Social and Economic Returns to College Education in the United … · 2017-02-02 · Social and Economic Returns to College Education in the United States Michael Hout Department

SO38CH18-Hout ARI 2 June 2012 12:29

Social and Economic Returnsto College Education in theUnited StatesMichael HoutDepartment of Sociology, University of California, Berkeley, California 94720;email: [email protected]

Annu. Rev. Sociol. 2012. 38:379–400

First published online as a Review in Advance onApril 23, 2012

The Annual Review of Sociology is online atsoc.annualreviews.org

This article’s doi:10.1146/annurev.soc.012809.102503

Copyright c© 2012 by Annual Reviews.All rights reserved

0360-0572/12/0811-0379$20.00

Keywords

stratification, mobility, inequality, opportunity, selection,credentialing

Abstract

Education correlates strongly with most important social and economicoutcomes such as economic success, health, family stability, and so-cial connections. Theories of stratification and selection created doubtsabout whether education actually caused good things to happen. Be-cause schools and colleges select who continues and who does not, itwas easy to imagine that education added little of substance. Evidencenow tips the balance away from bias and selection and in favor of sub-stance. Investments in education pay off for individuals in many ways.The size of the direct effect of education varies among individuals anddemographic groups. Education affects individuals and groups who areless likely to pursue a college education more than traditional collegestudents. A smaller literature on social returns to education indicatesthat communities, states, and nations also benefit from increased edu-cation of their populations; some estimates imply that the social returnsexceed the private returns.

379

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


INTRODUCTION

College graduates find better jobs, earn moremoney, and suffer less unemployment than highschool graduates do. They also live more sta-ble family lives, enjoy better health, and livelonger. They commit fewer crimes and par-ticipate more in civic life. With all this go-ing for them, it is hardly surprising that col-lege graduates are significantly more likely thanhigh school graduates to say they are “veryhappy.” Social science research has reproducedthese patterns in many societies over many years(see, for example, Kingston et al. 2003; Fischer& Hout 2006, pp. 18–22, for reviews of USpatterns).

Conventional wisdom—imparted by par-ents, teachers, guidance counselors, and policymakers—reads these differences as evidencethat young people would improve their livesby staying in high school, graduating, going onto college, and earning a degree. Sociologistsand other social scientists have been skeptical.Educated people have other advantages thatmay account for their good fortune. Educationmay merely be a manifestation of those ad-vantages, imparting little value in and of itself.The advantages of educated people are almostas well known as their successes. They scorewell on ability tests; their parents bestow onthem social, cultural, and economic assets thatfoster success; and they come to school withtacit knowledge and habits that are seldom partof the curriculum but foster success. Indeed,the correlation between education and successmight be spurious.

Or maybe education benefits the educatedbut would not help those who have left or beenthrown out. Perhaps young people, schools, andcolleges make well-informed decisions aboutwho will benefit from education and who willnot. The people who go far in the educationalsystem are those who can take advantage ofschooling; the others either drop out or findthemselves left out when they have nothing leftto gain (Willis & Rosen 1979). If this selec-tion is optimal, then allowing, forcing, or en-ticing dropouts to go on would waste their time

and society’s resources. In academic shorthand,the correlation between education and successmight reflect positive selection bias in the ed-ucational system; schools treat those who willbenefit from the treatment.

As this review shows, the conventionalwisdom is mostly right this time, and socialscientists’ skepticism, although well worthconsidering, is excessive. The correlations be-tween education and desired outcomes reflect,in surprisingly large part, the causal impact ofeducation on those outcomes. Important newresearch shows that selection bias is actuallynegative; unlikely college students probablybenefit from their education more than typicalcollege students do (Brand & Xie 2010).Evaluation of this hypothesis continues as ofthis writing (Carneiro et al. 2011).

A smaller literature, mostly in economicsand demography, has investigated what arecalled the social returns to education (Topel1999). Billions of dollars in public money areinvested in institutions and individuals on thetheory that society benefits from having an edu-cated populace. The evidence suggests that thistheory is also right. To that economic evidence,political sociologists add the observation thateducation also reduces prejudice and intoler-ance while increasing support for civil liberties.This subjective social return is also valuable,although no dollar sign is attached.

Being educated is not only good in its ownright (Abbott 2002); it also promotes good out-comes for individuals, their communities, andthe nation as a whole.

EDUCATION AND ECONOMICOUTCOMES FOR INDIVIDUALS

The correlation between education and eco-nomic fortunes in the United States has neverbeen higher (Goldin & Katz 2007, pp. 71–85).The literature has dozens of studies that featurethe role of education in economic outcomes(Card 1999). I illustrate the robust findings withmy own calculations using the most recent dataavailable (Figure 1). My calculations focus onpeople of prime working age, 30–54 years old,

380 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


12

Men

Un

em

plo

ym

en

t (%

)

Occ

up

ati

on

al

ea

rnin

gs

sco

re

Pe

rso

na

l e

arn

ing

s (t

ho

usa

nd

s)

Tota

l fa

mil

y i

nco

me

(t

ho

usa

nd

s)

Years of educationYears of education

Women

9

6

3

011–12 HS SC AA BA MA PhD Prof.

$100

$50

$25

$12.5

$200

25

50

75

100

$100

$50

$25

<11 11–12 HS SC AA BA MA PhD Prof.<11

11–12 HS SC AA BA MA PhD Prof.<11 11–12 HS SC AA BA MA PhD Prof.<11

Figure 1Occupational earnings score, personal earnings, family income, and unemployment by years of educationand gender: United States, 2007–2009. Incomes were adjusted for inflation using the consumer price indexfor urban households (CPI-U) and are expressed in 2009 dollars on a ratio scale (i.e., doublings from $12,500to $25,000 to $50,000 to $100,000 appear as equal intervals). Key to education labels: <11 = 0–10 yearscompleted, 11–12 = 11 or 12 years completed but no diploma, HS = high school diploma, SC = somecollege, AA = two-year degree, BA = four-year degree, MA = master’s degree, PhD = doctoral degree,Prof. = professional degree (e.g., JD, MD, DDS). Source: author’s calculations from the US CensusBureau’s March Current Population Survey, persons 30–54 years old (see King et al. 2010).

in order to avoid biases that could creep into theanalysis because some people extended their ed-ucations after failing to find a job and others re-tired early in lieu of a layoff. The main patternsin descriptive data like these do not depend onwhich of several meaningful ways of categoriz-ing education is used (Fischer & Hout 2006,pp. 260–61).

Newspapers featured stories about unem-ployed college graduates as the 2007–2009 re-cession ground on, but the data in the upper leftof Figure 1 here show that the least-educatedprime-age workers were almost four times morelikely than college graduates to be unemployedduring the recession. Prime-age workers withno credentials had an unemployment rate of11% over the 2007–2009 period compared with

7.4% for prime-age men and 5.2% for prime-age women with high school diplomas, 2.8% forprime-age college graduates, and less than 2%for prime-age workers with advanced degrees.College graduates also had much shorter spellsof unemployment (Hout et al. 2011); in pastrecessions, laid-off college graduates recoveredmore quickly (Gangl 2006).

People with more education also had moredesirable jobs. I scaled occupations accordingto the percentage of people in the occupationwho had annual earnings above the nationalmedian; the pattern would be the same if I usedany reasonable score (Hauser & Warren 1997).Getting a job that paid well rose almost lin-early with educational levels: 7.4 points for eachrung of the educational ladder among men and

www.annualreviews.org • Social and Economic Returns to College 381

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


7.8 points for each rung among women.1

Graduating from college instead of high schoolboosted prime-age men’s occupational stand-ing up to 69 points from a base of 45 points;it boosted prime-age women’s occupationalstanding up to 59 points from a base of 34points. Advanced degrees improved occupa-tional standing beyond that achieved by collegegraduates.

College graduates made more money aswell. Men’s and women’s annual earnings dur-ing their prime working ages rose roughly 20%for each educational level.2 Further analysisshows that men’s tendency and/or opportu-nity to work more hours explains almost halfof the gender difference in annual earnings.Hourly wages were more similar for men andwomen; they rose 17.5% for each educationallevel among prime-age men and women alike.3

Family incomes combine educational dif-ferences in marriage and economic outcomes.That makes family income ill-suited for ananalysis that seeks to parse the separate causalcontributions to economic inequalities. But italso makes family income an interesting anduseful summary measure of education’s com-bined potential (Harding et al. 2004). The in-comes of prime-age men’s families were about10% higher than those of prime-age women’sfamilies because 30- to 54-year-old men wereslightly more likely to be currently married andbecause unmarried men of these ages earnedslightly more than unmarried women. Familyincomes rose 21% for each educational level.Among men, college graduates’ family incomeswere $91,800 compared with high school grad-uates’ $50,100; among women, the comparable

1These slopes are from regressions using individual obser-vations, not from the few data points in the figures. With96,000 men and 90,000 women in the data set, the differenceof 0.4 is statistically significant at conventional levels.2The slopes from the individual observations were 0.2066for men and 0.1964 for women. The slopes are significantlydifferent in a statistical test, but 0.0102 is a substantively trivialdifference.3The slopes from the individual observations were 0.1745 formen and 0.1752 for women, a statistically and substantivelytrivial difference.

figures were $86,700 and $45,200. Familystructure interacts with education in complexways because each partner’s education affectshis or her prospect of marrying, divorcing, andremarrying as well as work hours (DiPrete &Buchmann 2006, Western et al. 2008).

Causal Inference

To say that education causes good outcomessuch as the economic successes in Figure 1 isto move beyond the descriptive statement thatcollege graduates make more money than highschool graduates. The conclusion that collegeactually causes the difference requires substan-tially more evidence than Figure 1 provides.Specific counterfactual statements such as “thiscollege graduate would be making less moneyif she had not gone on to college” or “that highschool graduate would be making more moneyif he had only earned a college degree” wouldhave to be true. The burden of proof is muchhigher in a causal statement than in a descriptiveone (Gangl 2010). The first step is to base com-parisons on situations in which everything buteducation is equal by controlling for observabledifferences that correlate with education.

Ability is the key to the critique and the re-buttal. Academic abilities, such as speaking andwriting clearly or doing arithmetic easily, con-fer advantages both at school and at work. TheK–12 curriculum emphasizes those skills, andcollege courses hone them. Teachers may try tooffset preexisting differences among students,but academic aptitudes and abilities affect whoearns educational credentials. Consequently,people who score highly on verbal and mathtests in tenth grade are more likely to graduatefrom college than people who test poorly(Hauser 2002). This correlation between aca-demic abilities and educational outcomes makesit difficult to interpret familiar correlations likethose in Figure 1 as cause-effect relationships.(Of course, similar arguments could be madeabout how experience, hours worked, gender,racial ancestry, local labor market conditions,industry, and any number of other factorsbesides ability are correlated with education

382 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


and might also be part of the differences inFigure 1.) Without statistical controls orcarefully chosen comparisons, it is hard tosay if getting more education causes pay toincrease or spuriously reflects the influence ofabilities correlated with getting more education(Kaymak 2009).

Further complicating the task is the fact thatabilities are only loosely coupled, as opposedto some overarching single thing (Fischer et al.1996, Nisbett 2009). Controlling for some abil-ities but not others leaves doubts that every-thing else is really equal in the comparisonsbehind the resulting coefficients (Card 2001).Abilities are not even necessarily all that aca-demic. In addition to the ability to read, write,and count with ease, the abilities to stick with atask from start to finish, to get along with oth-ers, to interpret vague instructions correctly,or to solve practical problems quickly can allcontribute to success in school and on the job.These things have been termed by some (e.g.,Heckman et al. 2006) as noncognitive skills, anunfortunate term because the abilities in ques-tion do require thought. They are less academicand seldom part of the formal curriculum, al-though even that generalization must be quali-fied because teachers routinely insert them intothe informal curriculum (Tyson 2002, Lareau2003). But the point for causal inference is thatabilities are so diffuse yet so important that itis hard to know when statistical controls forobservables have isolated the comparisons thattruly gauge the impact of education.

With these problems in mind, economiststurned to instrumental variables (IVs) in the1980s. An IV is a source of natural variation thatapproximates the random assignment of an ex-periment. The random assignment breaks theconnection between ability and education; ev-eryone has his or her naturally occurring abili-ties (and all other attributes, too), but now thetreatment group members have a random incre-ment or decrement to their education, whereasthe controls have their natural amount eventhough their abilities remain the same. The firstsuch instrument researchers analyzed was com-pulsory schooling rules that affect people born

late in the year more than people born earlyin the year (Angrist & Krueger 1991). Becausepeople do not choose their birthdays, usingmonth or quarter of birth as an IV approximatesthe conditions of random assignment in statesthat compel people with birthdays in the firsthalf of the year to stay in school longer than theymight otherwise have stayed. Other IVs includeVietnam-era draft lottery number (some peo-ple who had low lottery numbers had to leavecollege and join the army) (Angrist & Krueger1992) and distance from home to the nearestcollege or university (a reduction in price un-correlated with abilities) (Kane & Rouse 1995).The difference in earnings between treated andcontrol groups later in life provided an estimateof the effect of education net of abilities withoutthe need to make exhaustive tests of abilities (orany other confounding factor).

The IV studies produced a surprising result.Before looking at the data, economists reasonedthat ordinary least squares (OLS) estimates ofthe effects of education were too large becausethey combined the education effect of inter-est and the contaminating influence of abilities.Yet the IV estimates in the seven leading stud-ies were uniformly larger than the OLS esti-mates (Card 2001). The biggest difference wasin a British study that used as IVs secondaryand university reforms that took effect in 1947and 1973 (Harmon & Walker 1995); the IVestimate was 2.5 times larger than the OLSestimate in that study.

Apparently, the IV estimates containedmore than just a correction for ability bias(Deaton 2010). One thought was that observededucation—a self-report in each study—wasmeasured with so much error that the OLSestimate contained more downward bias frommeasurement error than upward bias from un-measured abilities. But that seemed implau-sible. Most studies tout the accuracy of self-reported education. Evidence from multiplesources indicates that errors occur more of-ten from proxies stating that the person of in-terest has more education than she does thanfrom errors about one’s own education (Warren& Halpern-Manners 2007). The interplay of


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


excluded variable bias and measurement error,is, nonetheless, complex, and easy generaliza-tions are few (Griliches 1977).

Perhaps IV estimates exceeded OLS esti-mates because researchers came up with flawedinstruments. For example, relatively few peo-ple with low draft numbers actually served inthe US Army, so that instrument was pickingup something else about men in the cohorts ex-posed to the draft lottery. It is hard to say whatthe missing causal factor was though.

A third explanation—negative selection—has gained support in new research. Most sta-tistical analyses approach observational data asif there is a single educational effect to be esti-mated. But intuition suggests that students whoare treated with more education benefit morefrom receiving it than most people do. If that’strue, then OLS would overestimate the averagecausal effect. If, against intuition, students usu-ally excluded from advanced education wouldactually benefit more from it than traditionalstudents, then OLS would underestimate thecausal effect.

Educators have, for the most part, fol-lowed intuition. Policy and practice assumethat high-ability students benefit more fromeducation than do students who struggle. So,high-scoring students get to take more chal-lenging courses in high school, and collegesinsist on tests and transcripts in addition todiplomas when they decide whom to acceptand whom to reject. The plan is to providehigher education to those most ready to benefitfrom it. Call that positive selection. Practically,it implies that an experimental assignment tomore education would expose young peoplewho could not benefit from that education towhat is—for them—a worthless treatment. Ifpositive selection succeeded, then IV estimateswould be less than OLS estimates. Data revealthe opposite pattern; most IV estimates exceedOLS estimates (Card 2001, Deaton 2010). Thedata imply negative selection. Students whogot more education than they would otherwisehave received actually benefited more thantheir peers. Although it runs counter to intu-ition, this result accords well with experience.

Reforms that opened universities to nontradi-tional students produced graduates who gaineda return to the college degree as large as orlarger than that of traditional college students.

Bowen & Bok (1998) studied students whogained admission to 28 of the nation’s mostselective liberal arts colleges and research uni-versities (they referred to them as the College& Beyond, or C&B, schools); all the schoolsused some form of racially sensitive affirmativeaction to increase student body diversity.Compared with a nationally representativesample of college students from the samecohort, the C&B students fared as well—andon some factors better. At the C&B schools,the probability of actually graduating with abachelor’s degree was uniformly higher thanin the national sample; more importantly,the probability of graduating did not dependon SAT scores at the C&B schools but rosesharply with SAT scores in the national sample.The earnings of African American men andwomen from C&B schools not only exceededthose of African American men and women inthe national sample, but also exceeded those ofwhite men and women in the national sample.C&B minorities earned more advanced degreesthan did whites in the national sample.

Attewell & Lavin (2007) tracked womenfrom the first cohorts of students who enteredthe City University of New York (CUNY) un-der its open admissions policy. They comparedwomen who would have been rejected underthe previous admissions policies with those whowould have been admitted under those policiesand with a nationally representative sample ofwomen. After 25 years, they found that thoseadmitted only under the open policy (referredto as open admits) appeared to gain slightlymore from college than the women who wouldhave gotten into CUNY under the 1960s ad-missions policies. Few differences were statis-tically significant, but all were positive. Inter-estingly, the children of open admits benefitedfully from having college-educated parents, too.Thus, heritable ability differences, whateverthey might be, appear to be small relative to therealized benefits of the university education.

384 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


Maurin & McNally (2008) comparedFrench college students from the cohort of1968 with those in cohorts before and after thisyear because the mass protests of May 1968 dis-rupted college entrance exams and allowed stu-dents who might not have done well on suchexams to gain university admittance. Despitecrowding in university classrooms and subse-quently in the labor market, the 1968 enteringcohort gained more from university than theprevious and subsequent cohorts did. Further-more, just as with the CUNY open admits, theirchildren are indistinguishable from the childrenof university graduates from other cohorts.

Researchers have also simulated naturalexperiments by comparing college studentsand high school graduates who are statisticallymatched on the propensity to attend university.If the matches are good, then the differencebetween the success of people who graduatedfrom university and those who graduated fromhigh school is a better estimate of the causaleffect of university education than ordinaryestimates would be. Brand & Xie (2010) usedtwo American data sets to make matches andestimate the effect of education this way. Theyfound that the effect of education was biggestfor students who were least likely to go tocollege and smallest (though still significantand substantial) for students most likely togo. Carneiro et al. (2011) question negativeselection in general and critique Brand & Xie’s(2010) estimates in particular. Their latent-class model found homogeneous effects ofeducation on earnings. In unpublished new re-sults discussed in detail in the next section, Dale& Krueger (2011) found negative selectionin the form of significant college-selectivityeffects for nontraditional students.

These four findings about causalheterogeneity—if they hold up under cri-tique (Carneiro et al. 2011)—all reflect back onthe puzzle of why randomly assigning peopleto education yielded bigger estimates of theeffect of education than ordinary methodsdid. Bowen & Bok (1998), Attewell & Lavin(2007), and Maurin & McNally (2008) allfound that admitting students who would

normally be rejected resulted in larger thanaverage effects of college (some differenceswere not statistically significant). The randomassignments in the IV studies identified thesame kinds of people: those who usually chooseto leave school as soon as they can but who,surprisingly, benefit more if they are requiredto continue. Brand & Xie’s (2010) propensityscore methods showed that this is actually afairly general pattern.

The educator’s intuition may be exactlybackwards. The students who benefited mostfrom more education appear to be the last onesadmitted to advanced math classes or selec-tive universities. The ones who oozed abilitydid almost as well when they did not fulfilltheir potential for formal education as whenthey did. The marginal students gained themost from the opportunity to be educated.Anecdotes make for unreliable evidence, but,as food for thought, it is worth noting thatseveral leaders of the computing industry, in-cluding Microsoft founder Bill Gates, Applefounders Steve Jobs and Steve Wozniak, andFacebook founder Mark Zuckerberg, droppedout of college to pursue business opportunities(Wozniak is the only one of the four to sub-sequently return to college and complete a de-gree). Faculty teach what they know, and Gates,Jobs, and Zuckerberg worked beyond the fron-tiers of established knowledge.

Research on secondary school effects showsa pattern that closely resembles negative selec-tion. School effects on academic achievementare largest for students who score in the middlerange of abilities (Hoffer et al. 1985). Studentswho score in the middle range on achievementtests gain more from positive school effects andsuffer more from negative school effects than dostudents at the top and bottom of the test-scoredistribution.

Further corroboration comes from thesummer learning literature (Fischer et al. 1996,Downey et al. 2004). Students whose parentsgraduated from college and students whoachieved high test scores continued learningover the summer, whereas most students didnot. Students whose parents had little education


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


and students who got low test scores actuallyscored worse on fall tests than on tests theprevious spring, suggesting they forgot someof what they had learned the previous year.In other words, schools affected educationallydisadvantaged and low-scoring students morethan advantaged and high-scoring students.

The secondary school effects literature fo-cuses on academic achievement as the out-come, whereas the selection effects literatureaddresses labor market outcomes. But the twoliteratures have converged to a consistent mes-sage: High schools and colleges matter most forstudents in the middle.4

One more piece of evidence corroboratesthis thread of research and supports the infer-ence that education affects new or nontradi-tional students more than others. In research onAmerican social mobility, Torche (2011) usedrecent data to replicate a pattern I found in datafrom the 1960s, 1970s, and 1980s (Hout 1984,1988). Family background constrains the occu-pational achievements of people who lack col-lege degrees but not those who have degrees.The same finding can be read this way: Educa-tion affects the occupational success of lower-origin workers more than higher-origin ones(Breen & Luijkx 2004).

These analyses of causal heterogeneity ab-sorb and recast the concerns regarding abil-ity bias. It now appears that education has ademonstrable causal impact on people of mod-est ability. It probably has a weaker effect onthe most able. The literature up to this pointhas not asked whether education affects the payof low- or middle-ability people more, but theschool effects literature suggests that those withmiddle ability get bigger returns.

Scholars have been discussing these issuesat least since the late 1920s (Sorokin 1927,Houthakker 1959) and actively pursuing re-search that would separate the effects since the1960s (Hauser 1970). The earliest projects used

4The least able get little out of high school and rarely go tocollege; thus, we know little about the returns that the lowestpropensity students might get from higher education.

multivariate statistics to separate ability andeducation. Research since the mid-1980s hasreevaluated that whole project and led to theconclusion that ability and education cannot beseparated. Rather, the correct perspective is toask how abilities make education more or lesseffective in producing the desired outcomes.Young people with the most abilities may learnand ultimately earn the most, but their edu-cation augments their success less than it aug-ments less-able people’s success (in the range,roughly, from the median to the top of the abil-ity distribution). Secondary education makesthe biggest difference for people with modestabilities, and that is probably true of college,too. (Because college is so selective, we do notsee many college students in the lowest quartileof test scores.)

Can the Positive Returns to EducationOffset Escalating Costs?

College costs more every year; increases in thefull cost of college outstripped inflation by largemargins in both the public and private sectors(see Figure 2). The full cost of attending aprivate, four-year college or university—whichincludes tuition, fees, room, and board forfull-time students who received no financialaid—averaged $31,300 in the 2008–2009academic year, up from $13,700 in 1981; bothamounts are stated in 2009 dollars so the 127%increase is on top of the average increase inthe price of goods and services. Public collegesand universities were a comparative bargain at$14,100 in 2008–2009, but the rate of increasewas almost identical—125% since 1981 whenfull cost was $6,200. Tuition hikes were themain cause of above-inflation increases for bothpublic and private colleges and universities;room and board increased at roughly the rateof overall inflation (Kane 1999, pp. 34–36).

The full cost of private and public highereducation rose more or less in tandem through-out the 30-year period. Private education’s costrose slightly faster than that of public educa-tion in the 1980s; public education’s cost roseslightly faster than that of private education in

386 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


$4

$8

$16

$32

Fu

ll c

ost

(th

ou

san

ds)

1980 1990 2000 2010Year

Private4-year2-year

Public4-year2-year

Figure 2Full cost of attending college by year, sector, and type of institution. Notes: Full cost includes average totalcharges—tuition, fees, room, and board—for full-year, full-time attendance. See Figure 1 caption forinformation on inflation adjustments. The dotted lines show 30-year trends at a constant rate of increase(1.16% per year for public, two-year colleges and 2.26% for the other three). Source: US Dep. Educ. 2011,table 239.

the most recent decade (Figure 2). Only thepublic, two-year (community) colleges held tu-ition down for a significant period; the full costof a community college education rose only asfast as other prices for the 15 years from 1985to 2000.

The full-cost data show what a studentwould pay at an average private or public col-lege or university. As with any average, thereis variation above and below it; some collegescharge substantially more, others less. But moststudents pay less than the stated amount fortheir education. Scholarships and grants basedon academic performance, financial need, orboth reduced the cost for 64% of recent full-time students (Natl. Cent. Educ. Stat. 2009).

Are these increases offset by the returns stu-dents can expect? Are today’s full costs toomuch to pay up front for an uncertain increaseto lifetime earnings? Academic researchers havegiven the difference between investment and re-turn surprisingly little attention. Fortunately,the US Census Bureau twice published esti-mates of lifetime earnings differences that ad-dress these questions (Yang 2008, Julian &

Kominski 2011). The latest estimates separatepeople by race and Hispanic ancestry and byhours worked; Figure 3 shows the results forall persons by race/ancestry.

Even the most cautious reading of the ev-idence confirms that earning a college degreewill pay back the cost of obtaining it severaltimes over. In a 40-year work life, men withcollege degrees can expect to earn $1.1 millionmore than high school graduates. The dif-ference is slightly larger than that for non-Hispanic white men and slightly less for theother three groups. Women earn substantiallyless than men at each level of education, mainlybecause fewer women than men work full-time, full-year (FTFY); the gender gap in life-time earnings is much smaller among FTFYworkers ( Julian & Kominski 2011). The fourracial/ancestry groups are virtually identical.Women with college degrees can expect to earn$636,000 more than high school graduates overtheir lifetimes.

Five years at full cost at the average pri-vate, four-year college or university worksout to $156,500 (with no financial aid). The


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


$0

$2

$4

$6

$0

$2

$4

$6

GS SHS HSG SC AA BA MA PhD Prof.

White, nonhispanic

Asian, nonhispanic

Black, nonhispanic

Any, Hispanic

Race, ancestry

Sy

nth

eti

c w

ork

life

ea

rnin

gs

(mil

lio

ns)

Education

Men

Women

Figure 3Work-life earnings by education, race, ancestry, and gender: United States2006–2008. Notes: Synthetic work-life earnings were calculated fromcross-sectional data pooled from American Community Surveys of 2006–2008,standardized to 2008 prices. Thicker line segments highlight the educationalattainments ranging from high school diploma to bachelor’s degree. Key toeducation labels: GS = 0–8 years completed, SHS = 10–12 years completedwith no diploma, HSG = high school diploma or GED (any number of yearsof education completed), SC = some college with no degree, AA = two-yeardegree, BA = four-year degree, MA = master’s degree, PhD = doctoraldegree, Prof. = advanced professional degree (e.g., JD, MD, DDS). Source:Julian & Kominski 2011.

average male college graduate’s degree willyield roughly 7.7 times what it might have cost;the average female college graduate’s degreewill yield 4.1 times what it might have cost.Financial aid reduces cost but not payoff, so theyield will be higher for the majority of gradu-ates who receive aid. At a public university, fiveyears at full cost works out to $70,500. That in-vestment will pay off 18 times over for men and10 times over for women. People who attendcollege lose out on work experience at first, butI have not adjusted for that. The census fig-ures for both college graduates and high schoolgraduates assume a 40-year work life; the timeout of the labor force while in college is offsetby a later retirement age for college graduatesin these calculations. Kane (1999) argues for ex-cluding room and board from calculations likethese, reasoning that people have to pay for food

and shelter whether they enroll or not. Remov-ing living expenses would further increase theestimated return on educational investment.

Calculating the full return on a college in-vestment must factor in the yield on advanceddegrees as well. Master’s, doctoral, and pro-fessional degrees compound the advantages ofgraduating from college. When the lifetimeearnings of men and women with advanced de-grees are figured in, earning a college degreelooks even better. Quantifying the post-BA pay-off is not possible from published sources, how-ever, because comparable data on the cost ofpursuing an advanced degree are not available.

The US Census Bureau’s estimates have sev-eral important limitations. Lifetime earningswere extrapolated from a single year’s earningsof men and women at different ages. The earn-ings of today’s older men and women may ormay not predict the earnings today’s young peo-ple will have in the future. Offsetting the uncer-tainty is the fact that these patterns have grownclearer over the past 25 years.

In conclusion, the returns to higher educa-tion are large enough to offset even the full costsstudents now face. The difference between theearnings of college graduates and high schoolgraduates has risen almost as much as tuition inthe past 25 years, so the yield now is almost aslarge as it was when tuition was lower.

The Benefits of Elite Colleges

Students strive for famous colleges. At the mostprestigious and probably throughout the rangeof selective colleges and universities, applica-tions have risen rapidly, whereas the num-ber admitted has increased much less. Conse-quently, admissions rates have fallen since 1980(Bound et al. 2009). Hoxby (2009) argues thatadmissions rates have fallen only for the mostselective. Highly selective, elite colleges offertwo important benefits to students: graduationis more certain (Bowen et al. 2009) and in-vestment per student is higher (Hoxby 2009).Hoxby calculated that the well-endowed, ex-pensive universities actually invested $15,000more per student each year than they charged.

388 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


Graduates entered the labor force endowedwith the equivalent of a $260,000 education forwhich they paid, at most, $200,000. The invest-ment in a graduate from a public university wascloser to $160,000. Thus, as high as tuition was,the cost paid by the university was even higher.

Finding an effect of graduating from anelite college on earnings has been surpris-ingly difficult. Average SAT scores and othermarkers of quality and status correlate withgraduates’ earnings. But the literature has asmany null findings as positive ones. Dale &Krueger (2002) studied college freshmen whowere admitted to an elite, selective university.Freshmen who chose to enroll at a less selectiveuniversity—despite admission to the elite one—subsequently earned as much as those who actu-ally enrolled at the elite school (Dale & Krueger2002). That is the strongest null evidence.

New unpublished work (Dale & Krueger2011) again questions the return to selectiv-ity. The authors compiled earnings data fromadministrative records, reducing measurementerror substantially. Cumulative earnings weresignificantly higher for people who attendedhighly selective colleges and universities, butthey were also correlated with the average SATscore at all the colleges and universities thosepeople applied to. If earnings correlate with at-tributes of the schools people did not attend aswell as the one they attended, then selectivityis probably telling us more about the studentsthan their schools. Dale & Krueger (2011) in-terpret this pattern as evidence of unobservedstudent abilities. Models that include both se-lectivity of the college attended and averageSAT scores at all colleges applied to show weakor no effect of selectivity for most students. Forblack and Hispanic students and for studentswhose parents had less education, college se-lectivity had a large, positive effect, consistentwith the negative selection argument discussedabove.

Black & Smith (2006) expanded the usualsearch for elite effects by using five measuresof college quality. Combining measures pro-duced an estimate of the effect of college qualityon wages that was significantly higher than the

estimates obtained by considering any measurealone (Black & Smith 2006). Graduates fromcolleges and universities that were in the top 5%of the quality distribution earned an average of12% more per hour than graduates of average-quality universities. The 12% boost was statis-tically significant but disappointing next to the56% investment advantage that they received(Hoxby 2009). And Black & Smith’s (2006) re-sults do not control for the quality of universi-ties that students applied to but did not attend,so they could not control for unobserved abili-ties as surely as Dale & Krueger (2011) did.

A degree from an elite college increases mar-riage prospects. For women, graduating froman elite college or university increases the prob-ability of marrying a man with a high income;for men, graduating from an elite college oruniversity increases the probability of marryinga woman from a privileged background (Arumet al. 2008). These patterns might well increasefamily income, even if the elite college does notincrease earnings.

Returns to Two-Year Colleges

The complement to worries that an expen-sive elite education will not pay off is the con-cern that community colleges divert nontra-ditional students from the lucrative academictrack to lower-reward, trade-oriented courses(Brint & Karabel 1989). That does occur atsome two-year colleges, especially overenrolledand underendowed public community colleges(Rosenbaum et al. 2006). But other two-yearcolleges, even some for-profit ones, achievegood outcomes for students by offsetting theirlow cultural capital and knowledge about highereducation (Rosenbaum et al. 2006). To someextent, vocational education is as remedial asacademic education at community colleges inthe sense that some people get the same valueout of well-structured secondary school voca-tional training as others get out of similar train-ing at two-year colleges (Arum 1998).

In short, degrees and certificates from two-year colleges boost the earnings for the studentswho complete such programs and perhaps for


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


students who complete only part of their pro-gram (Marcotte et al. 2005). In the language ofcausal analysis, there is evidence of an effect ofthe treatment on the treated. It does not implythat every student would benefit if reassignedfrom their preferred course of postsecondaryeducation to a two-year college. But for thestudents who go, education at a two-year col-lege is better than no postsecondary educationat all and perhaps better than a more demandingeducation (Marcotte et al. 2005, Stephan et al.2009).

ORIGIN, EDUCATION,AND OPPORTUNITY

The opportunity to pursue an advanced edu-cation is profoundly and persistently unequal(Blau & Duncan 1967, Mare 1981, Raftery &Hout 1993, Lucas 2001, Bailey & Dynarski2011, Hout & Janus 2011). This fact alone hasmade some sociologists skeptical of the efficacyof education. But that skepticism misses a keypoint. Education’s role in transmitting the ad-vantages of social origins depends on inequal-ity of educational opportunity as well as on theeconomic value of education (Blau & Duncan1967, pp. 165–75). For the sake of exposition,let us strip the Blau-Duncan model to its essen-tials: education (E) depends on socioeconomicorigins (X), abilities (A), and variation in edu-cation that is uncorrelated with either familysocioeconomic status or academic ability (ζ ):

Ei = β10 + β11 X i + β12 Ai + ζi . 1.

Subsequently, the person’s success in the formof a desirable job, salary, etc. (Y ) depends onsocioeconomic origins, abilities, education, andthe myriad causes of success that are uncorre-lated with origins, abilities, and education (ε):

Y i = β20 + β21 X i + β22 Ai + β23 Ei + εi . 2.

The correlation across generations can beexpressed in terms of these relationships asfollows:

rxy = β21 + β22rax + β23 (β11 + β12rax) . 3.

If education has no net effect on the out-come of interest after controlling for socioeco-nomic origins and abilities, then β23 = 0, andall the terms involving education drop out ofEquation 3. Thus, education is not the key topersistent inequality unless it directly affectsjobs, pay, and other outcomes. Just as impor-tant, however, is the effect of origin on educa-tion (β11). Without this indirect effect, the cor-relation between origins and destinations woulddepend solely on the direct effect of educationand its correlation with abilities.

The substantive implication of this simpleillustration continues to hold as the model isenriched with additional explanatory variables.The algebra grows more and more complex asvariables are added, but the conclusion is alwaysthe same. Education disappears from the inter-generational correlation if β23 is zero; that is,if education does not cause success. Therefore,skepticism of education’s efficacy that is basedon selection is misplaced.

The other concern in the “engine of inequal-ity” skepticism is that intergenerational corre-lations are rising (Karen 2002). Data show noincrease in β11 in the past 50 years (Bailey &Dynarski 2011, Hout & Janus 2011).

Skeptics and Critics

Some serious sociologists and economists de-veloped strong arguments in the 1970s aboutthe limits of mass education (Berg 1970; Collins1971, 1979; Freeman 1976). They noted howfew of the skills that define academic successtranslate to skills used on the job. The disjunc-ture led them to doubt that education causedsuccess. Instead, education represented to thema tool elites used to limit opportunity to peo-ple like them. Collins (1971) articulates it thisway:

1. Society is composed of status groups thatare differentiated by practices and habitsinformed by culture and norms.

2. Practices and habits turn into a status rankordering through class advantages (andcomplementary disadvantages).

390 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


3. “The main activity of schools is to teachparticular status cultures, both inside andoutside the classroom. In this light, anyfailure of schools to impart technicalknowledge (although it may also be suc-cessful in this) is not important; schoolsprimarily teach vocabulary and inflection,styles of dress, aesthetic tastes, values andmanners” (p. 1010).

4. Education allows employers to selectworkers deemed to be appropriate onthe basis of status group membershipand then teach the job skills on the job.“Educational requirements for employ-ment can serve both to select new mem-bers for elite positions who share the eliteculture and, at a lower level of education,to hire lower and middle employees whohave acquired a general respect for theseelite values and styles” (p. 1011).

The Credential Society (Collins 1979) extends theargument.

Berg (1970) and Freeman (1976) provokedcontroversy by arguing that most college grad-uates had more education than they needed, atleast more than they needed to get their jobsdone. As Smith (1986) notes, these argumentshave two parts: the link between education andoccupation, and differences in pay among work-ers within the same occupation with differentamounts of education.

All this work carries the implicit assumptionthat the American economy somehow got themix of high school– and college-educated la-bor right in the 1950s or 1960s and that sub-sequent increases in the fraction with a collegedegree represent irrationality on the part of em-ployers, students, or both. In Collins’s (1971,1979) work, there is the nuance that employ-ers are discriminatory or status seeking. Berg(1970) adds that colleges and universities gainat some students’ expense by overpromising re-wards and coming up short on delivering em-ployable skills. Freeman (1976) focuses on thetension between individual incentives that pro-mote more investment and the collective actionthat dilutes the return on that investment (alsosee Thurow 1975).

These arguments arose at the low point inthe pay advantage of college graduates. WhenCollins, Berg, and Freeman were writing(1970–1976), the difference between theaverage earnings of college graduates and highschool graduates was half of what it was in 1999(Fischer & Hout 2006, pp. 114–20). Theirconcerns have been supplanted by the obser-vation that education-based pay gaps are closeto the core of rising inequality (Fischer et al.1996, Fischer & Hout 2006, Goldin & Katz2007). As evidence of a true causal effect of ed-ucation on pay accumulates, the discussions ofcredentialing, training robbery, and overedu-cation become irrelevant. The microprocessorrevolution put a premium on information, dataprocessing, and the work of symbolic analysts(Reich 1992, Fernandez 2001). Those whoknow more about these things pull fartherahead, all else being equal. An educated personinvents things, works around tough problems,understands directions, documents tasks,misses less work, and puts in a more nearly fullday on the job—in short, educated workers pos-sess the cognitive and noncognitive skills thatemployers value (Fernandez 2001, Heckmanet al. 2006, Goldin & Katz 2007). Technologymakes some people—predominantly collegegraduates—more productive and others—mostly high school graduates—redundant.

In this new context, it is important tonote that education and cognitive ability af-fect both workers’ occupational placements andtheir earnings in those occupations, but the ef-fects are not additive (Carbonero 2007, Baker2009). Returns to education and cognitive abil-ity are significantly higher in occupations withhigh skill demands than in less skilled occupa-tions. Similarly, majoring in a science, technol-ogy, engineering, or math field pays off morethan majoring in the humanities (Roksa 2005,Poletaev & Robinson 2008, Pfeffer 2008,Shauman 2009).

An educational credential is substance andacquired abilities, not just status. Some ofthe ability may be a preexisting talent, butmost people need schooling or work ex-perience to bring that talent out (Miller


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


et al. 1986, Nisbett 2009, Arum & Roksa2010).

SOCIAL RETURNS

Economists use the term “social returns” tocharacterize the impact of education on thewhole economy (Topel 1999). All gain whenmore are educated. If people gain from hav-ing educated people in their neighborhood ormetropolitan area, then they receive a socialreturn on the education of others.

The Impact of Educationon Community

Moretti (2004a, 2012) found that high schoolgraduates’ wages increased where the propor-tion of college graduates in the labor marketincreased and that high school dropouts’ wagesincreased even more in those places. A key is-sue for this literature is the presence of unob-servable characteristics of individuals and citiesthat may raise wages and be correlated with col-lege share—an issue very familiar to sociologistsinterested in context effects whether they aretied to schools, locales, or other aggregations.Moretti’s longitudinal model controlled for thenonrandom selection of workers among citiesby using two IVs: the (lagged) city demographicstructure and the presence of a land-grant col-lege. He found that a percentage point increasein the supply of college graduates raised highschool dropouts’ wages by 1.9%, high schoolgraduates’ wages by 1.6%, and college gradu-ates’ wages by 0.4%. Everyone gained from theeducated workforce. The least educated gainedmore (collectively) than the most educated, buteven the college graduates received a bonuson top of their private returns to their owneducations for working among other collegegraduates. Furthermore, data matching work-ers and firms indicated that the social returnscame from productivity gains (Moretti 2004b).

Some of the productivity gains came fromthe social pressure that more productive work-ers (regardless of education) created and howless productive workers felt that pressure (Mas

& Moretti 2009). Highly productive workersmight either stimulate coworkers to lift theirperformance or they might make it possiblefor coworkers to put in less effort, yielding thesame overall output. Mas & Moretti (2009)found that both occur, but that social pres-sure to carry one’s weight plus learning-by-observing predominate. They reached that con-clusion by recording the distance between themost productive person in a retail store andthe other workers. Nearby workers had largergains in productivity than workers farther away.Most tellingly, “workers exhibit[ed] coopera-tive behavior only when they [were] observedby coworkers and when they [were] likely to in-teract with them again in the future” (Mas &Moretti 2009, p. 143). This combination of so-cial pressure and learning helps interpret thesocial returns to education.

If education boosts collective productivityas well as personal productivity as these papersand others like them suggest, then increasingeducational attainment for a population mightbe a key causal factor in overall economicgrowth. In fact, estimated social returns toeducation exceed private returns (Lange &Topel 2006). Metropolitan areas, states, andnations gain from having educated populations.

States invest huge sums in education. Re-searchers in Texas and California have esti-mated the return on these public investments.In The Texas Challenge, Murdock et al. (2003)totaled public outlays for higher education incommunity colleges and state universities inTexas. They found that the combined benefitsof lower use of public assistance, lower crimeand incarceration, and higher payback in theform of sales, property, and state income taxesyielded Texas more than $4.00 for every $1.00invested in higher education. In our replicationof the Texas calculations, Brady et al. (2005)found a net return of $3.65 in California.

Family

In the 1990s, inequality researchers reportedthat family life was dividing along educationallines in ways that it had not done in the past

392 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


(Ellwood & Jencks 2004). Children were sub-stantially more likely to live with two adults iftheir mother was a college graduate than if theirmother was a high school dropout (Figure 4).

Separating causation and selection here iscomplicated. Few studies have sorted throughthe links. Becker’s (1991) theories start with avery stable world of perfect foresight that en-ables young women to choose a lifelong trajec-tory of schooling, mate, and babies all at once.They cannot have it all—at least not all at thesame time—so they must choose the sequenceand timing of events such as graduation, mar-riage, and each birth, as well as the amountof education and desired number of children.The simultaneity of these strategizing decisionsmakes separating causal effects of schooling onfertility or vice versa very difficult.

Real life adds complexity, starting with thefact that many births are unplanned. Even in aworld of effective contraception and legal abor-tion, errors occur. Accidental pregnancies re-sult in extra births or births that occur soonerthan planned; effectively delaying any attemptsto get pregnant often results in fewer births orbirths that occur later than planned (Morgan &Taylor 2006).

Demographers have used data on unplannedbirths and miscarriages to disentangle the ef-fects of births and education. Some early studies(Rindfuss et al. 1980) used two-equation mod-els to explore relationships and concluded thateducation almost certainly affected fertility butthat the reciprocal effect of fertility on educa-tion was much less certain. Since then, mostanalyses have been purely correlational. NowBrand & Davis (2011) have used propensityscores to estimate the effect of education on fer-tility. They found that entering college at age19 reduced the total number of children everborn to those women. Entering college clearlyreduced births per woman if they were un-likely to enroll in college; it was not clear if go-ing to college mattered for those whose familybackground and academic achievement madecollege very likely.

Beyond fertility, theory predicts thateducated couples will stay together longer,

50

60

70

80

90

Ch

ild

ren

liv

ing

wit

h t

wo

ad

ult

s (%

)

1940 1950 1960 1970 1980 1990 2000Year

College degreeSome collegeHigh school diplomaNo diploma

Education ofmost educated adult

Figure 4Children living with two adults: United States 1940–2000. Source: Fischer &Hout 2006, p. 82.

contributing to the pattern in Figure 4. Causalanalysis has not resolved this issue, althoughthe timing of events strongly supports the in-ference that education increases the stability ofmarriages (Schwartz 2010). Furthermore, theincrease in educational homogamy reflects thisgreater stability, as having similar educationsreduces a couple’s probability of divorcing(Schwartz 2010).

Health

College graduates are decidedly healthier thanothers (Figure 5). This basic relationshiphas been replicated hundreds of times by re-searchers (Mirowski & Ross 2003). The ques-tion of causality is hard to settle, though. Therelationship is not direct; many social, behav-ioral, and biological factors stand between at-tainment of a college degree and quality ofhealth later in life (where most of the varianceis). There is even some concern that healthypeople might achieve more education by miss-ing less school, concentrating better, and thelike.

Lleras-Muney (2005) used state-to-statevariation in mandatory schooling to identifya causal effect on mortality. Her IV estimateshowed that achieving more schooling low-ered the risk of premature death. Other studies


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


0

10

20

30

40

50

GS SHS HSG SC AA BA MA+Education

Very happy

ObservedModeled

Excellent health

ObservedModeled

Ha

pp

ine

ss a

nd

he

alt

h (

%)

Figure 5Happiness and health by education: United States 2006–2010. Key toeducation labels: GS = grade school (0–8 years completed, no diploma),SHS = some high school (9–12 years completed, no diploma), HSG = highschool graduate (any number of years completed, high school diploma orGED), SC = some college, AA = degree from two-year college, BA =degree from four-year college, MA+ = advanced degree (e.g., MA, MBA,PhD, MD). Source: author’s calculations from Smith et al. 2010, persons25–64 years old, educated in the United States, 2006–2010 pooled.

(Cutler & Lleras-Muney 2006) have replicatedthe finding in Europe.

Mirowski & Ross (2003) argued for edu-cation as learned effectiveness. They carefullyspecified the direct and indirect paths fromeducation to positive health outcomes andconcluded that the statistical associations arerobust because in acquiring formal educationpeople learn things that promote good health.Recent evidence shows that education doesmore to suppress the onset of health problemsthan to aid recovery (Herd et al. 2007).

Social Capital and Morale

College graduates participate more fully in civilsociety and politics (Verba et al. 1995, Nieet al. 1996, Putnam 2000). The question iswhether education actually increases participa-tion or perhaps educated people just have anattribute that increases both their educationand their participation. Milligan et al. (2003)produced IV estimates that imply that educa-tion increased voter registration, knowledge,and turnout in the United States. Hauser (2000)

studied academic abilities and concluded thateducation had a far stronger effect on youngpeople’s social capital than their verbal andquantitative abilities. Brand (2010) found thata college degree raised the civic participation ofunlikely college graduates more than it raisedparticipation among traditional college gradu-ates when participation consisted of volunteer-ing to do unpaid work for community organiza-tions and charities. College graduates also hadprosocial attitudes toward civil liberties and mi-norities (Kingston et al. 2003).

Happiness research has had a renaissance inpsychology, sociology, and economics in thepast two decades. Much of that work centerson the role of money in subjective well-being.But sociologists have given education an equalamount of attention. Figure 5 shows the simpleassociation between the General Social Surveyhappiness question and education along withdata on subjective health. Sophisticated analy-ses (e.g., Yang 2008) show that educational dif-ferentials are robust with respect to happiness,but I know of no attempts to identify the causaleffect.

CONCLUSION

Education makes life better. People who pur-sue more education and achieve it make moremoney, live healthier lives, divorce less often,and contribute more to the functioning and ci-vility of their communities than less educatedpeople do. We would expect some of these pat-terns to emerge even if schools and colleges dolittle more than certify who is smart and whois not. But the evidence reviewed here pointsto a more substantive role for education inAmerica. Most recent evidence supports theproposition that education improves people inways that matter later in life. Some of those areskills that they could, in principle, pick up athome, on the job, or elsewhere. For example,most people learn to read in school. The factthat some learn at home suggests that otherscould, too. But education works for these kindsof widespread, general skills because the resultsare more sure and the process is more efficient

394 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


in the school setting. It is also more egalitarian;acquiring the skill does not depend on parentsand siblings mastering it and passing on theirmastery (Downey et al. 2004).

Other skills are much harder to acquire out-side school. Specific skills such as how to cal-culate the forces on a weight-bearing wall, theelements of the periodic table, the formula forcompound interest, or how to make sense ofShakespeare, Nieztsche, or Matisse come tomind. Then come broader skills such as howto marshal facts and rhetoric to craft a reasonedargument, or how to discipline oneself to seea task through from beginning to end. Manypeople learn these things at home, but schoolscounter the inequality that home-learning fos-ters. Inequality of educational opportunity per-sists (Lucas 2001, Lareau 2003, Hout & Janus2011), but it would be even more unequal with-out schools (Downey et al. 2004, Pfeffer 2008).

For all the advances in establishing the causalrole of education, we have learned surprisinglylittle about what exactly the educational treat-ment is (Arum & Roksa 2010). The researchsuggests that a mix of academic knowledgeand useful habits makes people better employ-ees, patients, and citizens. And although hav-ing talent or potential can accelerate the learn-ing that goes on in school, it is, demonstrably,the schooling itself that separates the promis-ing from the accomplished young person. Howhigh schools and colleges accomplish that is farless clear. Researchers need to look more closelyat the variety of educational experiences. Ac-complishing these next steps will not be easy.The problems of selection and heterogeneitycompound as we move from the causal impactof education to the causal mechanisms of ed-ucation. Take selective women’s colleges as acase in point. The young women who choosewomen’s colleges are hardly a random drawfrom the population of young women. Almostall of them have high school academic and so-cial accomplishments that make them strongprospects for admission to equally selective co-educational colleges. Some have chosen thewomen’s college for reasons such as a betterfinancial aid package or being near home. But

most choose a women’s college over a compa-rable coeducational one because the women’scollege is the right fit—their personal return islikely bigger than that for women who go some-where else would have been.

Probably the biggest surprise in recent re-search concerns the interaction of ability andschooling. Evidence from both high school andcollege research implies that the young peo-ple who benefit most from education are notthe most talented but rather those who haveskills and abilities in the middle of the range.It appears that the most talented students dowell on their own and the least talented onesdo not prosper anywhere. The broad middlerange of roughly average talent respond mostto variation in the schooling treatment. This isa crucial policy point. It means that through-out the history of American higher educationwe have seen appreciable gains by pushing thefrontier of opportunity further up the achieve-ment ladder and further down the selection lad-der (Goldin & Katz 1999). Continuing so thatthe nation can see half its young people succeedin college—the Obama administration’s goal—will yield even greater returns because the ex-pansion will embrace precisely the segmentof the population most likely to benefit fromit.

Stevens et al. (2008) characterized Americanhigher education as (a) sieve, (b) incubator,(c) temple, and (d ) hub. The research reviewedhere underscores all four. The functions over-lap; there is no adjudicating among them. Theyrefer to the ways higher education (a) stands be-tween the home environment of childhood andadult achievement; (b) creates the world-apartof the residential college and, for those whocommute, offers a respite from noneducationalresponsibilities; (c) collectively and simultane-ously produces new knowledge and legitimatessome forms of knowing but not others; and(d ) is the field on which the interests of family,industry, and the state coalesce. All four dependon and support the effects of education enumer-ated in this review. If higher education were nottied to economy and society by the causal rela-tionships identified in recent research, then it


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


would not be sieve, incubator, temple, or hub.It would still be the finishing school it once wasfor the offspring of elites who showed an inter-est in the arts and sciences.

Throughout this review, I have taken thepragmatist’s point of view by asking what ed-ucation is good for. I nonetheless recognize thetruth of what Abbott (2002) told an audience offreshmen in September 2001: The pragmaticview undersells education. Knowledge is bet-ter than ignorance, even if we never find usefor what we know. But if the topic is public in-vestment in education—and the United Statesis in the unenviable position of investing a lot

but not enough—then education has to justifyitself on pragmatic grounds. The research re-viewed here shows that education yields bothpersonal and social returns on investment.Education pays off because, in addition to sort-ing and certifying America’s young people, itadds value. In the nation’s colleges and univer-sities, students acquire new skills and new per-spectives that make them better workers, lifepartners, and citizens. The universities do notmerely identify the young people who fit thedesired profile, they disseminate skills and fos-ter values. Higher education causes good thingsto happen.

DISCLOSURE STATEMENT

The author is not aware of any affiliations, memberships, funding, or financial holdings that mightbe perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS

The author thanks Neil Fligstein for extensive discussions of these issues and Jennie Brand, ClaudeFischer, Ronald Lee, Mitchell Stevens, Josipa Roksa, Florencia Torche, and Steve Vaisey foradditional comments. The author acknowledges the financial support of the Berkeley PopulationCenter (National Institute of Child Health and Human Development grant R21 HD056581).These contents are solely the responsibility of the author and do not necessarily represent theofficial views of the National Institute of Child Health and Human Development.

LITERATURE CITED

Abbott A. 2002. The aims of education. Univ. Chicago Rec. 37(Nov. 21):4–8Angrist JD, Krueger AB. 1991. Does compulsory schooling attendance affect schooling and earnings? Q. J.

Econ. 106:979–1014Angrist JD, Krueger AB. 1992. Estimating the payoff to schooling using the Vietnam-era draft lottery. NBER Work.

Pap. 4067, Natl. Bur. Econ. Res., Cambridge, MA. http://www.nber.org/papers/w4067Arum R. 1998. Invested dollars or diverted dreams: the effects of resources on vocational student educational

outcomes. Sociol. Educ. 71:130–51Arum R, Roksa J. 2010. Academically Adrift. Chicago: Univ. Chicago PressArum R, Roksa J, Budig M. 2008. The romance of college attendance: higher education stratification and

mate selection. Res. Soc. Stratif. Mobil. 26:107–21Attewell P, Lavin DE. 2007. Passing the Torch: Does Higher Education for the Disadvantaged Pay Off Across the

Generations? New York: Russell Sage Found.Bailey MJ, Dynarski SM. 2011. Inequality in postsecondary education. In Whither Opportunity? Rising Inequal-

ity, Schools, and Children’s Life Chances, ed. GJ Duncan, R Murnane, pp. 117–32. New York: Russell SageFound.

Baker DP. 2009. The educational transformation of work: towards a new synthesis. J. Educ. Work 22(3):163–91Becker GS. 1991. A Treatise on the Family. Cambridge, MA: Harvard Univ. Press

396 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.

http://www.nber.org/papers/w4067


Berg I. 1970. Education and Jobs: The Great Training Robbery. New York: PraegerBlack DA, Smith JA. 2006. Estimating the returns to college quality with multiple proxies for quality.

J. Labor Econ. 24(3):701–28Blau PM, Duncan OD. 1967. The American Occupational Structure. New York: WileyBound J, Herschbein B, Long BT. 2009. Playing the admissions game: student reactions to increasing college

competition. J. Econ. Perspect. 23:119–46Bowen WG, Bok DC. 1998. The Shape of the River: Long-Term Consequences of Considering Race in College and

University Admissions. Princeton, NJ: Princeton Univ. PressBowen WG, Chingos MM, McPherson MS. 2009. Crossing the Finish Line: Completing College at America’s

Public Universities. Princeton, NJ: Princeton Univ. PressBrady HB, Hout M, Stiles J. 2005. Return on Investment: Educational Choices and Demographic Change in

California’s Future. Berkeley, CA: Surv. Res. Cent. Rep.Brand JE. 2010. Civic returns to higher education. Soc. Forces 89:417–34Brand JE, Davis D. 2011. The impact of college education on fertility: evidence of heterogeneous effects.

Demography 48:863–87Brand JE, Xie Y. 2010. Who benefits most from college? Evidence for negative selection in heterogeneous

economic returns to higher education. Am. Sociol. Rev. 75:273–302Breen R, Luijkx R. 2004. Conclusions. In Social Mobility in Europe, ed. R Breen, pp. 383–410. Oxford: Oxford

Univ. PressBrint S, Karabel J. 1989. Diverted Dreams: Community Colleges and the Promise of Educational Opportunity,

1900–1985. New York: Oxford Univ. PressCarbonero W. 2007. The effects of education and cognitive skill on earnings: How much do occupations and

jobs matter? Res. Soc. Stratif. Mobil. 25:57–71Card D. 1999. Causal effect of education. Handb. Labor Econ. 3:1802–63Card D. 2001. Estimating the return to schooling: progress on some persistent econometric problems.

Econometrica 69:1127–60Carneiro P, Heckman JJ, Vytlacil E. 2011. Estimating marginal and average returns to education. Am. Econ.

Rev. 101:2754–81Collins R. 1971. Functional and conflict theories of educational stratification. Am. Sociol. Rev. 36:1002–19Collins R. 1979. The Credential Society. New York: WileyCutler DM, Lleras-Muney A. 2006. Education and health: evaluating theories and evidence. In Making

Americans Healthier, ed. RF Schoeni, JS House, GA Kaplan, H Pollack, pp. 29–60. New York: RussellSage Found.

Dale SB, Krueger AB. 2002. Estimating the payoff to attending a more selective college: an application ofselection on observables and unobservables. Q. J. Econ. 117:1491–527

Dale SB, Krueger AB. 2011. Estimating the return to college selectivity over the career using administrative earningdata. Ind. Relat. Work. Pap. 563, Princeton Univ.

Deaton A. 2010. Instruments, randomization, and learning about development. J. Econ. Lit. 48:424–55DiPrete TA, Buchmann C. 2006. Gender-specific trends in the value of education and the emerging gender

gap in college completion. Demography 43:1–24Downey DB, von Hippel P, Broh B. 2004. Are schools the great equalizer? Cognitive inequality during the

summer months and the school year. Am. Sociol. Rev. 69:613–35Ellwood D, Jencks C. 2004. The uneven spread of single-parent families: What do we know? Where do we

look for answers? In Social Inequality, ed. K Neckerman, pp. 3–78. New York: Russell Sage Found.Fernandez R. 2001. Skill-biased technological change and wage inequality: evidence from a plant retooling.

Am. J. Sociol. 107:273–320Fischer CS, Hout M. 2006. Century of Difference: How America Changed in the Last 100 Years. New York: Russell

Sage Found.Fischer CS, Hout M, Sanchez-Jankowski M, Lucas SR, Swidler A, Voss K. 1996. Inequality by Design: Cracking

the Bell Curve Myth. Princeton, NJ: Princeton Univ. PressFreeman R. 1976. The Overeducated American. New York: AcademicGangl M. 2006. The scar effects of unemployment: an assessment of institutional complementarities.

Am. Sociol. Rev. 71:986–1013


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


Gangl M. 2010. Causal inference in sociological research. Annu. Rev. Sociol. 36:21–47Goldin C, Katz LF. 1999. The shaping of higher education: the formative years in the United States, 1890 to

1940. J. Econ. Perspect. 13(1):37–62Goldin C, Katz LF. 2007. The Race Between Education and Technology. Cambridge, MA: Belknap PressGriliches Z. 1977. Estimating the returns to schooling: some econometric problems. Econometrica 45:1–22Harding DJ, Jencks C, Lopoo LM, Mayer SE. 2004. The changing effect of family background on the incomes

of American adults. In Unequal Chances: Family Background and Economic Success, ed. S Bowles, H Gintis,MO Groves, pp. 100–44. Princeton, NJ: Princeton Univ. Press

Harmon C, Walker I. 1995. Estimates of the returns to schooling for the United Kingdom. Am. Econ. Rev.85:1278–86

Hauser RM. 1970. Educational stratification in the United States. Sociol. Inq. 40:102–29Hauser RM. 2002. Meritocracy, cognitive ability, and the sources of occupational success. Presented at Annu. Meet.

Am. Sociol. Assoc., Aug. 17, Chicago, ILHauser RM, Warren JR. 1997. Socioeconomic indexes for occupations: a review, update, and critique. Sociol.

Methodol. 27:177–298Hauser S. 2000. Education, ability, and civic engagement in the contemporary United States. Soc. Sci. Res.

29:556–82Heckman JJ, Stixrud J, Urzua S. 2006. The effects of cognitive and noncognitive abilities on labor market

outcomes and social behavior. J. Labor Econ. 24:411–82Herd P, Goesling B, House JS. 2007. Socioeconomic position and health: the differential effects of education

versus income on the onset versus progression of health problems. J. Health Soc. Behav. 48:223–38Hoffer T, Greeley AM, Coleman JS. 1985. Achievement growth in public and Catholic schools. Sociol. Educ.

58:74–97Hout M. 1984. Status, autonomy, and training in occupational mobility. Am. J. Sociol. 89:1379–409Hout M. 1988. More universalism and less structural mobility: the American occupational structure in the

1980s. Am. J. Sociol. 93:1358–400Hout M, Janus A. 2011. Educational mobility in the United States since the 1930s. In Whither Opportunity?

Rising Inequality, Schools, and Children’s Life Chances, ed. GJ Duncan, R Murnane, pp. 165–86. New York:Russell Sage Found.

Hout M, Levanon A, Cumberworth E. 2011. Job loss and unemployment. In The Great Recession, ed. DBGrusky, B Western, CT Wimer, pp. 59–81. New York: Russell Sage Found.

Houthakker HS. 1959. Education and income. Rev. Econ. Stat. 41:24–28Hoxby C. 2009. The changing selectivity of American colleges. J. Econ. Perspect. 23:95–118Julian T, Kominski R. 2011. Education and synthetic work-life earnings estimates. Am. Community Surv. Rep.

ACS-14, US Census Bur., Washington, DCKane TJ. 1999. The Price of Admission. New York: Russell Sage Found.Kane TJ, Rouse CE. 1995. Labor market returns to two- and four-year colleges: Is a credit a credit and do

degrees matter? Am. Econ. Rev. 85:600–14Karen D. 2002. Changes in access to higher education in the United States: 1980–1992. Sociol. Educ. 75(3):191–

210Kaymak B. 2009. Ability bias and the rising education premium in the US: a cohort-based analysis. J. Hum.

Cap. 3:224–67King M, Ruggles S, Alexander JT, Flood S, Genadek K, et al. 2010. Integrated Public Use Microdata Ser., Current

Population Survey: Version 3.0. (Machine-readable database). Minneapolis: Univ. Minn.Kingston PW, Hubbard R, Lapp B, Schroeder P, Wilson J. 2003. Why education matters. Sociol. Educ. 76:53–

70Lange F, Topel R. 2006. The social value of education and human capital. Handb. Econ. Educ. 1:459–509Lareau A. 2003. Unequal Childhoods. Berkeley: Univ. Calif. PressLleras-Muney A. 2005. The relationship between education and adult mortality in the United States.

Rev. Econ. Stat. 72:181–217Lucas SR. 2001. Effectively maintained inequality: education transitions, track mobility, and social background

effects. Am. J. Sociol. 106:1642–90

398 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


Marcotte DE, Bailey T, Borkoski C, Kienzl GS. 2005. The returns of a community college education: evidencefrom the National Education Longitudinal Survey (NELS). Educ. Eval. Policy Anal. 27:157–75

Mare RD. 1981. Change and stability in educational stratification. Am. Sociol. Rev. 46:72–87Mas A, Moretti E. 2009. Peers at work. Am. Econ. Rev. 99:112–45Maurin E, McNally S. 2008. Vive la revolution! Long-term educational returns of 1968 to the angry students.

J. Labor Econ. 26:1–33Miller KA, Kohn ML, Schooler C. 1986. Educational self-direction and personality. Am. Sociol. Rev. 51:372–90Milligan K, Moretti E, Oreopoulos P. 2003. Does education improve citizenship? Evidence from the US and the

UK. NBER Work. Pap. 9584, Natl. Bur. Econ. Res., Cambridge, MA. http://www.nber.org/papers/w9584.pdf

Mirowski J, Ross CE. 2003. Education, Social Status, and Health. Hawthorne, NY: Aldine de GruyterMoretti E. 2004a. Estimating the social return to higher education. J. Econom. 121:175–212Moretti E. 2004b. Workers’ education, spillovers, and productivity: evidence from plant-level production

functions. Am. Econ. Rev. 94:656–90Moretti E. 2012. The New Geography of Jobs. New York: Houghton Mifflin Harcourt. In pressMorgan SP, Taylor MG. 2006. Low fertility at the turn of the twenty-first century. Annu. Rev. Sociol. 32:375–99Murdock S, White S, Hoque N, Pecotte B, You X, Balkan J. 2003. The New Texas Challenge: Population Change

and the Future of Texas. College Station: Texas A&M Univ. PressNatl. Cent. Educ. Stat. 2009. 2007–08 National Postsecondary Student Aid Study (NPSAS:08): Student Financial

Aid Estimates for 2007–08. Washington, DC: US Dep. Educ.Nie NH, Junn J, Stehlik-Barry K. 1996. Education and Democratic Citizenship in America. Chicago: Univ.

Chicago PressNisbett RE. 2009. Intelligence and How to Get It. New York: NortonPfeffer FT. 2008. Persistent inequality in educational attainment and its institutional context. Eur. Sociol. Rev.

24(5):543–65Poletaev M, Robinson C. 2008. Human capital specificity. J. Labor Econ. 26:387–420Putnam RD. 2000. Bowling Alone: The Collapse and Revival of American Community. New York: Simon &

SchusterRaftery AE, Hout M. 1993. Maximally maintained inequality: expansion, reform, and opportunity in Irish

education, 1921–1975. Sociol. Educ. 66:41–62Reich R. 1992. The Work of Nations. New York: KnopfRindfuss RR, Bumpass L, St. John C. 1980. Education and fertility: implications for the roles women occupy.

Am. Sociol. Rev. 45:431–47Roksa J. 2005. Double disadvantage or blessing in disguise? Understanding the relationship between college

major and employment sector. Sociol. Educ. 78:207–32Rosenbaum JS, Deil-Amen R, Person AE. 2006. After Admission: From College Access to College Success.

New York: Russell Sage Found.Schwartz CR. 2010. Pathways to homogamy in marital and cohabiting unions. Demography 47:735–53Shauman KA. 2009. Are there sex differences in the utilization of educational capital among college-educated

workers? Soc. Sci. Res. 38:535–71Smith HL. 1986. Overeducation and underemployment: an agnostic review. Sociol. Educ. 59:85–99Smith TW, Marsden PV, Hout M. 2010. General Social Surveys Cumulative Data File, 1972–2010. [MDRF]

Storrs: Roper Cent. Public Opin. Res., Univ. Conn.Sorokin PA. 1927. Social and Cultural Mobility. Glencoe, IL: Free PressStephan JL, Rosenbaum JE, Person AE. 2009. Stratification in college entry and completion. Soc. Sci. Res.

38:572–93Stevens ML, Armstrong EA, Arum R. 2008. Sieve, incubator, temple, hub: empirical and theoretical advances

in the sociology of higher education. Annu. Rev. Sociol. 34:127–51Thurow L. 1975. Generating Inequality. New York: Basic BooksTopel R. 1999. Labor markets and economic growth. Handb. Labor Econ. 3:2943–83Torche F. 2011. Is a college degree still the great equalizer? Intergenerational mobility across levels of

schooling in the United States. Am. J. Sociol. 117:763–807


Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.

http://www.nber.org/papers/w9584.pdf

http://www.nber.org/papers/w9584.pdf


Tyson K. 2002. Weighing in: elementary-age students and the debate on attitudes toward school among Blackstudents. Soc. Forces 80:1157–89

US Dep. Educ. 2011. Digest of Education Statistics, 2010. Washington, DC: US Dep. Educ.Verba S, Schlozman KL, Brady HE. 1995. Voice and Equality: Civic Voluntarism in American Politics. Cambridge

MA: Harvard Univ. PressWarren JR, Halpern-Manners A. 2007. Is the glass emptying or filling up? Reconciling divergent trends in

high school completion and dropout. Educ. Res. 36:335–43Western B, Bloome D, Percheski C. 2008. Inequality among American families with children, 1975 to 2005.

Am. Sociol. Rev. 73:903–20Willis RJ, Rosen S. 1979. Education and self-selection. J. Polit. Econ. 87:S7–36Yang Y. 2008. Social inequalities in happiness in the United States, 1972–2004: an age-period-cohort analysis.

Am. Sociol. Rev. 73:204–26

400 Hout

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.

SO38-Frontmatter ARI 28 May 2012 12:26

Annual Reviewof Sociology

Volume 38, 2012Contents

Prefatory Chapters

My Life in SociologyNathan Glazer � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 1

The Race Discrimination SystemBarbara Reskin � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �17

Theory and Methods

Instrumental Variables in Sociology and the Social SciencesKenneth A. Bollen � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �37

Rational Choice Theory and Empirical Research: Methodologicaland Theoretical Contributions in EuropeClemens Kroneberg and Frank Kalter � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �73

Social Processes

Network Effects and Social InequalityPaul DiMaggio and Filiz Garip � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �93

Youth Political Participation: Bridging Activism and Electoral PoliticsDana R. Fisher � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 119

BrokerageKatherine Stovel and Lynette Shaw � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 139

Group Culture and the Interaction Order: Local Sociologyon the Meso-LevelGary Alan Fine � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 159

Resolution of Social ConflictRobin Wagner-Pacifici and Meredith Hall � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 181

Toward a Comparative Sociology of Valuation and EvaluationMichele Lamont � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 201

Construction, Concentration, and (Dis)Continuitiesin Social ValuationsEzra W. Zuckerman � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 223

v

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


Institutions and Culture

A Cultural Sociology of Religion: New DirectionsPenny Edgell � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 247

Formal Organizations

Status: Insights from Organizational SociologyMichael Sauder, Freda Lynn, and Joel M. Podolny � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 267

Outsourcing Social Transformation: Development NGOsas OrganizationsSusan Cotts Watkins, Ann Swidler, and Thomas Hannan � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 285

Political and Economic Sociology

The Arc of NeoliberalismMiguel A. Centeno and Joseph N. Cohen � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 317

Differentiation and Stratification

Economic Insecurity and Social StratificationBruce Western, Deirdre Bloome, Benjamin Sosnaud, and Laura Tach � � � � � � � � � � � � � � � � � � 341

The Sociology of ElitesShamus Rahman Khan � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 361

Social and Economic Returns to College Educationin the United StatesMichael Hout � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 379

Individual and Society

Race Relations Within the US MilitaryJames Burk and Evelyn Espinoza � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 401

Demography

The Future of Historical Family DemographySteven Ruggles � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 423

Causes and Consequences of Skewed Sex RatiosTim Dyson � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 443

Marital Instability and Female Labor SupplyBerkay Ozcan and Richard Breen � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 463

Urban and Rural Community Sociology

Urbanization and the Southern United StatesRichard Lloyd � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 483

Making a Place for Space: Spatial Thinking in Social ScienceJohn R. Logan � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 507

vi Contents

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.


Sociology and World Regions

Islam Moves West: Religious Change in the First and SecondGenerationsDavid Voas and Fenella Fleischmann � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 525

Indexes

Cumulative Index of Contributing Authors, Volumes 29–38 � � � � � � � � � � � � � � � � � � � � � � � � � � � 547

Cumulative Index of Chapter Titles, Volumes 29–38 � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 551

Errata

An online log of corrections to Annual Review of Sociology articles may be found athttp://soc.annualreviews.org/errata.shtml

Contents vii

Ann

u. R

ev. S

ocio

l. 20

12.3

8:37

9-40

0. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

by U

nive

rsity

of

Geo

rgia

on

06/2

0/13

. For

per

sona

l use

onl

y.

Documents

Social and Economic Returns to College Education in the United … · 2017-02-02 · Social and Economic Returns to College Education in the United States Michael Hout Department