Three Essays on the Korean Labor Market
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».