IDEAS home Printed from https://ideas.repec.org/a/epw/ejbmr0/v7y2022i4id51545.html

Income Loss and COVID-19: Evidence from Tunisia

Author

Listed:
  • Abdelkader Kasraoui

    (University of Manouba, Tunisia)

  • Karima Mekni

    (University of Tunis El manar, Tunisia)

Abstract

The purpose of this study is to analyze and to predict the individuals’ income loss associated with education, job sector, income brackets during the COVID-19 pandemic in the Tunisian context. A direct survey was conducted in 1842 Tunisian active worker and self-employment aged over 20 years (mean=35.61% female) between December 20, 2020, and February 8, 2021 in Grand Tunis region. Multinomial logistic regression had been used to assess the COVID-19 impact on an individual’s income change in the Tunisian context. The education attainment, job sector and income level had been mobilized to explain the income loss. We find that the education attainment, job sector and income predictor variables are statistically significant. In particular (1) the log-odds will decrease of being in ‘Partial Income Loss’ versus ‘No Income Loss’ class if the responder has a university degree. (2) The log-odds of being in ‘Partial Income Loss’ class relative to ‘No Income Loss’ class will increase if the individual is not in the Job state sector (3) The log-odds will decrease of being in ‘No Income’ versus ‘No Income Loss’ class if the responder has a secondary, or a university degree. Our predictions point out that four fifth of the responders losing their income temporarily or permanently during the year 2020. Tunisian government has to assist the vulnerable social classes and reduce the inequality between social classes.

Suggested Citation

  • Abdelkader Kasraoui & Karima Mekni, 2022. "Income Loss and COVID-19: Evidence from Tunisia," European Journal of Business and Management Research, European Open Science, vol. 7(4), pages 163-168, July.
  • Handle: RePEc:epw:ejbmr0:v:7:y:2022:i:4:id:51545
    DOI: 10.24018/ejbmr.2022.7.4.1545
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejbmr/article/view/51545
    File Function: Abstract page
    Download Restriction: no

    File URL: https://eu-opensci.org/index.php/ejbmr/article/download/51545/7505
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.24018/ejbmr.2022.7.4.1545?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:epw:ejbmr0:v:7:y:2022:i:4:id:51545. 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: Support Team (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejbmr .

    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.