Assessing policies to equalize opportunity using an equilibrium model of educational and occupational choices

The inter-generational correlation of education in the U.S. is tremendous. For instance, in PSID data from 1990, young males with college-educated parents had a 70% chance of attending college. But those with high school drop-out parents had only a 15% chance. In this paper, we analyze the impact of college attendance bonus schemes designed to increase college attendance rates (and PV of lifetime income) of youth from disadvantaged backgrounds. Of course, policies that increase the supply of skilled labor may reduce the college wage premium (see Heckman et al. Heckman, James, Lochner, Lance and Taber, Christopher, Explaining rising wage inequality: explorations with a dynamic equilibrium model of labor earnings with heterogeneous agents, Review of Economic Dynamics, 1 (1998a), 1–58; Heckman, James, Lochner, Lance and Taber, Christopher, General-equilibrium treatment effects: a study of tuition policy, American Economic Review, 88:2 (1998b), 381–386]). This may have the unintended consequence of wiping out most of the gains to the targeted groups. The strength of such equilibrium effects on wages depends on the substitutability between different types of labor. Thus, it is important to evaluate education subsidies within an equilibrium framework that allows for flexible patterns of substitution across factor inputs. This is exactly what we do here, using an overlapping generations equilibrium model of the U.S. labor market fit to PSID data from 1968 to 1996. The model allows for imperfect substitution among types of labor differentiated by education, gender, age and ten (1-digit level) occupations — a much finer differentiation than has been considered in prior work.We find that very large college attendance bonuses are necessary to equate college attendance rates between youth whose parents had only high school degrees or were high school dropouts and youth whose parents attended at least some college. The size of these bonuses far exceeds any reasonable measure of college costs; suggesting the “costs” the bonuses overcome are primarily psychic or effort costs. For example, youth from disadvantaged backgrounds may be poorly prepared for college. This suggests that bonuses targeted at college age youth are probably a very inefficient way to reduce inequality. Earlier intervention is likely called for.