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When bigger is not better: Family size, parental resources, and children's educational performance
Downey, Douglas B. American Sociological Review 60.5 (Oct 1995): 746.
Abstract (summary)
A framework for conceptualizing parental resources is provided, and tests of the resource dilution model's implications are specified. Interactions between
sibship size and parental resources support the dilution model as children benefit less from certain parental resources when they have many versus few
siblings.
Even before Simmel (1950) articulated the impact of group size on interaction, family researchers have compared the familial processes and outcomes of small
and large families. One relationship has been consistent: As the number of siblings increases, educational performance decreases. Despite the recent growth in
the number of studies emphasizing the sibship size­education relationship (Alwin 1991; Retherford and Sewell 1991, 1992; Shavit and Pierce 1991), little has
been done to clarify why additional siblings tend to reduce educational success. The resource dilution model posits that parental resources are finite and that
additional children dilute the total quantity of resources any one child receives, which in turn decreases their educational output. Without even having to
defend itself, the resource dilution model has become the most widely accepted explanation for the inverse association between sibship size and educational
performance.
At present, many questions stemming from the resource dilution model remain underexplored. Although highly intuitive, in its current form the model is
poorly conceptualized as key elements have been only vaguely described. The model describes the dilution of "parental resources:' yet these resources are
nebulously defined and rarely measured. I provide a framework for conceptualizing parental resources and specify tests of the model's implications.
NUMBER OF SIBLINGS AND EDUCATIONAL PERFORMANCE
The inverse relationship between the number of siblings (hereafter referred to as sibship size) and educational outcomes is one of the most consistent findings
in the status attainment literature. Across a variety of samples, methods, subgroups, and educational outcomes, individuals perform better when they have
fewer brothers and sisters. These patterns remain, net of the effect of parent's education, household income, race, and age (Blau and Duncan 1967;
Featherman and Hauser 1978). In early status attainment studies, sibship size was generally defined as a control variable and not until fairly recently have
studies emphasized its substantive importance. These subsequent works have confirmed the inverse association of sibship size with years of education attained
and have tested its association with other educational outcomes, such as grades, standardized test scores, the probability of graduating from high school, and
the probability of entering and graduating from college (Alwin 1991; Blake 1981, 1985, 1989; Mercy and Steelman 1982; Powell and Steelman 1993;
Steelman 1985; Steelman and Mercy 1983; Zajonc and Markus 1975).
The most impressive evidence comes from Blake's (1989) study, Family Size and Achievement, in which she analyzed nearly every national data set available
at the time and reproduced the general pattern noted by others: As sibship size increases, performance in school declines. Not only was this relationship
consistent, it was also substantial relative to other predictors, such as race and age. Across data sets, father's education was the only other variable in the
status attainment model that consistently had a stronger effect than sibship size on educational attainment (Blake 1989:52­53).
The overwhelming evidence suggests that the inverse relationship between sibship size and educational performance is substantial, consistent, and highly
generalizable.(1) With research agendas so frequently built around empirical findings having much less consistency, the modest amount of effort put forth to
explain the effect of the number of siblings on educational success is puzzling.
EXPLANATIONS
Explanations for the relationship between sibship size and educational performance remain underdeveloped. While the focus of this paper is the resource
dilution model, other explanations exist.
No Effect
Some maintain that the inverse relationship between the number of siblings and educational performance is artifactual and is actually a function of
socioeconomic status (Ernst and Angst 1983). Children from large families do less well in school than their counterparts from small families, the argument
goes, because large families are disproportionately from lower socioeconomic groups. This explanation has been largely discounted, however. While it is true
that sibship size is negatively associated with social class, sibship size effects remain quite strong, even when socioeconomic status is controlled (Blake 1989).
Of course, not all potentially confounding variables have been tested and rejected, and some have claimed that parents' intelligence is one of these variables.
Contending that intelligence is genetically transmitted, detractors argue that the inverse relationship between sibship size and educational achievement exists
because intellectually superior parents tend to have fewer children than their less intelligent counterparts. This alternative explanation is not entirely
convincing, however, for several reasons. First, the question regarding the heritability of intelligence remains unresolved (Jencks et al. 1972; Plomin and
Defries 1980). Second, sibship size is more strongly linked with verbal ability than with nonverbal ability (Steelman 1985), an association that implies an
environmental explanation. Third. evidence for a negative as sociation between parental IQ and parental fertility is methodologically weak or suggests only a
modest relationship (Higgins, Reed, and Reed 1982). Fourth, and most important, most studies reporting an inverse relationship between sibship size and
educational performance control for parents' intelligence in part by including parents' education in their models, which correlates strongly with parents' IQ
scores (Jensen 1980).

2. The Confluence Model
Among those contending that the inverse relationship between sibship size and educational performance is real are proponents of the confluence model, which
offers an attractive, environmentally­based explanation. The model, first posited by Zajonc and Markus (1975), states that a child's intelligence is a function of
the intellectual milieu in which he or she develops. The intellectual milieu is the unweighted average of the intellectual levels of all members of the child's
family, with other children depressing the family's intellectual environment because they do not possess the same mental knowledge and skills as adult family
members. Therefore, adding siblings to the family, particularly closely spaced siblings, negatively affects a child's intellectual growth by lowering the average
quality of the intellectual milieu in which he or she grows up.
Research on family size has flourished in the last 10 years, largely as a result of the appeal of the confluence model. Nevertheless, most recent work has
mounted convincing evidence challenging this model (Alwin 1991; Retherford and Sewell 1991; Steelman 1985). Zajonc and colleagues have actively disputed
these critiques, primarily on the grounds that these studies have employed inappropriate methods for testing the confluence model (see Retherford and Sewell
1991, 1992; Zajonc, Markus, Berbaum, Bargh, and Moreland 1991). Bogged down by these debates, little progress has been made toward clarifying the
model's merits.
The Resource Dilution Model
Interest in the confluence model has diverted attention from alternative explanations of the effects of sibship size. As a result, the resource dilution model,
while equally appealing, has received insufficient empirical attention.
Resource dilution offers a simple explanation for the effects of sibship size on educational performance. Beginning with the assumption that parental resources
are finite, the model posits that as the number of children in the family increases, the proportion of parental resources accrued by any one child decreases
(Anastasi 1956; Blake 1981 1989).
Blake (1981), the leading proponent of resource dilution, has outlined three types of finite parental resources: (1) "types of homes, necessities of life, cultural
objects (like books, pictures, music and so on)," (2) "personal attention, intervention, and teaching," and (3) "specific chances to engage the outside world or,
as kids say, 'to get to do things' " (p.422). She writes, "The more children, the more these resources are divided (even taking account of economies of scale)
and, hence, the lower the quality of the out; put" (Blake 1981:422).
Evidence for dilution. Some researchers have assumed that the inverse relationship between sibship size and educational outcomes is evidence of the dilution
of parental resources (Blake 1989; Coleman 1988), although these claims are not based on direct tests of this process. Extending our understanding of how
sibship size affects children's educational performance requires that the resources critical to educational success are identified and their dilution is
demonstrated.
Many previous studies reveal that a variety of parental resources are less available as sibship size increases. For example, the availability of educational objects
(such as newspapers, books, and a place to study) decreases as sibship size increases (Blake 1981; Teachman 1987), as does funding by parents for college
expenses (Steelman and Powell 1989, 1991), and the likelihood of taking music and dance lessons or travelling outside the United States (Blake 1989). As
sibship size increases, children also receive less time with their parents (Hill and Stafford 1974), receive less parental encouragement (Blake 1981), are less
likely to recall being read to as a preschooler (Blake 1989), and report less motivation for school work (Marjoribanks and Walberg 1975).
This evidence of decreasing parental resources as sibship size increases, coupled with the well documented inverse relationship between sibship size and
educational outcomes, is consistent with resource dilution claims. However, these two observations do not provide sufficient information to adequately assess
the merits of the dilution model. Specifically, examination of dilution claims can be improved upon in three ways.
First, most prior studies have simply tested a linear term representing the number of siblings, yet a linear term may not accurately reflect the dilution model.
Instead, according to the resource dilution hypothesis, the decline in resources available (y) as sibship size c) increases should approximate a y = 1/x functional
form, where x represents the total number of children in the family. As an example, adding one sibling should have a dramatic effect on the distribution of
parental resources (the existing child's resources are reduced by 50 percent), while the addition of an eighth sibling should have a relatively minor effect on
the resource distribution (existing children's resources are reduced by less than 2 percent). The negative effect of sibship size on resources, therefore, should
diminish as sibship size increases. Alternatively, certain parental resources may instead conform to a "threshold" pattern­­they become extremely difficult to
provide at all once family size reaches a particular threshold or "breaking point." At this threshold, parents can no longer provide expendable resources and
must concentrate their energies on meeting their children's basic needs. Resources involving discretionary time or money may be more likely to follow a
threshold pattern than resources considered to be necessary. To date, these nonlinear relationships (1/x and threshold) remain unexplored.
Second, little has been done to articulate various dimensions of parental resources which should affect their susceptibility to dilution. Those writing about the
dilution model have largely assumed that all parental resources are equally dilutable. This assumption is premature. There are compelling reasons to expect
that certain types of parental resources are more strictly finite, and therefore more sensitive to changes in sibship size than other resources. For example, I
expect parental economic resources to be more "finite" than interpersonal resources. Parents may find that as their family size grows, they can invest more of
their own time and energy, increasing the overall pool of interpersonal resources; but they may find it more difficult to increase household income and other
economic resources. Resources purchased with discretionary funds (e.g., a computer) are especially likely to be affected by increases in sibship size as parents
devote greater attention to meeting their children's basic needs.
Equally important in its implications for the resource dilution model is the way that parental resources are measured. Most parental resources, as measured by
survey questions, indicate the level of resources received by an individual child. For example, in the 1988 National Education Longitudinal Study, frequency
parents talk to child measures the level of investment parents make in a single target child. In contrast, other questions indicate the overall level of resources
available to both the target child and his or her siblings. For example, from the same data set, presence of a computer in the home is an educational resource
presumably available to all children in the household. This subtle distinction between the two levels of measurement (individual and household) has
meaningful implications for testing resource dilution claims. While both individual and household­level resources should become less available as sibship size
increases, resources at the household level should be more sensitive to increases in family size because they are shared resources.
Third, few researchers have focused on the relationship among sibship size, parental resources, and educational performance using a complete model.
Therefore, the role of parental resources as an intervening variable between sibship size and educational outcomes is not well understood. Blake (1981) has
provided one of the few examples in which parental resources were actually measured with the intent of testing resource dilution claims, but her study used
only a small number of parental resources.
The most direct test of the resource dilution model comes from Steelman and Powell (1989), who found that, independent of socioeconomic controls, children
receive less financial support for college from their parents for each additional sibling added to the family. More important, parental contributions mediated the
entire sibship size effect on the probability of continuing in college and graduating. Together, these two studies (Blake 1981; Steelman and Powell 1989)
suggest that parental resources may account for the effect of sibship size on educational performance. Clearly, however, there is a need to test resource
dilution using a wider array of parental resource measures, a broader range of educational outcomes, and a detailed analysis of nonlinear relationships between

3. sibship size and parental resources to more fully explore the implications of the dilution model.
I address several questions relevant to the dilution model: (1) Do parental resources decline as sibship size increases, net of back ground controls? (2) Does
this decline approximate a linear, 1/x, or threshold functional form? (3) Does educational performance decline as sibship size increases? (4) Do parental
resources mediate the relationship between sibship size and school performance? And, (5) do children in large families benefit less from parental resources
than do children in small families?
METHODS Sample
I use data from the National Education Longitudinal Study of 1988 (NELS:88), a large, nationally representative data set collected by the National Center for
Education Statistics. NELS:88 was designed to examine student educational achievement, along with familial, school, and others factors that may promote or
inhibit educational success. The data employ a two­stage sampling procedure: First, schools were randomly selected, and then students within the schools
were sampled. The sample of 24,599 boys and girls is representative of the eighth­grade population in the United States in spring 1988.
I chose this data set for several reasons. First, NELS:88 includes a wealth of information on children's academic performance and on parental investments in
children. Second, the data rely on multiple sources­­student­based information is supplemented by reports from one parent as well as by school records. Third,
this eighth­grade sample improves upon previous studies of high school students (e.g., High School and Beyond) because sibship size effects may be
abbreviated by the high school years as children from larger sibships have already disproportionately dropped out of school (Blake 1989).
Finally, the large sample size allows the use of powerful multivariate analysis and tests of interactions.
Measures
Sibship size. Although apparently straightforward, there are actually a number of ways to measure sibship size. In this study, I define sibship size as the
respondent's total number of brothers and sisters, including half­, step­, and adoptive siblings.(2) Two other definitions were also tested but were not used in
this study: the number of siblings "presently in the home." and the total number of people (both adult and child) "dependent upon" the parent. The sibship
measure used here (number of brothers and sisters) has a stronger relationship with both parental resources and educational outcomes than either alternative
measure with one exception: Number of siblings "presently in the home" has a stronger negative impact on the availability of interpersonal parental resources.
(3) Both a linear term for number of siblings and an alternative measure, a series of binary variables (0 siblings through 5 siblings, with 6 or more siblings
omitted), are used in the analysis.(4)
Parental resource variables, I analyze nine parental resources, capturing a broad range of parental investments in their children. Four of these are
interpersonal resources. The frequency with which parents talk to their eighth grader about school related matters (frequency of talk) indicates the day­to­day
involvement that parents have in their child's school success. Parent's educational expectations for their eighth grader also may be a strong predictor of the
child's educational success (Sewell, Hauser, and Wolf 1980). Whether the parent knows the eighth grader's friends and whether they know these friends'
parents are indicators of how involved the parent is in the child's everyday social network. Because the dilution model contends that parents' time and energy
are limited, I expect these interpersonal resources to become increasingly scarce as family size increases.
I include five gauges of economic resources. Among them are whether or not the family has a computer in the home and the number of educational objects in
the home. Educational objects include: a specific place for study, a daily newspaper, a regularly received magazine, an encyclopedia, an atlas, a dictionary,
more than 50 books, and a pocket calculator. Money saved for the child's educational future indicates the parents' financial commitment to their child's
educational success. Also, providing opportunities to participate in cultural events, which develops what Bourdieu (1977) calls "cultural capital," may reflect a
commitment to the child's education above and beyond the classroom. I, therefore, include two measures of activities which may promote cultural capital:
cultural classes (the number of dance, art, or music classes the student has taken outside of school) and cultural activities (the frequency the student attends
art, science, or history museums). As sibship size increases I expect parents to be less willing to incur the costs involved in providing these cultural
opportunities, instead diverting their energy toward meeting their children's basic needs.(5)
Table 1 charts these parental resources by resource type (interpersonal versus economic), measurement level (individual versus household), and
"shareability." While economic resources are, in general, expected to be more sensitive to sibship size than interpersonal resources, money saved for college,
along with cultural classes and cultural activities are measured at the individual level in the NELS:88 data set and so are balanced somewhat by having low
"shareability." In contrast, computer and educational objects are shareable resources and should, therefore, be the most sensitive to sibship size.
Educational outcome variables. NELS:88 yields a variety of indicators of student's school performance. In addition to student reported grades, I test the
relationship between sibship size and test scores on standardized math and reading tests. Means, standard deviations, and descriptions of parental resource
and educational outcome variables are shown in Table 2.
Background control variables. Because the number of siblings is related to socioeconomic background, it is important to control for this potentially confounding
factor. I use parent's education, parent's occupation,(6) and household income as measures of socioeconomic background. Also, since the number of parents in
the home influences the total availability of parental resources, I construct several dummy variables identifying students as living in a two­parent family,
mother/stepfather, father/stepmother, single­mother, single­father, or other type of family.(7) I include race, urban/suburban/rural, sex of child, and region in
the U.S. as additional controls.(8)
Analytic Approach
I test the resource dilution model by estimating the associations presented in Figure 1. First, I examine whether the availability of parental resources is
influenced by sibship size, studying closely the functional form between sibship size and each parental resource variable. Second, I test whether the inverse
relationship between the number of siblings and educational performance is reproduced. Third, I include parental resources as a block of intervening variables
and assess its ability to explain the inverse relationship between the number of siblings and educational outcomes. Finally, to supplement these analyses, I
regress educational outcomes on the interaction between the number of siblings and each parental resource variable separately. For shareable resources
(measured at the household level), the resource dilution model predicts that these interactions are negative and statistically significant, which would indicate
that children benefit less from parental resources as sibship size increases.
My analysis is limited by a recurrent problem in survey research. Without the ability to control all potentially competing factors, the possibility of a spurious
relationship occurring between the number of siblings and parental resources or educational outcomes cannot be entirely dismissed. For example, some
couples may choose to have few children because they place a high value on educational success. Or, couples who carefully plan a small family may also be
planning for their children's educational future. It is likely that controlling for parent's education, occupational status, race, and income does not account for
every possible difference between the parents of large and small families. These unmeasured dissimilarities may influence the results presented here­­a point I
return to later in the paper.
RESULTS

4. Sibship Size and Parental Resources Figure 2 presents the relationship between sibship size and the nine parental resource variables. Each graph represents
the results of regressing a parental resource on sibship dummy variables and the control variables. These dummy variables are plotted along the x­axis and
their unstandardized regression coefficients are plotted along the y­axis.(9) In each analysis the coefficient for six or more siblings is 0 as it is the omitted
category. The other coefficients, therefore, are interpreted with respect to the omitted category. This approach offers a clear picture of the empirical
relationship between each sibship size category and each parental resource variable, net of control variables.
Several observations are noteworthy. Consistent with previous studies, children with few siblings have more parental resources available than children with
many siblings, independent of background controls. This pattern holds for each parental resource, although the functional form of this relationship varies.(10)
A clear linear relationship occurs between sibship size and frequency of talk, parent's educational expectations, friends known by name, and friends' parents
known by name. For these resources, the addition of a sixth sibling has roughly the same negative effect on resource availability as the addition of a second
sibling.
The two resources measured at the household level, educational objects and computer in the home, yield a threshold relationship with sibship size. Indeed, a
dichotomous term representing 0 to 2 siblings and 3 or more siblings fits the data better than the linear sibship size term for both of these parental resources
(educational objects, F = 387.87 vs. 385.87, p < .05; computer in the home, F = 199.51 vs. 197.11, p<.05).
Although the nonlinear model (1/x) provides no improvement in predictive value over the linear model for most parental resources, it does produce a better fit
for three: money saved for college (F = 355.46 vs. 350.89; d.f. = 19 and 19,499, p < .05), cultural classes (F = 251.19 vs. 247.51; d.f. = 19 and 19,861, p
< .05), and cultural activities (F = 160.17 vs. 157.17; d.f. = 19 and 19,811, p < .05). These three economic resources yield a 1/x functional relationship with
sibship size in which resources decrease rapidly on the addition of only one or two siblings, but level off as family size grows large.
Combined with the threshold relationship produced by the two economic resources measured at the household level, it appears that economic resources, in
general, decline at a faster rate than interpersonal resources.
Parental Resource Variables Intervening between Sibship Size and Educational Performance
While the availability of parental resources clearly decreases as sibship size increases, do these resources mediate the relationship between sibship size and
educational performance? Table 3 presents the results of OLS regressions in which educational outcomes are regressed on sibship size alone (Model 1), with
background characteristics added (Model 2), and with parental resources also added (Model 3).
The inverse relationship between­sibship size and educational performance is reproduced­­all of the coefficients for Model 1 are negative and statistically
significant.(11) A sizable portion of the relationship between sibship size and educational performance disappears once background controls are introduced (in
Model 2). Notably, however, a direct effect of sibship size persists for all three educational outcomes, suggesting that the negative relationship between sibship
size and educational outcomes is not solely a function of sibship size's association with socioeconomic status.(12)
Moreover, parental resources prove to be an effective block of intervening variables, as the sibship size coefficient is greatly reduced when they are added.
Indeed, for grades and math test scores, adding the parental resource variables reduces the sibship size effect to nonsignificance. For verbal test scores, the
inclusion of parental resources reduces the sibship size coefficient by approximately one­half (from ­.057 to ­.026).(13) Interestingly, parental resources
explain a greater portion of the sibship size effect on math scores rather than verbal scores, although the bivariate relationship between sibship size and verbal
scores is larger in Model 1.
Which parental resources are key to explaining the effect of sibship size on educational performance? Rough comparisons can be made by contrasting the
changes in the sibship size coefficient predicting grades in school as each parental resource is added to the model separately (Table 4). The parental resources
producing the largest reduction of the effect of sibship size on educational performance are (in order): frequency of talk, parent's educational expectations,
money saved for college, and educational objects in the home. Indeed, including just these four indicators for parental resources is enough to reduce the effect
of sibship size on grades to nonsignificance.
Interaction Effects: Sibship Size x Parental Resource Variables
Additional tests of the resource dilution model are presented in models predicting educational outcomes with interactions for sibship size x parental resource
variables for the nine parental resources. Table 5 presents the results of these tests predicting student grades in school. Of primary interest are the coefficients
in the last column, which represent the effect of the interactions between sibship size and each parental resource. For example, the statistically significant
coefficient for the interaction between frequency of talk and sibship size suggests that as sibship size increases, parental discussions with their children about
school­related matters are of decreasing value for the children's school grades. Overall, eight of the interaction terms are negative and about half (5 of 9) are
statistically significant, operating as the resource dilution model predicts. These are frequency of talk, parent's educational expectations, knowing the eighth
grader's friends, knowing friends' parents, and educational objects in the home.(14) These five parental resources are not only less available as sibship size
increases (see Figure 2), but once provided, their value decreases as sibship size increases. In other words, even when children in large families have the same
level of these parental resources available, they accrue less benefit from them than their counterparts in smaller families.
DISCUSSION
Researchers in status attainment and education have long noted the inverse relationship between number of siblings and educational outcomes. Although
numerous recent studies test predictions of the confluence model, little progress has been made toward clarifying why additional siblings are related to
decreases in academic achievement. I have demonstrated that resource dilution, a more encompassing (and testable) explanation, is highly consistent with
data from a nationally representative sample of eighth­grade students. Even when parents are similar on a variety of characteristics (e.g., education, income,
race), they still provide fewer resources per child in large families than in small families.
In my analysis, a linear relationship occurred between sibship size and interpersonal resources measured at the individual level. Economic resources measured
at the individual level (cultural classes, cultural activities, money saved for college) followed a nonlinear (1/x) pattern while economic resources measured at
the household level (computer and educational objects) modeled a threshold pattern. Apparently economic resources, whether measured at the individual or
household level, decrease more rapidly than do interpersonal resources as sibship size increases. Interpersonal resources are also sensitive to sibship size
increases, but their decline is less dramatic, perhaps because parents' energy is more readily increased than are parents' economic resources.
Furthermore, a combination of interpersonal and economic resources successfully mediates the effect of sibship size on educational performance, explaining it
entirely in the cases of grades and scores on standardized math tests. Thus, either parental resources, or something highly correlated with parental resources,
is largely responsible for the lower educational performance of children in large versus small families.
Finally, about half of the resources tested here are not just less available as sibship size increases, but they also benefit children less. This finding is consistent
with resource dilution claims for parental resources measured at the household level. The total quantity of parental resources (such as books or a computer)

5. should benefit each child less as sibship size increases. While children are probably not competing for the use of books or a computer, the value of these
resources may decline as sibship size increases because the resource is less likely to be combined with an interpersonal investment of time from parents.
Interestingly, however, the pattern also extended to many resources measured at the individual level. Interpreting this result is more complex. For example,
while children in large families are less likely to have a parent who expects them to graduate from college, even when they do, they accrue less benefit from
parental expectations than children from smaller families. Some resources may, in effect, be diluted twice­­first, by simply being less available as sibship size
increases, and second, by being of less benefit to children in large families even if they are provided.
Although the resource dilution model offers an appealing explanation for these patterns, several questions remain. First, how does one account for the
observation that very few parental resources produced 1/x functional relationships with sibship size? This may have occurred because most parental resources
in this study were measured at the household level rather than at the individual level. Since few of these indicators captured the "whole pie" of resources
parents provide to all of their children, it is not surprising that they did not match the model's predictions exactly. However, even the two resources that were
measured at the household level more closely resembled a threshold rather than 1/x relationship with sibship size. The "threshold" patterns suggest a process
somewhat different than resource dilution. Instead of "diluting" resources as siblings are added one by one, sibship size may not affect some resources until a
certain family size is reached, at which time the parents begin transferring their resources from nonessential to essential areas. The data studied here suggest
that parents may begin shifting resources away from providing a computer or other educational objects once they have four children.
Several cautions are worth noting. First, the causal relationship assumed in Figure 1 between parental resources and educational outcomes may not be
unidirectional as is indicated, but rather reciprocal: Parents' investments may be a function of student progress, as human capitalists would contend (Becker
1964). This alternative account for parental behavior assumes a level of rationality, however, that is not entirely consistent with the data presented here or
elsewhere (Steelman and Powell 1991). For example, human capital theory assumes that parents invest more in favored children, that is, males and those
demonstrating academic potential (Becker 1964), yet these patterns are not unequivocally supported in NELS:88. The generally weak correlations among
gender, parental resources, and standardized test scores discourage an explanation based primarily on rational investment. It would be premature, however, to
dismiss the human capital argument entirely until longitudinal analyses starting in early childhood fully tested these possibilities.
Second, this study focuses on the resources important to the school performance of eighth­grade students. At other ages, different resources would be
important. For example, saving for college may become a more significant parental resource for seniors in high school, while parental attention may be more
important while children are young. Discerning what parental resources are crucial to the educational success of children at different ages and their
susceptibility to being "diluted" would improve our understanding of how adding siblings to families affects educational performance.
Finally, as we cannot perform a controlled experiment (randomly distributing individuals among large and small families at birth), it is impossible to completely
dismiss alternative explanations for the patterns reported here. Parents with few children may differ from those having many children in ways not captured by
the control variables in this study. More detailed measures of parental characteristics would allow for further explorations of this possibility.
Future work in this area may benefit from expanding the resource dilution model beyond the parameters of the traditional nuclear family. While this study
demonstrates the importance of parental resources, we may understand the relationship between family structure and educational performance better if we
also conceptualize community resources. Shavit and Pierce (1991) noted that, while the number of siblings has negative impact on educational attainment for
Ashkenazi Jews, and Oriental Jews, it has no effect for Moslem Arabs. They explain that the Moslem's extended family (the hamula), plays an active role in
supporting the nuclear family. While the size of the nuclear family does not affect educational success, the size of the hamula does. Similarly, Coleman (1988)
argued that the lack of resources in the family can be offset by strong community bonds, or what he refers to as "social capital."
Future research should also consider the possibility that negative parental resources, or parental characteristics that have deleterious effects on children's
school performance, may also be diluted as family size increases. If positive parental resources, such as attention and money, are diluted as sibship size
increases, we should also expect negative parental resources, such as nagging or physical abuse, to be less available as family size increases. If this logical
extension of the resource dilution model were true, additional siblings could have, in some cases, a positive effect on educational performance.
If the resource dilution model is accurate, what implications does it have for families? The decline in the average number of children born per woman in the
United States in the last 30 years from 3.6 to 1.9 (U.S Bureau of the Census 1991) has probably benefited today's children because they are more likely to
receive undiluted resources than were their counterparts from 30 years ago. If most parental resources are sensitive to a certain family­size threshold, and the
fourth child is the one that "breaks the camel's back," then Americans have already reduced their family sizes to levels that have few deleterious effects on
their children. However, if future analyses confirm a 1/x relationship between sibship size and parental resources, families with only two children would still be
greatly affected. Having a single child, a policy the Chinese once formalized, would be the only way to avoid the dilution process.
Douglas B. Downey is Assistant Professor of Sociology at The Ohio State University. His research focuses on he relationship between family structure and
children's well­being. He is currently collaborating with Jim Ainsworth and Mikaela Dufur on a study comparing youths' experiences in single­mother and single­
father households.
* Direct correspondence to Douglas B. Downey, Department of Sociology , 300 Bricker Hall, 190 N. Oval Mall, Columbus, Ohio 43210
(Internet:DOWNEY.32(at)OSU.EDU), Preparation of this paper was supported by a Spencer Dissertation Fellowship and a University Research Grant from The
Wichita State University. I appreciate the comments and suggestions of Brian Powell and Maureen Tobin.
1 There are of course. nuances to this general pattern that children perform less well in school as number of siblings increases. First, the relationship is more
dramatic for some educational outcomes than for others. Sibship size has a more negative effect on years of education attained than on other measures of
educational performance (Blake 1989), and it has a stronger effect on verbal than on quantitative ability (Steelman 1985), perhaps because of the greater
vulnerability of verbal skills to environmental influences. Second, in some cases sibship size effects have not been reproduced for certain subgroups, such as
those with high socioeconomic backgrounds (Marjoribanks and Walberg 1975), Mormons (Gailbraith 1982), and American Samoan children (Rankin, Gaite, and
Heiry 1979), although these studies have been questioned by Blake (1989).
2 The NELS:88 data set includes information sibship size from both parent and student questionnaires. These two reports match each other about 80 percent
of the time (Kaufman and Raskinksi 1991). I report analyses based on the stud dents' reports of sibship size, but there are no substantive differences in the
overall patterns if parental reports are used instead.
3 The finding that siblings "presently in the home" has a more negative relationship with interpersonal parental resources than does the number of people
"dependent upon" the parents supports my contention that the relationship between sibship size and parental resources is not spurious.
4 The number of years between siblings, or what has been referred to as sibship density (Powell and Steelman 1993), also affects educational performance;
children from closely spaced sibships are outperformed by children from families spaced at wider intervals. These findings are consistent with dilution claims, as
one would expect greater competition for parental resources as sibship density increases. Unfortunately, NELS:88 does not provide detailed information on
sibling density.

6. 5 Although one could also conceptualize household income as an economic resource, I define income as a background characteristic, including it in models as a
control variable rather than as a substantive variable. In alternative analyses (not presented), I conceptualized household income as a parental resource; this
resulted in a pattern similar to those of other parental resources shown in Figure 2 (see page 754).
6 Cases were assigned to one of five broad categories of occupational status based on parental reports. Categories included: upper professional 1 (e.g.,
physician, lawyer) lower professional (e.g., manager, nurse), nonprofessional (e.g., bank teller, secretary, salesperson), manual worker (e.g., construction
worker, truck driver), and unemployed. The occupational status for a family represents the highest status occupation between the parents.
7 I also performed separate analyses on children living in these various family types. The inverse relationship between sibship size and educational outcomes is
robust within each group.
8 I tested a variety of combinations of these background controls. No significant changes occurred upon the exclusion of any particular variable, with the
exception of parent's education. I
9 Logistic regression results are presented for the variable for computer in the home.
10 There are, of course, individual cases that did not follow this general pattern. In separate analyses I profiled these exceptions, those children who came
from large families (more than 4 siblings) but who received parental resources at a level one standard deviation above the mean. Parental education was the
strongest and most consistent predictor of being a member of this group, suggesting that the benefits provided by highly educated parents may, for a few
children, overcome the negative effect of sibship size on parental resources.
11 In other tests (not presented) the inverse relationship between sibship size and educational performance was reproduced within birth­order groupings.
While first­borns outperform last­born and middle­born children. birth order does not affect the sibship size effect on educational performance. In other words,
if I restrict the analysis to just firstborn children, those individuals with the fewest number of siblings still do the best in school, a pattern replicated for middle­
born and last­born children.
12 Sibship size does not account for a large percentage of variance in school performance. When evaluated relative to other independent variables in the
model, however, sibship size merits attention. For example, when predicting grades, the effect of having one versus six or more siblings is nearly equivalent to
decreasing the level of parental education (for the most educated parent) from a high school graduate to a dropout or decreasing yearly household income by
$18,000. The correlations produced here between sibship size and educational performance, while small, are consistent with past research based on large
surveys, and are sizable relative to other important predictors.
13 These patterns are similar if alternative measures of sibship size (dummy variables or sibship size are estimated.
14 The results when predicting standardized math and reading test scores are similar. Frequency of talk and parent's educational expectations again produce
strong negative interactions. Knowing the eighth grader's friends or knowing the friends' parents do not produce similar negative interactions, although my
measure for cultural activities does.
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7. Indexing (details) Cite
Subject Sociology ;
Siblings;
Parents & parenting;
Children & youth;
Academic achievement
Title When bigger is not better: Family size, parental resources, and children's educational
performance
Author Downey, Douglas B
Publication title American Sociological Review
Volume 60
Issue 5
Pages 746
Publication year 1995
Publication date Oct 1995
Year 1995
Publisher American Sociological Association
Place of publication Albany
Country of publication United States
Publication subject Psychology, Sociology , Population Studies, Social Sciences: Comprehensive Works
ISSN 00031224
CODEN ASREAL
Source type Scholarly Journals
Language of publication English
Document type Feature
Accession number 02588875
ProQuest document ID 218783888
Document URL http://210.48.222.80/proxy.pac/docview/218783888?accountid=44024
Copyright Copyright American Sociological Association Oct 1995
Last updated 2012­07­24
Database 2 databases View list
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Review 58: 367­81.
Rankin, Richard J., A. J. H. Gaite, and Thomas Heiry. 1979. "Cultural Modification of Effects Family Size on Intelligence." Psychological Reports 45:391­97.
Retherford, Robert D. and William H. Sewell. 1991. "Birth Order and Intelligence: Further Tests of the Confluence Model." American Sociological Review
56:141­58.
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Sewell, William H., Robert M. Hauser, and Wendy Wolf. 1980. "Sex, Schooling and Occupational Status." American Journal of Sociology 86:551­83.
Shavit, Yossi and Jennifer L. Pierce. 1991. "Sibship Size and Educational Attainment in Nuclear and Extended Families." American Sociological Review 56:321­
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Steelman, Lala Carr. 1985. "A Tale of Two Variables: A Review of the Intellectual Consequences of Sibship Size and Birth Order." Review of Educational
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Social Psychology Quarterly 46:157­62.
Steelman, Lala Car and Brian Powell. 1989. "Acquiring Capital for College: The Constraints of Family Configuration." American Sociological Review 54:844­55.
­­. 1991. "Sponsoring the Next Generation: Parental Willingness to Pay for Higher Education." American Journal of Sociology 96: 1 50529.
Teachman, Jay D. 1987. "Family Background, Educational Resources, and Educational Attainment." American Sociological Review 52: 548­57.
U.S. Bureau of the Census. 1991. Statistical Abstract of the United States, 1991. Washington, DC: U.S. Government Printing Office.
Zajonc, Robert B. and Gregory B. Markus. 1975. "Birth Order and Intellectual Development." Psychological Review 82: 74­88.
Zajonc, R. B., Gregory B. Markus, Michael L. Berbaum, John A. Bargh, and Richard L. Moreland. 1991. "One Justified Criticism Plus Three Flawed Analyses
Equals Two Unwarranted Conclusions: A Reply to Retherford and Sewell." American Sociological Review 56: 159­65.
Copyright American Sociological Association Oct 1995

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