Nonparametric estimation of matching efficiency and elasticity on a private on-the-job search platform: Evidence from Japan, 2014–2024
Suguru Otani
What the paper says
I analyze proprietary data from BizReach (2014–2024) to estimate the matching function for high-skill workers on a private on-the-job search platform using Lange and Papageorgiou (2020) nonparametric approach. Comparing it to Hello Work, I find that matching efficiency on the private platform is both more volatile and higher, reflecting its growing popularity. Matching elasticity with respect to users is around 0.75, while for vacancies, it reaches 1.0, suggesting a more balanced elasticity than Hello Work. The study also uncovers industry-level heterogeneity, highlighting differences in matching dynamics across sectors. • Estimates matching efficiency using nonparametric methods on platform data. • Compares private and public platforms using a unified matching framework. • Finds higher responsiveness and volatility in private, scout-based matching. • Policy section links findings to Japan’s ongoing Hello Work reforms.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.