Does Money Whiten? Intergenerational Changes in Racial Classification in Brazil

Does Money Whiten? Intergenerational Changes in Racial Classification in Brazil*

                                      Luisa Farah Schwartzman

                                  University of Wisconsin, Madison


        The idea that “money whitens” is a classic topic in the sociological literature on race in
Brazil. This paper estimates the extent to which socio-economic status translates into racial
boundary-crossing (“whitening” and “darkening”) across generations, by examining the effect of
parents’ education the racial classification of their children racially in a national household
survey (PNAD 2005). The role of inter-racial marriage as an intervening variable is discussed.
The paper finds that more educated non-white parents are more likely to classify their children as
white than comparable less educated non-white parents. This happens because 1) more educated
non-white parents are more likely to marry whites and less likely to marry non-whites and 2)
more educated inter-racial couples label their children white more often than do less educated
inter-racial couples. Conversely, less educated white parents are less likely to classify their
children as white than more educated white parents. Comparisons with 1996 data also suggest
that recent shifts in racial politics have offset the whitening effects of college education for
non-white men with white wives. The results allow us to better understand the nature of racial
boundaries in Brazil and lead us to re-examine the relationship between race and the inheritance
of socio-economic advantage.

* This is a pre-edited version of a paper published in the American Sociological Review. Vol 72,
pp. 940-963, December 2007. The edited, published version could not be posted due to copyright
restrictions. If you would like to cite this paper, please refer to the published version, or contact the
author at

The high correlation between skin color and socio-economic status in Brazil and its

persistence from one generation to another has attracted continuous interest among stratification

researchers. Many scholars attempted to examine this relation by looking at how the chances of

intergenerational mobility vary by “racial group,” assuming that group boundaries stay fixed

from one generation to the next (for example, Hasenbalg and Silva 1988; Pastore and Silva 2000).

However, in Brazil, this assumption is problematic because of a process long known as

“whitening.” Following Harris (1956) and others, Ianni (1960) argued that “black” or “mulatto”

families become “white” as they move upward:

       To “whiten” is a “universal” aspiration. Blacks, dark mulattoes and many light mulattoes – all

       want to whiten (…). Marrying a lighter individual suffices for the darker one to be satisfied.

       This person feels as if she had whitened a little, only by marrying a lighter-skinned person.

       Another peculiarity of this phenomenon is the effective whitening of the offspring. To have

       lighter descendents is a reason for pride. The individual becomes better regarded in his own

       group. To marry their offspring with even whiter – or less black - individuals, is the most

       important goal of the parents. It seems to them that in this way their integration into the white

       group becomes realized. (Ianni, 1960, my translation)

“Whitening” for Ianni is a matter of both being treated as “white” after moving up in the

socio-economic hierarchy, and of marrying a partner with whiter skin. This process is cumulative:

upwardly mobile blacks and mulattoes are treated as whiter, then inter-marry with yet whiter

people and give birth to whiter children, who they hope will have even whiter spouses. The goal

of whitening is to integrate into the white group.

       Survey-based research has confirmed that non-whites tend to marry whites more often

when they have higher socio-economic status (Berquó 1987; Silva 1987; Scalon 1992; Telles

2004).1 Comparisons between interviewer and interviewee classification also show a relationship

between category ambiguity and socio-economic status (Silva 1994; Telles 2004; Bailey and

Telles 2006). However, survey research has not fully examined how inter-marriage and changes

in racial classification operate in conjunction. Following Ianni’s idea, this paper looks at

“whitening” from an inter-generational perspective, searching for links between inter-marriage,

socio-economic status and the classification of children in a nationally representative dataset.

       Though recent survey-based research on racial inequality in Brazil has recognized the

possibility of racial reclassification (whitening), this phenomenon has been typically treated as

an “error” to be corrected for when explaining inequalities between “racial groups” (e.g. Silva

1994; Lovell and Wood 1998; Telles 2004). This paper instead looks at whitening as an inherent

part of stratification processes that generate racial inequality, investigating the conditions and

magnitude of intergenerational boundary-crossing in relationship to processes of distribution or

concentration of resources in society.

       The tendency to treat racial reclassification (whitening) as an error has resulted from

implicit borrowing of the “caste assumption” from studies of inequality between blacks and

whites in the United States. What has been described as “race” in both Brazil and the United
States can be understood as instances of Weberian status groups (Weber [1922] 1970).

Black-white relationships in the United States are characterized by an extreme degree of closure,

and resemble what Weber would call a “caste.”3 Relationships between whites and non-whites in

Brazil do not have such a high degree of closure. Research on race in Brazil may thus learn from

studies other racial or ethnic groups in the United States that have a more open set of relationship

with whites. As studies of non-black racial/ethnic minorities such as Asians and American

Indians in the United States have done, it is useful to examine the relationship between

socio-economic status and the degree to which boundary-crossing occurs (e.g., Nagel 1995; Xie

and Goyette 1997; Alba and Nee 2003; Qian and Lichter 2007).

       With these insights in mind, I take an inter-generational approach to whitening, looking

at how the education of a person is correlated with the racial classification of his or her children

and how intermarriage mediates this relationship. I also estimate the relationship between

education and whitening for inter-racially married couples. I use nationally representative

household survey data, which allows me to make claims for the Brazilian population as a whole

and provides an estimate of the magnitude of the effects of socio-economic status on whitening.

My findings confirm the idea that “money whitens” and also that “poverty darkens.” Children of

highly educated non-white parents are significantly more likely to be classified as white than

children of parents with less education. This happens both because of the higher rate of

inter-marriage of non-whites at higher educational levels and because more highly educated

inter-married parents have a greater likelihood of classifying their children as white. Conversely,

children of white parents tend to be classified in non-white categories more often when parents

have less education.

       Comparing survey data from 1996 with 2005, I discuss how changes in racial politics of

the last decade may be changing how parents classify their children. Men with college degrees

married to white women are now as likely to classify their children as “white” as their less

educated counterparts.


       The claim that upwardly mobile blacks or mulattoes would try to become incorporated into

Brazilian white society was common in classic qualitative studies of the 1950s and 60s (Harris

1956; Ianni 1960; Harris and Kotak 1963). Early quantitative studies of race in Brazil (e.g.,

Hasenbalg and Silva 1988) ignored this whitening process at first, and focused instead on

documenting the differences in socio-economic achievement between whites and non-whites which

remain after racial differences in socio-economic background are taken into account. Studies of

mobility, for example, have shown that non-whites have much more difficulty rising in the

socio-economic scale than whites (Hasenbalg and Silva 1988; Pastore and Silva 2000).

       Silva realized, however, that if “money whitens” these results would be problematic, due to

the possibility that people change their racial classification when they move upward, in which case

the studies would be underestimating the upward mobility of non-whites. This led Silva (1994) to

look for measures of race that would not be affected by socio-economic status. He compared

interviewer and interviewee classifications, using a 1986 Gallup survey of São Paulo. He wrote

that interviewers were “trained,” implying that their classification would be less affected by the

interviewee’s socio-economic status than the interviewee’s self-classification. Finding that

interviewees classified themselves whiter than interviewers’ classification when they were richer

and more educated, and that the opposite was true when they were less educated, Silva concluded

that “money whitens” and that “poverty darkens.”

       Telles and Lim (1998) and Telles (2002; 2004) used a similar approach as Silva’s, claiming

that interviewers’ classification represented the views of the discriminator more accurately than the

interviewee’s self-classification, and using a nationally representative sample from 1995. However,

they found the opposite results: money whitened the interviewer’s classification, not the

interviewee’s. In explaining the difference between his own and Silva’s findings, Telles (2002)

noted that, in Silva’s (1994) sample, 29% of respondents classified themselves in categories that

were not available for interviewers to choose from. 4

       Another approach to dealing with the possibility of “whitening” using quantitative

techniques has been demographic estimates of how many Brazilians have been racially reclassified

between censuses (Wood 1991; Wood and Carvalho 1994; Lovell and Wood 1998; Carvalho,

Wood and Andrade 2004). Carvalho et al. (2004) found a large trend in reclassification from black

to brown in the 1950-80 period, a much smaller one from white to brown and a similar but less

pronounced pattern between 1980 and 1990. They attribute this switch from black to brown to high

rates of social mobility in the 1970s, consistent with a “money whitens” hypothesis.

       Authors in both lines of research used their estimates of whitening to account for potential

“errors” in studies of racial inequality. Silva (1994) and Telles (2004) justify their comparisons

between self- and interviewer classification as a way of finding out whether their estimates of racial

inequality in education and income are overstated (Silva’s conclusion) or understated (Telles’s

conclusion). Lovell and Wood (1998) use Wood’s (1991) estimates of changes in classification

between censuses to justify their use of a “white” and a “non-white” categories that are

subsequently used to show racial disparities in life expectancy, schooling, occupation and earnings.

They argued that the white category is relatively stable while people cross between black and

brown more easily, so it makes more sense to analyze browns and blacks as belonging to one racial

group and whites as belonging to another. Along similar lines, Carvalho et al. (2004) justify their

estimates of inter-census classification as a response to a need for “accurate” measures of racial

status for diagnosing of racial inequality and for designing policies to address it.


        Approaching “whitening” as an “error” is partly a consequence of the use of a U.S.

black-white model, where racial boundaries are seldom crossed between generations or within an

individual’s lifetime. In contrast, this paper frames “whitening” as a form of boundary-crossing,

using a framework that has been used to examine the extent and forms of assimilation of ethnic

minorities into mainstream United States (Alba and Nee 2003) and, more recently, to examine

“whitening” in contexts with more blurred black-white boundaries, such as Puerto Rico

(Loveman and Muniz, Forthcoming). More specifically, this paper addresses the extent to which

socio-economic status affects inter-generational boundary-crossing (i.e., the extent to which

“money whitens” across generations) as a result of its effects on inter-marriage and on the

classification of children. Though in the United States socio-economic status has caused very

little inter-generational boundary-crossing across the black-white boundary, it has affected

inter-marriage and classification of children among other American racial minority groups

(Nagel 1994; Qian and Lichter 2007; Xie and Goyette 1997; Qian 2004; Roth 2005).

       The ethnic assimilation literature identifies several mechanisms that mediate the

relationship between socio-economic status and inter-generational boundary-crossing. Such

factors influence both inter-marriage patterns and norms of categorization of children of mixed

marriages. Because ethnic and racial categories are often experienced as rooted in lineage and

biology, an individual’s range of classification choices is often constrained by the classification of

her ancestors. Inter-marriage thus tends to decrease the constraints on the ethnic/racial identification

of children, often blurring racial/ethnic boundaries (Alba and Nee 2003; Qian and Lichter 2007) or

making them “optional” (Waters 1990; Nagel 1995; Xie and Goyette 1997). At the same time,

prevailing social norms may influence or even determine how children of inter-racial marriages

should be classified.

       Marriage choices are constrained by the degree and nature of the interaction between

groups, which in turn depends on relative group size and their geographic distribution. Since

people tend to have closer social interactions with people of a similar social position, the relative

distribution of groups across the socio-economic scale will matter as well (Gordon 1964; Blau

1977; Alba and Nee 2003). The perceived social distance between racial/ethnic groups and the

degree of class endogamy will also affect inter-marriage patterns.

       Social contact between groups can also affect how people assign labels to children and to

themselves. A minority group member’s higher position in the socio-economic hierarchy may

either increase or decrease his chances of identifying himself - or his children - with the dominant

group. On the one hand, in a context where minority groups are disproportionately represented in

the lower classes, upwardly mobile individuals may decrease contacts with their minority group of

origin to enter into social networks of the dominant group. Therefore, a minority group member

may be more likely to start identifying herself or her children with the majority group (Gordon

1964; Xie and Goyette 1997). If this contact results in marriage with a dominant group member,

then children are even more likely to be identified as belonging to the dominant group. On the

other hand, heightened contact with the dominant group may increase individuals’ awareness of

their minority status through more direct experiences with discrimination and competition with the

dominant group (Portes 1984; Xie and Goyette 1997). In the Brazilian case, the removal of class

differences between whites and blacks through social mobility sometimes also heightens the

awareness that existing discrimination is based on race, not class (Teixeira 2003).

        The direction of this effect depends on the specific historical, normative and political

context. In the U.S., the multi-racial movement has caused a blurring of racial boundaries for

some people (Nobles 2000), while government policies have encouraged minority identification

for descendants of others – such as American Indians (Nagel 1995). The impact of political and

cultural shifts may also differ by social class. New government policies may disproportionately

benefit people with a particular class background or educational level. Social movements that

advocate for identity politics might operate in certain class-related contexts, such as labor unions,

neighborhood associations or college campuses.

       How do cultural and structural factors affect inter-generational boundary-crossing in Brazil?

The impact of these factors on inter-marriage has been well studied in the Brazilianist literature and

will be reviewed in the next section. How those factors affect the labeling of Brazilian children is

an original contribution of this paper. Because I identify a change in the norms for labeling children

between 1996 and 2005, I will also give the reader some background on recent changes in racial

politics that most likely explain this shift.


        Marriage between browns and whites in Brazil is much higher than marriage between

blacks and whites in the United States, even when the relative population sizes are taken into

account (Telles 2004). 5 Marriage between blacks and whites in Brazil is less common than

between browns and whites (though still more common than between blacks and whites in the
U.S.), with browns serving as a buffer zone between the two (Silva 1987, Petruccelli 2001; Telles


          Browns and blacks out-marry more as their socio-economic status increases (Berquó 1987;

Scalon 1992; Telles 2004). Out-marriage of upper-class non-whites could be explained by people’s

tendency to marry within their own social class, combined with the fact that whites are

over-represented in higher socio-economic levels. When the proportion of whites at each

socio-economic level is taken into account, higher SES actually makes blacks and browns more

endogamous (Scalon 1992).

          Models that control for racial composition by social class presuppose a high degree of class

homogamy (marriage within the same or adjacent class categories). Research on educational

assortative mating in Brazil shows that this is not an unreasonable assumption. Silva (2003) found

that, in 1999, about half of Brazilians married within their own educational level, and they were

more likely to marry adjacent levels than levels that were further removed from their own. 7 These

effects can be found even if one accounts for people’s distribution across educational categories. In

a comparison between 65 countries, Smits, Ultee and Lammers (1998) find that Brazilian

educational homogamy is not only higher than the United States, but also quite high for world

standards, taking into account differences in the distribution of education among men and women.

          In sum, research shows that people with higher socio-economic status (regardless of race)

tend to marry whites more often than those with lower socio-economic status. However, this does

not seem to be solely due to a strategic decision by non-whites as Ianni’s description suggests:

since people tend to marry those with similar socio-economic status and since there is a greater

proportion of whites in the higher social strata, there is a higher probability that people with more

money and more education, whether white or non-white, will marry whites more often than people

with less money or less education.


As the data analysis will show, there has been a change in the relationship between

socio-economic status and the racial classification of children between 1996 and 2005. This

change is most likely explained by a shift in racial politics between the late 1990s and the early

2000s. The last ten years were characterized by a closer relationship between the Brazilian black

movement and the federal government and an increasing use of race as a criterion for policy.

This shift has provoked a radical break from the previously officially sanctioned ideal of racial

democracy, which advocated that Brazilians were – and should be - a mixed-race people, consisting

of a mixture of “whites”, “blacks” and “Indians” (Fry 2000; Loveman 2001; Nobles 2000; Htun

2004). Instead, the media and government officials have increasingly stressed the country’s

division between blacks (negros) and whites.

       Though the influence of the black movement on government discourse and policy was a

gradual process that began with the democratization period in the late 1980s (Mitchell 1985;

Telles 2004), a major black movement demonstration in 1995, pressuring a government that was

more open to new ideas about racial politics than before, started a major shift in Brazilian racial

politics (Htun 2004). In 1996, the Brazilian government for the first time officially

acknowledged the existence of racial discrimination in Brazil. During the late 1990s, several

joint committees and meetings were organized where black movement activists, academics and

the government met to discuss race-targeted policies, culminating in a joint elaboration of the

Brazilian delegation’s document at the Durban Conference on Racism in 2001 (Htun 2001) - a

document that proposed, among other things, race-targeted affirmative action for university

admissions (Peria 2004, Machado 2004, Htun 2004). The press coverage of the conference led to

a public discussion of racial inequality and racism, whose language implied a conflict between

blacks (negros) and whites (Peria 2004). In 2002, race-targeted policies were adopted for

university admissions (Htun 2004; Machado 2004; Peria 2004; Telles 2004).

       Higher education has been disproportionately affected by this shift. Besides the

introduction of race-based affirmative action policies in several Brazilian public and private

universities, several black movement organizations have, since the beginning of the 1990s,

started to organize more grassroots preparatory courses for the “black and needy” to go to the

university, some of them requiring students to attend lectures about “citizenship,” where racial

consciousness is an important component. Because of this, we would expect that an “ethnic

renewal” (Nagel 1995) would occur disproportionately among more highly educated Brazilians.


        The goal of this paper is to investigate the combined roles that inter-marriage,

socio-economic status and the racial classification of children in inter-racial marriages play in

explaining “whitening” across generations. This relationship can be explained in terms of the

following empirical questions.

        1) To what extent is a non-white person with higher socio-economic status more likely to

            label his or her children white than a non-white person with lower socio-economic


        2) Through what mechanisms does the socio-economic status of a non-white parent affect

            the chances that his or her children will be classified as white?

      I investigate two mechanisms through which a non-white parent’s education can affect his or

her child’s racial classification. The first is that socio-economic status can affect inter-marriage:

upper-class non-whites tend to marry whites more often than lower-class non-whites, and thus

are more likely to label their children “white.” The second mechanism is that socio-economic

status can affect “inheritance rules,” that is, the prevailing practices of transmission of racial

categories between parents and children.8 I also investigate if these rules of inheritance change

over time. In order to evaluate the impact of any changes in cultural norms as related to racial

identification, I compare results of 2005 with those of 1996.

This paper will investigate not only if “money whitens”, but also whether “poverty

darkens,” that is, if whites of lower socio-economic status classify their children in non-white

categories more often than whites of higher socio-economic status. This hypothesis can be found

in the literature. Silva (1994) found that “poverty darkens” when comparing interviewer and

interviewee classifications. Twine’s (1994) ethnographic study also found that poor whites often

downplay their whiteness in order to show solidarity with lower-class blacks. In Brazil class

solidarity in labor movement (Andrews 1991; Seidman 1994) and in attitudes toward affirmative

action (Bailey 2004) are stronger than racial solidarities.


        In order to answer the questions delineated above, I use a dataset from a national

household survey (PNAD) collected in 2005 by the Brazilian Institute of Geography and Statistics

(IBGE), the agency also responsible for the Brazilian census. The original dataset is a

geographically stratified sample covering all the Brazilian territory, with 142,471 household units

and 408,148 individual cases. 9

       Each household unit contains a “mother,” which is the female head or spouse, a “father,”

which is the male head or spouse and children, whose position in the household is classified as

“child” in the survey (the survey does not distinguish between stepparents, adoptive parents and

biological parents). People not in one of these three positions (child, head, or spouse) were

excluded from the sample.10 My subsample is also restricted to two-parent households.

       The original survey had five options for racial categories: black (preto), brown (pardo),

white (branco), yellow (amarelo), and indigenous (indígena). Because the yellow and indigenous

categories are too small to be treated statistically using these data, I excluded all the cases where

either mother, father or child were classified within these categories. I also excluded cases where

information on their “race or color” was missing or “other.” 11 I also excluded 3,201 children were

from the sample where fertility questions indicated that they were not the mother’s biological

children and 3,180 children whose biological ties to the mother could not be determined. There

was not enough information to determine which children were adopted, step- or biological children

of the fathers. This means that children of more educated mothers may be labeling their children as

white more often than less educated ones simply because the unobserved biological father is more

likely to be white when mothers are more educated. The same might be true for adopted children

(higher class parents may be more likely to adopt white children). However, other data suggest that

stepchildren in two-parent households are not very common in Brazil. 12

        This paper focuses on parents’ classification of their children, not on children’s

classification of themselves. There is a pragmatic and a theoretical rationale for this. Pragmatically,

current data do not allow for comparisons between children’s and parents’ choices, because there is

no survey in Brazil that asks both parents and children to classify themselves. The theoretical

rationale is that examining parents’ choices of how to label their children reveals the way that

Brazilians think about race and its inheritability.

        Evidence suggests that the respondent in the household is usually the head or the spouse,

and that women are more likely to be respondents than men (Saboia, 2002). 13 In order to have

more confidence that children in the sample were not classifying themselves, I eliminated all the

cases where the children were 15 years or older. Also, since I wanted to know parents’

classification choices and therefore did not want to count multiple times parents with more than one

child, I randomly selected one child in each household. This substantially reduced the sample size

but made it more interpretable and eliminated a likely problem of correlation among observations

within households. Thus, my final sample consists of 41,647 two-parent families where children

are younger than 15, where everyone is black, white, or brown, and where the mother and the

father are classified as the head or the spouse in the household.

        In order to assess the changes caused by the political shift of the last decade, I did the same

analysis using the 1996 PNAD, which I use to compare with results from 2005. However, the

results for 1996 are only shown in Figure 1. All tables refer to the 2005 data.


        In order to investigate the relationship between socio-economic status and intergenerational

whitening and darkening, I ran a series of logistic regressions, which are shown in Tables 5 and 6.

I use education as a proxy for socio-economic status, for reasons that will be explained below.

First, I predict child’s racial classification from one of the parents’ education, separately for

mothers and fathers (models 1,3, 6 and 8). Then, I repeat the procedure controlling for the other

parents’ racial category (models 2, 4, 5, 7, 9 and 10). By controlling for the other parent’s racial

category, I am able to investigate the extent to which education affects whitening (and darkening)

through its effects on inter-marriage, and the extent to which the effect of education on whitening

(and darkening) occurs because it changes inheritance rules.

        Because I am interested in the changes in racial classification from one generation to the

next, I do separate regressions for non-white (black or brown) and white parents. For white

parents, I predict the log odds that the child is classified as black or brown. For non-white parents,

I predict the log odds that the child is classified as white.

        I consider mothers and fathers separately because there are two reasons to believe that

effects of education on whitening (and darkening) differ for men and women. First, education may

be a poor proxy for women’s social class, since traditionally many women have maintained their

social status through marriage rather than through the job market, and have tended to marry men

that were more educated than themselves (this is changing for younger age groups though).

Therefore, differences in whitening between educational levels should be lower for women (thus

we would expect a smaller coefficient for women). Second, since women are the more likely

respondents to the survey (and thus are the ones classifying the children), women’s characteristics

are more likely to matter in determining results. This means that there are also reasons to expect

coefficients to be smaller (and variances to be larger) for men because their responses are being
measured less. In sum, one can expect results for both men and women to be biased for different

reasons, which means that doing separate regressions by gender makes this paper’s conclusions

more robust. Besides, as we will see, changes in racial politics have impacted women and men


D ependent V ariable: Child’s Racial Category

        The dependent variable is the child’s racial category. As noted above, racial categories

used in the regression are branco (white), preto (black), and pardo (brown). These categories are

used in the Brazilian census and in surveys, but do not neatly map onto people’s understandings

of race. Research with open questionnaires (Silva 1996; Telles 2004; Bailey and Telles 2006),

combining quantitative and qualitative measures (Sansone 2003) or comparing interviewer and

interviewee classification (Silva 1994; Telles 2004) suggest a high - though not absolute - degree

of consistency. 14 More importantly, research on racial disparities using census categories,

showing disparities in income, education and other outcomes between brancos, pretos, and

pardos (e.g., Hasenbalg and Silva 1988; Pastore and Silva 2000; Henriques 2001; Telles 2004)

suggests that those categories reflect prevailing social relationships. Therefore, even though all

claims made here about “whitening” refer to changes in classification according to census

categories, it is not unrealistic to assume that on average such change reflects an underlying

change of “racial status” in a family’s social life.

        The regression analyses collapse the brown and black categories together into a

“non-white” category, for both practical and theoretical reasons. Practically, it is simpler to interpret

binary logistic regressions than multinomial regressions. Also, the black category is very small,

especially at the college level. This means that one often runs out of degrees of freedom and that

standard errors get very large.

        The theoretical reason is that the white-nonwhite boundary is seen as more “real” and

“stable” in social science research and for policymakers. Blacks and browns have similar

socio-economic outcomes, which are both distant from whites (Hasenbalg and Silva 1988; Pastore

and Silva 2000; Henriques 2001; Telles 2004). People have historically changed their classification

between black and brown more often than between white and brown (Carvalho et al. 2004). Based

on these results, there has been a recent tendency in the literature to collapse the black and brown

categories (e.g., Lovell 1994, 2000; Henriques 2001; Bailey 2002). Following this trend, recent

affirmative action policies in Brazil are using the white-nonwhite boundary as a criterion for

selecting who qualifies for those policies. Therefore examining the relationship between social

stratification and the crossing of the white-nonwhite boundary challenges more radically the

prevailing social scientific and policy-oriented understandings of race relations in Brazil than

examining the crossing of the black-brown boundary.

Independent V ariable: P arents ’ education

       In order to investigate if “money whitens,” I use the parent’s education as an independent

variable. I thus use education of the parent as a proxy for social class or socio-economic status.

The large inequalities in the distribution of education and the high returns from education in

Brazil make education an important predictor for earnings inequality in that country (Lam 1992).

Also, according to Pastore and Silva (2000) education is the most important determinant of

Brazilians’ position in the socio-economic hierarchy, and is crucial in the process of

intergenerational transmission of occupational status. Education is also used because it is usually

prior to marriage and childbearing, unlike other possible proxies such as income and occupation.

This allows us to use social class as an independent variable. 15

       I use four educational categories in the analysis: “less than primary school” for people with

less than 8 years of education; “primary school” for people with 8 to 10 years of education; “high

school” for people with 11 to 14 years of education; and “college” for people with 15 or more

years of education. The labels reflect the educational level the person has completed.
M ediating V ariable: S pous es ’ racial categories

         I use the racial category of the parent’s spouse as a mediating variable between the parent’s

education and the child’s racial category. A parents’ educational level can affect his or her child’s

classification in two ways: by affecting who this parent is married to and by affecting the

“inheritance rules.” If parents’ education is still correlated with the child’s classification once the

spouse’s race is taken into account, it means that education also whitens by affecting the

“inheritance rules.”

Control variables


         The regions used are North, Northeast, South, Southeast, and Center-West. I control for

region because region is correlated both with race and with education (see Telles 2004). The South

and Southeast are more developed regions, and also have received the largest quantities of

European immigrants during the early 20th century, which partly explains why they have the larger

proportions of whites in their populations. The other regions are poorer and also have more blacks

and browns. It has also been suggested that different regions may have different “racial systems” in

place, the Northeast being a more fluid system with many intermediary categories, the South and

Southeast more rigid and based on fewer categories (see Guimarães 1999). Thus whitening could

be more common in some regions than in others. For these reasons, correlation between whitening

and education could simply be a compositional effect of regions: regions that have more whites and

where whitening occurs more often also have more educated people.

         It is also possible that the relationship between parents’ education and racial classification

of children varies by region. Lovell (2000) has found that the relationship between race and

socio-economic status varies by region. In order to account for this, I also did interactions between

region and education. In order to save space I do not include those results in the tables shown in

this paper, but describe the results briefly in the data analysis section.

Age Cohorts

        Since it is possible that conceptions of race may be changing between cohorts, and since

more educated parents tend to have children later (thus the more educated people in our sample will

also tend to be older), I control for the age of the parents as well. Cohorts were divided into five

groups, according to the decade when they were born: before 1950; 1950-59; 1960-69; 1970-79;

and 1980 or after. I use mother’s cohort for regressions that use the mother as the unit of analysis

and father’s cohort for those that use the father as the unit of analysis.16

        Historical evidence would suggest that successive cohorts would have been progressively

less exposed to official ideologies that value whiteness, and progressively more exposed to one that

valued mixture, and more recently, blackness (Nobles 2000; Telles 2004). 17 This might lead us to

conclude that younger cohorts would progressively whiten their children less, given the increased

symbolic value of race mixture and blackness. On the other hand, a tendency toward valuing race

mixture and blackness over whiteness may lead to opposite results than expected. This is because a

change in norms would affect not only the classification of children, but also how parents

self-classify. If the relative value of whiteness decreases, people who would previously classify

themselves as white now use non-white labels. This means that previously all-white couples now

appear in statistics as inter-racial couples (see Qian and Lichter 2007) and, in the same way, white

parents with white children would now be counted as non-white parents with white children.


        Descriptive statistics confirm previous findings that Brazilians tend to marry within the

same or adjacent racial categories and that they also tend to marry within the same or adjacent

educational categories. The high correlation between racial category and educational level

suggests that the insularity of the Brazilian white elite may be due not only to racial endogamy

but also to class homogamy. Descriptive statistics also provide a general outline of the Brazilian

“inheritance rules”: children of white-brown marriages are classified as white about half of the

time, and when one parent is black and the other is not black, children are usually labeled brown

or white rather than black.

       The regression analyses shows that non-white parents are more likely to “whiten” their

children at higher educational levels, while white parents are more likely to “darken” their

children at lower educational levels. Differences in inter-marriage between parents of different

educational levels explains much but not all of this phenomenon, since parents in inter-racial

marriages are more likely to classify their children as white at higher educational levels.

       Regression analyses also show a gender difference in the relationship between education

and inheritance rules. Among non-white fathers with white spouses, having a college degree

does not increase the probability that his child will be classified as white. However, having a

college degree significantly increases the chances that non-white mothers with white spouses

will classify her children as white. Because this gender difference did not exist in 1996, changes

in racial politics in the turn of this century are probably altering the norms of racial classification

for college-educated men. Nonetheless, a college degree still increases a non-white man’s chance

of marrying a white woman. The likelihood of inter-generational whitening is still therefore

higher for men with more education.


       Table 1 shows a tendency toward racial endogamy. 18 Nonetheless, a substantial

proportion of the population is inter-racially married: about 25% of whites in Brazil marry


Table 2 shows that people tend to marry within their own or adjacent educational levels.

In order to assess the magnitude of educational homogamy, it is necessary to take the educational

distribution of the population into account. 51% of mothers have less than primary school, only

17% have primary school, 25% have secondary school and 6% have a college degree. Fathers’

educational levels are on average only a bit lower than mothers’. 19 People with less than primary

school education tend to marry people with less than a primary school education about 80% of

the time, and are extremely unlikely to marry college graduates. Low rates of inter-marriage

between people with less than primary school and those with high school degrees is high even if

one takes into account the marginals, i.e., the fact that the total proportion of people without

primary school in the population is much higher than the proportion of people at the higher levels

of education.20 People with college degrees marry those that have high school or college degrees

90% of the time. Only 6% of college-educated women and 4% of college-educated men marry

people with less than primary school degrees despite the relative disproportion of these two

educational groups in the population. Marriage between college-degree and primary-school

degree holders is more common, but still much less than we would expect if couples had been

paired randomly. People with secondary education are most likely to marry within their own

educational level, though they often marry college and primary degree holders as well. Their

marriage to those who did not complete primary school, though not uncommon, is very small if

compared to the proportion of this least educated group in the population. People with primary

school degrees tend to have the most diversely educated marriage partners, though they

disproportionately marry those with a primary and secondary education.

                                  [TABLE 1 ABOUT HERE]

                                  [TABLE 2 ABOUT HERE]

Table 3 shows that whites are disproportionately represented among higher educational

groups. This disparity is most visible among college degree holders, of which 75% are white.

Given that college graduates marry disproportionately among themselves, non-whites with

college degrees face a “marriage market” which is predominantly white. As we will see, this is

an important mechanism for inter-generational whitening.

                                   [TABLE 3 ABOUT HERE]

Clas s ification of P arents and Children

       Table 4 shows children’s racial classification by parents’ classification. In most cases

where both parents are classified within the same category, the child’s classification will be the

same as the parents’.

       In inter-racial marriages, children are classified more often according to the mother’s race

than to the father’s. There are, I believe, two plausible explanations for this: 1) mothers are the

typical respondent to the survey 2) mothers are more likely biological, since stepfathers were not

eliminated from the sample. 21

       Results are consistent with an understanding of the brown category as a mixed-race or

intermediary term between black and white: in 50% of the cases, children of black-white

marriages are labeled brown. 22 Marriage between browns and whites and between browns and

blacks also often results in brown children.

       The norms for racial classification regarding the “black” label are equivalent to a “reverse

one-drop rule,” where the majority of children of black and non-black (white or brown) parents

are classified as either brown or white. While children of black-white marriages are labeled as

white 30-40% of the time and children of brown-white marriages are labeled as white 50-60% of

the time, children of black-brown marriages are only labeled black 15-25% of the time, and

children of black-white marriages are labeled black only in 10-20% of cases. 23
Most importantly, children of white-brown marriages are about equally likely to be

classified as brown or white when the father is white and 60% more likely to be classified as

white when the mother is white. This means that, in comparison with black-white marriages in

the United States, it is very common for Brazilians to label children of inter-racial marriages as

white. It follows, as I will show below, that inter-marriage will have significant consequences for

inter-generational whitening.

                                    [TABLE 4 ABOUT HERE]

Effects of P arents ’ Education on Children’s Racial Clas s ification

       Regression analyses show that higher educational levels raise the likelihood that a

non-white parent will classify his or her child as white (Table 5, “whitening”), and also lowers

the likelihood that a white parent will classify his or her child as black or brown (Table 6,

“darkening”). More education increases the probability that a non-white mother will classify her

child as white (Model 1, Table 5), and decreases the probability that a white mother will classify

her child in a non-white category (Model 1, Table 6). The effect of father’s education on the

child’s classification is similar to that of mother’s education (Model 6, Tables 5 and 6).

Darkening effects are significant across all adjacent educational categories. However, non-white

parents with secondary school are no more likely to whiten their children than parents with

primary school. Regional and age composition do not account for the effects of parents’

education on children’s racial classification: the sizes of education coefficients remain practically

unaltered when region and age cohort are included into the model (Model 3 and 8).

                                    [TABLE 5 ABOUT HERE]

                                    [TABLE 6 ABOUT HERE]

       Table 7 gives the reader an idea of the magnitude of the effects described above. The first
column in the table shows the predicted probabilities of an inter-generational crossing of the

white-nonwhite barrier by parent’s educational level, for parents born in the 1970s who live in

the Southeast (calculated from models 3 and 8 in tables 5 and 6). The probability that children of

non-white parents will be labeled white increases steadily with parents’ educational level, from

about 20% if the parent has less than a primary education to about 35% when he or she has a

college degree. White men and women, in contrast, label their children “white” most of the time,

though their chances of labeling their children in non-white categories increases (from about 5%

for both genders to about 15% for men and 17% for women) as their education decreases.

                                      [TABLE 7 ABOUT HERE]

       Adding a control for the spouse’s race to the model (Models 2 and 7) greatly reduces the

education coefficients. This means that inter-marriage is responsible for much of the effect of

education on racial category change across generations. Parents with more education tend to

marry whites more often than their less educated counterparts, which is an important explanation

for the effects of education on intergenerational whitening. Similarly, less educated whites are

less likely to classify their children as white than more educated whites partly because less

educated whites are more likely to inter-marry.

       However, education does not only affect intergenerational whitening and darkening

through its effect on inter-marriage. Once the spouse’s racial category is taken into account,

education still has a large, positive, and significant effect on the likelihood of a child being

labeled white and a significant, negative effect on the likelihood that a child will be labeled

non-white (Models 2 and 7). Again, region and age cohort have little bearing on those results

(Model 4 and 9).

These results could in theory be explained by the higher prevalence of blacks (pretos) in the

lower classes. Thus, whitening would be more common at higher educational levels simply

because more highly educated non-whites would more likely be brown than black, and darkening

would be more common among less educated non-whites because their spouses would tend to be

black instead of brown. In order to account for this possibility, I controlled for whether the parents

were black (models 5 and 10 on Tables 6 and 7), and the results remained practically unaltered. I

also re-made the analysis after excluding all black mothers, fathers and children from the sample,

and the results are very similar to the ones that include blacks. Browns are probably driving the

results, since blacks are a minority in the sample. This means more educated parents would be

more likely to classify their children as white (and less likely to classify them as in a non-white

category) than equally classified less educated parents.

        The second column on Table 7 estimates the magnitude of the effects of education on

inheritance rules (calculated from models 4 and 9 in Tables 5 and 6) by showing the predicted

probability of an inter-generational change in racial classification given that the parent in

question lives in the Southeast, was born in the 1970s, and has married across the

white-nonwhite barrier.

        The effects of education remain quite large, with one major exception: differently from

what happens with college-educated non-white mothers, college educated non-white fathers with

white spouses are no more likely than their less educated counterparts to classify their children as

white. Although one might conclude from this that for fathers a college education does not have

an effect on inheritance rules, comparisons across time suggest that there is a countervailing

“darkening” phenomenon that affects college-educated men disproportionately. This

countervailing effect is most likely the result of the shift in racial politics of the last decade.

Effects of the shift in racial politics

In 1996, a college degree would have increased the likelihood that a non-white father

with a white wife would classify his child as white, as can be seen in Figure 1. The two graphs

show a reduced effect of both high school and college degrees. However, the high school degree

effect has diminished for both genders, while the college degree effect has increased for women

and decreased for men.

                              [INSERT FIGURE 1 ABOUT HERE]

       The expansion of the educational system in the last decade would be a plausible

explanation for the shift in the “money whitens” effect from high school to college among

non-white women with white husbands. The proportion of non-whites with high school degrees

doubled within this period, and this proportion increased by a third for whites. Because having a

high school diploma has become much more common, it is possible that secondary school has

come to reflect class differences to a lesser extent than before, and that college degrees has

become a better indicator of this divide.

       However, the decline in the whitening effects of a high school degree has not coincided

with an increase in the whitening effects of college education for non-white men with white

wives. The most likely explanation is that the dramatic changes in Brazilian racial politics and

policymaking in the last decade have increased the value of blackness (and brownness) for

college-educated men disproportionately, offsetting a tendency of these men to label their

children as white more often than their less educated counterparts.

       The interpretation that a surge in black consciousness (consciência negra) would occur

disproportionately among the most educated is consistent with previous evidence that black

movement ideology have been most successful in shaping the identities of middle-class black

Brazilians (Bailey and Telles 2006).24 These results are also consistent with the focus of recent

race-targeted policies on university admissions. The reason why changes in racial politics has

not affected women presents an interesting puzzle for scholars of race in Brazil, which requires

further research on the interactions between race, class and gender in that country.

       Although new trends in racial politics has influenced the “inheritance rules” that college

educated non-white fathers use for their children, the children of college-educated non-white

men are still more likely to be labeled white than those of their less-educated counterparts. This

is because their spouses are still more likely to be white. Whether this change will also affect

inter-marriage rates is too early to say, since older cohorts have married before the change, and

younger cohorts with college degrees are, for the most part, still single.

Effects of Region

       Regional effects are consistent with the idea that people tend to classify their children so

as to “fit in” with the racial category of the majority. Regions with smaller proportions of whites

(North, Northeast and Center-West) tend to have more darkening and less whitening than regions

with larger proportions of whites (South and Southeast). I also tested for an interaction between

region and education (not shown in the tables). I found no significant whitening effects for the

interaction between education and region. I did find a significant interaction between region and

education in determining the probability that white women would classify their children in

non-white categories: education has a smaller effect in the Northeast and Center-West. However,

this can be explained by the weaker association between education and inter-marriage in those


Cohort Effects

       Younger cohorts whiten their children more and darken them less than older cohorts. At
first sight, this finding would suggest that Brazilians have increased their preference for the

“white” label over time, which would be counter-intuitive given what we know about the recent

history of Brazilian race relations. However, analyses of changes between censuses show that

people have re-classified themselves from white to brown over time more often than from brown

to white (Carvalho et al 2004). This suggests that the apparent increase in whitening is more

likely a selection effect, where families that would have been all-white if they were older appear

in the sample of families with a brown parent, a white spouse and a white child. Because brown

parents who would be classified as white in an older cohort may be more likely to classify their

child as white (because they have lighter skin tone and/or a more fluid identity) than brown

parents who would have been brown regardless of age, the probability of intergenerational

whitening increases on average.

A n A lternative Interpretation: S election by S kin Color

       The main interpretation offered for the findings in this paper is that socio-economic status

triggers an inter-generational change in racial status because 1) the same person will be more likely

to marry into a white family if she has higher socio-economic status and 2) the “rules” that parents

use to assign racial status to children change by socio-economic status. This interpretation is the

only plausible one if one accepts the prevailing view that socio-economic advantage in Brazil is

mainly distributed according to a bi-racial system, with whites on one side and non-whites on the

other (Silva 1985; Hasenbalg and Silva 1988; Skidmore 1993; Telles 2004).

       However, if we drop this assumption and instead consider that socio-economic advantage

varies continuously as physical traits such as skin color become further away from the black

stereotype and closer to the white stereotype, accepting that there is a range of skin tones within

racial categories labeled as brown and white, then another interpretation is possible. If

lighter-skinned browns have a higher socio-economic advantage than darker-skinned browns, than

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