Competition for limited seats in prestigious colleges generates a "rat-race" equilibrium effect, driving demand for parental investment. Using admissions cutoffs, I document that attending a more prestigious college tier yields a substantial initial income premium—controlling for college entrance exam scores—with this gap widening over the lifecycle. I develop and estimate a dynamic tournament model in which each household chooses tutoring quality, tutoring hours, and student self-study hours. The model explains persistently high educational investment despite modest effects on test scores, as students maintain investment to avoid dropping to lower tiers. Using the estimated model, I find that a substantial portion of tutoring is driven by the competition channel. Counterfactual analysis shows that expanding elite college seats improves household welfare by reducing tutoring expenditure and hours.

This paper supersedes earlier versions circulated as "Dynamic Competition in Parental Investment and Child's Efforts" and "Parental Investment, Child's Efforts, and Intergenerational Mobility."

Recognition KAEA Best Job Market Paper Award (2022); Award for Excellence in Research (Dissertation Award), Stony Brook University (2023).

Presented at Hitotsubashi University, Stone Center at U Chicago, GRIPS, Toulouse Economics of Education Workshop, University of Southampton, SOLE, SEHO, Kansai Labor, Yokohama National University, Korea University, Mannheim Family Economics Workshop, UNSW, ANU, Kyoto University, IAAE, University of Gothenburg, Missouri University of Science & Technology, KDI, KIEP, KLI, SEA, DSE Summer School, AASLE, SBU Game Theory, and WEAI.

We investigate how reduced in-person school days affect educational inequality through parental responses. Exploiting quasi-experimental variation in school-level in-person days and a linked administrative–survey panel, we find that each ten-day loss increases household tutoring expenditure by 4 percent and within-school test-score dispersion by 25 percent. We build and estimate a household choice model in which formal schooling and tutoring jointly generate test scores. Estimates suggest that tutoring substitutes for in-person days and that closures burden low-income households disproportionately. Counterfactual simulations show that a means-tested tutoring-voucher program matches the overall inequality reduction of a universal scheme while cutting costs by 20 percent.

Media coverage The Kyunghyang Shinmun.

Parents may invest differently across children by compensating the disadvantaged child or by reinforcing the child with higher expected returns. We study this question using a conditional cash transfer experiment that uniquely randomized transfers at the student level, generating exogenous variation in transfer exposure across siblings within the same household. The transfers increased short-run attendance among treated students but generated negative spillovers on untreated siblings: untreated siblings of treated students were 3.7 percentage points less likely to graduate from college, a decline of about 30 percent relative to the control mean. We interpret these effects using a dynamic model of household schooling decisions that identifies parental aversion to inequality in children's educational outcomes. The estimated model implies limited aversion to inequality in children's educational outcomes and reproduces held-out treatment effects not used in estimation. A decomposition shows that the negative spillover is primarily driven by substitution in educational investments toward the treated child.

Presented at Seoul National University, Aoyama Gakuin University, Australian National University, University of Technology Sydney, Korea University, Kyoto University, ISER at Osaka University, the Labor Economics Workshop at the University of Tokyo, AASLE 2023, SOLE/AASLE/EALE 2025, the Sejong Applied Micro Workshop, and the Econometric Society World Congress. Coauthors' presentations are not included.

We develop a one-sided Wald test for positive assortative mating (PAM) that tests the null hypothesis of random matching against the alternative of PAM. By framing the problem as testing equality constraints against inequality constraints, our test statistic follows a chi-bar-squared distribution under the null. Monte Carlo simulations demonstrate that the test performs well under weak assortative mating and moderate sample sizes. Empirical applications using CPS data confirm that our method effectively detects PAM on predicted wages.