If workers are uncertain about their labor market productivity, this uncertainty could have crucial implications for occupational sorting and wage dynamics. This paper starts by documenting the key features in the US labor market that can be explained by the presence of uncertainty about workers’ own skills and the learning process that unfolds depending on specific experiences. A structural model is built on these empirical patterns and characterizes that workers in their initial occupations decide each year whether to stay or quit in response to the wage outcomes while accumulating and learning about their skills. The dynamic discrete choice model, extending conventional discrete-time duration analysis, is estimated using the Kalman filter and a conditional choice probability estimator. I find supporting evidence that workers experience significant uncertainty about their skills. The results depict that the difference in the dynamics of wage distribution across occupations can be attributed to workers’ sorting as well as human capital accumulation in different occupations. Counterfactual analysis shows that, in occupations with non-trivial probabilities of mismatch due to the choices based not on the true skills but on the beliefs, an information provision policy has a sorting effect. By reducing the share of the mismatched, the policy influences employment duration in the initial occupations, resulting in higher wage growth and lower wage dispersion.

We study educational investment decisions when students are uncertain about their own ability and preferences. We estimate a dynamic discrete choice model in which we allow agents to be uncertain about their own unobserved type. We estimate the degree of uncertainty by exploiting commonly available data on agents' self-reported most likely outcome. We apply this model to the Korean context and find large uncertainty before important high school track and effort decisions are made, particularly among the (overconfident) low-ability students. Providing more information would lead to stronger sorting as it disincentivizes low-ability students to exert effort and choose academically focused tracks, while it incentivizes high-ability students more. We also find effects in the long run, leading them to more different types of college degrees.

Parents in Korea spend heavily on their children’s education, and the spending appears to pay off: children from families that spend more earn higher grades, and children with higher grades also seem to work harder. These patterns have three possible sources. Money and effort may really build skills. Families that spend more may simply be the families whose children would have done well anyway. Or parents may spend more, and children may work harder, because of the grades they see. This paper builds a model that tells these three apart. A parent and a teenager make decisions in turn. The parent decides how much to spend on private tutoring and how closely to engage with the child, whether through encouragement or pressure. The child decides how hard to work at school, a choice the parent can influence but not control. The model is designed to be estimated with six years of data from the Korean Youth Panel Survey. The model and the identification strategy are nearly complete, and estimation is the next step. Once estimated, the model will show what happens to the gap in children’s skills when educational spending is equalized across families but children’s initial heterogeneity is held fixed to study how much of the gap would close.

This paper investigates spillover effects from the U.S. stock market to the Korean stock market by considering a functional regression model. Instead of using stock market indices, we consider cross-sectional distributions of all stock returns that comprise the KOSPI index and the S&P 500 index. We use daily data from January 2005 to December 2013 and consider three subsamples: pre-crisis, crisis and post-crisis period. We estimate a functional regression model and adopt novel econometric tools recently proposed by Hu et al. (2016) to analyze the relationship between cross-sectional distributions of two stock markets. We use response functions to examine how each moment and tail probability of the Korean stock market distribution react to shocks in the US stock market distribution. We also conduct variance decomposition and provide interpretations on spillover effect from the U.S. stock market to the Korean stock market. The spillover effects to mean, variance and left tail probability were higher in the post-crisis period than in the pre-crisis period and were the highest during the crisis period. On the contrary, the spillover effect to right tail probability was the highest in the post-crisis period.