Research

1.  Investments and the Technology of Skill Formation: The Role of Children’s Time Allocation [Draft]

Abstract: The literature on children’s human capital production emphasizes the role of parental investment, but it leaves the role of children's time allocation understudied. This paper examines how child time allocation across academic and non-academic activities, alongside parental investment, shapes the dynamic formation of cognitive and socio-emotional skills. I extend the dynamic skill production framework of Cunha and Heckman (2008), allowing households to decide optimal child time allocation and parental resource investment together. Estimating the model on unique longitudinal microdata from South Korea, I find distinct roles for parent and child inputs in cognitive and socio-emotional skill formation. While I find that latent parental investment works as a generalized input across both skill domains, the effect of child time input shows a significant trade-off: academic time serves as a primary driver of cognitive development at the cost of socio-emotional growth, while non-academic time exhibits the opposite pattern.

Presented at: Southern Economic Association Annual Conference (2025); Michigan State University Empirical Micro Lunch Seminar (2026); Economic Graduate Students' Conference (2026, upcoming); Southern Economic Association Annual Conference (2026, upcoming) 

1.  Skill Production Technology and Children's Time Allocation: Evidence from U.S. Data  [Draft]

Abstract: While the active role of children in their own skill development is increasingly recognized, empirical analysis remains constrained by the difficulty of measuring child inputs. This paper uses categorical activity records from National Longitudinal Survey of Youth 1979 Child and Adult (NLSYCA) as multiple proxy variables for child time allocation and examines how these inputs contribute to cognitive and socio-emotional skill formation. Applying the dynamic latent factor framework of Lim (2026), I jointly estimate investment policies for children's time and parental investment, cognitive and socio-emotional skill production technologies, and the underlying measurement system. While the estimates reproduce several establisehd aptterns in the skill formation literature, they also reveal distinctive heterogeneity across activity types.

2. Teacher–Student Match Effects: Structured Shrinkage over a Matching Surface (joint work with Soo Jeong Lee) 

Abstract: Standard teacher value-added models impose common effects across students, while unrestricted heterogeneous models can be unstable in sparse teacher–student demographic cells. We develop a structured regularization framework for teacher-specific match heterogeneity. The approach represents teacher effectiveness through a dyadic surface capturing race and gender match effects and their complementarity, while allowing unrestricted student-type effects to deviate from this surface. Penalization shrinks only these deviations, continuously linking the structured and unrestricted estimators, with tuning selected by leave-cohort-out prediction. Monte Carlo simulations show that structured shrinkage improves stability under sparse demographic support while retaining flexibility when heterogeneity departs from the dyadic structure. An application to North Carolina administrative data studies teacher–student matching patterns, teacher-specific match heterogeneity, and out-of-sample prediction.