IDEAS home Printed from https://ideas.repec.org/a/asi/aeafrj/v10y2020i11p1342-1355id2019.html
   My bibliography  Save this article

An Empirical Assessment of Probability Rates for Financial Technology Adoption among African Economies: A Multiple Logistic Regression Approach

Author

Listed:
  • Tochukwu Timothy Okoli
  • Devi Datt Tewari

Abstract

The extent of financial exclusion in Africa drives the adoption of fintech across the continent, but the disruption it can cause hinders progress. This study therefore assesses both the probability and actual rates of fintech adoption in 32 African economies between 2002 and 2018. Based on the information spill-over and rank theories, multiple logistic regression analysis revealed that the average probability of fintech adoption for all, emerging and frontier African economies to be 50.9%, 83.1%, and 23.1%, respectively, whereas the actual rates are 27%, 40%, and 29%, respectively. The fragile economies, however, had no reasonable probability or actual rates of fintech adoption. Further, odds ratios of 1 or more- suggest a one-unit change in the predicators will exert no impact on these rates. Thus, it is concluded that emerging economies and mobile phone banking drive fintech adoption in Africa, and is largely dependent mainly on structural changes rather than economic and financial factors. The current study consequently recommends improved literacy, ICT training, and structural changes to promote fintech across the continent.

Suggested Citation

  • Tochukwu Timothy Okoli & Devi Datt Tewari, 2020. "An Empirical Assessment of Probability Rates for Financial Technology Adoption among African Economies: A Multiple Logistic Regression Approach," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 10(11), pages 1342-1355.
  • Handle: RePEc:asi:aeafrj:v:10:y:2020:i:11:p:1342-1355:id:2019
    as

    Download full text from publisher

    File URL: https://archive.aessweb.com/index.php/5002/article/view/2019/3223
    Download Restriction: no

    File URL: https://archive.aessweb.com/index.php/5002/article/view/2019/7282
    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:asi:aeafrj:v:10:y:2020:i:11:p:1342-1355:id:2019. 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: Robert Allen (email available below). General contact details of provider: https://archive.aessweb.com/index.php/5002/ .

    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.