Nonparametric Estimation of Matching Efficiency and Elasticity in a Spot Gig Work Platform: 2019-2023

TL;DR

This study analyzes the growth and efficiency of a Japanese spot gig work platform from 2019 to 2023, revealing high elasticity and variability in matching efficiency, with less regional disparity than traditional employment services.

Contribution

It introduces a novel nonparametric method to estimate matching efficiency and elasticity, providing new insights into gig work dynamics using proprietary data.

Findings

Market expanded significantly from 2019 to 2023

Elasticity with respect to users fluctuates from below 0.7 to above 1.5

Higher elasticity and less regional heterogeneity compared to traditional employment platforms

Abstract

This paper provides new evidence on spot gig work platforms for unemployed workers searching for occupations with minimal educational or experience requirements in Japan. Using proprietary data from a private online spot work matching platform, Timee, it examines trends in key variables such as the numbers of unemployed users, vacancies, hires, and labor market tightness. The study compares these trends with part-time worker data from the public employment platform, Hello Work. The private platform shows a significant market expansion from December 2019 to December 2023. Applying a novel nonparametric approach, the paper finds greater variability in efficiency and higher elasticity, with elasticity with respect to the number of users fluctuating from below 0.7 to above 1.5, and elasticity with respect to the number of vacancies often exceeding 1.0, which is higher than Hello Work. Lastly, the study highlights less geographical heterogeneity of the spot work compared to Hello Work.