This paper examines the family income–college enrolment relationship and the evidence on credit constraints in post-secondary schooling. We distinguish short run liquidity constraints from the long term factors that promote cognitive and noncognitive ability. Long run factors crystallised in ability are the major determinants of the family income- schooling relationship, although there is some evidence that up to 8 % of the total US population is credit constrained in a short run sense. Evidence that IV estimates of the returns to schooling exceed OLS estimates is sometimes claimed to support the existence of substantial credit constraints. This argument is critically examined. This paper interprets the evidence on the relationship between family income and college attendance. Fig. 1 displays aggregate time series college participation rates for 18–24 year old American males classified by their parental income. Parental income is measured in the child’s late adolescent years. There are substantial differences in college participation rates across family income classes in each year. This pattern is found in many other countries; see the essays in Blossfeld and Shavit (1993). In the late 1970s or early 1980s, college participation rates start to

A number of recent studies have documented important gaps in post-secondary enrollment by family income and cognitive ability or achievement (Manski and Wise 1983, Cameron and Heckman 1998, 2001, Ellwood and Kane 2000, Carneiro and Heckman 2002). This paper uses very similar data from

Abstract: Forward looking, unconstrained households make child labor and schooling decisions considering their permanent income and weighing the relative returns to child time in various potential activities. The timing of anticipated changes in income should have no effect on child labor and schooling in a setting where households can borrow against permanent income. However, this study documents large increases in schooling attendance and declines in total hours worked when black South African families become eligible for fully anticipatable social pension income. As an explanation, the data are most consistent with liquidity constraints for black elder males forcing rural families into less schooling for boys than they would choose absent the constraint, perhaps because of schooling costs.

Using unique Italian panel data, in which individual differences in behavior toward risk are measured from answers to a lottery question, we investigate if (and to what extent) risk aversion can explain differences in schooling attainments. We formulate the schooling decision process as a reduced-form dynamic discrete choice and we analyze how grade transition from one level to the next varies with preference heterogeneity (risk aversion), parental human capital, socioeconomic variables, market skills and persistent unobserved (to the econometrician) heterogeneity. We present evidence that schooling attainments decrease with risk aversion, but despite a statistically significant effect, differences in attitudes toward risk account for a modest portion of the probability of entering higher education. Differences in ability(ies) and in parental human capital are much more important. JEL Classification: J24. We thank David Card and Winfried Koeniger for useful comments.

As the title of this essay suggests, I believe there are both positive and negative effects of inequality. On the positive side, differential rewards provide incentives for individuals to work hard, invest and innovate. On the negative side, differences in rewards that are unrelated to productivity – due to racial discrimination, for example – are corrosive to civil society and cause resources to be misallocated. Even if discrimination did not exist, however, income inequality would be problematic in a democratic society if those who are privileged use their economic muscle to curry favor in the political arena and thereby secure monopoly rents or other advantages. Moreover, for several reasons discussed in the next section, poverty and income inequality create negative externalities. Consequently, it can be in the interest of the wealthy as well as the poor to raise the incomes of the poor, especially by using education and training as a means for redistribution. The term inequality is often used rather loosely, and can be a lightning rod. 2 Some have argued that only extreme poverty is a concern. Others have argued that the gap in income

Abstract not found

We exploit the changes in the distribution of family income to estimate the e¤ect of parental resources on college education. Our strategy exploits the fact that families at the bottom of the income distribution were much poorer in the 1990s than they were in the 1970s, while the opposite is true for families in the top quartile of the distribution. Our estimates suggest large e¤ects of family income on enrollments. For example, we …nd that a 10 percent increase in family income is associated with a 1.4 percent increase in the probability of attending a four-year college. Paper prepared for the European Economic Association Meeting 2000, Bolzano, Italy. We thank seminar participants in the European Economic Association 2000 Conference, the MIT labor lunch, and the University of Chicago Harris School Seminar for helpful comments. Some of the work for this paper was undertaken while Pischke was visiting the Northwestern University/University of Chicago Joint Center for Poverty Research. He thanks the Center for their hospitality and …nancial support. 1 1

Yigal Gelb provided excellent research assistance. This paper was initiated while the authors were employees of the Federal Reserve Bank of New York. The views expressed herein are those of the authors and not

One would expect that family income is an important positive factor in the school attainment of children. However, evidence on this relationship is often tainted by the lack of control for parental ability, since at least a portion of ability is transferred genetically to children. This paper uses a sample of adopted children and offers genetically unbiased estimates. We further aim to correct for biases arising from unobserved parenting qualities, parents ’ emotional and material differentiation between their own ∗ This research is part of the NWO priority program on schooling, labour market performance and economic development, and a TSER program on private returns and public finance. Financial support from IZA is gratefully acknowledged. We also thank Femmie Juffers,

This paper studies the determinants of college attendance in Mexico. I use subjective quantitative expectations of future earnings to analyze both the causes and the implications of the steep income gradient in higher-education enrollment. In particular, I examine whether data on individuals ’ expected returns to college as well as on their perceived earnings risk can improve our understanding of heterogeneity in college attendance choices. I find that while expected returns and perceived risk from human capital investment are important determinants, lower returns or higher risk are not sufficient, alone, to explain the poor’s low attendance rates. I also find that poor individuals require significantly higher expected returns to be induced to attend college, implying that they face significantly higher costs than individuals with wealthy parents. I then test predictions of a simple model of college attendance choice in the presence of credit constraints, using parental income and wealth as a proxy for the household’s (unobserved) interest rate. I find that poor individuals with high expected returns are particularly responsive to changes in direct costs such as tuition, which is consistent with credit constraints playing an important role. To evaluate potential welfare implications of introducing a means-tested student loan program, I apply the Local Instrumental Variables approach of Heckman and Vytlacil (2005) to my model of college attendance choice. I find that a sizeable