Week 2 the Inheritance of Inequality

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La herencia de la desigualdad

Samuel Bowles y Herbert Gintis

P ersonas difieren marcadamente en sus opiniones sobre el papel apropiado deGobierno en la reduccin de la desigualdad econmica. Intereses y diferenciasen los valores de explicar parte de las TIC con sobre redistribucin. Pero el msfalla importante es que las personas tienen creencias diferentes acerca de por qu los ricos son ricosy los pobres son pobres. Datos de la encuesta muestran que las personas ricos y pobres queCreo que \"getting ahead y posteriores en la vida\" depende de trabajo duro o\"deseo de tomar riesgos\" tiende a oponerse a los programas de redistribucin. Por el contrario, losque piensan que la clave del xito es \"dinero heredado de la familia,\" \"los padres y laambiente familiar,\"\"conexiones y conocer a las personas adecuadas\"o ser blancoredistribucin de apoyo (Fong, 2001; Fong, Bowles y Gintis, 2002). Dictarxito golpea muchas personas como injusto, incluso si los riesgos son pequeos, mientras que las difen xito obtenido puede ser inobjetable incluso con altas apuestas, tan largo como el

jugando eld es considerado el nivel.Cmo nivel es la eld reproduccin intergeneracional? Cules son los mecanismos causales1

que subyacen a la transmisin intergeneracional de la situacin econmica? Son estas

1 Vase Bowles y Gintis (2001) para los modelos formales pertinentes y otros aspectos tcnicos de esteinvestigacin, tambin disponible enhttp:\/\/www.Santafe.edu\/s\/Publications\/Working-Papers.html. Flecha,Bowles y Durlauf (1999) y Bowles, Gintis y Osborne (disponible prximamente) presentes colecciones recientes

investigacin emprica y terica.

y Samuel Bowles es profesor de economa en la Universidad de Siena, Siena, Italia, yDirector de la economa programa, Instituto de Santa Fe, Santa Fe, Nuevo Mxico. HerbertGintis es miembro de la externa Facultad, Instituto de Santa Fe, Santa Fe, Nuevo Mxico.

Ambos autores son profesores emrito de economa, Universidad de Massachusetts, AmhMassachusetts. Sus direcciones de correo electrnico son [email protected] y [email protected],y sus sitios Web http:\/\/www-UNIX. OIT.umass.edu\/ bowles y http:\/\/www-

UNIX.OIT.umass.edu\/ gintis.

Journal of Economic Perspectives, volumen 16, nmero 3, verano 2002 pginas puedeMultilizer PDF Translator Free version - translation is limited to ~ 3 pages p

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mecanismos susceptibles de polticas pblicas de manera que permita el logro dexito econmico ms justo? Estas son las preguntas que intentaremos responder.

Nadie duda de que los hijos de padres pudientes suelen reciban ms ymejor educacin y benet de herencias materiales, culturales y genticas. Perohasta hace poco, el consenso entre los economistas ha estado en los Estados Unidos,el xito es en gran parte ganada o perdida en cada generacin. Las primeras investigaciones sobre lrelacin entre los padres y sus hijos econmico estado despus de convertirse enadultos, comenzando con Blau y Duncan (1967), encontraron slo una conexin dbil yas pareca conrm que Estados Unidos era la \"tierra de oportunidad-nidad.\" Por ejemplo, las correlaciones simples entre los ingresos de los padres y los hijos olas ganancias (o sus logaritmos) en Estados Unidos reportado por Becker y tomos(1986) un promedio de 0.15, llevando a los autores a concluir: \"aparte de las familias vic -timized por la discriminacin... [a] uno todas las ganancias ventajas y desventajas deancestros son exterminados en tres generaciones.\" Becker (1988) expresada una ampliamentecelebr el consenso cuando, en su discurso presidencial a la economa estadounidense

Asociacin, concluy (p. 10): \"[L] ujo ganancias as como altos ingresos no sonfuertemente transmitidas de padres a hijos.\"

Pero las investigaciones ms recientes muestran que las estimaciones de altos niveles de intergemovilidad de erational fueron artefactos de dos tipos de error de medicin: errores en

informes de ingresos, especialmente cuando los individuos se les pidi recordar el ingreso desus padres y componentes transitorios en el ingreso actual incorreladas coningreso permanente subyacente (Bowles, 1972; Bowles y Nelson, 1974; Atkinson,Maynard y Trinder, 1983; Soln, 1992, 1999; Zimmerman, 1992). La altaruido seal en los ingresos de ambas generaciones deprimido intergenera-correlacin de internacional. Cuando se corrige, las correlaciones entre las generaciones para eco -Estado de actividad parecen ser importantes, muchos de ellos tres veces el promedio de laEstudios de U.S. encuestados por Becker y tomos (1986).

Las mayores estimaciones de consenso de la transmisin intergeneracional dexito econmico ha estimulado la investigacin emprica. Los hechos relevantes enque la mayora de los investigadores concuerdan ahora incluyen los siguientes: los ingresos de los hemucho ms similares que los de los hombres elegidos al azar de la misma raza ydiferencias de edad similar; los ingresos de los gemelos idnticos son mucho ms similaresque mellizos o hermanos no gemelos; los hijos de padres adinerados obtenerescolarizacin de ms y de mejor calidad; y hace una importante herencia de riquezacontribucin a la riqueza de propiedad de los descendientes de los muy ricos. Sobre la base de

de estas y otras regularidades empricas, parece seguro concluir que eltransmisin intergeneracional de la situacin econmica se debe a un heter-ogeneous coleccin de mecanismos, incluyendo el trans genticos y culturales-Misin de habilidades cognoscitivas y rasgos de la personalidad no-cognitivas en la demanda porempleadores, la herencia de la riqueza y aumento de ingresos grupo miembro-buques, como la raza y el estado de salud y educacin superior disfrutado por lanios de familias de estado mayor.

Sin embargo, sigue siendo la transmisin de xito econmico a travs de generaciones

algo de una caja negra. Nos nd que procesa la herencia combinada

4 Journal of Economic PerspectivesMultilizer PDF Translator Free version - translation is limited to ~ 3 pages p

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operando a travs de superior rendimiento cognitivo y logros educativos de laaquellos con padres adinerados, aunque importante, explican como mximo tres fths de la

transmisin intergeneracional de la situacin econmica. Adems, mientras gentica trans-Misin de mejorar ingresos rasgos parece desempear un papel, la transmisin genticade IQ parece ser relativamente poco importante.

Podra pensarse que la caja negra es un artefacto de medicin pobre delas variables intervinientes en relacin con la medicin de los ingresos o ganancias depadres e hijos. Pero esto no parece ser el caso. Aos de escolaridad yotras medidas de logro escolar, como el rendimiento cognitivo, se midencon relativamente poco error. Por supuesto ayudar a mediciones mejores; pero no somosprobablemente mejore mucho en nuestras medidas de IQ y mejoras recientes en lamedicin de la calidad de las escuelas no nos han dado mucha iluminacin sobre lo que deocurre dentro de la caja negra. El problema fundamental no es que seamosmedir las variables derecha mal, pero que nos faltan algunos de los importantesvariables totalmente. Cules podran ser estas?

Mayora de los modelos econmica trata los ingresos como la suma de los retornos a lafactores de produccin se incorpora al mercado, como habilidades, o bienes de capital. Pero cualquierrasgo individual que afecta a ingresos y para que padres-The offspring similitud esfuerte contribuir a la transmisin intergeneracional de xito econmico.

Incluyen la raza, ubicacin geogrfica, altura, belleza u otros aspectos de la fsicaapariencia, estado de salud y personalidad. As, por contraste con la ap estndar-Proach, damos una atencin considerable a la generacin de ingresos caractersticas quegeneralmente no se consideran factores de produccin. En los estudios de la inter-transmisin generacional de la situacin econmica, nuestras estimaciones sugieren que cognitivohabilidades y educacin overstudied, mientras que la riqueza, la raza y no-cognitivasrasgos de comportamiento han sido suplente.

Medicin de la transmisin intergeneracional de la situacin econmica

Estatus econmico puede medirse en categoras discretas, por pertenencia aordenadas jerrquicamente las clases, por ejemplo o continuamente, por los ingresos, ingresoso riqueza. El enfoque discreto permite un SID de ricos, pero difcult a resumir-tacin del proceso de persistencia intergeneracional del estado a travs de la transicinprobabilidades entre los rangos sociales relevantes (Erikson y Goldthorpe, 1992; este

en la correlacin entre la situacin econmica de las dos generaciones. Por otra parte,Estas correlaciones se pueden descomponer en componentes aditivos re ejo eldiversos mecanismos causales representan similitud econmica de padres e hijos. Ambosenfoques son acertados, pero aqu nos basaremos principalmente en el continuomedicin de estado. Por razones de disponibilidad de los datos, usamos los ingresos o gananciascomo la medida de la situacin econmica, aunque son ingresos (la medida ms inclusiva)preferible para la mayora de las aplicaciones.

Utilizamos el subndice p para referirse a las medidas de los padres, mientras que un individuo es

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economic status, adjusted so that its mean, y, is constant across generations,# byis aconstant, and yis a di sturbance uncorrelated with y . Thus,p

y2 y#5 by~yp 2 y#! 1 y;

that is, the deviation of the offsprings economic status from the mean is bytimesthe deviation of the parent from mean economic status, plus an errorterm. In theempirical work reviewed below, earnings, income, wealth and o thermeasures ofeconomic success are measured by theirnatural logarithm unless otherwise noted.Thus, by, termed the intergenerational income elasticity, is the percentage change

in offsprings economic success associated with a 1 pe rcent change in parentseconomic success. The in uence ofmean economic status on the economics statusof the o ffspring, 1 2 by, is called regression to the mean, since it shows that one mayexpect to be c loser to the m ean than ones par ents by the fraction 1 2 by(Goldberger, 1989).

The relationship between the intergenerational income elasticity and t heintergenerational correlation is given by

ry5 bys yp

s y,

where s y is the standard deviation of y. If y is a natural logarithm, its standarddeviation is a com mon unit-free measure of ine quality. Thus, if inequality isunchanging across generations, so s yp 5 s y, then ry5 by. However, the intergen-erational income elasticity exceeds rywhen income inequality is rising, but is lessthan ry when income inequality is declining. In e ffect, the i ntergenerational

correlation coefcient r is affected by changes in the dist ribution ofincome whilethe intergenerational income elasticity is not.Also, r

2 measures the fraction of thevariance in this generations measure of economic success that is linearly associatedwith the same measure in the previous generation.

Estimates of t he intergenerational income elasticity are presented in S olon(1999, this issue) and Mulligan (1997). The mean estimates reported in Mulliganare as follows: for consu mption, 0.68; for wealth, 0.50; for income, 0.43; forearnings (or wages), 0.34; and foryears of schooling, 0.29. Evidence concerning

trends in the degree of i ncome persistence across generations is mixed. Moststudies indicate that persistence rises with age, is greaterforsons than daughtersand i s greater when multiple years of i ncome or e arnings are ave raged. Theimportance of averaging multiple years to capture permanent aspects of economicstatus is dramatized in Mazumder (forthcoming). He u sed a rich U.S. SocialSecurityAdministration data set to estimate an intergenerational income elasticityof0.27, averaging sons earnings overthree years and fatherearnings averaged overtwo years. But the estimate increases to 0.47 when six years of the fathers earnings

are averaged and to 0.65 when 15 years are averaged.

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Do intergenerational elasticities of this magnitude mean that rags toriches i s no more than a fantasy for most poor children? The intergenerational

correlation is an average measure and may be unilluminating about the prob-abilities o f economic success conditional o n being the child of poor or richparents. Calculating t hese conditional p robabilities and inspecting the entiretransition matrix gives a more complete picture. The results of a s tudy by Hertz(2002) appear in Figure 1 w ith the parents arranged by income decile (frompoor to rich moving from left to right) and with adult children arranged byincome decile along the other axis. The height of the surface indicates thelikelihood of making the transition from the indicated parents d ecile to thechildrens d ecile.

Though the unde rlying intergenerational correlation of i ncomes in the dat aset Hertz (2002) used is a modest 0.42, the differences in the likely life trajectoriesofthe children of the poor and the rich are substantial. The twin peaks representthose stuck in poverty and af uence (though we do not expect the term af uencetrap t o catch on). A son born to the top de cile has a 2 2.9 percent chance ofattaining the top decile (point D) and a 4 0.7 percent chance of att aining the topquintile.A indicates that the son of the poorest decile has a 1.3 percent chance ofattaining the top decile and a 3.7 pe rcent chance of attaining the top quintile. C

indicates that children of the poorest decile have a 31.2 percent chance ofoccu-pying the lowest decile and a 50.7 percent chance of occupying the lowest quintile,while B shows that the probability that a chil d ofthe richest decile ends up in t hepoorest decile is 2.4 pe rcent, with a 6 .8 percent chance o foccupying the lowestquintile. Hertzs transmission matrix and otherstudies suggest that distinct trans-mission mechanisms may be at w ork at various points of the income distribution(Corak and He isz, 1999; Cooper, Durlauf and Johnson, 1994; Hertz, 2001). Forexample, wealth bequests may play a majorrole at the top ofthe income distribu-

tion, while at the bottom, vulnerability to violence or otheradverse health episodesmay be more important. Mobility patterns by race also differdramatically (Hertz,2002). Downward mobility from the top quartile to the bottom quartile is nearly vetimes as great forblacks as forwhites. Thus, whateverit is that accounts fortheirsuccess, successful blacks do not transmit it to the irchildren as effectively as dosuccessful whites. Correspondingly, blacks born to the b ottom quartile attain thetop quartile at one half the rat e ofwhites.

Sources of Persistence: Cultural, Genetic and Bequest

Economic status does persist substantially across generations. We se ek touncover the c hannels through which parental incomes in uence offspring in-comes. We d o this by de composing the intergenerational correlation (or t heintergenerational income elasticity) into additive components re ecting the co n-

tribution of various causal mechanisms. This will allow us to conclude, forexample,

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that a certain fraction of the int ergenerational correlation is accounted forby thegenetic inheritance of IQ o rby the fact that the chi ldren of rich parents are alsowealthy.

It i s a remarkable fact about correlation coefcients that this can be do ne.Moreover, the technique we use does not require that we introduce variables in anyparticularorder. Suppose that parents income (measured by its logarithm, y) andpoffspring education (s) affect offspring income (also measured by its logarithm, y).

Like any cor relation coefcient, this intergenerational correlation ry yp can b eexpressed as the sum of the no rmalized regression coefcients of measures ofparental income (by yp ) and of fspring education (bys) in a m ultiple regressionpredicting y, e ach multiplied by the co rrelation between yp and t he regressor(which, of course, for p arental income itself is just 1) . A normalized regressioncoefcient is the c hange in the de pendent variable, in standard deviation units,associated with a one standard deviation change in the independent variable. Thedirecteffectof parentalincome is the normalizedregression coefcientofparental

income from this regression. The education component of this decomposition of

Figure 1Intergenerational Income Transition Probabilities

Notes: The heightofthe surface in cell(i, j) is the probabilitythat a pe rson whoseparentshousehold income was in the ith decile will have household income in the jth decile as an adu lt.The income ofthe children was measured when they were aged 26 orolderand was averaged overall such years for which it was observed (an average of ten years). Parents income was averaged overall observed years in which the child lived with the parents (an average of9.4 years).Source: From PSID data, Hertz(2002). The 103 10 transition matrix on which this gure is based isavailable at http://www-unix.oit.umass.edu/ gintis .

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the intergenerational correlation is called an indirecteffect. Figure 2 illustrates this2

breakdown, which gives

ryyp5 byp y1 ryp sb ys

intergenerational correlation 5 direct effect 1 indirect effect.

As long as the multiple regression coefcients are unbiased, the decomposition isvalid whateverthe relationship among the variables. Specically, it does not requirethat the re gressors be uncorrelated. This decomposition allows us to be m oreprecise about our black box claim in the introduction. We mean that the directparental effect is a sub stantial fraction of the int ergenerational correlation in anumber of studies allowing this comparison (Bowles, 1972; Bowles and N elson,1974; Atkinson, Maynard and Trinder, 1983; Mulligan, 1999).

Our strategy is to estimate the size of these direct and indirect effects. Note thatthe decomposition uses correlations between parental incomes and o thervariablesschooling in the examplethought to be causally related to the income-

generating process. These correlations with parental income need not re ectcausal relationships, of course. But the above decomposition can be repeated forthe correlations between parental income and the cau ses of offspring income, insome cases permitting causal interpretations. Forexample, a study of the role ofwealth in the transmission process could ask why parental income and o ffspringwealth are correlated. Is i t bequests and int er vivos transfers or t he culturaltransmission of savings behaviors that account forthis correlation? Or do we simplynot know why parent and offspring wealth is correlated and as a result should avoid

giving the data a cau sal interpretation? Similarly, parent-offspring similarity inhuman capital may be due to genetic orcultural inheritance ofwhateverit takes topersist in schooling and to acq uire skills and behaviors that are rewarded in thelabor market. Unlike the models of parental and chi ld behavior accounting forpersistence pioneered by Becker and pre sented in thi s issue by G rawe and

2 This decomposition can be found in Blalock (1964) and is de scribed in the Ap pendix to this paper.Goldberger(1991) describes the standard regression model with normalized (mean zero, unit standard

deviation) variables on which it is based.

Figure 2Representing a Correlation as the Sum ofDirect and Indirect Effects

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Mulligan, our approach is more diagnostic, not giving an adequate causal accountof the transmission process, but indicating where to look to nd t he causes. The

next sections ofthis paperwill explore such decompositions.

The Role of Genetic Inheritance of Cognitive Skill

One of the transmission channels deserves special attention not only becauseofits prima facie plausibility, but also because of the ex traordinary attention givento it i n popular discussions of the subje ct. This is the ge netic inheritance ofcognitive skill. The similarity ofparents and offsprings scores on cognitive tests iswell documented. Correlations of IQ be tween parents and o ffspring range from0.42 to 0.72, where the highergure refers to measures of average parental andaverage offspring IQ ( Bouchard and M cGue, 1981; Plomin et al., 2000). Thecontribution of co gnitive functioning to e arnings both directly and via schoolingattainment has also been established in a variety of studies that estimate determi-nants of earnings using IQ ( and related) test scores. The di rect effect of IQ onearnings is estimated from multiple regression studies that typically use the l oga-rithm ofearnings as a dependent variable and estimate the regression coefcients

of a variety of e xplanatory variables, including performance on a cog nitive test,years (and perhaps othermeasures) of schooling, a measure of parental economicand/or so cial status, work experience, race and sex . The ind irect effect of IQoperating through its contribution to hi gher levels of educational attainment isestimated using measures of chi ldhood IQ (along with othervariables) to predictthe level of schooling obtained.

We have located 65 estimates of the normalized regression coefcient of a testscore in an earnings equation in 24 different studies of U.S. data overa period of

three decades. Our meta-analysis of these studies is presented in Bowles, Gintis andOsborne (2002). The mean of these estimates is 0.15, indicating that a stand arddeviation change in the cognitive score, holding constant the remaining variables(including schooling), changes the natural logarithm of e arnings by about one-seventh of a standard deviation. By contrast, the mean value of the normalizedregression coefcient of years of school ing in the same equation predicting thenatural log of e arnings in these studies is 0.22, suggesting a som ewhat largerindependent effect of schooling. We checked to see ifthese results were dependent

on the weight of overrepresented authors, the type of cognitive test used, at whatage the te st was t aken and o ther differences among the studies and fo und nosignicant effects. An estimate of the causal impact of childhood IQ on y ears ofschooling (also normalized) is 0.53 (Winship and Ko renman, 1999). A ro ughestimate of the direct and indi rect effect of IQ on e arnings, call it b, is then b 50.15 1 (0.53)(0.22) 5 0.266.

Do these two factsparent-child similarity in IQ and an i mportant direct andindirect causal role for IQ i n generating earningsimply a major role for genetic

inheritance of cognitive ability in the transmission of intergenerational economic



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status? One way to formulate this question is to ask how similarwould parental andoffspring IQ be i fthe sole source of the sim ilarity were genetic transmission.Also,

how similarwould the incomes of parents and offspring be ifthere were no othertransmission channel?For this we need some genetics (the details are in the Appendix and in Bowles

and G intis, 2001) and a f ew termsphenotype, genotype, heritability and t hegenetic correlationunfamiliar to many economists. A pe rsons IQme aning, atest scoreis aphenotypictrait, while the genes in uencing IQ are the pe rsonsgenotypic IQ. Heritability is the relationship between the two. Suppose that, for agiven environment, a standard deviation difference in genotype is associated witha fraction h ofa standard deviation difference in IQ . Then h is the heritability of2

IQ. Estimates ofh are based on the degree ofsimilarity ofIQ among twins, siblings,2

cousins and others with differing degrees of genetic relatedness. The value cannotbe higherthan 1, and most recent estimates are substantially lower, possibly morelike a half or l ess (Devlin, Daniels and Roeder, 1997; Feldman, Otto and Chris-tiansen, 2000; Plomin, 1999). The geneticcorrelation is the degree of statisticalassociation between genotypes ofparents and children, which is 0.5 if the parentsgenotypes are uncorrelated (random mating). B ut couples tend to be m oresimilarin IQ than would occur by random mate choice (assortative mating), and

this similarity is associated with an unknown correlation m oftheirgenotypes. Theeffect is to raise the genetic correlation of parent and o ffspring to (1 1 m)/ 2.

Using the m ethod of de composition introduced in the p revious section, thecorrelation g between parental and o ffspring IQ t hat is attributable to g eneticinheritance of IQ alone is the he ritability of IQ times the genetic correlation. Thus,we haveg 5 h (1

21 m)/2. The correlation between parentand offspring income

that is attributable to ge netic inheritance of IQ is thi s correlation times thenormalized (direct and indirect) effect of IQ on the i ncome of parents, times the

analogous effect forthe offspring, orgb . Anotherway to see this is to note that the2

correlation between parental income and offspring IQ that we would observe werethe genetic inheritance of IQ t he only channel at wo rk is gb, and this times theeffect of offspring IQ on earnings, which is b, gives the same result.

Using the values estimated above, we se e that the cont ribution of g eneticinheritance of IQ to the int ergenerational transmission of income is

~h 12~ 1 m /2 0.266! !~ !2

5 .035 1~ 1 m h .!2

If the heritability of IQ w ere 0.5 and the de gree of assortation, m, were 0.2 (bothreasonable, ifonly ballpark estimates) and the g enetic inheritance of IQ w ere theonly mechanism accounting for intergenerational income transmission, then theintergenerational correlation would be 0.0 1, or roughly 2 pe rcent the ob servedintergenerational correlation. Note the conclusion that the c ontribution of geneticinheritance of IQ is ne gligible is not the result of any assum ptions concerning

assortative mating or the he ritability of IQ: the IQ g enotype of parents could be



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perfectly correlated and the her itability of IQ 10 0 percent without appreciablychanging the qualitative conclusions. The estimate results from the fact that IQ is

just not an i mportant enough determinant of economic success.Might the sm all contribution of ge netic inheritance of IQ to p arent-offspringsimilarity ofincomes be the result of measurement errorin the cognitive measures?There are two issues here. First, what is the reliabilityof the test: whateverthe testmeasures, does it measure well? Second, what is the validityofthe test: does the testmeasure the right thing? The concern that the te sts are a very noisy measure ismisplaced. In fact, the tests are among the more reliable variables used in standardearnings equations, where reliability is measured by the correlation between testsand retests, between odd and e ven numbered items on the t ests, and by moresophisticated methods. For the commonly used Armed Forces Qualication Test(AFQT), for examplea test used to predict vocational success that is often used asa measure of cognitive skillsthe correlation between two test scores taken onsuccessive days b y the same p erson is likely to be hi gher than the correlationbetween the same persons reported years ofschooling orincome on two successivedays.

The second concern, that the tests measure the wrong thing, is weightierandless easy to address with any certainty. Could it be that cognitive skills not measured

on existing test instruments are both highly heritable and have a m ajor impact onearnings, thereby possibly explaining a more substantial fraction of the transmis-sion process? The search for g eneral cognitive measures that are substantiallyuncorrelated with IQ and predictive ofsuccess in adult roles began with EdwardThorndikes (1 919) paper on so cial intelligence. S ome alternative test instru-ments, such as Robert Sternberg and collaborators practical intelligence predicteconomic success in particularoccupations (Sternberg et al., 1995; Williams andSternberg, 1995). But despite the substantial fame and fo rtune that would have

accrued to success in this area, the quest that Thorndike launched three genera-tions ago has y ielded no ro bust alternative to IQ, le t alone one t hat is hi ghlyheritable. Thus, the possible existence of economically important but as ye t un-measured heritable general cognitive skills cannot be excluded, but should at thisstage be treated as speculation.

Indeed, we are inclined to think that available estimates overstate the impor-tance of general cognitive skill as a determinant ofearnings, since in many respectstaking a test is like doing a job. Successful performance in eithercase results from

a combination of abi lity and motivation, including the d isposition to follow instruc-tions, persistence, work ethic and othertraits likely to contribute independently toones earnings. This is the reason we eschew the common label ofa test score ascognitive skill, but ratheruse the more descriptive term cognitive performance.Eysenck (1994, p. 9), a leading student ofcognitive testing, writes: Low problemsolving in an IQ te st is a m easure of p erformance; personality may i n uenceperformance rather than abstract intellect, with measurable effects on the IQ. AnIQ te st lasts for up t o 1 hou r or m ore, and co nsiderations of fatigue, vigilance,

arousal, etc. may very well play a part. Thus, some of the explanatory powerof the



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cognitive measure in predicting earnings does not re ect cognitive skill, but ratherother individual attributes contributing to the successful performance of tasks.

Genetic and Environmental Inheritance

Although the genetic inheritance of IQ e xplains little of the intergenerationaltransmission process, this says nothi ng about the possi ble importance of o thergenetically transmitted traits. Indeed, the remarkable income similarity of identicaltwins compared to fraternal twins suggests that genetic effects may be important.We will use the similarity oftwins to estimate the genetic heritability of income aswell as the e nvironmental component of intergenerational transmission.

But t wo words of caution are in or der. First, as we wi ll demonstrate, ourestimates are quite sensitive to variations in unobserved parameters. Second, it issometimes mistakenly supposed that ifthe heritability ofa trait is substantial, thenthe trait cannot be affected much by changing the environment. The fallacy of thisview is dramatized by the case of stature. The heritability of height estimated fromU.S. twin samples is substantialabout 0.90 (Plomin et al., 2000). Moreover, thereare signicant height differences among the peoples of the wo rld: Dinka men in

the Sudan average 5 feet and 11 i nchesa bi t taller than Norwegian and U.S .military servicemen and a w hopping 8 i nches taller than the Hadz a hunter-gatherers in southernAfrica (Floud, Wachterand Gregory, 1990). But the fact thatNorwegian recruits in 1761 were shorterthan todays Hadza shows that even quiteheritable traits are sensitive to e nvironments. What can be concl uded from anding that a smal l fraction of the var iance of a t rait is due t o environmentalvariance is that pol icies to al ter the t rait through changed environments willrequire nonstandard environments that differ from the environments on which the

estimates are based.Consider the case o f South Africa, where in 1993 (the ye ar before Nelson

Mandela became president), roughly two-thirds of the i ntergenerational transmis-sion ofearnings was attributable to the fact that fathers and sons are of the samerace, and race is a strong predictorof earnings (Hertz, 2001). That is, adding raceto an equation predicting sons earnings reduces the estimated effect of fathersearnings by over two-thirds. Because the t raits designated by race are highlyheritable and interracial parenting uncommon, we thus nd a subst antial role of

genetic inheritance in the i ntergenerational transmission of economic status. Yet,it is especially clearin the case of SouthAfrica underapartheid that the economicimportance of the ge netic inheritance ofphysical traits derived from environmen-tal in uences. What made the ge netic inheritance of sk in color and o ther racialmarkers central to the transmission process were matters of publ ic policy, nothuman nature, including the v ery denition of races, racial patterns in marriageand the di scrimination suffered by nonwhites. Thus, the d etermination of thegenetic component in a transmission process says little by itselfabout the extent to

which public policy can or shou ld level a p laying eld.



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Estimates of heritability use data on pairs of individuals with varying degrees ofshared genes and env ironments. For example, identical and fraternal twins are

exposed to si milar environments during their upbringing, but fraternal twins areless closely related genetically than identical twins. Underquite strong simplifyingassumptions (explained in the Appendix) one can exploit the variation in geneticand environmental similarities among pairs of relatives to estimate heritability of atrait such as i ncome, years of schoo ling or other standard economic variables.Taubman (1976) was the rst economist to use this method. The model underlyingthe following calculations assumes that genes and e nvironment affect humancapital, which produces earnings, as the equation below indicates, but the effects ofwealth and ot her contributions to income are unaffected by g enes and env iron-ment and w ill be introduced subsequently.

Here are the assum ptions. First, genes and env ironments have add itiveeffectsgenes and environment may be correlated, but the direct effect of goodgenes on earnings (its regression coefcient) is independent ofthe quality oftheenvironment and conversely. Thus, an ind ividuals earnings can be written

earnings 5 h genes~ ! 1 b~environment ! 1 idiosyncratic effects.

Second, within-pair genetic differences (for the fraternals) are unco rrelated withwithin-pair environmental differences (for example, the good-looking twin doesnot get more loving attention). Third, the environments affecting individual de-velopment are as similarformembers offraternal pairs oftwins as forthe identicaltwins pairs. Fourth, the e arnings genotypes of the tw o parents are uncorrelated(random mating). G iven these assumptions, we show i n the Appendix that theheritability (h ) of e arnings is twice the difference between the earnings correla-2

tions ofidentical and fraternal twins.As the difference between these two correla-

tions is 0.2 in be st data se ts availablethe Swedish Twin Registry studied byBjorklund, Jantti and Solon (forthcoming) and a smallerU.S. Twinsburg data setstudied by Ashenfelterand Krueger(1994)these assumptions give an estimate ofh2 equal to 0.4.

Because, due to the assumption of random mating, the correlation ofgenes forthe fraternal twins is 0.5 , the i mplied correlation of fraternal twins e arningsbecause of genetic factors is h / 2. The fact that the observed correlation oftwins2

earnings exceeds this estimate is explained by the fact that tw ins share similar

environments. Thus, once we know h , we can use information about the degree of2

similarity of these environments to estimate how large the environmental effectswould have to be to generate the observed earnings correlations.

The assumptions concerning random mating and common environments areunrealistic and can be relaxed. First, we need an estimate ofm , the correlation ofyparents earnings genotypes. The relevant measure is the earnings potential(thecorrelation ofactual earnings would understate the degree of assortation, becausemany women do not w ork full time). The degree of assortation on phenotype is

likely to be considerably larger than on g enotype for the si mple reason that the



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basis ofthe assortation is the phenotype, not the genotype (which is unobservable),and the two are not very closely related for the case of e arnings, as we will see.

Assuming that the genotype for potential earnings of parents is half as similaras arethe actual incomes ofbrothers, the correlation would be about 0.2.Second, note that because it was assumed that the environments experienced

by the two identical twins are not, on the average, more similarto the environmentsofthe two fraternal twins, the fact that within-twin-pairearnings differences are lessfor the identical twins must be explained entirely by the irgenetic similarity. But ifthe identical twins experience more similar environments (because they lookalike, for example) than the fraternals, the estimate will overstate the d egree ofheritability.

It is l ikely that identical twins share more similarenvironments than fraternaltwins and ot her siblings (Loehlin and N ichols, 1976; Feldman, Otto and Chr is-tiansen, 2000; Cloninger, Rice and Reich, 1979; Rao et al., 1982). Estimates of theextent to which the environments of identical twins are more similarthan those offraternal twins are qui te imprecise, and we can do no be tter than to i ndicate theeffects of using plausible alternative assumptions. Just how sensitive the estimatesare to reasonable variations in the assumptions concerning differences in thecorrelations of twins environments can be estimated by assuming some degree of

statistical association of genes and environment, with the correlated but not iden-tical genes ofthe fraternal twins giving them less correlated environments than theidentical twins.

Table 1 p resents estimates based on v arious magnitudes of t his genes-environment effect. As the assumed correlation between genes and env ironmentincreases, the c orrelation of the e nvironments of the id entical twins rises, andbecause this then explains some ofthe earnings similarity ofthe identical twins, theresulting estimate of he ritability falls.3 We t ake the thi rd numerical column of

Table 1 as the most reasonable set of estimates. On this basis, two striking conclu-sions follow. First, the he ritability of earnings appears substantial. Second, theenvironmental effects are also large. The no rmalized regression coefcient ofenvironment on earnings is be 5 0.38, which may be compared with the normal-ized regression coefcient for a m easure of ye ars of scho oling in an earningsequation, from our earlier meta-analysis, which is 0 .22. Thus, whi le educationalattainment captures important aspects of the relevant environments, it is far fromexhaustive.

What is the intergenerational correlation ofearnings implied by our e stimateof be and h? To answ er this question, in addi tion to h and be, w e require thecorrelation of parents e arnings with genes (which is already implied by o urestimates) and the cor relation of parents e arnings with environment. The rst

3 The Swedish Twin Registry data set assembled by Bjorklund, Jantti and Solon (forthcoming) has datanotjust on twins, but on many pairs with varying degrees ofrelatedness (half-siblings, for example) andmay allow more robust estimates using the methods developed by Cloninger, Rice and Reich (1979),

Rao et al. (1982) and Feldman, Otto and Christiansen (2000).



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column in Table 2 gives our estimates. The genetic contribution is simply h timesthe correlation between parental earnings and offspring genotype, orh (12 1 m)/ 2. The environmental contribution, similarly, is be times a correlation

of parents earnings and e nvironment (namely 0.74) selected to yi eld a tot alintergenerational earnings correlation of 0 .4.

The estimate that genetic inheritance may account foralmost one-third oftheintergenerational correlation is somewhat unexpected, in light of our neg ativendings concerning the inheritance of IQ. The surprising importance of bothenvironment and genes point to a puzzle. If the genetic contribution is not stronglyrelated to IQ and if the env ironmental contribution is much larger than t hecontribution of years of school ing, what are the m echanisms accounting for per-

sistence of income overthe generations? We shall return to this puzzle, but will turnto data otherthan twins studies rst to show that the same puzzle arises.

Human Capital

Because schooling attainment is persistent across generations and has clearlinks to ski lls and pe rhaps other traits that are rewarded in labor markets, an

account of the transmission of intergenerational status based on human capital hasstrong prima facie plausibility. The data al ready introduced allow a calculation ofthe portion of the i ntergenerational income correlation accounted for by the factthat offspring of high-income parents get more schooling (measured in years). Thisis the correlation of parent income and offspring schooling (about 0.45) multipliedby the normalized regression coefcient of schooling in an earnings equation (0.22from ourmeta-analysis), or0.10. This correlation is substantial, particularly in thelight of the fact that it is restricted to the e ffects of years ofschooling operating

independently of IQ ( because our estimate of 0 .22 is from earnings functions in

Table 1Estimating the Heritability of Earnings

Assumed Correlation ofGenes and Environment 0.00 0.50 0.70 0.80Heritability of Earnings (h )2 0.50 0.29 0.19 0.13Normalized Regression Coefcient:

Genes on Earnings (h) 0.71 0.54 0.44 0.36Environment on Ear nings ( )b 0.29 0.33 0.38 0.44

Correlation of Environments:Fraternal Twins 0.70 0.70 0.70 0.70Identical Twins 0.70 0.80 0.90 0.97

Notes: The association of genes with environment is represented by the normalized regression coefcient

ofgenes on environment. This table assumes that parental earnings-determining genes are correlated0.2, and the c orrelation of fraternal twins environment is 0 .7. We use the correlations of income foridentical twins of0.56 and of fraternal twins of 0.36, taken from the U.S. Twinsburg Study, and assumethat these are also the correlations of earnings.



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which the regressors include the AF QT test or a si milar instrument). The ful lcontribution, including the e ffect of schooling on IQ and i ts effect on earnings aswell as the di rect effect ofschooling on earnings holding constant IQ is 0.12.

It used to be commonly assumed that once adequate measures of schoolingquality were developed, the only effects of parental economic status on offspringearnings would operate through effects on cog nitive functioning and schoo ling,

with the direct effect of parental status on offspring earnings vanishing. But even asthe measurement of schoo l quality has i mproved over the y ears, the estimateddirect effect of parental incomes (or earnings) on offspring earnings has t urnedout to be remarkably robust. Forexample, Mulligan (1999), using early 1990s datafrom the (U.S.) National Longitudinal Study of Youth, rst estimated the effect ofa change in the logarithm of parental earnings on offsprings logarithm ofearningswithout controlling for any o ther factors and the n controlled for a num ber ofmeasures of school quality, as we ll as the AF QT and standard educational anddemographic variables. He found that between two-fths and one-halfof the gross(unconditional) statistical relationship of parental and o ffspring earnings remainseven aftercontrolling forthe otherfactors. These resultsjust reafrm the black boxpuzzle using entirely different data and m ethods: more than two-fths of theintergenerational transmission coefcient is unacc ounted for.4

Taking account of t he fact that the chi ldren of the well-to-do are m uchhealthierthan poorchildren (Case, Lubotsky and Paxson, 2001) along with the factthat poorhealth has substantial effects on incomes laterin life (Smith, 1999) wouldprobably account for a sub stantial part of the i ntergenerational transmission pro-

cess. The role of he alth in t he process is particularly striking because parentalincomes appearto have strong impacts on child health that are not accounted forby either the he alth status of the pare nts nor by the ge netic similarity betweenparents and chi ldren.

4 It is also true that we can typically statistically account for less than half ofthe variance of the earningsorincome using the conventional variables described above. But this fact d oes not explain ourlimitedsuccess in accounting for the i ntergenerational correlation, as this co rrelation measures only that part

of the variation of earnings that we can explain statistically by parental economic status.

Table 2Contribution of Environmental, Genetic and Wealth Effects to Intergenerational

Transmission

Earnings Income

Environmental 0.28 0.20Genetic 0.12 0.09Wealth 0.12Intergenerational correlation 0.40 0.41

Notes: The income column and the estimatedcontribution ofwealth are discussedbelow. The environ-

mental versus genetic breakdown assumes the gures in the third numerical column in Table 1.



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Wealth Effects

Economic success can be passe d on in a fam ily through the inheritance ofwealth as well as intervivos wealth transfers to children. Remarkably little scholarlyattention has be en given to this mechanism, in p art because no re presentativepanel data set with adequate measures ofotherearnings determinants exists forwhich the second generation has reached the age at whi ch the i nheritance ofwealth typically has been completed. The only study of w hich we are aw are thataddresses this problem by following the second generation to theirdeaths estimatesa much higher intergenerational wealth correlation than those reported by Mu lli-gan, above (Menchik, 1979). But while inheritances of wealth clearly matterfor thetop of the income distribution, we doubt whethersuch transfers play an importantrole for most families. Very few individuals receive inheritances of signicantmagnitude. Mulligan (1997) estimates that estates passing on sufcient wealth to besubject to inheritance tax in the United States constituted between 2 and 4 percentofdeaths overthe years 19601995. Even though this gure leaves out some quitesubstantial inheritances, as well as transfers that occurduring life, it seems unlikelythat for most ofthe population a substantial degree of economic status is transmit-ted directly by the intergenerational transfer of property or nancial wealth.

It thus seems likely that the intergenerational persistence of wealth re ects, atleast in part, parent-offspring similarities in traits in uencing wealth accumulation,such as o rientation toward the future, sense of pe rsonal efcacy, work ethic,schooling attainment and risk taking. Some ofthese traits covary with the level ofwealth: forexample, less well-offpeople may be more likely to be risk averse, todiscount the future and have a low sense ofefcacy. Because ofthis correlation ofwealth with the traits conducive to wealth accumulation, parent-offspring similarityin wealth may arise from sources independent ofany bequests or transfers.

Whatever their source, for families with signicant income from wealth,parent-offspring wealth similarities can contribute a sub stantial fraction to t heintergenerational persistence of incomes. Using the same decomposition methodsas abov e, this contribution is the correlation of parent income and chi ld wealthtimes the normalized regression coefcient ofwealth in an income equation. Weuse data from the Panel Study of Income Dynamics analyzed by Charles and Hurst(2002). The correlation between parent income and child wealth (both in naturallogarithms) in this data set is 0.24. The average age of the children is only 37 years,

so this correlation does not capture inheritance ofwealth at death of the parents.To get a rough idea of the normalized regression coefcient, one way to proceedis by starting with the percentage change in income associated with a 1 p ercentchange in wealth; this elasticity will range from virtually zero (for those with littleor no wealth) to one ( for those with no sou rce of income other than w ealth). Aplausible mean value (based on average factorincome shares) forthe U.S. popu-lation is 0.20. We convert this to a normalized regression coefcient by multiplyingby the ratio of the standard deviation oflog wealth to the standard deviation of log

income, also from the PSID data set provided by Charles and Hurst (2002). This



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calculation suggests that the fact that hig her income parents have wealthierchil-dren contributes 0.12 to the i ntergenerational correlation of i ncomes.

This gure, while substantial, may be an underestimate, as it is based on datathat, for the reasons mentioned above, do not capture a key transmission process,namely inheritance of we alth upon the d eath of ones p arents. Moreover, theestimate should be adjusted upward to take account of the fact t hat those w ithgreater wealth tend to have hi gher average returns to their wealth (Bardhan,Bowles and Gintis, 2000; Yitzhaki, 1987). Greaterparental or own wealth may alsoraise the rate ofreturn to schooling and otherhuman investments, but we have noway of taking account of this empirically. For a samp le of ve ry rich parents, thecontribution of wealth to the int ergenerational correlation would be much higher,ofcourse. Fora sample offamilies with very limited wealth, the contribution wouldbe nearly zero. The difference in the contribution of w ealth effects across theincome distribution is a re ection ofthe heterogeneous nature of the transmissionprocess mentioned earlier. Because of the ve ry skewed distribution of wealth, thefamily with the mean level of wealth (to which our estimates apply) is considerablywealthier than the m edian family.

Group Membership and Personality

Thus far, we have fo llowed the production function approach, which under-pins most economic approaches to i ntergenerational transmission, seeking todetermine the contribution of parent-child similarity in o wnership of fac tors ofproduction. We have complemented the usual choice-based approach by includingthe in uence of genetic inheritance. But othertraits are persistent across genera-tions and are arguably as importantfor example, race, rst language, numberof

children, numberof siblings and others. For example, obesity is a predictoroflowearnings for women, while height predicts high earnings for men. Good lookspredict high earnings for both men and wo men, the latter independently ofwhether they hold jobs interacting with the pub lic (Hammermesh and Bi ddle,1993). Bowles, Gintis and Osborne (2002) provide a survey ofempirical evidenceconcerning these and many othe rnonskill determinants ofeconomic success.

Two such v ariables illustrate the potential importance of nonsk ill factors inthe intergenerational transmission of e conomic status: group membership and

personality.Suppose that economic success is in uenced not only by a persons traits, but

also by characteristics of the group of individuals with whom the person typicallyinteracts. Groups may differin a variety of dimensions: average level ofschooling,economic success, cognitive functioning and wealth level. Groups may be residen-tial neighborhoods, ethnic or racial groups, linguistic groups, citizens of a nation orany otherset of individuals who typically interact with one another. Group effectson economic success are well documented and may arise for a numberof reasons,

including discrimination, conformist effects on behavior, differential access to



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information and complementarities in production (Cooper, Durlauf, and Johnson,1994; Durlauf, 2001; Borjas, 1995).

Race apparently plays a signicant role in the intergenerational transmissionofeconomic success. This is suggested by the fact that for t he United States, thecorrelation among brothers earnings estimated by Bjorklund et al. (2002), namely0.43, falls by 0.10 when the sample is restricted to whites.Apparently, what brothersalmost always have in common, namely race, accounts formuch of theirsimilarityof income. The same is true ofparents and theirchildren. In the data se t under-lying Figure 1, the el asticity of offspring family income with respect to parentsfamily income is 0.54, but the same elasticity forwhites only is 0.43 and forblacksonly is 0 .41 (Hertz, 2002). Parent-offspring similarity in i ncome is explained inimportant measure by the fact that race is transmitted across generations. UsingHertzs estimates, we nd that race (that is, the correlation of parents income withoffspring race) contributes 0.07 to the i ntergenerational correlation. While thisestimate is a bit lowerthat those suggested by the above data, it may nonetheless bean overestimate, as it is based on an income equation with the standard regressors,but without a m easure of co gnitive performance, the inclusion of whi ch wouldprobably lowerthe race coefcient somewhat.

A se cond example of traits not found in a co nventional production function

but that contribute to intergenerational status transmission are dispositions such asa sense o fpersonal efcacy, work ethic or a rat e of time discount (present orien-tation). The importance ofthese aspects of personality stems from the fact that ina large class ofexchanges, including the hiring oflabor, borrowing and lending, orthe exchange ofgoods of uncertain quality, it is impossible to specify all relevantaspects of the exchange in a contract enforceable by the courts. Where this is thecase, the act ual terms of the exchange are in uenced by the de gree of t rust,honesty, hard wo rk and ot her dispositions of the parties to the ex change. For

example, a very present-oriented employee will not value the employers promise ofcontinued employment in the future, conditional on hard work now. Instead, suchan employee will require a higherwage to motivate hard work in the present and,therefore, is less likely to be employed.As anotherexample, fatalistic workers whobelieve that the probability of job termination is unaffected by theirown actions willbe costly to motivate underthis type oflaborcontract (Bowles, Gintis and Osborne,2002). The empirical importance of these traits is suggested in a numberof studies(Duncan and D unifon, 1998; Heckman and R ubinstein, 2001; Kuhn and W ein-

berger, 2001; Heckman, forthcoming).Osborne (forthcoming) has st udied the ec onomic importance and int ergen-

erational persistence of fatalism, as m easured by the R otter Scale, a com monmeasure of the de gree to which individuals believe that important events in theirlives are caused by external events ratherthan by theirown actions. Herstudy of asample of U.S m en and the ir parents found that the sco re on the Rot ter Scalemeasured before entry to the labormarket has a stat istically signicant and largein uence on earnings. Moreover, the Rot ter score is pe rsistent from parents to

offspring. The normalized in uence of the RotterScale on earnings in Osbornes



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study is somewhat larger(in absolute value, namely 2 0.2) than the average in u-ence of IQ in o ur meta-analysis of 65 stu dies discussed earlier. The estimated

correlation of parental income with child fatalism is 2 0.14. The contribution of thefatalism channel to the i ntergenerational correlation is the correlation of pare ntincome to chil d fatalism multiplied by the co rrelation from child fatalism tosubsequent income, 0.028that is, (2 0.2)( 2 0.14).

Osborne (forthcoming) also studied a sample ofwomen in England and foundthat measures of social maladjustment taken at ag e eleven (the Bristol Social

Adjustment Scale), such as agg ression and w ithdrawal, are strong predictors ofearnings at age 33. The normalized in uence ofpersonality traits of aggression andwithdrawal on earnings is considerably larger than the i n uence of IQ. The re areno measures of intergenerational persistence ofpersonality traits in the OsbornesEnglish data set, but otherstudies suggest that parent-child similarity in measuresofsocial maladjustment may be quite high. For example, Duncan et al. (forthcom-ing) found that deviant forms of behaviors ofU.S. mothers were strong predictorsofthe same behaviors in daughters, including drug use, violent behaviors, early sex,suspension from school and criminal convictions. Osbornes work thus suggeststhat the int ergenerational transmission of p ersonality traits (whether genetic orcultural) may be an i mportant channel explaining the i ntergenerational persis-

tence of income.We know relatively little about the workings of the intergenerational transmis-

sion process forpersonality traits relevant to economic success, otherthan cognitivefunctioning. However, Kohns (1 969) study of c hild rearing values of pare ntssuggests that at l east forsome traits, parents experiences in the wo rkplace aregeneralized and passed on to children. Kohn categorizes his parent sample by thedegree of self-determination that each experiences on the job, rang ing from thosewho are relatively unsupervised to those who are closely directed by superiors. Kohn

found that parents with high levels of what he te rmed occupational self-directionemphasize curiosity, self-control, happiness and independence as values for theirchildren. Those who are closely monitored by supervisors at w ork emphasizeconformity to external authority. Kohn concluded: Whether consciously or not,parents tend to impart to the irchildren the lessons derived from theirown socialclass and thus help prepare theirchildren fora similarclass position. The work byOsborne suggests that the degree of self-direction has signicant effects on earn-ings laterin life. Otherwork by Yeung, Hill and Duncan (2000) shows that parental

behavior, including church attendance, membership in social organizations andsuch precautionary behavioras seat belt usage have signicant impacts on the irchildrens e arnings.

Conclusion

Recent evidence points to a m uch higher level of intergenerational transmis-

sion of economic position than was previously thought to be the case.America may



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still be the land of opportunity by some measures, but parental income and wealthare strong predictors of the l ikely economic status of the next generation.

Our main objective has been to assess the extent of intergenerational

transmission and the mechanisms a ccounting for it. Table 3 s ummarizes ourbest estimates o f the relative importance o f the main causal channels we havebeen able to identify. The only entry not previously explained is the rst, whichis an estimate of the correlation between parental income and child IQ multi-plied by our estimate of the normalized effect of IQ on earnings, conditionedon, among other things, years ofschooling. The estimates for IQ, schooling andpersonality in the income column are simply those in the earnings columnadjusted to take account of the effect of earnings differences on income

differences, suitably normalized as described in Bowles and Gintis (2001). Thus,we do not take account of the way that these earnings determinants may affectthe rate of return to ones wealth. By contrast, we assume that the race effect isof the same magnitude in determining the returns to both human capital andconventional wealth (if the race effect on incomes worked solely via an effect onearnings, its contribution to the intergenerational earnings correlation wouldbe signi cantly greater).

While the estimates in Table 3 are qui te imprecise, the qualitative results are

not likely to be affected by reasonable alternative methods. The results are some-what surprising: wealth, race and sc hooling are i mportant to the i nheritance ofeconomic status, but IQ is not a majorcontributor, and, as we have seen above, thegenetic transmission of IQ is e ven less important.

A pol icymaker seeking to l evel the playing eld might use these results todesign interventions that w ould loosen the connection between the e conomicsuccess of parents and the economic prospects of theirchildren. But does a levelplaying eld entail no correlation between parental and chi ld incomes (Swift,

forthcoming)? There are important values of family life and privacy that would be

Table 3The Main Causal Channels of Intergenerational Status Transmission in the U.S.

Channel Earnings Income

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

Correlation Accounted For 0.25 0.32

Notes: Foreach channel, the entryis the correlation ofparentincome with the indicatedpredictorofoffspring income, multiplied by its normalized regression coefcient in an earnings or income equation.The total is the intergenerational correlation resulting from these channels, in the absence of a di recteffect of parents status on offspring status.Source: Calculations describedin textand Bowles and Gintis (2001).



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compromised by any serious attempt to di sconnect the fortunes of parents andchildren completely. Ratherthan pursuing an abstract (and to ourminds unattrac-

tive) objective ofzero intergenerational correlation, a betterapproach might be toask which mechanisms ofintergenerational transmission seem unfair, and to directpolicies accordingly. The role of race in transmitting status from generation togeneration is clearly unfair. Many pe ople regard the strong correlation betweenparental income and child health as morally suspect, and many feel the same wayabout high levels of wealth inheritance. Large majorities favorpolicies to compen-sate for i nherited disabilities. Other mechanisms of pe rsistencethe g enetic in-heritance of good looks, forexamplestrike most people as unobjectionable andnot an appropriate target for compensatory policy interventions. Even if som econsensus could be formed on which of these mechanisms are morally suspect, thepolicy implications would be far from clear. For example, the po ssible incentiveeffects on parental behaviors of reduced parental in uence on child success wouldhave to be estimated and considered.

Appendix

Decomposing Correlation Coef cients and Estimating Heritability

Suppose parental earnings ydirectly affects offspring earnings y, but offspringpearnings is also affected by tw o variables, v1 and v , that ar e correlated with2parental earnings. Then, if r5 y vp 1 and ry vp 2 are the correlations of parental earningswith vand v, respectively, and ifthe normalized regression coefcients ofy, v,1 2 p 1and v predicting y are g iven by

2 by yp , bv y1 and bv y2 respectively, we have

(1) rypy5 bypy1 rypv1bv y1 1 rypv2 bv y2 .

This is the correlation between parental and offspring earnings, decomposed intoits direct effect (the rst te rm), the effect via variable v(the second term) and the

1

effect via variable v2 (the thi rd term). To derive this equation, we write

(2) y5 bypy py 1 bv y1 v1 1 bv y2 v2 1 y,

where all variables are normalized to have zero mean and unit variance, and yisuncorrelated with the independent variables. Then, substituting the above expres-sion foryinto the expectation E[ y y], and noting that iftwo variables (e.g., yandpy ) have zero mean and unitvariance, the correlation between these variables is thepexpected value of theirproduct, we get

5 Forprevious treatments of this material, see Rao, Morton and Yee (1976), Cloninger, Rice and Reich

(1979), Rao et al. (1982) and Otto, Feldman and Christiansen (1994).



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(3) rypp5 E y y@p #5 E y y@p p#byp y1 E v y@1 #bv y1 1 E v y@2 #bv y2 .

Since, given our normalization, E[ y y ]p p 5 1, E[v y]1 5 rv y, and E[v y ]1 2 5 rv y2 ,we arrive at equation 1.6

We now apply this method to estimating heritability using data on similarity ofidentical and fraternal twins. A m ore general treatment, using pairs of varyingdegrees of re latedness, is developed in Fe ldman, Otto and Christiansen (2000).Suppose a family has two sons whose earnings, yand y, depend additively on their1 2genotypes, gand g , and the irenvironments, e1 2 1 and e . Thus,2

(4) yi5 be ie 1 hgi 1 yi for i5 1, 2,

where yi is uncorrelated with the independent variables in the model and is chosensuch that the variance ofyis unity. The variances ofe and gare also normalizedi i ito unity. Note that the normalized regression coefcient of genotype is then h, thesquare root of the heritability ofearnings. We assume the environment e ofbrotherii depends both on his genotype g and the common familyenvironmentE. We thusihave

(5) ei5 bEE1 bgegi1 ei for i5 1, 2,

where ei is uncorrelated with the independent variables in the model and is chosensuch that the var iance of e is uni ty. We i nterpret E as i ncluding the effect ofiparental earnings, education and any othe r environmental factor that affectsoffspring earnings and i s shared by brothers. For simplicity, we include the fulleffect of genes on environment in the co efcient bge, so g is uncorrelated with E.iFinally, the genotype gofbrotheriis determined by the genotypes of the parents,igiven by

(6) gi5 bggf1 bgg ,m

where gand gf m are the genotypes of fatherand mother, and bgis the normalizedregression coefcient (path) o f fathers (o r mothers) g enotype predicting sonsgenotype. The structure of this model is illustrated in Figure 3.

To show that bgis 1/2, suppose m is the correlation ofmaternal and paternaly

genes. Since we are assum ing additivity (meaning that the tot al effect of t hegenome is the sum of the effects of each gene), we can derivebgfora single locus.We label each possible gene at thi s locus with the amo unt x it contributes toearnings. We normalizedxso that E[x] 5 0 and E[x]

25 2. By basic genetics, a son

6 Note that the same argument holds ifwe replace the expectations, which referto population values,with the sample means, variances and covariances. In this case, the statistical independence ofthe errorterms and the i ndependent variables is assured by construction, whereas on the population level this

independence is assumed.



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inherits one copy of the gene at the locus from each parent, sayxfrom the fatherfandxm from the mother. The value ofgenes at this locus fora son i s then (xf 1

x )/2, assumingthat both genes have equalexpectedeffecton economicsuccess,mwhich we do here and throughout. In addition to x , the fatherhas anothergene7 fwith value zat this locus, with the same mean 0 and variance 2. The correspondingfvalue for the father is then ( xf 1 z )/ 2, whe re x and z are uncorrelated. Thef f fcorresponding value forthe motheris (xm 1 z )/ 2, where zm m is the mothers othergene at this locus, andxm and zm are uncorrelated. Because ofassortative mating,

each gene of the fatherx, z, is correlated m with each gene of the motherx, z.f f y m mThe variance of the parents g enetic value at thi s locus is E[(xm 1 z ) /4 ]m

25

E[(x f 1 z ) /4]f2

5 1, and the c ovariance of father and son is E[(xf 1 z )(xf f 1x )/4]m 5 (1 1 m )/ 2. The refore, the correlation of fathe rs and so ns geneticyvalue at this locus is the quotient of the previous two expressions, or

(7) rgfgi5 b 1 bge gemy51

2 1my2

.

The rst term in this expression represents the direct path from fathers genometo sons, and the second is the correlation of fathers and mothers genetic value atthe locus, m , multiplied by the direct path from motherto son at that locus. To seeythis, recall that the least squares estimator of b

1in the regression equation

7 The actual value ofa pair of genes at a locus can be higheror lowerthan theiraverage value, ofcourse,

as when one gene is dominant or recessive.

Figure 3The Earnings of Brothers

Notes: In this diagram, g and gf m are the g enotypes of fatherand mother, gand gare the genotypes1 2of brothers, E is the common environment of brothers, e and e are the to tal environment of1 2brothers and y1 and y2 are the earnings ofbrothers. Here, m is the ge netic relatedness of parentsybased on assortative mating and as explained below, b g5 1/ 2, while h

2 is t he heritability ofearnings. The path l abeled b gerepresents the tendency ofgenes to affect the environments ( b ge. 0means that identical twins experience more similar environments than fraternal twins).



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y5 b x1 1 1 b x2 2 1 , wherex,xand yare normalized to mean zero and variance1 2unity, and where is uncorrelated with xand x , is given by (Goldberger, 1991):1 2

(8) b1 5rx y1 2 rx x1 2rx y2

1 2 rx x1 2.

In ourcase, b1 5 bg, rx y1 5 rx y2 5 (1 1 m )/ 2, and ry x x1 2 5 m . Substitutingin they

above expression, we get bg5 1/ 2.To d etermine the correlation of fraternal twins ge notypes, we multiply the

right sides of (6 ) for i 5 1, 2, and tak e expectations, giving

rg g1 2

fr5 E g g@1 2#5 ~1/2 E g!

2@f

2#1 ~1/2 E g! 2 @m

2#1 2 1/ 2 E g g~ ! 2 @m f#

5 ~1/2 ! ~2 2 1 2my! 5 ~1 1 my! /2,

which, consulting (7), conrms the standard result in genetics that fathers and sonson the one hand and nonidentical brothers with the same parents on the otherareequally related. To determine the correlation of environments of fraternal twins, we

multiply the right sides of (5 ) for i 5 1, 2 and tak e expectations, giving

re e1 2

fr5 b 1E

2 rg g1 2

frb 5 b 1ge

2E2

~1 1 my!bge2 /2.

Finally, multiplying the right sides of (4) fori5 1, 2 and taking expectations, we get

ry y1 2

fr5 be

2re e1 2

fr1 h r2 g g

1 2

fr1 2behrg g1 2b ge,

which expands to

(8) ry y1 2

fr5 be

2~b 1E

2~1 1 my!bge

2 /2 ! 1 h 12~ 1 m /2y! 1 ~1 1 my!b be geh.

In the case o f identical twins, the same gure is relevant, but now the correlationofgenotypes ofbrothers is rg g1 2

id5 1. We the n

re e1 2

id5 b 1

E

2 rg g1 2

idb 5 b 1 b

e

2

E

2

ge

2 ,

and

ry y1 2

id5 be

2re e1 2

id1 h r2 g g

1 2

id1 behre g

1 2

id1 behre g

2 1

id ,

which becomes

(9) ry y1 2

id

5 bE2

~b 1 bE2

ge

2

! 1 h

2

1 2b be geh.



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In the text, we assume re e1 2

id5 0.9 for id entical twins (although our results are not

very sensitive to this assumption), so be 5 = 0.9 2 bg2. The two equations for the

correlations of brotherearnings, (8) and (9), togetherwith the observed values ofthese correlations, allow us to d etermine h and be for various values ofbg.Equations (8) and (9 ) imply that the di fference between the correlations of

earnings of identical and fraternal twins is given by

(10) ry y1 2

id2 ry y

1 2

fr5 ~1 2 my!~h 1 b be ge!

2/2.

Note that assum ing greater assortative mating raises the estimate of h , whi le2

assuming a strongertendency forgenes to effect environment (raising bge) has theopposite effect, as one would expect. In the literature, it is often assumed that my50 and bge 5 0, in w hich case we g et the standard equation for estimatingheritability:

(11) h2 5 2 r~ y y1 2

id2 ry y

1 2

fr! .

If this is the case, we can estimate h directly from this equation and then use this2

estimate ofh , togetherwith (8), to estimate2 be.

y We would like to thankJere Behrman,Anders Bjorklund, Kerwin KoCharles,BradfordDe Long, Williams Dickens, Marcus Feldman, James Heckman, Tom Hertz,ErikHurst,Arjun Jayadev, ChristopherJencks,Alan Krueger, John Loehlin, CaseyMulligan, Suresh Naidu, RobertPlomin, Cecelia Rouse, MichaelWaldman andElisabethWoodfortheircontributions to thispaper, BridgetLongridge andBae Smith forresearchassistance and the John D. andCatherine T. MacArthur Foundation fornancial

support.

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Week 2 the Inheritance of Inequality

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