Frictions and mismatches in the labor market


Biner B., GÖKSEL T.

Singapore Economic Review, 2019 (SSCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1142/s0217590819500504
  • Dergi Adı: Singapore Economic Review
  • Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus
  • Anahtar Kelimeler: Dynamic search, mismatch, Monte Carlo Simulation, overeducation
  • Ankara Üniversitesi Adresli: Evet

Özet

© 2019 World Scientific Publishing Company.We develop an infinite-horizon dynamic search model to understand education-job mismatches in the labor markets where job seekers face three different types of labor markets based on their minimum educational requirements. Using a new dataset, we find that our model matches the US data well when we introduce heterogeneity through wage distributions. We use counterfactual experiments to show that even when the general unemployment level is kept constant, if the conditions within different job market types change, overeducation levels may increase or decrease dramatically. We find that regardless of the general unemployment level, frictions in the job market is the main reason for overeducation. However when unemployment is high, highly educated job seekers may settle for jobs below their education level at a higher level leading to a high degree of overeducation in the labor market and crowding out job seekers who have lower level of education.