41 The existing evidence on preschools is limited largely to their impact on disadvantaged students. There is no evidence about positive impacts for middle- and upper- income students. 42 Conclusions The starting point for this article is that achievement gaps by race (and income) are large and substantively important. Moreover, except for the gap closing during the 1980s, there has been little systematic movement. Some conclude that schools lack the power to effect signifi- cant changes in achievement gaps. But there is a difference between having the capacity to lessen existing gaps and having an institutional structure and set of policies that ac- complish such an objective. The existing research suggests that there are three places to look for improvements. First, without a doubt, the biggest in- fluence of schools comes through teachers. Improving teach- er effectiveness could dramatically improve the achievement of disadvantaged students. Second, at least for blacks, it appears that racial concentration in schools is a significant factor. Here, the policies that would be effective are quite
11 unclear, given the importance of residential segregation and the force of legal restraints. Third, some sort of preschool education for disadvantaged students could potentially deal with the typical lesser preparation these students have at entry to school, yet, the exact policies and nature of any new preschool programs need to be developed. n 1 Simple Mincer earnings models have shown that school attainment has an independent effect on individual earnings even when achievement is controlled for. However, in an international analysis, Hanushek and Zhang (E. A. Hanushek and L. Zhang, “Quality-Consistent Estimates of Interna- tional Schooling and Skill Gradients,” Journal of Human Capital 3, No. 2 (Summer 2009): 107–143) indicate that the estimated “Mincer return” falls by 40 percent on average after measures of mother’s education, health, and ability are added to the Mincer earnings equation. This impact on the esti- mated schooling gradients is far larger than those reported in D. Card, “The Causal Effect of Education on Earnings,” in Handbook of Labor Econom- ics , Eds. O. Ashenfelter and D. Card (Amsterdam: North-Holland, 1999): 1801–1863, where other inputs to human capital are not considered. 2 See C. B. Mulligan, “Galton Versus the Human Capital Approach to Inheri- tance,” Journal of Political Economy 107, No. 6, part 2 (1999): S184–S224; R. J. Murnane, J. B. Willett, Y. Duhaldeborde, and J. H. Tyler, “How impor- tant are the cognitive skills of teenagers in predicting subsequent earnings?” Journal of Policy Analysis and Management 19, No. 4 (Fall 2000): 547–568; and E. P. Lazear, “Teacher Incentives,” Swedish Economic Policy Review 10, No. 3 (2003): 179–214. 3 It is convenient to convert test scores into measures of the distribution of achievement across the population. E. A. Hanushek and L. Zhang, “Qual- ity-Consistent Estimates of International Schooling and Skill Gradients,” Journal of Human Capital 3, No. 2 (Summer 2009): 107–143, analyze data
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