IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2022-172.html
   My bibliography  Save this paper

What Matters for Job Finding and Separation in the Long Run? Evidence from Labor Market Dynamics in New Zealand

Author

Listed:
  • Guanyu Zheng
  • Gulnara Nolan
  • Christopher Ball
  • Siddharth Kothari
  • Yosuke Kido

Abstract

We use the novel anonymized Household Labour Force Survey (HLFS) microdata to analyze job finding rates and job separation rates in New Zealand. We find that individual characteristics, including age, gender, ethnicity and education have a significant impact on job finding and separation rates, even after controlling for other factors. We use a decomposition approach to analyze how the effects of individual characteristics on job finding and separation rates contribute to heterogeneity in employment outcomes. Overall, we find that higher separation rates of young workers play a disproportionate role in explaining heterogeneity of employment outcomes across age groups, while differences in finding rates are somewhat more important in explaining differences by education level. Both finding and separation rate differences are important in explaining differences across ethnicities. We also find some heterogeneous response of worker groups to business cycle after controlling for other factors. The results underscore the importance of well-targeted labor market support policies.

Suggested Citation

  • Guanyu Zheng & Gulnara Nolan & Christopher Ball & Siddharth Kothari & Yosuke Kido, 2022. "What Matters for Job Finding and Separation in the Long Run? Evidence from Labor Market Dynamics in New Zealand," IMF Working Papers 2022/172, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2022/172
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=522556
    Download Restriction: no
    ---><---

    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:imf:imfwpa:2022/172. 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: Akshay Modi (email available below). General contact details of provider: https://edirc.repec.org/data/imfffus.html .

    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.