Principal investigator: Eduarda Miller Figueiredo
Original title: Education Policy and Intergenerational Transfers in Equilibrium
Authors: Brant Abbott, Giovanni Gallipoli, Costas Meghir and Giovanni L. Violante
Location of the Intervention: United States
Sample Size:
Sector: Education
Primary Variable of Interest: Welfare
Type of Intervention: Student Loans
Methodology: GMM
Summary
This article studied the impact of financial aid policies on university performance, well-being, and the aggregate economy. The authors analyzed here constructed a heterogeneous agent life cycle with incomplete insurance and credit markets, showing generational interconnections. The results suggest that financial returns are always positive and increase with capacity. Through the lens of the model applied in this study, the authors suggest that the current configuration of federal loans and grant programs has substantial value in terms of outcomes and well-being.
- Policy Problem
Investment in human capital is a fundamental source of aggregate productivity growth and important for social mobility. However, imperfections in insurance and credit markets can distort investment choices in skills, leading to educational outcomes below the socially ideal. This is why governments promote educational attainment through a variety of interventions, including financial aid for university students.
Cognitive and non-cognitive skills, passed down through generations, determine the non-monetary cost of education for students and their productivity upon entering the job market. Government subsidies and loans, private loans, and job offers during college are used to supplement resources provided by parents as a means of financing the financial cost of university education. While transfers made by parents to their children depend on the political environment, such as the availability of financial aid, they are motivated by altruism and the paternalistic attitude of those who prioritize their children's education.
This article aimed to study the impact of financial aid policies on university performance, well-being, and the aggregate economy. At the heart of the analysis is the role of liquidity constraints and uninsurable income risk, policy-induced exclusion of private funding sources, heterogeneity, and selection.
- Implementation and Evaluation Context
Studies using data from the 1980s and 1990s concluded that family income played a small role in college decisions (Cameron and Heckman, 1998; Cameron and Taber, 2004). However, more recently, Belley and Lochner (2007) found that parental financial resources mattered significantly for college attendance in the 2000s.
The authors define the life cycle of individuals based on four phases:
- minimum age education (
) up to the maximum age (
);
- marital union (age)
);
- work (until age
);
- retirement (from age
to
)
In the first phase, the decision-making unit is the individual; in the last two phases, the decision-making unit is the couple.
In this model, men and women begin making their choices at age 16. Their skills are derived from a distribution that depends on their parents' education and abilities. Furthermore, parents provide financial support to their children, giving them a head start in life.
- Policy/Program Details
Given these inherited endowments of financial resources and skills, young people make their educational choices sequentially: less than high school, secondary school, or college. During college, students can finance their education through loans in private markets, through government grants and loans, and also by working part-time.
Regarding financial markets, the authors emphasize that households with positive savings receive an equilibrium interest rate from banks equal to For other families, banks lend at a rate of...
Where
It is the cost of loan supervision per unit of intermediated consumption. Therefore,
It is an important determinant of the proportion of families with negative net worth, which is 6,8% of the sample.
Individuals face debt limits that vary throughout the life cycle: high school students, young workers, and retired families cannot take out loans. Therefore, high school students cannot borrow money nor work. College lasts two semesters, and while job opportunities in college are flexible, the available work time is reduced due to the time required for study.
All university students have access to non-subsidized loans up to the amount of b, which accrue interest at the rate r During and after college. Students with financial needs have the interest on subsidized loans forgiven during college. Federal grants are awarded by the government through a formula that makes them a function of parental wealth and student abilities – that is, based on need and merit.
- Assessment Method
This article analyzed here constructed a heterogeneous agent model of the life cycle with incomplete insurance and credit markets, of the type popularized by Ríos-Rull (1995) and Hugget (1996), presenting intergenerational links in the tradition of Laitner (1992) and situated in a context of overlapping generations. The study data were extracted from various sources in the United States.[1].
The model is estimated in stages:
- They estimated wage processes for each education and gender group, as well as the intergenerational transmission of skills and the aggregate production function.
- They used the Method of Moments to estimate the remaining parameters.[2] of model.
In equilibrium, individuals maximize their expected lifetime utility by choosing their level of education, federal loans as college students, consumption and savings, job offers, and inter vivos transfers to their children.
- Main results
When estimating wage processes, they observed that the higher the level of education, the more pronounced the wage increases. The capacity gradient for wages increases with education, suggesting a complementarity between the two. There is also a greater increase in capacity returns for women than for men.
The authors' results also show that the mother's education and cognition are important for her child's cognitive abilities. However, the results for the psychic cost of education show that being female increases the cost of secondary education but has no effect on the psychic costs in college. Furthermore, non-cognitive and cognitive skills reduce the costs of education. Therefore, although measurable cognitive and non-cognitive competencies play an important role, a large part of the psychic costs of education remains unexplained, particularly for college.
The authors observed that, based on the data from this research, male children receive larger transfers than female children. While boys receive an average transfer of just over $33, girls receive approximately $29.
The results also suggest that financial returns are always positive and increasing by ability, ranging from 5% in the lowest-ability group to 10% in the highest-ability group. What is surprising, according to the authors, is that total returns are negative for those in the lowest-ability group, once psychic costs are taken into account.
After analyzing all the results, the authors conclude that the current student aid program in the United States, including grants and subsidized loans, has improved well-being. This improvement in well-being means: (i) improvements in aggregate output due to a larger stock of human capital; (ii) a reduction in inequality in initial conditions due to income redistribution. Part of the effectiveness of expanding student aid programs through scholarships lies in the fact that parental capacity and education interact positively in the development of the next generation's skills.
- Lessons in Public Policy
Through the lens of the model applied in this study, the authors suggest that the current configuration of federal loans and grant programs has substantial value in terms of outcomes and well-being. They further argue that expansions of grant programs would improve well-being and that the best way to expand student aid is through ability-based scholarships.
References
Belley, P., and L. Lochner (2007): “The Changing Role of Family Income and Ability in Determining Educational Achievement,” Journal of Human Capital1, 37–89.
Cameron, S.V., and C. Taber (2004): “Estimation of Educational Borrowing Constraints Using Returns to Schooling,” Journal of Political Economy, 112 (1), 132–182.
Cameron, SV, and JJ Heckman (1998): “Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males,” Journal of Political Economy, 106 (2), 262–311.
Huggett, M. (1996): “Wealth Distribution in Life-Cycle Economies,” Journal of Monetary Economics, 38 (3), 469–494.
Laitner, J.P. (1992): “Random Earnings Differences, Lifetime Liquidity Constraints, and Altruistic Intergenerational Transfers,” Journal of Economic Theory58, 135–170.
Ríos-Rull, J.-V. (1995): “Models with Heterogeneous Agents”, in Frontiers of Business Cycle Research, ed. By T. F. Cooley, chap. 4. Princeton University Press, Princeton.
[1] Current Population Survey (CPS), the Panel Study of Income Dynamics (PSID), the National Longitudinal Survey of Youth (NLSY, 79 and 97), the National Center for Education Statistics (NCES), the Survey of Consumer Finances (SCF), and the National Accounts.
[2] Parameters that determine the psychological costs of education, some preference parameters and others listed in Table 6.2 of Abbot et al. (2020).
