[UTMD-078] Nonparametric Estimation of Matching Efficiency and Mismatch in Labor Markets via Public Employment Security Offices in Japan, 1972-2024 (by Suguru Otani)

Suguru Otani

I identify significant biases in the traditional Cobb-Douglas function under misspecification of nonadditive, time-varying matching efficiency, and evaluate the finite sample performance of the nonparametric estimation method of Lange and Papageorgiou (2020). Additionally, I extend the mismatch index by Şahin et al. (2014) to a nonparametric framework and develop a computational methodology. Applying the method, I analyze changes in matching efficiency, elasticities, and mismatch in Japan’s labor market using Hello Work data for unemployed workers from January 1972 to April 2024. I find a declining trend in matching efficiency, aligned with decreasing job and worker finding rates. The estimated elasticities range from 0.5 to 0.9 for unemployment and between -0.4 and 0.4 for vacancies. Furthermore, I demonstrate that occupational mismatch is more severe than geographical mismatch, with the Cobb-Douglas mismatch index significantly underestimating the true extent of mismatch.