Three Essays on the Korean Labor Market
Bibliographic record
Abstract
This dissertation concerns various types of economic or policy shocks and their impacts on labor market outcomes and households’ decisions in South Korea. South Korea’s postwar development was shaped by rapid, government-led, and export-driven economic growth. Consequently, South Korea has some of the longest work hours of any OECD nation. Additionally, the government is an active player in the housing market seeking to regularly stabilize the market. Economic and social mobility are also tied to education and families regularly make significant monetary and time investments to get children into prestigious high schools and colleges in a way that exceeds international norms. Considering these factors, this dissertation examines how households and the labor market respond to changes in the legal maximum working hours, housing prices, and high school assignment policy. The first chapter examines the effect of a new maximum work hour restriction introduced in South Korea in 2018 that limited maximum working hours from 68 h/week to 52 h/week. It measures the treatment intensity by the prevalence of workers working longer than 52 h/week prior to the policy change across industry-occupation-education groups. It shows that the policy reduces work hours while increasing monthly earnings and hourly wages for male full-time workers. However, the policy does not significantly affect total work hours, total employment, and total worker pay at the industry-occupation-education group level. The second chapter examines the effect of a positive housing wealth shock on married couples’ decisions on labor supply, fertility, and education spending by exploiting regional housing price variation from 2003 to 2008 in South Korea. It finds generally weaker housing wealth effects than those in literature: no housing wealth effect on labor supply and fertility, and a net positive housing wealth effect on education spending for children. It further finds that strict regulations on Loan-To-Value (LTV) ratio and Debt-To-Income (DTI) ratio during the period of housing appreciation may prevent significant housing wealth effects from arising as many homeowners have little access to home equity loans under the regulations. The third chapter analyzes the effect of a high school leveling policy on students’ high school and college attendance and their later labor market earnings in South Korea. Since 1974, some cities have replaced the traditional high school assignment system, where students took an entrance exam to get accepted to high schools, with a lottery-based enrollment system within a school district. By using a new DiD estimation method for staggered policy adoptions, proposed by Callaway and Sant’Anna (2021), I revisit the policy impact on labor market earnings. I also investigate a potential mechanism through which the policy affected the labor market earnings: the high school tuition effect on students’ high school choices. My estimation results show that the high school leveling policy increased tuition for public high schools and college attendance while there are heterogeneous policy impacts on high school choices, college outcomes, and labor market earnings across different groups of cities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".