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What Threatens Tunisian Banking Stability? Bayesian Model Versus Panel Data Analysis

Author

Listed:
  • Abdelaziz Hakimi
  • Khemais Zaghdoudi
  • Taha Zaghdoudi
  • Nesrine Djebali

Abstract

This paper aims to investigate the main determinants of Tunisian bank stability. To achieve this goal; we have used a dataset of ten (10) Tunisian banks during the period 1990-2015. These banks are the most dynamic and the most involved in the financing of the economy. The econometric strategy used in this paper was based on two approaches. The first one performed the Bayesian Model Average (BMA) to detect the most important indicators influencing bank stability. The second one was based on panel data analysis involving random effect regression. Results of these two methods have indicated that Tunisian bank stability is more sensitive to capital adequacy ratio, liquidity risk and the interaction between credit risk and liquidity risk. The capital adequacy ratio is positively and highly significantly associated with the dependent variable (Z-Score). However, liquidity risk and interaction variables exert a negative and significant effect on bank stability. These results have important policy implications. Banks and policy makers should continue to strengthen the capital adequacy ratio since it significantly contributes to improving bank stability. However, they should pay attention to liquidity risk as the main determinant of bank instability

Suggested Citation

  • Abdelaziz Hakimi & Khemais Zaghdoudi & Taha Zaghdoudi & Nesrine Djebali, 2017. "What Threatens Tunisian Banking Stability? Bayesian Model Versus Panel Data Analysis," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 11(2), pages 21-37.
    • Handle: RePEc:ibf:ijbfre:v:11:y:2017:i:2:p:21-37
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    Citations

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    Cited by:

    1. Khemais Zaghdoudi, 2019. "The Effects of Risks on the Stability of Tunisian Conventional Banks," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 9(3), pages 389-401, March.
    2. Nesrine Djebali & Khemais Zaghdoudi, 2020. "Testing the governance-performance relationship for the Tunisian banks: a GMM in system analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-24, December.
    3. Djebali, Nesrine & Zaghdoudi, Khemais, 2020. "Threshold effects of liquidity risk and credit risk on bank stability in the MENA region," Journal of Policy Modeling, Elsevier, vol. 42(5), pages 1049-1063.

    More about this item

    Keywords

    Bank Stability; Bank Specifics; Industry Specifics; Macroeconomics; Bayesian Model; Panel Data; Tunisia;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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