Does Money Whiten? Intergenerational Changes in Racial Classification in Brazil
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Does Money Whiten? Intergenerational Changes in Racial Classification in Brazil*
Luisa Farah Schwartzman
University of Wisconsin, Madison
Abstract
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 luisa.fs@utoronto.ca
1The 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
2Telles 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
2
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
3at 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.
EFFECTS OF SOCIAL CLASS ON WHITENING: PREVIOUS APPROACHES
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
4socio-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
5“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.
FROM ERROR TO BOUNDARY-CROSSING
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
6(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,
7then 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.
RACE, CLASS AND INTER-MARRIAGE IN BRAZIL
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
8U.S.), with browns serving as a buffer zone between the two (Silva 1987, Petruccelli 2001; Telles
2004).6
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.
THE RECENT SHIFT IN RACIAL POLITICS
9As 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
10introduction 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.
EMPIRICAL QUESTIONS
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
status?
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.
11This 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.
DATA
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
12from 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
13results for 1996 are only shown in Figure 1. All tables refer to the 2005 data.
METHODS
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
14measured 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
differently.
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
15“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.
16M 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
Region
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
17this 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.
FINDINGS
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
18but 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.
Inter-marriage
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
browns.
19Table 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]
20Table 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
21Most 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
22column 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).
23These 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
24In 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
25Brazilians (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
regions.
Cohort Effects
Younger cohorts whiten their children more and darken them less than older cohorts. At
26first 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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