IDEAS home Printed from https://ideas.repec.org/p/qed/dpaper/4625.html
   My bibliography  Save this paper

CORRUPTION AND BANKS’ NON-PERFORMING LOANS: Empirical Evidence from Mena Countries

Author

Listed:
  • Amer Mohamad

    (Department of Banking and Finance, Eastern Mediterranean University, Famagusta, Northern Cyprus via Mersin 10, Turkey)

  • Hatice Jenkins

    (Department of Banking and Finance, Eastern Mediterranean University, Famagusta, Northern Cyprus via Mersin 10, Turkey)

Abstract

Corruption has long been a serious problem in most countries in the Middle East and North Africa (MENA). This research aims to investigate the impact of country-wide corruption on banks’ credit risk across 16 countries in this region over the period 2011–2019. Applying the interactive fixed effects estimation technique on a model consisting of both macro and bank-specific variables and utilizing data from 197 banks, the results show a positive significant association between corruption and banks non-performing loans (NPL). Corruption was found to have a positive relation with credit risk even in banks with high risk aversion.

Suggested Citation

  • Amer Mohamad & Hatice Jenkins, 2025. "CORRUPTION AND BANKS’ NON-PERFORMING LOANS: Empirical Evidence from Mena Countries," Development Discussion Papers 2020-25, JDI Executive Programs.
    • Handle: RePEc:qed:dpaper:4625
    as

    Download full text from publisher

    File URL: http://cri-world.com/publications/qed_dp_4625.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    MENA; non-performing; loans; transparency; International; corruption; banks;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    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:qed:dpaper:4625. 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: Mark Babcock (email available below). General contact details of provider: https://edirc.repec.org/data/qedquca.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.