IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v38y2011i4p817-832.html
   My bibliography  Save this article

Bivariate transition model for analysing ordinal and nominal categorical responses: an application to the Labour Force Survey data

Author

Listed:
  • Z. Rezaei Ghahroodi
  • M. Ganjali
  • F. Harandi
  • D. Berridge

Abstract

In many panel studies, bivariate ordinal--nominal responses are measured and the aim is to investigate the effects of explanatory variables on these responses. A regression analysis for these types of data must allow for the correlation among responses of the same individual. To analyse such ordinal--nominal responses using a proper weighting approach, an ordinal--nominal bivariate transition model is proposed and maximum likelihood is used to find the parameter estimates. We propose a method in which the likelihood function can be partitioned to make possible the use of existing software. The approach is applied to the Labour Force Survey data in Iran, where the ordinal response, at the first period, is the duration of unemployment for unemployed people and the nominal response, in the second period, is economic activity status of these individuals. The interest is to find the reasons for staying unemployed or moving to another status of economic activity.

Suggested Citation

  • Z. Rezaei Ghahroodi & M. Ganjali & F. Harandi & D. Berridge, 2011. "Bivariate transition model for analysing ordinal and nominal categorical responses: an application to the Labour Force Survey data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 817-832, February.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:4:p:817-832
    DOI: 10.1080/02664761003692324
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664761003692324
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664761003692324?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zahra Rezaei Ghahroodi, 2023. "Statistical matching of sample survey data: application to integrate Iranian time use and labour force surveys," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 1023-1051, September.

    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:taf:japsta:v:38:y:2011:i:4:p:817-832. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.