IDEAS home Printed from https://ideas.repec.org/a/wsi/apjorx/v39y2022i04ns0217595920400254.html
   My bibliography  Save this article

New Tests for Richness and Poorness: A Stochastic Dominance Analysis of Income Distributions in Hong Kong

Author

Listed:
  • Nikolai Sheung-Chi Chow

    (Research School of Economics, Australian National University, Kingsley Pl, Acton ACT 2601, Australia)

  • Maria Rebecca Valenzuela

    (Centre for Efficiency & Productivity Analysis, School of Economics, University of Queensland, St Lucia QLD 4072, Australia)

  • Wing-Keung Wong

    (Department of Finance, Fintech & Blockchain Research Center, and Big Data Research Center, Asia University, Taiwan, ROC4Department of Medical Research, China Medical University Hospital, Taiwan, ROC5Department of Economics and Finance, The Hang Seng University of Hong Kong, Hong Kong)

Abstract

This paper applies stochastic dominance techniques for income distribution analysis and develops tests of richness and poorness to achieve more accurate characterizations of relative welfare in populations than was previously possible. Results from our empirical application, using Hong Kong data, are consistent with predictions of the life-cycle theory of income and savings. Among other things, we find high concentrations of poor individuals among the younger cohorts, and at the same time, there are high concentrations of rich individuals amongst the oldest cohorts. Our results help to explain Hong Kong’s persistently high levels of income inequality in the population.

Suggested Citation

  • Nikolai Sheung-Chi Chow & Maria Rebecca Valenzuela & Wing-Keung Wong, 2022. "New Tests for Richness and Poorness: A Stochastic Dominance Analysis of Income Distributions in Hong Kong," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 39(04), pages 1-26, August.
    • Handle: RePEc:wsi:apjorx:v:39:y:2022:i:04:n:s0217595920400254
    DOI: 10.1142/S0217595920400254
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0217595920400254
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0217595920400254?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.

    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:wsi:apjorx:v:39:y:2022:i:04:n:s0217595920400254. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/apjor/apjor.shtml .

    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.