Estimation of Educational Borrowing Constraints Using Returns to ...

educational borrowing constraints 137
A. Literature on Determinants of Educational Attainment
A ubiquitous empirical regularity that emerges from the literature on
determinants of schooling is the strong correlation between family income
and schooling attainment. This correlation has been documented
in legions of U.S. data sets covering the entire twentieth century (see,
e.g., Mare 1980; Manski and Wise 1983; Hauser 1993; Manski 1993;
Kane 1994; Mayer 1997; Cameron and Heckman 1998, 2001; Levy and
Duncan 2000) and in data from dozens of other countries in many
stages of political and economic development (see, e.g., the studies
collected in Shavit and Blossfeld [1993]). 5 Educational financing constraints
have been the popular behavioral interpretation of the schooling–family
income correlation, particularly in studies of college
attendance.
However, credit access is only one of many possible interpretations
of this correlation. Family income and other family background measures
have been found to be correlated with achievement test performance
in elementary and secondary school as well as with schooling
continuation choices at all levels of schooling from eighth grade through
graduate school. Cameron and Heckman (1998, 2001) adopt a “life
cycle” view of the importance of family income and other family factors
and argue that family income is a prime determinant of the string of
early schooling decisions. They conclude that the measured effect of
family income on continuing college is largely a proxy for its influence
on early achievement. 6
Shea’s (2000) findings support this interpretation of the data. He
isolates the component of family income variation that could arguably
be ascribed to “luck,” coming from union status, job loss, and other
factors, to estimate the causal effect of income on schooling. He finds
little or no correlation between this component of income and children’s
schooling outcomes. 7 Keane and Wolpin (2001) take a different
approach. They estimate a rich discrete dynamic programming model
of schooling, work, and savings. Model simulations reveal that relaxing
borrowing constraints has almost no effect on schooling, but these constraints
are important determinants of working during school.
5
Tomes (1981) and Mulligan (1997) are related but look at the elasticity of schooling
to income. They find higher elasticities for families that are more likely to be borrowingconstrained.
6
Carneiro, Heckman, and Manoli (2002) extend this work using similar methods but
get different outcomes. They find evidence that suggests that borrowing constraints may
delay entrance and affect college completion and quality.
7
Shea studies extracts from the Panel Study of Income Dynamics and finds no effects
in the full sample. He does find modest evidence of a relationship in the low-income
subsample, though such a finding is not inconsistent with Cameron and Heckman’s (2001)
view that family income effects operate at the earliest stages of schooling.