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Modelling the effect of the geographical environment on Islamic banking performance: A panel quantile regression analysis


  • Jawadi, Fredj
  • Jawadi, Nabila
  • Idi Cheffou, Abdoulkarim
  • Ben Ameur, Hachmi
  • Louhichi, Wael


While studies have focused on Islamic banking, research on the effect of the geographical environment on Islamic banks is scarce. We investigate this issue by using daily data on 12 Islamic banks in four regions (Africa, Asia, Europe, and the United States) from July 2007 to April 2016. We apply different methodological approaches (principal component analysis, panel data tests, and quantile regression). First, the principal component analysis shows that the performance of Islamic banks varies among regions. Second, the linear panel regression highlights that the geographical environment positively and significantly affects Islamic banking, suggesting the importance of externality effects. Finally, the environmental effect seems to vary with quantiles (positive effect for the lowest quantile versus negative effect for the highest quantile). This quantile specification points to nonlinearity in the environment–Islamic bank performance relationship, reflecting a time-varying discipline imposed by the Sharia board (Islamic Law). This finding helps better explain the main difference between Islamic banks in the East (Africa and Asia) and those in the West (Europe and the United States) and also enables investors to adjust their portfolio choices when considering the products of Islamic banks according to regional specificities.

Suggested Citation

  • Jawadi, Fredj & Jawadi, Nabila & Idi Cheffou, Abdoulkarim & Ben Ameur, Hachmi & Louhichi, Wael, 2017. "Modelling the effect of the geographical environment on Islamic banking performance: A panel quantile regression analysis," Economic Modelling, Elsevier, vol. 67(C), pages 300-306.
  • Handle: RePEc:eee:ecmode:v:67:y:2017:i:c:p:300-306
    DOI: 10.1016/j.econmod.2017.01.018

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    References listed on IDEAS

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    Cited by:

    1. Serhat Yuksel & Hasan Dincer & Senol Emir, 2017. "Comparing the performance of Turkish deposit banks by using DEMATEL, Grey Relational Analysis (GRA) and MOORA approaches," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 3(2), pages 26-47, December.
    2. Bitar, Mohammad & Kabir Hassan, M. & Hippler, William J., 2018. "The determinants of Islamic bank capital decisions," Emerging Markets Review, Elsevier, vol. 35(C), pages 48-68.
    3. Alexakis, Christos & Izzeldin, Marwan & Johnes, Jill & Pappas, Vasileios, 2019. "Performance and productivity in Islamic and conventional banks: Evidence from the global financial crisis," Economic Modelling, Elsevier, vol. 79(C), pages 1-14.

    More about this item


    Islamic banking; Geographical environment; Panel data; Quantile regression; Nonlinearity;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets


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