IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2412.19024.html
   My bibliography  Save this paper

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

Author

Listed:
  • Hayato Kanayama
  • Suguru Otani

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 that Tokyo's labor market exhibits higher efficiency compared to Osaka and Aichi, while elasticities are similar, indicating less geographical heterogeneity of the spot work compared to Hello Work.

Suggested Citation

  • Hayato Kanayama & Suguru Otani, 2024. "Nonparametric Estimation of Matching Efficiency and Elasticity in a Spot Gig Work Platform: 2019-2023," Papers 2412.19024, arXiv.org.
    • Handle: RePEc:arx:papers:2412.19024
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2412.19024
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2412.19024. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.