312 M. Binder Economics of Education Review 18 1999 311–325
schooling outcomes if community effects exist. But if Tiebout behavior dominates, where a child goes to
school should make little difference. Unfortunately, the two theories are difficult to dis-
tinguish empirically, since a finding that communities matter does not rule out the possibility of an unobserved
trait that all families in the community share Jencks Mayer, 1990; Manski, 1993. In this case, The shared
trait matters, and not the community per se
1
. Neverthe- less, as Jencks and Mayer 1990 argue, the community
effects and Tiebout theories predict opposite effects for length of residence. If the community matters, then pre-
sumably it will matter more over time: new-comers will be less affected by it. If self-selection matters, then the
community trait will describe new-comers best, since they are choosing where to live now, as the community
exists today, and long-term residents may have made their choice under different community conditions. In
applying this distinction to a new data set that records the desired schooling of Mexican school children and
their parents, I find evidence for true community effects: the desired schooling of recent migrant adults for their
children is not significantly predicted by their communi- ties, whereas for long-term resident adults, community
residence is a highly significant predictor.
I begin by setting out the theoretical importance of desired schooling and the potential role of community
effects in its determination. I then present the data and explore the empirical content of desired schooling. I find
that desired schooling is largely determined by com- munity fixed effects. These effects cannot be explained
by measurement error or omitted variable bias, and, through the length of residence test, appear to reflect true
community effects. Finally, I investigate the cause of these effects by using neighborhood-level data from the
Mexican Census. Schooling and income levels of the community are significant predictors of desired school-
ing, but school enrollment figures for neighborhood youth are not.
2. Demand for schooling, desired schooling, liquidity constraints and neighborhoods
I follow standard human capital theory in treating schooling as a personal investment in a future income
1
Summers and Wolfe 1977, Dachter 1982, Case and Katz 1991, Crane 1991 and Borjas 1992, 1995 claim to find true
community effects. Evans, Oates and Schwab 1992 endo- genize the location decision and find no community effects.
stream Schultz, 1963; Becker, 1964; Mincer, 1974
2
. The optimal desired schooling decision, S
i
, meets the investment condition that
d
i
d
i
F
1 2
S
1 1 1 d
i
D
N
i
G
5 C
i
1 where the left-hand side is the discounted marginal bene-
fit and C is the marginal cost of an additional year of schooling. The term d is typically the wage differential
earned for the next unit of schooling, but may also include the marginal consumption value. The term d is
the rate of time preference, and N is planned working years. These parameters are subscripted to indicate that
they may vary for each investor i. A simple formulation, where the wage differential reflects a constant return on
human capital and a correspondingly constant marginal benefit schedule, is illustrated in Fig. 1a
3
. Marginal costs rise with years of schooling because both direct
costs especially tuition and opportunity costs foregone wages increase for more advanced students. Fig. 1a
also shows that the optimal schooling level will vary among students depending on the positions of the mar-
ginal benefit and marginal cost curves. These in turn depend on individual values of d, d, N and C: low values
of d and high values of d and N result in a higher mar- ginal benefit and more schooling; low C values not
shown would lower the marginal cost curve and also lead to more schooling.
The ability of students to invest in optimal schooling levels depends on their ability to finance direct and
indirect costs. Liquidity constraints arise because mar- kets are not available to provide unsecured loans on
human capital investments. For this reason, a student’s family background, especially the family’s willingness
and ability to finance schooling, will alter schooling out- comes Becker, 1964. In Fig. 1b, family i can provide
at most L dollars for schooling, and so faces a vertical marginal cost curve at L. Schooling attainment for a
2
Generally, studies of schooling determinants in developing countries use a household production framework that includes
leisure and consumption for all family members, and schooling for children. Schooling is included because parents care about
the “quality” of their children, which is measured by children’s future earnings. But, while parents care about future income,
they are not making an investment decision: schooling is treated like an ordinary consumption good. See, for example,
Rosenzweig and Evenson 1977, King and Lillard 1983, Birdsall and Cochrane 1982, Wolfe and Behrman 1984,
Birdsall 1985 and Handa 1996. Behrman and Wolfe 1987 and Glewwe and Jacoby 1994 are two studies that appeal to
the investment model.
3
The conclusions from this analysis do not depend on the assumption that marginal benefits are constant: the results also
hold for declining marginal benefits.
313 M. Binder Economics of Education Review 18 1999 311–325
Fig. 1. Optimal schooling investments and liquidity con-
straints. a: No liquidity constraints; different investors face dif- ferent marginal benefits schedules depending on individual
schooling differentials, time preferences and working horizons. b: Investment with binding liquidity constraints reduces attained
schooling. Family i exhausts its resources and is constrained to stop school at S
i
. In family j the liquidity constraint does not bind and schooling continues until S.
child in this family falls short of optimal desired school- ing.
The presence of liquidity constraints is likely to coincide with a higher marginal cost curve, so that
desired schooling will be related to realized school attainment. In poor families, parents face both direct and
opportunity costs of schooling. In wealthy families, a child’s opportunity wages are likely to be a tiny fraction
of the family budget so that, in some sense, the family does not face them. Thus even when liquidity constraints
bind, we would expect that desired schooling would be correlated with schooling eventually attained.
The foregoing discussion points to the relevance of desired schooling both as an integral part of schooling
demand and also in terms of contributing to schooling outcomes, even in the presence of liquidity constraints.
What role, if any, might the community have in determining desired schooling? Community conveys the
meaning of something common to all members, some- thing shared. The most basic thing that can be shared is
a geographic area: families living next to each other share the same external environment, including the same
local establishments and institutions, such as schools and churches. Social relations are likely to arise from this
sharing, be they friendships or conflicts. Anthropological studies suggest that extra-family friendships and net-
works of reciprocal exchange abound in Mexican neigh- borhoods Lewis, 1959; Lomnitz, 1977. While com-
munities under this definition may span neighborhoods, I assume here that sources of community effects, both
social and institutional, arise within neighborhoods.
The community effects literature suggests four poss- ible mechanisms by which neighborhoods might have
independent effects on individual outcomes such as desired schooling, apart from and in addition to family
and personal effects. First, there may be different market and institutional resources in different neighborhoods.
For example, a rural community might have more opportunities for child labor; an urban community might
have better schools. The former would raise the marginal cost of schooling; the latter would lower it. Second, com-
munities might form the basis for information about labor market opportunities and schools. There may be
less of this information available in neighborhoods where few have studied beyond primary school Wilson,
1987. This mechanism would raise marginal schooling costs by increasing the costs of collecting information.
Third, communities may provide social networks that are useful in locating jobs Montgomery, 1991. Marginal
benefits might be higher in neighborhoods with good connections. Finally, peer effects, also discussed in the
literature as epidemic theory Crane, 1991 and tipping models Schelling, 1978, suggest that people behave as
the majority of their peers do, regardless of family back- ground. With peer effects, there may be social costs to
pursuing goals that are not the norm, or added benefits from pursuing goals that are. The remarks of the mother
quoted at the beginning of this article are emblematic of a neighborhood peer effect.
3. A survey of Mexican school children and their families
