There should be, as it were, a ‘‘Cinderella Effect,’’ such that foster children would be likely to work more and would be less likely to attend school than biological
children.
3
Yet, as Yoram Ben Porath 1980 has pointed out, not all exchange need be immediately reciprocal. It is possible, in other words, that households may treat
foster children as well as their biological children in the interest of complying with social norms, cementing social ties or providing insurance for themselves in times
of old age or hardship. The return need not be immediate, explicit, or even certain, but might take the form of participation in an entire set of social norms, the sum of
which is beneficial to the household. If so, one need not expect the Cinderella effect to be particularly pronounced, or even to exist at all.
Testing the existence and magnitude of the Cinderella effect among black South African foster children is an important contribution of this paper. However, the full
effect of fostering on children is not well measured by the Cinderella effect, since even foster children who are treated poorly in foster homes might still be better off
relative to their treatment in their own biological families. This would be particularly true if fostering-out of a crisis in the sending family, such as a death of a parent,
through which the family becomes unable to adequately care for the children. Thus, in additional to the Cinderella effect, this paper tests the hypotheses that foster chil-
dren typically move from low-resource families without good access to educational opportunities to families with more resources and better access to education. Regard-
less of the immediate reasons for fostering, parents will presumably do everything possible to place their children in good homes, and this migration effect is presum-
ably positive. The net effect of fostering will emerge out of the relative strengths of this migration effect and the Cinderella effect.
III. A Model of Child Fostering and School Enrollment
Assume a household has utility that depends on six things: its per- capita consumption of market goods C ; its per-capita consumption of home-pro-
duced goods and services Z ; the leisure time of its adult women L ; social ties it has with other households S; and the average level of education of its biological
children E
c
and of any foster children the household might have E
f
. In what fol- lows, the subscript c will represent biological children, and the subscript f will repre-
sent foster children. The leisure time of adult men is assumed to be exogenous to the decisions modeled here. Finally, the household derives utility indirectly from
fostering, for example because fostering-in household enjoy caring for their foster children, or because these children confer benefits on them by helping them negotiate
the modern economy or by solidifying their ties to other households. The reasons social ties contribute to utility are twofold. Households in South Africa and no doubt
elsewhere have been shown to intrinsically value their social connections to other households May 1996. In addition, these ties form a kind of risk-managing social
network upon which the household may call in times of need May 1996; See also Platteau 1991 1994; Udry 1994; Fafchamps 1992.
3. Cinderella was of course a step-child, but the point holds equally well, if not better for foster children.
The number of biological children that the households has N
c
is assumed to be fixed, as are the numbers of adult women W
and adult M . However, the house-
hold may adjust the number of its children by fostering children in or out. The house- hold’s utility function may be written:
1 u ⫽ uC, Z, L, E
c
, E
f
, S; W , M
, N
c
In this formulation, fostering children in or out does not directly contributed to the household’s utility, but doing so creates indirect benefits, such as social ties S, that
do, and may contribute to the probability that the biological children will be enrolled in school. Fostering-in children may also release household adult labor time from
home production, thereby raising household income andor increasing the leisure time of adult women.
The value of the social ties depends on the number of children fostered in or out N
f
, and the education provided to such children E
f
for children fostered in E ˜
f
for children fostered out to another household.
2 S ⫽ θN
f
, E
f
, E ˜
f
The household has some technology for producing home-produced goods and ser- vices using market inputs X
z
, and time of adult women T
zw
, biological children T
zc
, and foster children T
zf
. Note that there is no reason to suppose that biological children and foster children are equally productive per unit of time; moreover, foster
children may require training or supervision differently than biological children. Ac- cordingly, the time of foster children and biological children enters the production
function separately:
3 Z ⫽
ζX
z
, T
zw
, T
zc
, T
zf
W ⫹ M
⫹ N
c
⫹ N
f
with ζ′
i
⬎ 0; ζ″
i
⬍ 0 for i ⫽ 1,2,3,4 Note the adjustment of total household production for household size in Equation
3 to arrive at per-capita consumption of home-produced goods and services. This formulation is clearly a simplification but without loss of generality, given the
extensive evidence both of unequal distribution of resources within the household for example, Rose 1999; Haddad, Hoddinott, and Alderman 1997; Lundberg and
Pollak 1993; Folbre 1984 as well as of economies of scale inherent in certain home-produced services, such as cooking and heating Lanjouw and Ravallion
1995.
For both foster children and biological children, the household determines the allocation of their time between home-production T
zf
, T
zc
and school T
ef
, T
ec
, sub- ject to an overall time constraint:
4 N
f
⫽ T
zf
⫹ T
ef
foster children N
c
⫽ T
zc
⫹ T
ec
biological children where N
f
is the endogenous number of foster children in the household. A simpli- fying assumption in this formulation is that the leisure time of children is exoge-
nously determined and is not systematically different between foster children and biological children.
4
The time endowment of the household’s adult women is divided between their leisure time L their time in home production T
ZW
and their time in market work T
mw
: 5
W ⫽ L ⫹ T
zw
⫹ T
mw
The household produces education for its children according to a production function that includes the child’s time and purchased inputs for education X
c
, X
f
. Households simultaneously determine the time and money allocations to education, and deter-
mine whether it would be optimal to enroll the child in school. The average propen- sity to enroll the foster children and the biological children in school is:
6 E
i
⫽ ξT
ei
, X
i
; A, G
i
N
i
for i ⫽ {c, f }
where A represents household assets and G
i
is matrix one vector per child of child- specific attributes, such as age and ability, and including whether the child is a foster
child. Such characteristics might plausibly be at least partly endogenous, since house- holds have some choice in the children they foster in or out. Included in household
assets are the household’s land endowment, the education levels of its adult mem- bers, the average health status of members, and the household’s access to water, fuel
wood, and health providers.
The model is closed with the household’s budget constraint, which equates the sum of exogenous income R, which includes men’s earnings and the women’s
wage earnings where w is the exogenous market wage to the sum of household consumption expenditures and investments in education and inputs into household
production:
7 R ⫹ w ⋅ T
mw
⫽ C ⋅ W ⫹ M
⫹ N
c
⫹ N
f
⫹ X
z
⫹ X
f
⫹ X
c
The choice variables in the model are the use of children’s time T
ec
, T
zc
, T
ef
, T
zf
, the use of the time of the adult women T
mw
, T
zw
, L, the household’s expenditures C, X
c
, X
f
, X
z
, the children’s educational levels E
c
, E
f
, the level of home-produced goods Z, and the number of foster children N
f
. The exogenous variables include the household’s exogenous income R, the women’s market wage w, household
assets A, and demographic variables W , M
, N
c
. The model may be solved by using the time constraints Equations 4 and 5 to
substitute out the children’s and women’s time from the production of home goods, Equation 3; then substituting this function into the Utility Function 1 replacing the
home-goods variable; substituting the children’s Education Functions 6 similarly into the utility function; rearranging the Budget Constraint 7 and substituting out
the consumption of market goods from the utility function. The utility function can
4. In the fairy tale, Cinderella works while the other children play, and one could reasonably expect the model to endogenize children’s choices for leisure. However, since empirical data are not available on
children’s time allocation, including their play time, the simpler specification is retained. This is without loss of generality, since parents’ preferences for their children’s leisure may be similar to their preferences
for the children’s education, at least for the purposes here.
then be maximized in the usual way, and the first-order conditions on the remaining choice variables may be combined to determine the optimal levels of the choice
variables as a function of exogenous variables. The household’s choice for the optimal number of foster children may be repre-
sented as: 8
N
f
⫽ N
f
W , M
, N
c
, A, R, w Similarly, the household chooses the optimal level of education for its biological
children and its foster children: 9
E
i
⫽ E
i
W , M
, N
c
, A, R, w for i ⫽ {c, f }
IV. Data and Econometric Specification
