This paper investigates the role of parents' investment and child's self-efforts made during adolescence on the intergenerational persistence of economic status. First, empirical evidence suggests that the college-tier a student graduates from significantly affects lifetime income. As seats for prestigious colleges are limited, households compete against each other using parental investment and child's self-efforts. This college admission competition is a channel through which parental income translates into the future income of the child. Second, parental income does not affect hours of self-study as much as it affects hours of tutoring. To assess the role of parents' investment and the child's efforts on intergenerational mobility accounting for the admissions competition, I build and estimate a dynamic tournament model where each household chooses quality of private tutoring, hours of private tutoring, and hours of student self-study. Using a unique longitudinal dataset on secondary school students, I find that heterogeneity in parental income in adolescent periods accounts for 46% of intergenerational persistence of earnings. Parental investment is responsible for a substantial portion of intergenerational persistence of earnings controlling for the child's efforts. Removing child's efforts from the mechanism leads to an increase in intergenerational persistence of earnings by 30%, which suggests the role of self-effort as a mitigator of intergenerational persistence of earnings. Finally, in light of the advent of the extremely low fertility regimes, I assess the impact of the rapidly shrinking cohort size on parental investment. Based on the model projection, low income households spend more on private tutoring expenditure as cohort size decreases, while there is virtually no change in the private tutoring expenditure of high income households.

Using predicted wages from 18 CPS data waves between 1962 and 2019, we use local linear regression estimates of each spouses predicted wage as a function of his/her spouses wage and show how they have changed over time. We look further into issues such as how much of assortative mating on wages can be explained by assortative mating on education and when, in a couples lifetime, wages should be observed. We find strong evidence of assortative mating in both wages and education with assortative mating in education explaining much of the assortative mating in wages. We find that using wages at the time of marriage causes significant measurement problems as they do not reflect the true long-term expected variation in wages. Finally, we find that most of the assortative mating occurs at relatively low values of wages.

We propose easy econometric methods to test for positive assortative mating. Compared to existing methods such as by Siow (2015), our procedure avoids the cost associated with imposing positive assortative mating restrictions, and it allows for more general tests. The test does not require numerical optimization, and the test statistics can be calculated easily. We compare the power of the tests using simulation. The empirical application suggests that the null hypothesis of no assortative mating is rejected for selected years of CPS data that range from 1962 to 2019.

Compulsory public education is a common policy tool to achieve greater participation in education, particularly from marginalized groups. The COVID-19 pandemic brought unprecedented school closures around the globe. Households seek their own mitigation strategy against education loss via private substitutes. We use the COVID-19 response of South Korea as a laboratory for investigating the effects of pandemic-induced school closure on parental investment and educational outcomes. Specifically, we exploit the school-level variations in in-person learning days driven by government and local authorities. Combining administrative data and longitudinal survey, our fixed effects regression identifies that losing 10 additional days implies a 9.5% increase in private education expenditure. In addition, we build and estimate a structural model tournament to quantify the impact of school closure on educational inequalities. A counterfactual experiment suggests that a $450 voucher for private tutoring may compensate for the test score loss caused by a 20-day loss of in-person schooling. Our results shed light on how households make schooling decisions and have implications on the longer-run educational inequality induced by the pandemic. Methodologically, we propose an estimation algorithm that tightly links the natural experiment estimates and the structural model.