Bowles-Gintis 2002

Journalof Economic Perspectives—Volume 16,Number 3—Summer 2002—Pages 3– 30

TheInheritance ofInequality

SamuelBowles and HerbertGintis

eoplediffer markedly in their views concerning the appropriate role of governmentin reducingeconomic inequality. Self-interest and differences P invaluesexplain part ofthe con ict over redistribution. But by far the most importantfault line is that peoplehold differentbeliefs about whythe rich are rich and thepoor are poor. Surveydata show that people—rich and pooralike— who thinkthat “gettingahead and succeedingin life” depends on “hard work”or “willingnessto take risks” tend tooppose redistributiveprograms. Conversely, those who thinkthat thekey to success is“moneyinherited from family,” “parents and the familyenvironment,” “connections and knowingthe right people” or being white support redistribution(Fong, 2001;Fong, Bowlesand Gintis,2002). Handing down success strikesmany peopleas unfaireven if the stakes are small, while differences inachieved success maybe unobjectionable even with high stakes, as longas the playing eldis considered level. How levelis the intergenerational playing eld? 1 What arethe causal mechanisms that underliethe intergenerational transmission ofeconomic status? Arethese

1 SeeBowles and Gintis(2001) forthe relevantformal models and othertechnical aspects ofthis research,also available at http://www.santafe.edu/s/ publications/working-papers.html . Arrow, Bowlesand Durlauf(1999) and Bowles,Gintis and Osborne(forthcoming) presentcollections of recent empiricaland theoreticalresearch. y Samuel Bowles isProfessorof Economics attheUniversit yofSiena, Siena, Italy, and Directorof the Economics Program,Santa Fe Institute,SantaFe, New Mexico.Herbert Gintisis a member ofthe External Faculty, SantaFe Institute,SantaFe, New Mexico. Bothauthors are Emeritus Professors of Economics,Universit yofMassachusetts,Amherst, Massachusetts.Their e-mail addressesare [email protected] and [email protected] , andtheir websites are http://www-unix.oit.umass .edu/bowles and http://www- unix.oit.umass.edu/ gintis . 4Journalof Economic Perspectives

mechanisms amenableto public policies in a waythat wouldmake the attainment of economicsuccess morefair? These are the questions wewill try to answer. Noone doubts that thechildren of well-off parents generallyreceive more and betterschooling and bene tfrommaterial, cultural and geneticinheritances. But untilrecently, the consensus among economistshas beenthat intheUnited States, success islargely won orlost in every generation. Early research on thestatistical relationshipbetween parents ’ and theirchildren ’seconomicstatus afterbecoming adults, startingwith Blau and Duncan (1967),found onlya weakconnection and thus seemedto con rmthat theUnited States was indeedthe “land ofopportunity.” Forexample, the simple correlations between parents ’ and sons’ income or earnings(or their logarithms) in theUnited States reported by Becker and Tomes (1986)averaged 0.15, leading the authors toconclude: “Asidefrom families vic- timizedby discrimination . ..[a]lmostall earnings advantages and disadvantages of ancestors arewiped out inthree generations. ” Becker(1988) expressed a widely heldconsensus when, inhis presidentialaddress tothe American Economics Association, heconcluded (p. 10): “[L]owearnings as wellas high earningsare not stronglytransmitted from fathers to sons. ” Butmore recent research shows that theestimates of high levelsof intergen- erationalmobility were artifacts of two types of measurement error: mistakes in reportingincome, particularly when individualswere asked torecall the income of theirparents, and transitorycomponents incurrent income uncorrelated with underlyingpermanent income (Bowles, 1972; Bowles and Nelson,1974; Atkinson, Maynard and Trinder,1983; Solon, 1992,1999; Zimmerman, 1992). The high noise-to-signal-ratioin theincomes of both generationsdepressed the intergenerationalcorrelation. When corrected,the intergenerational correlations for economicstatus appear tobe substantial, many ofthem three times the average of the U.S. studiessurveyed by Becker and Tomes(1986). Thehigher consensus estimatesof the intergene rationaltransmissi on of economicsuccess has stimulatedempiricalresearch.The relevant facts on which mostresearche rsnow agreeinclude the following :brothers ’ incomes are much moresimilar than those ofrandomly chosen malesof the same race and similarage differen ces; theincomes of identical twins are much moresimilar than fraternaltwins or non-twin brothers;the children of well-offparents obtain moreand higherquality schooling; and wealthinheritan cemakesan important contributionto thewealth owned bytheoffspring of thevery rich. Onthebasis ofthese and otherempirica lregularities,it seems safe toconclude that the intergenerationaltransmissi on ofeconomic status isaccounted forby a heter- ogeneouscollecti on ofmechanism s, includingthe genetic and culturaltrans- missionof cognitive skills and noncognitivepersonali tytraits in demand by employers, theinheritan ceof wealth and income-enhancing groupmember- ships, such asrace, and thesuperior education and health status enjoyedby the childrenof higher status families. However,the transmission ofeconomic success across generationsremains somethingof a blackbox. We nd that thecombined inheritance processes Samuel Bowles andHerbert Gintis 5

operatingthrough superiorcognitive performance and educational attainments of those withwell-off parents, whileimportant, explainat mostthree- fths of the intergenerationaltransmission ofeconomic status. Moreover,while genetic transmissionof earnings-enhancing traitsappears toplay a role,the genetic transmission ofIQ appears tobe relatively unimportant. It mightbe thought that theblack box is an artifactof poor measurement of theintervening variables relative to the measurement of theincome or earnings of parents and offspring.But this does not seemto be thecase. Yearsof schooling and othermeasures of school attainment, likecognitive performance, are measured withrelatively little error. Better measurements will of course help; but wearenot likelyto improve much on ourmeasures of IQ, and recentimprovements in the measurementof school qualityhave not givenus much illuminationabout what ’s goingon insidethe black box. Thefundamental problemis not that weare measuringthe right variables poorly, but that wearemissing some of theimportant variablesentirely. What mightthese be? Most economicmodels treat one ’sincomeas thesum ofthe returns to the factors ofproduction onebrings to themarket, like skills, or capital goods. But any individualtrait that affectsincome and forwhich parent-offspringsimilarity is strongwill contribute to the intergenerational transmission ofeconomic success. Included arerace, geographical location, height,beauty or other aspects ofphysical appearance, health status and personality.Thus, bycontrast tothe standard approach, wegive considerable attention to income-generating characteristics that arenot generallyconsidered to be factors ofproduction. In studiesof the intergenerationaltransmission ofeconomicstatus, ourestimates suggest that cognitive skillsand education have beenoverstudied, while wealth, race and noncognitive behavioraltraits have beenunderstudied.

Measuring the Intergenerational Transmission of EconomicStatus

Economicstatus can bemeasured in discrete categories —bymembership in hierarchicallyordered classes, forexample — orcontinuously, byearnings, income orwealth.The discrete approach allowsa richbut dif cult-to-summarizerepresen- tation ofthe process ofintergenerational persistence of status using transition probabilitiesamong therelevant social ranks (Eriksonand Goldthorpe,1992; this issue). Bycontrast, continuous measuresallow a simplemetric of persistence, based onthecorrelation between the economic status ofthe two generations. Moreover, thesecorrelations may be decomposed into additive components re ecting the variouscausal mechanisms accounting forparent-child economic similarity. Both approaches areinsightful, but herewe will rely primarily on thecontinuous measurementof status. Forreasons ofdata availability,we useincome or earnings as themeasure of economic status, though income(the more inclusive measure) is preferablefor most applications. Weuse subscript p torefer to parental measures, while y isan individual ’s 6Journalof Economic Perspectives

economicstatus, adjusted so that itsmean, y#,isconstant across generations, by is a constant, and «y isa disturbance uncorrelatedwith yp. Thus,

y 2 y# 5 by ~yp 2 y#! 1 «y ;

that is, thedeviation of the offspring ’seconomicstatus fromthe mean is by times thedeviation of the parent from mean economicstatus, plus an errorterm. In the empiricalwork reviewed below, earnings, income,wealth and othermeasures of economicsuccess aremeasured by their natural logarithmunless otherwisenoted.

Thus, by,termedthe intergenerational income elasticity, is thepercentage change inoffspring ’seconomicsuccess associated witha 1percentchange inparents ’ economicsuccess. Thein uenceof meaneconomic status on theeconomics status oftheoffspring, 1 2 by, is called regressionto themean, sinceit shows that onemay expectto be closer to the mean than one ’sparents bythe fraction 1 2 by (Goldberger,1989). Therelationship between the intergenerational income elasticity and the intergenerationalcorrelation is given by

syp ry 5 by , sy

where sy isthe standard deviationof y. If y isa natural logarithm,its standard deviationis a common unit-freemeasure of inequality. Thus, ifinequality is s 5 s r 5 b unchanging across generations,so yp y, then y y.However,the intergenerationalincome elasticity exceeds ry when incomeinequality is rising, but isless than ry when incomeinequality is declining. In effect,the intergenerational correlationcoef cient r isaffected by changes inthe distribution of incomewhile theintergenerational income elasticity is not. Also, r2 measuresthe fraction of the variancein this generation ’smeasureof economic success that islinearlyassociated withthe same measure in the previous generation. Estimatesof the intergenerational income elasticity are presented in Solon (1999,this issue)and Mulligan(1997). The mean estimates reported in Mulligan areas follows:for consumption, 0.68;for wealth, 0.50; for income, 0.43; for earnings(or wages), 0.34; and foryears of schooling, 0.29.Evidence concerning trendsin the degree of income persistence across generationsis mixed. Most studiesindicate that persistencerises with age, is greater for sons than daughters and isgreater when multipleyears of income or earnings are averaged. The importanceof averaging multiple years to capturepermanent aspects ofeconomic status isdramatized in Mazumder (forthcoming). He used arichU.S. Social SecurityAdministration data setto estimate an intergenerationalincome elasticity of0.27,averaging son ’searningsover three years and fatherearnings averaged over twoyears. But the estimate increases to 0.47 when sixyears of the fathers ’ earnings areaveraged and to0.65 when 15years are averaged. TheInheritance of Inequality 7

Dointergen erationalelasticit iesof this magnitudemean that “rags to riches” isnomorethan afantasy formost poor children? The intergene rational correlation isan averagemeasure and maybe unillumin atingabout theprob- abilitiesofeconomic success conditionalon beingthe child of poor or rich parents. Calculatingtheseconditiona lprobabilitiesand inspectingthe entire transitionmatrixgives a morecomplete picture. The results of astudy byHertz (2002)appear inFigure 1 withthe parents arrangedby income decile (from poorto rich moving from left to right) and withadult childrenarranged by incomedecile along theother axis. Theheight of the surface indicatesthe likelihood ofmaking the transition from the indicated parents ’ decileto the children’s decile. Though theunderlying intergenerational correlation of incomes in the data setHertz (2002) used isa modest0.42, the differences in thelikely life trajectories ofthechildren of the poor and therich are substantial. The “twin peaks” represent those stuck inpovertyand af uence(though wedo not expectthe term “af uence trap” tocatch on). Ason born tothe top decilehas a22.9percent chance of attainingthe top decile(point D)and a40.7percent chance ofattaining the top quintile. A indicatesthat theson ofthe poorest decile has a1.3percent chance of attainingthe top decileand a3.7percent chance ofattaining the top quintile. C indicatesthat childrenof the poorest decile have a31.2percent chance ofoccu- pyingthe lowest decile and a50.7percent chance ofoccupying thelowest quintile, while B shows that theprobability that achildof therichest decile ends up inthe poorestdecile is 2.4 percent, with a 6.8percent chance ofoccupying thelowest quintile.Hertz ’stransmission matrixand otherstudies suggest that distincttrans- missionmechanisms maybe at workat variouspoints ofthe income distribution (Corakand Heisz,1999; Cooper, Durlauf and Johnson, 1994;Hertz, 2001). For example,wealth bequests may play a major roleat thetop oftheincome distribution, whileat thebottom, vulnerabilityto violence or other adverse health episodes maybe more important. Mobilitypatterns byrace also differdramatically (Hertz, 2002).Downward mobility from the top quartileto thebottom quartile is nearly ve timesas greatfor blacks as forwhites. Thus, whateverit is that accounts fortheir success, successful blacksdo not transmitit to their children as effectivelyas do successful whites.Correspondingly, blacks born tothe bottom quartile attain the top quartileat onehalf therate of whites.

Sources of Persistence: Cultural, Genetic and Bequest

Economicstatus does persistsubstantially across generations.We seek to uncoverthe channels through which parentalincomes in uenceoffspring incomes. Wedo this bydecomposing the intergenerational correlation (or the intergenerationalincome elasticity) into additive components re ectingthe contributionof various causal mechanisms. This willallow us toconclude, forexample, 8Journalof Economic Perspectives

Figure 1 IntergenerationalIncome Transition Probabilities

Notes: Theheight of the surfacein cell ( i, j)isthe probabilitythat apersonwhose parents ’ householdincome was inthe ith decilewill have householdincome in the jth decileas an adult. Theincome of the childrenwas measuredwhen they wereaged 26 or olderand was averagedover allsuch yearsfor which it was observed(an averageof ten years). Parents ’ incomewas averagedover allobserved years in which the childlived with the parents (an averageof 9.4 years). Source: FromPSID data, Hertz(2002). The10 3 10transition matrixon whichthis gureis based is availableat http://www-unix.oit.umass.edu/ gintis . that acertainfraction of the intergenerational correlation is accounted forby the geneticinheritance of IQ orby the fact that thechildren of rich parents arealso wealthy. It isa remarkablefact about correlationcoef cientsthat this can bedone. Moreover,the technique we use does not requirethat weintroduce variables in any particularorder. Suppose that parents ’ income(measured by itslogarithm, yp) and offspringeducation ( s)affectoffspring income (also measuredby its logarithm, y).

Likeany correlationcoef cient,this intergenerationalcorrelation rypy can be expressedas thesum ofthe normalized regression coef cientsof measures of b b parentalincome ( ypy)and offspringeducation ( ys)ina multipleregression predicting y,each multipliedby the correlation between yp and theregressor (which, ofcourse, forparental income itself is just 1). Anormalizedregression coef cientis the change inthe dependent variable, in standard deviationunits, associated witha onestandard deviationchange inthe independent variable. The directeffect ofparental income is thenormalized regression coef cientof parental incomefrom this regression.The education component ofthis decompositionof Samuel Bowles andHerbert Gintis 9

Figure 2 Representinga Correlationas the Sum of Direct and IndirectEffects

theintergenerational correlation is calledan indirecteffect. 2 Figure2 illustratesthis breakdown,which gives

ryyp 5 byp y 1 ryp sbys intergenerationalcorrelat ion 5 directeffect 1 indirecteffect.

Aslongas themultiple regression coef cientsare unbiased, thedecomposition is validwhatever the relationship among thevariables. Speci cally,it does not require that theregressors be uncorrelated. This decompositionallows us tobe more preciseabout our “black box” claimin theintroduction. Wemean that thedirect parentaleffect is a substantial fractionof the intergenerational correlation in a numberof studies allowing this comparison (Bowles,1972; Bowles and Nelson, 1974;Atkinson, Maynard and Trinder,1983; Mulligan, 1999). Our strategyis toestimatethe size of these direct and indirecteffects. Note that thedecomposition uses correlationsbetween parental incomes and other variables—schooling intheexample —thought tobecausally relatedto the income- generatingprocess. Thesecorrelations with parental income need not re ect causal relationships,of course. Butthe above decomposition can berepeated for thecorrelations between parental income and thecauses ofoffspring income, in somecases permittingcausal interpretations.For example, a study ofthe role of wealthin the transmission process could ask whyparental income and offspring wealthare correlated. Is itbequests and intervivos transfers or the cultural transmission ofsavings behaviorsthat account forthis correlation?Or do wesimply not knowwhy parent and offspringwealth is correlatedand as aresultshould avoid givingthe data acausal interpretation?Similarly, parent-offspring similarity in human capitalmay be due to genetic or culturalinheritance of whateverit takesto persistin schooling and toacquire skills and behaviorsthat arerewarded in the labormarket. Unlike the models of parental and childbehavior accounting for persistencepioneered by Becker and presentedin this issueby Grawe and

2 This decompositioncan befound in Blalock (1964) and isdescribed in the Appendixto this paper. Goldberger(1991) describesthe standard regressionmodel with normalized(mean zero, unit standard deviation)variables on whichit isbased. 10Journal of Economic Perspectives

Mulligan,our approach ismorediagnostic, not givingan adequate causal account ofthe transmission process, but indicatingwhere to look to nd thecauses. The nextsections ofthis paperwill explore such decompositions.

The Role of Genetic Inheritance of Cognitive Skill

One ofthe transmission channels deservesspecial attention not onlybecause ofitsprima facie plausibility, but also becauseof the extraordinary attention given toit in popular discussions ofthe subject. This isthe genetic inheritance of cognitiveskill. The similarity of parents ’ and offsprings ’ scoreson cognitivetests is welldocumented. Correlationsof IQ betweenparents and offspringrange from 0.42to 0.72, where the higher gurerefers to measures of average parental and averageoffspring IQ (Bouchard and McGue,1981; Plomin et al., 2000).The contributionof cognitive functioning toearnings both directlyand via schooling attainmenthas also beenestablished in a varietyof studies that estimatedetermi- nants ofearnings using IQ(and related)test scores. Thedirect effect of IQ on earningsis estimated from multiple regression studies that typicallyuse the logarithmof earningsas adependentvariable and estimatethe regression coef cients ofa varietyof explanatory variables, including performance on acognitivetest, years(and perhaps othermeasures) of schooling, ameasureof parental economic and/orsocial status, workexperience, race and sex.The indirect effect of IQ operatingthrough itscontribution to higher levels of educational attainmentis estimatedusing measuresof childhood IQ(alongwith other variables) to predict thelevel of schooling obtained. Wehave located65 estimatesof the normalized regression coef cientof a test scorein an earningsequation in 24differentstudies of U.S. data overa periodof threedecades. Our meta-analysis ofthese studies is presentedin Bowles, Gintis and Osborne (2002).The mean ofthese estimates is 0.15, indicating that astandard deviationchange inthecognitive score, holding constant theremaining variables (includingschooling), changes thenatural logarithmof earnings by about one- seventhof a standard deviation.By contrast, themean valueof the normalized regressioncoef cientof years of schooling inthe same equation predicting the natural logof earnings in these studies is 0.22, suggesting a somewhatlarger independenteffect of schooling. Wechecked to see if theseresults were dependent on theweight of overrepresented authors, thetype of cognitive test used, at what agethe test was takenand otherdifferences among thestudies and found no signi cant effects.An estimateof the causal impactof childhood IQon yearsof schooling (also normalized)is 0.53 (Winship and Korenman, 1999).A rough estimateof the direct and indirecteffect of IQ on earnings, callit b, is then b 5 0.15 1 (0.53)(0.22) 5 0.266. Dothese two facts —parent-childsimilarity in IQand an importantdirect and indirectcausal rolefor IQ ingeneratingearnings —implya major rolefor genetic inheritanceof cognitive ability in the transmission ofintergenerational economic TheInheritance of Inequality 11

status? One wayto formulate this questionis toask how similarwould parental and offspringIQ beif thesole source of the similarity were genetic transmission. Also, how similarwould the incomes of parents and offspringbe if therewere no other transmission channel? Forthis weneedsome genetics (the details are in theAppendix and inBowles and Gintis,2001) and afewterms —phenotype, genotype,heritability and the geneticcorrelation — unfamiliarto many economists. Aperson ’s IQ—meaning, a test score—is a phenotypic trait,while the genes in uencingIQ arethe person ’s genotypic IQ. Heritability isthe relationship between the two. Suppose that, fora givenenvironment, a standard deviationdifference in genotype is associated with a fraction h ofastandard deviationdifference in IQ. Then h2 istheheritability of IQ.Estimatesof h2 arebased on thedegree of similarityof IQamong twins, siblings, cousins and otherswith differing degrees of genetic relatedness. The value cannot behigherthan 1,and mostrecent estimates are substantially lower, possibly more likea half orless (Devlin, Daniels and Roeder,1997; Feldman, Otto and Chris- tiansen, 2000;Plomin, 1999). The geneticcorrelation isthe degree of statistical association betweengenotypes of parents and children,which is0.5if the parents ’ genotypesare uncorrelated ( “random mating ”).Butcouples tend tobe more similarin IQthan wouldoccur byrandom matechoice ( “assortativemating ”), and this similarityis associated withan unknown correlation m oftheirgenotypes. The effectis to raise the genetic correlation of parent and offspringto (1 1 m)/ 2. Usingthe method of decomposition introduced in the previous section, the correlation g betweenparental and offspringIQ that isattributable to genetic inheritanceof IQ aloneis the heritability of IQ timesthe genetic correlation. Thus, we have g 5 h2 (1 1 m)/2.Thecorrelation between parent and offspringincome that isattributable to genetic inheritance of IQ isthis correlationtimes the normalized(direct and indirect)effect of IQ on theincome of parents, timesthe analogous effectfor the offspring, or gb2 .Anotherway to see this isto notethat the correlationbetween parental income and offspringIQ that wewouldobserve were thegenetic inheritance of IQ theonly channel at workis gb,and this timesthe effectof offspring IQ on earnings, which is b,givesthe same result. Usingthe values estimated above, wesee that thecontribution of genetic inheritanceof IQ tothe intergenerational transmission ofincome is

~h2~1 1 m!/2!~0.266!2 5 .035~1 1 m!h2 .

If theheritability of IQ were0.5 and thedegree of assortation, m,were0.2 (both reasonable,if onlyballpark estimates) and thegenetic inheritance of IQ werethe onlymechanism accounting forintergenerational income transmission, then the intergenerationalcorrelation would be 0.01, or roughly 2 percentthe observed intergenerationalcorrelation. Note the conclusion that thecontribution of genetic inheritanceof IQ isnegligible is not theresult of any assumptions concerning assortativemating or the heritability of IQ: theIQ genotypeof parents could be 12Journal of Economic Perspectives

perfectlycorrelated and theheritability of IQ 100percent without appreciably changing thequalitative conclusions. Theestimate results from the fact that IQis just not an importantenough determinantof economic success. Mightthe small contribution of genetic inheritance of IQtoparent-offspring similarityof incomesbe theresult of measurement error in thecognitive measures? Thereare two issues here. First, what isthe reliability ofthe test: whatever the test measures,does itmeasurewell? Second, what isthe validity ofthetest: does thetest measurethe right thing? The concern that thetests are a verynoisy measureis misplaced.In fact, thetests are among themore reliable variables used instandard earningsequations, wherereliability is measured by the correlation between tests and retests,between odd and evennumbered items on thetests, and bymore sophisticated methods. Forthe commonly used ArmedForces Quali cation Test (AFQT), forexample —atestused topredict vocational success that isoftenused as ameasureof cognitive skills —thecorrelation between two test scores taken on successivedays bythe same person islikely to be higher than thecorrelation betweenthe same person ’sreportedyears of schooling orincomeon twosuccessive days. Thesecond concern, that thetests measure the wrong thing, isweightierand lesseasy to address withany certainty.Could itbethat cognitiveskills not measured onexistingtest instruments are both highlyheritable and have amajor impacton earnings, therebypossibly explaining a moresubstantial fractionof the transmission process?The search forgeneral cognitive measures that aresubstantially uncorrelatedwith IQ and predictiveof success inadult rolesbegan withEdward Thorndike’s(1919)paper on “socialintelligence. ” Somealternative test instruments, such as RobertSternberg and collaborators ’ “practicalintelligence ” predict economicsuccess inparticular occupations (Sternberget al., 1995;Williams and Sternberg,1995). But despite the substantial fameand fortunethat wouldhave accrued tosuccess inthis area, thequest that Thorndikelaunched threegenera- tions ago has yieldedno robust alternativeto IQ ,letalone one that ishighly heritable.Thus, thepossible existence of economically important but as yetun- measuredheritable general cognitive skills cannot beexcluded, but should at this stagebe treated as speculation. Indeed, weare inclined to think that availableestimates overstate the importance ofgeneral cognitive skill as adeterminantof earnings, sincein many respects takinga testis likedoing a job. Successfulperformance in either case resultsfrom acombination ofability and motivation,including the disposition to follow instruc- tions, persistence,work ethic and othertraits likely to contributeindependently to one’searnings. This isthe reason weeschew the common labelof a testscore as “cognitiveskill, ” but ratheruse the more descriptive term “cognitiveperformance. ” Eysenck(1994, p. 9), aleadingstudent ofcognitive testing, writes: “Low problem solvingin an IQtestis a measureof performance; personality may in uence performancerather than abstract intellect,with measurable effects on theIQ. An IQtestlasts forup to1 hour ormore, and considerations offatigue, vigilance, arousal, etc.may very well play a part. ” Thus, someof the explanatory power of the Samuel Bowles andHerbert Gintis 13

cognitivemeasure in predicting earnings does not re ectcognitive skill, but rather otherindividual attributes contributing to the successful performanceof tasks.

Genetic and Environmental Inheritance

Although thegenetic inheritance of IQ explainslittle of theintergenerational transmission process, this says nothing about thepossible importance of other geneticallytransmitted traits. Indeed, theremarkable income similarity of identical twinscompared to fraternal twins suggests that geneticeffects may be important. Wewill use the similarity of twinsto estimate the genetic heritability of income as wellas theenvironmental component ofintergenerational transmission. Buttwo words of caution arein order. First, as wewill demonstrate, our estimatesare quite sensitive to variations in unobserved parameters. Second, itis sometimesmistakenly supposed that iftheheritability of atraitis substantial, then thetrait cannot beaffectedmuch bychanging theenvironment. The fallacy of this viewis dramatizedby thecase ofstature. Theheritability of height estimated from U.S. twinsamples is substantial —about 0.90(Plomin et al., 2000).Moreover, there are signi cant heightdifferences among thepeoples of the world: Dinka men in theSudan average5 feetand 11inches —abittaller than Norwegianand U.S. militaryservicemen and awhopping 8inches tallerthan theHadza hunter- gatherersin southern Africa(Floud, Wachterand Gregory,1990). But the fact that Norwegianrecruits in 1761 were shorter than today’sHadza shows that evenquite heritabletraits are sensitive to environments. What can beconcluded froma nding that asmallfraction of the variance of a traitis due to environmental varianceis that policiesto alter the trait through changed environmentswill requirenonstandard environmentsthat differfrom the environments on which the estimatesare based. Considerthe case ofSouth Africa,where in 1993 (the year before Nelson Mandela becamepresident), roughly two-thirds of the intergenerational transmission ofearnings was attributableto the fact that fathersand sons areof the same race,and raceis a strongpredictor of earnings (Hertz, 2001). That is, adding race toan equationpredicting sons ’ earningsreduces the estimated effect of fathers ’ earningsby over two-thirds. Becausethe traits designated by “race” are highly heritableand interracialparenting uncommon, wethus nd asubstantial roleof geneticinheritance in the intergenerational transmission ofeconomic status. Yet, itisespeciallyclear in thecase ofSouth Africaunder apartheid that theeconomic importanceof the genetic inheritance of physical traitsderived from environmental in uences. What madethe genetic inheritance of skin color and otherracial markerscentral to the transmission process werematters of public policy, not human nature, includingthe very de nitionof races, racialpatterns inmarriage and thediscrimination suffered by nonwhites. Thus, thedetermination of the geneticcomponent ina transmission process says littleby itself about theextent to which publicpolicy can orshould levela playing eld. 14Journal of Economic Perspectives

Estimatesof heritability use data onpairsof individuals with varying degrees of shared genesand environments.For example, identical and fraternaltwins are exposedto similar environments during their upbringing, but fraternaltwins are lessclosely related genetically than identicaltwins. Underquite strong simplifying assumptions (explainedin theAppendix) one can exploitthe variation in genetic and environmentalsimilarities among pairsof relatives to estimate heritability of a traitsuch as income,years of schooling orother standard economicvariables. Taubman (1976)was the rsteconomist to use this method. Themodel underlying thefollowing calculations assumes that genesand environmentaffect human capital, which produces earnings, as theequation belowindicates, but theeffects of wealthand othercontributions to income are unaffected bygenes and environmentand willbe introduced subsequently. Hereare the assumptions. First,genes and environmentshave additive effects— genesand environmentmay be correlated, but thedirect effect of “good genes” onearnings(its regression coef cient)is independentof thequality of the environmentand conversely.Thus, an individual ’searningscan bewritten

earnings 5 h~genes! 1 b~environment ! 1 idiosyncraticeffects.

Second, within-pairgenetic differences (for the fraternals) are uncorrelated with within-pairenvironmental differences (for example, the good-looking twin does not getmore loving attention). Third, theenvironments affecting individual de- velopmentare as similarfor members of fraternalpairs of twinsas forthe identical twinspairs. Fourth, theearnings genotypes of the two parents areuncorrelated (“random mating ”).Giventhese assumptions, weshow inthe Appendix that the heritability( h2 )ofearnings is twice the difference between the earnings correlations ofidenticaland fraternaltwins. As thedifference between these two correlations is0.2 in best data setsavailable —theSwedish Twin Registry studied by Bjo¨rklund, Ja¨nttiand Solon(forthcoming) and asmallerU.S. Twinsburgdata set studiedby Ashenfelter and Krueger(1994) —theseassumptions givean estimateof h2 equalto 0.4. Because, dueto the assumption ofrandom mating,the correlation of genesfor thefraternal twins is 0.5, theimplied correlation of fraternal twins ’ earnings becauseof genetic factors is h2 /2.Thefact that theobserved correlation of twins ’ earningsexceeds this estimateis explained by the fact that twinsshare similar environments.Thus, once weknow h2 ,wecan useinformation about thedegree of similarityof these environments to estimate how largethe environmental effects wouldhave tobe to generate the observed earnings correlations. Theassumptions concerningrandom matingand common environmentsare unrealisticand can berelaxed.First, we need an estimateof my,thecorrelation of parents’ earningsgenotypes. The relevant measure is the earnings potential (the correlationof actual earningswould understate the degree of assortation, because many womendo not workfull time). The degree of assortation on phenotypeis likelyto be considerably larger than on genotypefor the simple reason that the TheInheritance of Inequality 15

basis oftheassortation isthephenotype, not thegenotype (which isunobservable), and thetwo are not veryclosely related for the case ofearnings, as wewill see. Assuming that thegenotype for potential earnings of parents ishalf as similaras are theactual incomesof brothers, the correlation would be about 0.2. Second, notethat becauseit was assumed that theenvironments experienced bythetwo identical twins are not, ontheaverage, more similar to the environments ofthetwo fraternal twins, thefact that within-twin-pairearnings differences are less forthe identical twins must beexplained entirely by their genetic similarity. But if theidentical twins experience more similar environments (because they look alike,for example) than thefraternals, the estimate will overstate the degree of heritability. It islikely that identicaltwins share moresimilar environments than fraternal twinsand othersiblings (Loehlin and Nichols, 1976;Feldman, Otto and Chris- tiansen, 2000;Cloninger, Rice and Reich,1979; Rao etal., 1982).Estimates of the extentto which theenvironments of identical twins are more similar than those of fraternaltwins are quite imprecise, and wecan do no betterthan toindicate the effectsof using plausiblealternative assumptions. Just how sensitivethe estimates areto reasonable variations in the assumptions concerningdifferences in the correlationsof twins ’ environmentscan beestimatedby assuming somedegree of statisticalassociation ofgenes and environment,with the correlated but not iden- ticalgenes of thefraternal twins giving them less correlated environments than the identicaltwins. Table1 presentsestimates based on variousmagnitudes of this genes- environmenteffect. As theassumed correlationbetween genes and environment increases,the correlation of the environments of the identical twins rises, and because this then explainssome of theearnings similarity of theidentical twins, the resultingestimate of heritability falls. 3 Wetake the third numerical column of Table1 as themost reasonable set of estimates. On this basis, twostriking conclusions follow.First, the heritability of earnings appears substantial. Second, the environmentaleffects are also large.The normalized regression coef cient of environmenton earningsis be 5 0.38,which maybe compared with the normalizedregression coef cientfor a measureof years of schooling inan earnings equation, fromour earlier meta-analysis, which is0.22. Thus, whileeducational attainmentcaptures importantaspects oftherelevant environments, it isfarfrom exhaustive. What istheintergenerational correlation of earningsimplied by our estimate of be and h?Toanswer this question, inaddition to h and be,werequire the correlationof parents ’ earningswith genes (which isalready implied by our estimates)and thecorrelation of parents ’ earningswith environment. The rst

3 TheSwedish Twin Registrydata set assembledby Bjo¨rklund, Ja¨ntti and Solon(forthcoming) has data not just ontwins, buton many pairswith varying degreesof relatedness(half-siblings, forexample) and mayallow more robust estimates using the methodsdeveloped by Cloninger, Rice and Reich(1979), Raoet al. (1982) and Feldman,Otto and Christiansen(2000). 16Journal of Economic Perspectives

Table 1 Estimatingthe Heritability of Earnings

AssumedCorrelation of Genesand Environment 0.00 0.50 0.70 0.80 Heritabilityof Earnings(h 2) 0.50 0.29 0.19 0.13 NormalizedRegression Coef cient: Geneson Earnings (h) 0.71 0.54 0.44 0.36 Environmenton Earnings ( b) 0.29 0.33 0.38 0.44 Correlationof Environments: Fraternal Twins 0.70 0.70 0.70 0.70 IdenticalTwins 0.70 0.80 0.90 0.97

Notes: Theassociation of genes with environmentis represented by the normalizedregression coef cient ofgeneson environment.This tableassumes that parentalearnings-determining genes are correlated 0.2, and the correlationof fraternal twins ’ environmentis 0.7. Weuse the correlationsof incomefor identicaltwins of0.56and offraternal twins of0.36, taken fromthe U.S. TwinsburgStudy, and assume that theseare also the correlationsof earnings. column inTable2 givesour estimates. The genetic contribution is simply h times thecorrelati on betweenparental earnings and offspringgenotype, or 2 h (1 1 m)/2.Theenvironmental contribution, similarly,is be timesa correlation of parents’ earningsand environment(namely 0.74) selected to yield a total intergenerationalearnings correlation of 0.4. Theestimate that geneticinheritance may account foralmost one-third of the intergenerationalcorrelation is somewhat unexpected, in light of our negative ndings concerningthe inheritance of IQ. Thesurprising importance of both environmentand genespoint toa puzzle.If thegenetic contribution is not strongly relatedto IQ and ifthe environmental contribution is much largerthan the contributionof years of schooling, what arethe mechanisms accounting forper- sistenceof income over the generations? We shall returnto this puzzle,but willturn todata otherthan twinsstudies rstto show that thesame puzzle arises.

Human Capital

Becauseschooling attainmentis persistent across generationsand has clear linksto skills and perhaps othertraits that arerewarded in labor markets, an account ofthe transmission ofintergenerational status based on human capitalhas strongprima facie plausibility. The data alreadyintroduced allow a calculation of theportion of theintergenerational income correlation accounted forby thefact that offspringof high-income parents getmore schooling (measuredin years). This isthecorrelation of parent income and offspringschooling (about 0.45)multiplied bythenormalized regression coef cientof schooling inan earningsequation (0.22 fromour meta-analysis), or0.10.This correlationis substantial, particularlyin the lightof the fact that itis restricted to the effects of years of schooling operating independentlyof IQ (becauseour estimate of 0.22 is from earnings functions in Samuel Bowles andHerbert Gintis 17

Table 2 Contributionof Environmental, Genetic and WealthEffects to Intergenerational Transmission

Earnings Income

Environmental 0.28 0.20 Genetic 0.12 0.09 Wealth 0.12 Intergenerationalcorrelation 0.40 0.41

Notes: Theincome column and the estimatedcontribution of wealthare discussed below. The environ- mentalversus genetic breakdown assumes the guresin the third numericalcolumn in Table 1. which theregressors include the AFQT test or a similarinstrument). The full contribution, includingthe effect of schooling on IQand itseffect on earningsas wellas thedirect effect of schooling on earningsholding constant IQis0.12. It used tobe commonly assumed that once adequate measuresof schooling qualitywere developed, the only effects of parental economic status on offspring earningswould operate through effectson cognitivefunctioning and schooling, withthe direct effect of parental status on offspringearnings vanishing. Buteven as themeasurement of school qualityhas improvedover the years, the estimated directeffect of parental incomes (or earnings) on offspringearnings has turned out tobe remarkably robust. Forexample, Mulligan (1999), using early1990s data fromthe (U.S.) NationalLongitudinal Study of Youth, rstestimated the effect of achange inthe logarithm of parental earnings on offspring ’slogarithmof earnings withoutcontrolling for any otherfactors and then controlledfor a numberof measuresof school quality,as wellas theAFQT and standard educational and demographicvariables. He found that betweentwo- fths and one-half ofthe gross (unconditional) statisticalrelationship of parental and offspringearnings remains evenafter controlling for the other factors. Theseresults just reaf rmthe black box puzzleusing entirelydifferent data and methods: morethan two- fths of the intergenerationaltransmission coef cientis unaccounted for. 4 Takingaccount ofthe fact that thechildren of the well-to-do are much healthierthan poorchildren (Case, Lubotskyand Paxson, 2001)along with the fact that poorhealth has substantial effectson incomeslater in life(Smith, 1999) would probablyaccount fora substantial part ofthe intergenerational transmission process. Therole of health inthe process isparticularly striking because parental incomesappear tohave strongimpacts on childhealth that arenot accounted for byeither the health status ofthe parents nor bythe genetic similarity between parents and children.

4 It isalso true that we can typicallystatistically accountfor less than half ofthe varianceof the earnings orincomeusing the conventionalvariables described above. But this fact doesnot explainour limited successin accounting for the intergenerationalcorrelation, as this correlationmeasures only that part ofthe variationof earnings that wecan explainstatistically byparental economic status. 18Journal of Economic Perspectives

WealthEffects

Economicsuccess can bepassed on ina familythrough theinheritance of wealthas wellas intervivos wealth transfers to children. Remarkably little scholarly attentionhas beengiven to this mechanism, inpart because no representative panel data setwith adequate measuresof other earnings determinants exists for which thesecond generationhas reachedthe age at which theinheritance of wealthtypically has beencompleted. The only study ofwhich weare aware that addresses this problemby following the second generationto theirdeaths estimates amuch higherintergenerational wealth correlation than those reportedby Mulli- gan, above(Menchik, 1979). But while inheritances of wealth clearly matter for the top ofthe income distribution, we doubt whethersuch transfersplay an important rolefor most families. Very few individuals receive inheritances of signi cant magnitude.Mulligan (1997) estimates that estatespassing onsuf cientwealth to be subject toinheritance tax in theUnited States constituted between 2 and 4percent ofdeaths overthe years 1960 –1995.Even though this gureleaves out somequite substantial inheritances,as wellas transfersthat occur duringlife, it seems unlikely that formost of thepopulation asubstantial degreeof economic status istransmit- teddirectly by the intergenerational transfer of property or nancial wealth. It thus seemslikely that theintergenerational persistence of wealth re ects, at leastin part, parent-offspringsimilarities in traitsin uencingwealth accumulation, such as orientationtoward the future, sense of personal ef cacy, workethic, schooling attainmentand risktaking. Some of these traits covary with the level of wealth:for example, less well-off people may be more likely to be risk averse, to discount thefuture and have alowsense of ef cacy. Becauseof this correlationof wealthwith the traits conducive towealthaccumulation, parent-offspringsimilarity inwealth may arise from sources independentof any bequestsor transfers. Whatevertheir source, forfamilies with signi cant incomefrom wealth, parent-offspringwealth similarities can contributea substantial fractionto the intergenerationalpersistence of incomes. Using the same decomposition methods as above, this contributionis the correlation of parent income and childwealth timesthe normalized regression coef cientof wealth in an incomeequation. We usedata fromthe Panel Study of Income Dynamicsanalyzed by Charlesand Hurst (2002).The correlation between parent income and childwealth (both innatural logarithms)in this data setis 0.24. The average age of the children is only 37 years, so this correlationdoes not captureinheritance of wealthat death ofthe parents. To geta roughidea of the normalized regression coef cient,one way to proceed isby starting with the percentage change inincome associated witha 1percent change inwealth; this elasticitywill range from virtually zero (for those withlittle orno wealth)to one (for those withno sourceof income other than wealth).A plausiblemean value (based on averagefactor income shares) forthe U.S. popu- lationis 0.20.We convert this toa normalizedregression coef cientby multiplying bytheratio of the standard deviationof logwealth to the standard deviationof log income,also fromthe PSID data setprovided by Charles and Hurst (2002).This TheInheritance of Inequality 19

calculation suggeststhat thefact that higherincome parents have wealthierchil- drencontributes 0.12 to the intergenerational correlation of incomes. This gure,while substantial, maybe an underestimate,as itis based on data that, forthe reasons mentionedabove, do not capturea keytransmission process, namelyinheritance of wealth upon thedeath ofone ’sparents. Moreover,the estimateshould beadjusted upward totake account ofthe fact that those with greaterwealth tend tohave higheraverage returns to their wealth (Bardhan, Bowlesand Gintis,2000; Yitzhaki, 1987). Greater parental or own wealthmay also raisethe rate of returnto schooling and otherhuman investments,but wehave no wayof taking account ofthis empirically.For a sampleof very rich parents, the contributionof wealthto the intergenerational correlation would be much higher, ofcourse. Fora sampleof familieswith very limited wealth, the contribution would benearly zero. The difference in the contribution of wealth effects across the incomedistribution is are ectionof theheterogeneous nature of the transmission process mentionedearlier. Because of the very skewed distribution of wealth, the familywith the mean levelof wealth (to which ourestimates apply) isconsiderably wealthierthan themedian family.

Group Membership and Personality

Thus far, wehave followedthe production function approach, which under- pins mosteconomic approaches tointergenerational transmission, seekingto determinethe contribution of parent-child similarity in ownership of factors of production. Wehave complementedthe usual choice-based approach byincluding the in uenceof genetic inheritance. But other traits are persistent across generations and arearguably as important —forexample, race, rstlanguage, numberof children,number of siblings and others. Forexample, obesity is a predictorof low earningsfor women, while height predicts high earningsfor men. Good looks predicthigh earningsfor both menand women,the latter independently of whetherthey hold jobs interactingwith the public (Hammermesh and Biddle, 1993).Bowles, Gintis and Osborne (2002)provide a surveyof empirical evidence concerningthese and many othernonskill determinants of economic success. Twosuch variablesillustrate the potential importance of nonskill factors in theintergenerational transmission ofeconomic status: groupmembership and personality. Suppose that economicsuccess isin uenced not onlyby aperson ’straits,but also bycharacteristics of the group of individuals with whom the person typically interacts.Groups maydiffer in avarietyof dimensions: averagelevel of schooling, economicsuccess, cognitivefunctioning and wealthlevel. Groups maybe residen- tialneighborhoods, ethnicor racial groups, linguisticgroups, citizensof a nation or any otherset of individuals who typicallyinteract with one another. Groupeffects oneconomicsuccess arewell documented and mayarise for a numberof reasons, includingdiscrimination, conformist effects on behavior,differential access to 20Journal of Economic Perspectives

informationand complementaritiesin production (Cooper,Durlauf, and Johnson, 1994;Durlauf, 2001; Borjas, 1995). Raceapparently plays asigni cant rolein the intergenerational transmission ofeconomic success. This issuggested by the fact that forthe United States, the correlationamong brothers ’ earningsestimated by Bjo ¨rklundet al. (2002),namely 0.43,falls by 0.10 when thesample is restrictedto whites. Apparently, what brothers almostalways have incommon, namelyrace, accounts formuch oftheir similarity ofincome. The same is true of parents and theirchildren. In thedata setunder- lyingFigure 1, theelasticity of offspring family income with respect to parents ’ familyincome is 0.54,but thesame elasticity for whites only is 0.43and forblacks onlyis 0.41 (Hertz, 2002). Parent-offspring similarity in income is explained in importantmeasure by the fact that “race” istransmittedacross generations.Using Hertz’sestimates,we nd that race(that is, thecorrelation of parents incomewith offspringrace) contributes 0.07 to the intergenerational correlation. While this estimateis a bitlower that those suggestedby theabove data, itmay nonetheless be an overestimate,as itisbased onan incomeequation with the standard regressors, but withouta measureof cognitive performance, the inclusion ofwhich would probablylower the race coef cientsomewhat. Asecond exampleof traits not found ina conventional production function but that contributeto intergenerationalstatus transmission aredispositions such as asenseof personal ef cacy, workethic or a rateof time discount (presentorien- tation). Theimportance of theseaspects ofpersonality stems from the fact that in alargeclass ofexchanges, includingthe hiring of labor,borrowing and lending,or theexchange of goods ofuncertain quality,it is impossible to specify all relevant aspects ofthe exchange in acontract enforceableby thecourts. Wherethis isthe case, theactual termsof the exchange are in uenced bythe degree of trust, honesty, hard workand otherdispositions ofthe parties to the exchange. For example,a verypresent-oriented employee will not valuethe employer ’s promise of continued employmentin thefuture, conditional onhard worknow. Instead, such an employeewill require a higherwage to motivate hard workin thepresent and, therefore,is lesslikely to be employed. As another example,fatalistic workers who believethat theprobability of job terminationis unaffected bytheir own actions will becostlyto motivate under this typeof laborcontract (Bowles,Gintis and Osborne, 2002).The empirical importance of these traits is suggested in anumberof studies (Duncan and Dunifon, 1998;Heckman and Rubinstein, 2001;Kuhn and Wein- berger,2001; Heckman, forthcoming). Osborne (forthcoming)has studiedthe economic importance and intergenerationalpersistence of fatalism, as measuredby the Rotter Scale, a common measureof the degree to which individualsbelieve that importantevents in their livesare caused byexternal events rather than bytheir own actions. Herstudy ofa sampleof U.S menand theirparents found that thescore on theRotter Scale measuredbefore entry to the labor market has astatisticallysigni cant and large in uenceon earnings. Moreover,the Rotter score is persistent from parents to offspring.The normalized in uenceof theRotter Scale on earningsin Osborne ’s Samuel Bowles andHerbert Gintis 21

study issomewhat larger (in absolute value, namely 20.2)than theaverage in u- enceof IQ inour meta-analysis of65 studies discussed earlier.The estimated correlationof parental income with child fatalism is 20.14.The contribution of the fatalismchannel tothe intergenerational correlation is the correlation of parent incometo child fatalism multiplied by the correlation from child fatalism to subsequent income,0.028 —that is, (20.2)(20.14). Osborne (forthcoming)also studieda sampleof womenin England and found that measuresof social maladjustment takenat ageeleven (the Bristol Social Adjustment Scale),such as aggressionand withdrawal,are strong predictors of earningsat age33. The normalized in uenceof personalitytraits of aggression and withdrawalon earningsis considerablylarger than thein uenceof IQ. Thereare no measuresof intergenerational persistence of personalitytraits in theOsborne ’s Englishdata set,but otherstudies suggest that parent-childsimilarity in measures ofsocialmaladjustment maybe quite high. Forexample, Duncan etal. (forthcoming)found that deviantforms of behaviors of U.S. motherswere strong predictors ofthesame behaviors in daughters, includingdrug use, violentbehaviors, early sex, suspension fromschool and criminalconvictions. Osborne ’sworkthus suggests that theintergenerational transmission ofpersonality traits (whether genetic or cultural)may be an importantchannel explainingthe intergenerational persis- tenceof income. Weknow relatively little about theworkings of the intergenerational transmission process forpersonality traits relevant to economicsuccess, otherthan cognitive functioning. However,Kohn ’s(1969)study ofchild rearing values of parents suggeststhat at leastfor some traits, parents ’ experiencesin the workplace are generalizedand passed ontochildren. Kohn categorizeshis parentsample by the degreeof self-determination that each experienceson thejob, rangingfrom those who arerelatively unsupervised to those who areclosely directed by superiors. Kohn found that parents withhigh levelsof what hetermed “occupational self-direction ” emphasizecuriosity, self-control, happiness and independenceas valuesfor their children.Those who areclosely monitored by supervisors at workemphasize conformityto external authority. Kohn concluded: “Whetherconsciously ornot, parents tend toimpart to their children the lessons derivedfrom their own social class and thus helpprepare their children for a similarclass position. ” The work by Osborne suggeststhat thedegree of self-direction has signi cant effectson earn- ingslater in life.Other work by Yeung,Hill and Duncan (2000)shows that parental behavior,including church attendance, membershipin social organizations and such precautionarybehavior as seatbelt usage have signi cant impacts on their children’s earnings.

Conclusion

Recentevidence points toa much higherlevel of intergenerational transmission ofeconomic position than was previouslythought tobethe case. Americamay 22Journal of Economic Perspectives

Table 3 TheMain Causal Channelsof Intergenerational Status Transmission in the U.S.

Channel Earnings Income

IQ,conditionedon schooling 0.05 0.04 Schooling,conditioned on IQ 0.10 0.07 Wealth 0.12 Personality(fatalism) 0.03 0.02 Race 0.07 0.07 Total Intergenerational CorrelationAccounted For 0.25 0.32

Notes: Foreach channel, the entry isthe correlationof parentincome with the indicatedpredictor of offspring income,multiplied by its normalizedregression coef cientin an earningsor income equation. Thetotal isthe intergenerationalcorrelation resulting from these channels, inthe absenceof a direct effect ofparents ’ status onoffspring status. Source: Calculationsdescribed in text and Bowlesand Gintis(2001). stillbe the land ofopportunity by some measures, but parentalincome and wealth arestrong predictors of the likely economic status ofthe next generation. Our main objectivehas beento assess theextent of intergene rational transmission and themechanism saccounting forit. Table 3 summarizesour bestestimate softhe relative importanc eofthe main causal channels wehave beenable to identify.The only entry not previouslyexplainedis the rst, which isan estimateof the correlati on betweenparental income and childIQ multipliedby ourestimate of the normaliz edeffect of IQ onearnings, conditioned on, among otherthings, yearsof schooling.Theestimates for IQ, schooling and personalityin the income column aresimply those inthe earnings column adjusted totake account ofthe effect of earnings differenc eson income differences, suitablynormalize dasdescribedin Bowlesand Gintis(2001). Thus, wedo not takeaccount ofthe way that theseearnings determin ants mayaffect therate of return to one ’swealth.By contrast, weassume that therace effect is ofthe same magnitude in determiningthe returns to both human capital and conventional wealth(if the race effect on incomesworked solely via an effecton earnings, itscontribut ion tothe intergen erationalearnings correlati on would be signi cantly greater). Whilethe estimates in Table 3 arequite imprecise, the qualitative results are not likelyto be affected by reasonable alternative methods. Theresults are somewhat surprising:wealth, race and schooling areimportant to the inheritance of economicstatus, but IQisnot amajor contributor,and, as wehave seenabove, the genetictransmission ofIQ iseven less important. Apolicymakerseeking to level the playing eldmight use these results to designinterventions that wouldloosen the connection betweenthe economic success ofparents and theeconomic prospects oftheir children. But does alevel playing eld entail no correlationbetween parental and childincomes (Swift, forthcoming)?There are important values of family life and privacythat wouldbe TheInheritance of Inequality 23

compromisedby any seriousattempt to disconnect thefortunes of parents and childrencompletely. Rather than pursuing an abstract (and toour minds unattrac- tive)objective of zerointergenerational correlation, a betterapproach mightbe to ask which mechanisms ofintergenerationaltransmission seemunfair, and todirect policiesaccordingly. The role of race in transmitting status fromgeneration to generationis clearly unfair. Many peopleregard the strong correlation between parentalincome and childhealth as morallysuspect, and many feelthe same way about high levelsof wealth inheritance. Large majorities favor policies to compen- satefor inherited disabilities. Other mechanisms ofpersistence —thegenetic inheritanceof good looks, for example —strikemost people as unobjectionableand not an appropriatetarget for compensatory policy interventions. Even if some consensus could beformed on which ofthese mechanisms aremorally suspect, the policyimplications would be far from clear. For example, the possible incentive effectson parentalbehaviors of reduced parental in uenceon childsuccess would have tobe estimated and considered.

Appendix Decomposing CorrelationCoef cients and Estimating Heritability

Suppose parentalearnings yp directlyaffects offspring earnings y,but offspring earningsis also affectedby two variables, v1 and v2 ,that arecorrelated with parentalearnings. 5 Then, if r and r arethe correlations of parental earnings ypv1 ypv2 with v1 and v2 ,respectively,and ifthenormalized regression coef cients of yp, v1 , and v predicting y are given by b , b and b respectively,we have 2 ypy v1 y v2 y

(1) r 5 b 1 r b 1 r b . ypy ypy ypv 1 v 1y ypv 2 v 2 y

This isthecorrelation between parental and offspringearnings, decomposedinto itsdirect effect (the rstterm), the effect via variable v1 (thesecond term)and the effect via variable v2 (thethird term). To derivethis equation, wewrite

5 b 1 b 1 b 1 « (2) y yp yyp v 1 yv1 v 2 yv2 y ,

whereall variables are normalized to have zeromean and unit variance,and «y is uncorrelatedwith the independent variables. Then, substitutingthe above expres- sion for y intothe expectation E[ ypy],and notingthat iftwovariables (e.g., y and yp)have zeromean and unit variance,the correlation between these variables is the expectedvalue of their product, weget

5 Forprevious treatments ofthis material,see Rao, Mortonand Yee(1976), Cloninger,Rice and Reich (1979), Raoet al. (1982) and Otto, Feldmanand Christiansen(1994). 24Journal of Economic Perspectives

(3) r 5 E @y y# 5 E @y y #b 1 E@v y#b 1 E @v y#b . yp p p p p yp y 1 v 1 y 2 v 2 y

Since,given our normalization, E[ y y ] 5 1, E[v y] 5 rv y, and E[v y] 5 r , p p 1 1 2 v2 y wearrive at equation1. 6 Wenow apply this methodto estimating heritability using data on similarityof identicaland fraternaltwins. Amoregeneral treatment, using pairsof varying degreesof relatedness, is developed in Feldman, Otto and Christiansen (2000).

Suppose afamilyhas twosons whoseearnings, y1 and y2 ,depend additivelyon their genotypes, g1 and g2 ,and theirenvironments, e1 and e2 . Thus,

(4) yi 5 be ei 1 hgi 1 «yi for i 5 1, 2, where « isuncorrelatedwith the independent variables in themodel and ischosen yi such that thevariance of yi isunity. Thevariances of ei and gi arealso normalized tounity. Notethat thenormalized regression coef cientof genotype is then h, the squareroot of the heritability of earnings. Weassume theenvironment ei of brother i depends both onhis genotype gi and thecommon familyenvironment E. We thus have

(5) ei 5 bE E 1 bge gi 1 «ei for i 5 1, 2,

« where ei isuncorrelatedwith the independent variables in the model and ischosen such that thevariance of ei isunity. Weinterpret E as includingthe effect of parentalearnings, education and any otherenvironmental factor that affects offspringearnings and isshared bybrothers. For simplicity, we include the full effectof genes on environmentin the coef cient bge, so gi isuncorrelated with E. Finally,the genotype gi of brother i isdeterminedby the genotypes of the parents, given by

(6) gi 5 bg gf 1 bg gm ,

where gf and gm arethe genotypes of father and mother,and bg isthe normalized regressioncoef cient (path) of father’s (or mother’s) genotypepredicting son ’s genotype.The structure of this modelis illustrated in Figure 3.

To show that bg is1/ 2,suppose my isthecorrelation of maternaland paternal genes.Since we are assuming additivity(meaning that thetotal effect of the genomeis thesum ofthe effects of each gene),we can derive bg fora singlelocus. Welabel each possiblegene at this locus withthe amount x itcontributes to earnings. Wenormalized x so that E[x] 5 0 and E[ x2 ] 5 2.Bybasic genetics,a son

6 Notethat the sameargument holds if wereplacethe expectations,which refer to population values, with the samplemeans, variancesand covariances.In this case, the statistical independenceof the error termsand the independentvariables is assured by construction, whereas on the populationlevel this independenceis assumed. Samuel Bowles andHerbert Gintis 25

Figure 3 TheEarnings of Brothers

Notes: In this diagram, gf and gm arethe genotypesof father and mother, g1 and g2 arethe genotypes ofbrothers, E isthe commonenvironment of brothers, e1 and e2 arethe total environmentof brothersand y1 and y2 arethe earningsof brothers.Here, my isthe geneticrelatedness of parents 2 basedon assortative mating and as explainedbelow, bg 5 1/ 2, while h isthe heritabilityof earnings. Thepath labeled b ge representsthe tendencyof genesto affect the environments( bge . 0 meansthat identicaltwins experiencemore similar environments than fraternal twins).

inheritsone copy ofthe gene at thelocus fromeach parent, say xf fromthe father and xm fromthe mother. The value of genes at this locus fora son isthen ( xf 1 xm)/2,assuming that both geneshave equalexpected effect on economicsuccess, 7 which wedo hereand throughout. In addition to xf ,thefather has another gene with value zf at this locus, withthe same mean 0and variance2. Thecorresponding valuefor the father is then ( xf 1 zf)/ 2, where xf and zf areuncorrelated. The correspondingvalue for the mother is ( xm 1 zm)/ 2, where zm isthemother ’s other geneat this locus, and xm and zm areuncorrelated. Because of assortativemating, each geneof the father xf , zf ,iscorrelated my witheach geneof the mother xm, zm. 2 Thevariance of the parents ’ geneticvalue at this locus is E[( xm 1 zm) /4] 5 2 E[( xf 1 zf) /4] 5 1,and thecovariance of father and son is E[( xf 1 zf)( xf 1 xm)/4] 5 (1 1 my)/2.Therefore,the correlation of father ’s and son’s genetic valueat this locus isthe quotient of the previous two expressions, or

1 my (7) r 5 b 1 b m 5 1 . g f g i ge ge y 2 2

The rstterm in this expressionrepresents the direct path fromfather ’s genome to son’s, and thesecond isthecorrelation of father ’s and mother’sgeneticvalue at the locus, my,multipliedby thedirect path frommother to son at that locus. Tosee this, recallthat theleast squares estimatorof b1 inthe regression equation

7 Theactual valueof apairof genes at alocuscan behigher or lower than theiraverage value, of course, as whenone gene is dominant or recessive. 26Journal of Economic Perspectives

y 5 b1 x1 1 b2 x2 1 «, where x1 , x2 and y arenormalized to mean zeroand variance unity, and where « isuncorrelatedwith x1 and x2 ,isgivenby (Goldberger, 1991):

rx1y 2 rx1x 2rx 2y (8) b1 5 . 1 2 rx1x 2

In our case, b 5 b , r 5 r 5 (1 1 m )/ 2, and r 5 m .Substitutingin the 1 g x1 y x2 y y x1 x 2 y aboveexpression, we get bg 5 1/ 2. To determinethe correlation of fraternal twins ’ genotypes,we multiply the rightsides of (6) for i 5 1,2,and takeexpectations, giving

r fr 5 E @g g # 5 ~1/2!2E @g2# 1 ~1/2!2E @g2 # 1 2~1/2!2E @g g # g1 g2 1 2 f m m f

2 5 ~1/2! ~2 1 2my ! 5 ~1 1 my !/2, which, consulting (7),con rmsthestandard resultin genetics that fathersand sons ontheone hand and nonidenticalbrothers with the same parents ontheother are equallyrelated. To determinethe correlation of environments of fraternal twins, we multiplythe right sides of (5) for i 5 1,2and takeexpectations, giving

r fr 5 b2 1 r fr b2 5 b2 1 ~1 1 m !b2 /2. e1 e2 E g1 g 2 ge E y ge

Finally,multiplying the right sides of (4) for i 5 1, 2and takingexpectations, we get

r fr 5 b2r fr 1 h2r fr 1 2b hr b , y1 y 2 e e1 e 2 g1 g 2 e g1g 2 ge which expands to

(8) r fr 5 b2~b2 1 ~1 1 m !b2 /2! 1 h2~1 1 m !/2 1 ~1 1 m !b b h. y1 y 2 e E y ge y y e ge

In thecase ofidentical twins, thesame gureis relevant, but now thecorrelation ofgenotypes of brothers is rid 5 1. We then g1 g2

r id 5 b2 1 r id b2 5 b2 1 b2 , e1 e 2 E g1 g 2 e E ge and

r id 5 b2r id 1 h2r id 1 b hr id 1 b hr id , y1 y 2 e e1 e 2 g1 g 2 e e1 g 2 e e 2 g1 which becomes

(9) r id 5 b2~b2 1 b2 ! 1 h2 1 2b b h. y1 y 2 E E ge e ge TheInheritance of Inequality 27

In thetext, we assume r id 5 0.9for identical twins (although ourresults are not e1 e2 2 verysensitive to this assumption), so be 5 =0.9 2 bg.Thetwo equations forthe correlationsof brother earnings, (8)and (9),together with the observed values of thesecorrelations, allow us todetermine h and be forvarious values of bg. Equations (8)and (9)imply that thedifference between the correlations of earningsof identical and fraternaltwins is givenby

(10) r id 2 r fr 5 ~1 2 m !~h 1 b b !2/2. y1 y 2 y1 y 2 y e ge

Notethat assuming greaterassortative mating raises the estimate of h2 , while assuming astrongertendency for genes to effectenvironment (raising bge) has the oppositeeffect, as onewould expect. In theliterature, it isoften assumed that my 5 0 and bge 5 0,inwhich case weget the standard equationfor estimating heritability:

(11) h2 5 2~r id 2 r fr !. y1 y 2 y1 y 2

If this isthecase, wecan estimate h2 directlyfrom this equationand then usethis 2 estimate of h ,togetherwith (8), to estimate be. y Wewould like to thank Jere Behrman, Anders Bjo ¨rklund,Kerwin Ko Charles, BradfordDe Long,Williams Dickens, Marcus Feldman, James Heckman, Tom Hertz, ErikHurst, Arjun Jayadev,Christop herJencks, Alan Krueger, John Loehlin, Casey Mulligan,Suresh Naidu,Robert Plomin, Cecelia Rouse, Michael Waldman and Elisabeth Woodfor their contribut ionsto thispaper, Bridget Longridge and Bae Smithfor research assistance andthe John D. andCatherin eT.MacArthurFoundationfor nancial support.

References

Arrow,Kenneth, Samuel Bowles, and Steven Trinder. 1983. Parentsand Children: Incomes in Durlauf. 1999. Meritocracyand Economic Inequal- TwoGenerations. London:Heinemann. ity. Princeton,N.J.: PrincetonUniversity Press. Bardhan,Pranab, Samuel Bowles and Herbert Ashenfelter,Orley and Alan Krueger. 1994. Gintis. 2000. “Wealth Inequality,Credit Con- “Estimatesof the EconomicReturn toSchool- straints, and EconomicPerformance, ” in Hand- ingfrom a NewSample of Twins. ” American book ofIncome Distribution. Anthony Atkinson and EconomicReview. December,84:5, pp. 1157 – Franc¸oisBourguignon, eds. Dortrecht: North- 172. Holland,pp. 541 – 604. Atkinson,A. B.,A.K.Maynardand C. G. Becker,Gary S. 1988. “FamilyEconomics and 28Journal of Economic Perspectives

MacroBehavior. ” AmericanEconomic Review. Paxson. 2001. “EconomicStatus and Health in March, 78:1, pp. 1 –13. Childhood:The Origins of the Gradient. ” NBER Becker,Gary S.andNigel Tomes. 1986. WorkingPaper No. W8344, June. “HumanCapital and the Riseand Fallof Fam- Charles,Kerwin Ko andErik Hurst. 2002. ilies.” Journalof Labor Economics. July, 4:3, pp. “TheCorrelation of Wealth AcrossGenera- S1–39. tions.” University ofChicago Working Paper. Bjo¨rklund,Anders, Markus Ja ¨ntti,and Gary Cloninger,C. Robert,John Rice and Theo- Solon. Forthcoming. “In uencesof Nature and dore Reich. 1979. “MultifactorialInheritance Nurtureon Earnings: An EarlyProgress Report with CulturalTransmission and Assortative Mat- onaStudy ofVarious Sibling Types in Sweden, ” ing. II. AGeneralModel of CombinedPolygenic in UnequalChances: Family Backgroundand Eco- and CulturalInheritance. ” AmericanJournal of nomicSuccess. SamuelBowles, Herbert Gintis and HumanGenetics. 29:31, pp. 176 –98. MelissaOsborne, eds. New York: Russell Sage Cooper,Suzanne, Steven Durlauf and Paul Foundation. Johnson. 1994. “Onthe Evolutionof Economic Bjo¨rklund,Anders et al. 2002. “BrotherCor- Status acrossGenerations. ” AmericanEconomic Re- relationsin Earnings in Denmark, Finland, Nor- view. 84:2, pp. 50–58. way and SwedenCompared to the United Corak,Miles and Andrew Heisz. 1999. “The States.” Journalof Population Economics. Forth- IntergenerationalEarnings and IncomeMobil- coming. ity ofCanadian Men: Evidencefrom the Longi- Blalock,Hubert. 1964. CausalInferences in Non- tudinal IncomeTax Data. ” Journalof Human Re- experimentalResearch. ChapelHill, N.C.: Univer- sources. 34:3, pp. 505 –33. sity ofNorthCarolina Press. Devlin,Bernie, Michael Daniels and Kathryn Blau,Peter and Otis DudleyDuncan. 1967. Roeder. 1997. “TheHeritability of IQ. ” Nature. TheAmerican Occupational Structure. New York: July31, 388,pp. 468 –71. Wiley. Duncan,Greg J. andRachel Dunifon. 1998. Borjas,George. 1995. “Ethnicity, Neighbor- “‘Soft-Skills ’ and Long-RunMarket Success. ” Re- hoods,and HumanCapital Exernalities. ” Ameri- searchin Labor Economics. 17, pp. 123–50. canEconomic Review. June,85:3, pp. 365 –90. Duncan,Greg, et al. Forthcoming. “The Ap- Bouchard,T. J.Jr. andM. McGue. 1981. “Fa- pleDoes Not Fall Far fromthe Tree, ” in Un- milialStudies of Intelligence. ” Science. 212: 4498, equalChances: Family Backgroundand Economic pp. 1055– 059. Success. SamuelBowles, Herbert Gintis and Bowles,Samuel. 1972. “Schoolingand In- MelissaOsborne, eds. New York: Russell Sage equalityfrom Generation to Generation. ” Jour- Foundation. nalof Political Economy. May/June,80:3, pp. Durlauf,Stephen. 2001. “AFrameworkfor S219 –51. the Study ofIndividual Behavior and Social Bowles,Samuel and Herbert Gintis. 2001. Interactions. ” Sociological Methodology. 31:1, pp. “TheInheritance of Economic Status: Educa- 47– 87. tion, Classand Genetics, ” in InternationalEncyclo- Erikson,R. andJ. H.Goldthorpe. 1992. The pediaof the Social andBehavioral Sciences: Genetics, ConstantFlux: A Studyof Class Mobility inthe In- Behaviorand Society, Volume 6. MarcusFeldman dustrialSocieties. Oxford:Oxford University and PaulBaltes, eds.New York: Oxford Univer- Press. sity Pressand Elsevier,pp. 4132 –141. Eysenck,H. J. 1994. “Intelligenceand Bowles,Samuel and Valerie Nelson. 1974. Introversion-Extraversion, ” in Personalityand In- “The ‘Inheritanceof IQ ’ and the Intergenera- telligence. RobertJ. Sternbergand PatriciaRuzgis, tionalReproduction of Economic Inequality. ” eds.Cambridge: Cambridge University Press, Reviewof Economics and Statistics. February,56:1, pp. 3–31. pp. 39–51. Feldman,Marcus W., SarahP. Otto and Bowles,Samuel, Herbert Gintis, and Melissa FreddyB. Christiansen. 2000. “Genes,Culture, Osborne. 2002. “TheDeterminants of Individual and Inequality, ” in Meritocracyand Economic In- Earnings: Skills,Preferences, and Schooling. ” equality. Kenneth Arrow,Samuel Bowles and Journalof Economic Literature. December,39:4, StevenDurlauf, eds. Princeton, N.J.: Princeton pp. 1137–176. University Press,pp. 61 – 85. Bowles,Samuel, Herbert Gintis, and Melissa Floud,Roderick, Kenneth Wachter and An- Osborne,eds. Forthcoming. UnequalChances: nabelGregory. 1990. Height,Health and His- Family Backgroundand Economic Success. New tory:Nutritional Status in the United Kingdom, York:Russell Sage Foundation. 1750 –1980. Cambridge:Cambridge University Case,Anne, Darren Lubotsky and Christina Press. Samuel Bowles andHerbert Gintis 29

Fong,Christina. 2001. “SocialPreferences, Mulligan,Casey. 1999. “Galtonvs. the Human Self-Interest, and the Demandfor Redistribu- CapitalApproach to Inheritance. ” Journalof Po- tion.” Journalof Public Economics. 82:2, pp. 225 – liticalEconomy. December,Part 2, 107:6, pp. 46. S184 –224. Fong,Christina, Samuel Bowles and Herbert Osborne,Melissa A. Forthcoming. “Personal- Gintis. 2002. “Reciprocityand the Welfare ity and the IntergenerationalTransmission of State,” in Handbookon the Economics of Giving, EconomicStatus, ” in UnequalChances: Family Reciprocityand Altruism. JeanMercier-Ythier, Backgroundand Economic Success. SamuelBowles, SergeKolm, and Louis-Andre´ G9rard-Varet,eds. HerbertGintis and MelissaOsborne, eds. New Amsterdam:Elsevier. Forthcoming. York:Russell Sage Foundation. Goldberger,Arthur S. 1989. “Economicand Otto, SarahP., MarcusW. Feldmanand MechanicalModels of Intergenerational Trans- FreddyB. Christiansen. 1994. “Geneticand Cul- mission.” AmericanEconomic Review. June, 79:3, tural Transmissionof Continuous Traits. ” pp. 504 –13. Stanford University, MorrissonInstitute Work- Goldberger,Arthur S. 1991. ACoursein Econo- ingPaper No. 64. metrics. Cambridge,Mass.: HarvardUniversity Plomin,Robert. 1999. “Geneticand General Press. CognitiveAbility. ” Nature. December,402:2, pp. Hammermesh,Daniel S. andJeff E. Biddle. c25– c29. 1993. “Beauty and the LaborMarkets. ” NBER Plomin,Robert, et al. 2000. BehavioralGenetics. WorkingPaper 4518, November. NewYork: W. H.Freemanand Company. Heckman,James. Forthcoming. The GED. Rao,D. C.,N.E.Mortonand S. Yee. 1976. Heckman,James andYona Rubinstein. 2001. “Resolutionof Cultural and BiologicalInheri- “TheImportance of NoncognitiveSkills: Lessons tance byPath Analysis. ” AmericanJournal of Hu- fromthe GEDTesting Program. ” AmericanEco- manGenetics. 28, pp. 228– 42. nomicReview. May, 91:2, pp. 145 – 49. Rao,D. C.etal. 1982. “Path Analysis Under Hertz,Thomas. 2001. “Education,Inequality GeneralizedAssortative Mating. II: American and EconomicMobility in South Africa. ” Un- IQ.” GeneticalResearch. 39, 187–98. publishedPh.D. Dissertation,University ofMas- Smith,James. 1999. “Healthy Bodiesand sachusetts. ThickWallets: TheDual Relation between Hertz,Thomas. 2002. “Intergenerational Health and EconomicStatus. ” Journalof Economic EconomicMobility of Black and White Fami- Perspectives. Spring,13:2, pp. 145 – 66. liesin the United States. ” Paperpresented at Solon,Gary R. 1992. “IntergenerationalIn- the Societyof LaborEconomists Annual Meet- comeMobility in the United States. ” American ing, May. EconomicReview. June,82:3, pp. 393 – 408. Kohn,Melvin. 1969. Classand Conformity. Homewood,Ill.: DorseyPress. Solon,Gary R. 1999. “IntergenerationalMo- Kuhn,Peter and Catherine Weinberger. 2001. bilityin the LaborMarket, ” in Handbookof Labor “LeadershipSkills and Wages. ” Institute forSo- Economics,Volume 3A. OrleyAshenfelter and cial,Behavioral and EconomicResearch, De- DavidCard, eds. Amsterdam: North-Holland, cember. pp. 1761– 800. Loehlin,John and Robert Nichols. 1976. He- Sternberg,Robert J. etal. 1995. “Testing Com- redity,Environment, and Personality. Austin, Texas: mon Sense.” AmericanPsychologist. November,50: University ofTexas Press. 11, pp. 912–27. Mazumder,Bhashkar. Forthcoming. “Earn- Swift, Adam. Forthcoming. “Justice,Luck ingsMobility in the U.S.:ANewLook at In- and FamilyValues: The Intergenerat ional tergenerational Inequality, ” in UnequalChanc- Transmissionof Economic Status froma Nor- es:Family Backgroundand Economic Success. mativePerspective , ” in UnequalChances: Family SamuelBowles, Herbert Gintis and Melissa Backgroundand Economic Success. Samuel Osborne,eds. New York: Russell Sage Founda- Bowles,Herbert Gintis and MelissaOsborne, tion. eds.New York: Russell Sage Foundation. Menchik,Paul. 1979. “Inter-Generational Taubman,Paul. 1976. “TheDeterminants of Transmissionof Inequality: An EmpiricalStudy Earnings: Genetic,Family, and OtherEnviron- ofWealth Mobility. ” Economica. November,46: ments; AStudy ofWhite MaleTwins. ” American 184, pp. 349 –62. EconomicReview. December,66:5, pp. 858 –70. Mulligan,Casey. 1997. ParentalPriorities and Thorndike,Edward L. 1919. “Intelligenceand EconomicInequality. Chicago:University ofChi- Its Uses.” Harper’sMonthlyMagazine. December/ cago Press. January, 140,pp. 227 –35. 30Journal of Economic Perspectives

Williams,Wendy M. andRobert J. Sternberg. 2000. “Putting Fathers Backin the Picture:Pa- 1995. SuccessActs for Managers. Florida:Harcourt rentalActivities and Children ’sAdult Attain- Brace. ments.” Marriageand Family Review. Part I, 29: Winship,Christopher and Sanders Korenman. 2–3, pp. 97–113. 1999. “EconomicSuccess and the Evolutionof Yitzhaki,Shlomo. 1987. “TheRelation Be- Schoolingwith Mental Ability, ” in Earning and tweenReturn and Income. ” QuarterlyJournal of Learning:How Schools Matter. Susan Mayerand Economics. February,102:1, pp. 77 –95. PaulPeterson, eds. Washington, D.C.: Brookings Zimmerman,David J. 1992. “RegressionTo- Institution, pp. 49 –78. wardMediocrity in EconomicStature. ” American Yeung,Jean, Martha Hilland Greg Duncan. EconomicReview. June,82:3, pp. 409 –29.