IDEAS home Printed from https://ideas.repec.org/p/eti/dpaper/10001.html
   My bibliography  Save this paper

A Stochastic Model of Labor Productivity and Employment

Author

Listed:
  • FUJIWARA Yoshi
  • AOYAMA Hideaki

Abstract

We investigate the productivity dispersion, i.e., allocation of workers among different levels of productivity and output, by employing the largest database for small and medium-sized companies, Credit Risk Database (CRD). Focusing on the manufacturing sector and small and medium levels of productivity, where more workers are distributed among higher levels of productivity, we have new empirical findings in a pivotal role of workers' allocation among different levels of output as a key to understand their allocation among varying levels of productivity. We also propose a stochastic process, mathematically a jump Markov process, in which workers are allocated to firms of differing output and productivity, interrupted by transitions to unemployment, where transitions are coupled with growth and contraction of firms' output that relate to fluctuations of demand.

Suggested Citation

  • FUJIWARA Yoshi & AOYAMA Hideaki, 2010. "A Stochastic Model of Labor Productivity and Employment," Discussion papers 10001, Research Institute of Economy, Trade and Industry (RIETI).
  • Handle: RePEc:eti:dpaper:10001
    as

    Download full text from publisher

    File URL: https://www.rieti.go.jp/jp/publications/dp/10e001.pdf
    Download Restriction: no
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:eti:dpaper:10001. 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: TANIMOTO, Toko (email available below). General contact details of provider: https://edirc.repec.org/data/rietijp.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.