070908200202

http://dx.doi.org/10.1177/003804070908200202

http://dx.doi.org/10.1080/01491987042000189196

http://dx.doi.org/10.1080/01491987042000189196

http://dx.doi.org/10.1080/01419871003624076

http://dx.doi.org/10.1080/01419871003624076


Acknowledgements: A prior version of this manu-script, entitled “Immigrant Generational Status,Occupational Plans, and Postsecondary Edu-cation in the United States,” was presented atthe Meetings of the Population Association ofAmerica (Boston, Massachusetts, May 1, 2014).We thank the discussant Mike Hout and otherattendees for their helpful comments, as wellas Sarah Ovink. Construction of the measuresbased on occupational plans was supportedby the National Science Foundation (SBES-1023798). Opinions reflect those of the authorsalone.

Stephen L. Morgan: Johns Hopkins University andCornell University.Email: [email protected].

Dafna Gelbgiser: Cornell University. E-mail:[email protected]


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