Determinants of bank lending rates: Empirical evidence from conventional retail banks in Bahrain

  • Received August 3, 2022;
    Accepted October 28, 2022;
    Published December 19, 2022
  • Author(s)
  • DOI
  • Article Info
    Volume 17 2022, Issue #4, pp. 140-153
  • Cited by
    5 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

The study attempts to identify the determinants of lending rates in the Kingdom of Bahrain. It examines the impact of certain macroeconomic and banks’ aggregate data variables on the level of interest rates on loans charged by Bahraini conventional retail banks using quarterly data for the period from the 4th quarter of 2012 to the 4th quarter of 2021. The study tests the impact of a consumer price index (CPI), GDP growth rates, loan-to-total assets (loan ratio), liquid assets as a proportion of total assets (liquidity position), personal lending rate, loan-to-deposit ratio, money supply (M2) growth, non-performing loans (NPL) ratio, and return on assets (ROA) on banks’ lending rates. The study is mainly based on data retrieved from the publications of the Central Bank of Bahrain and the CEIC Data Global Database. The study uses EViews 12 The results reveal that CPI, liquidity position, the lending rate for personal loans, deposit ratio, and return on assets are the major determinants of bank lending rates to businesses. The study found that GDP growth, money supply growth, and non-performing loans ratio are insignificant in determining the lending rate to businesses in Bahrain. In addition to yielding insights to the respective authorities, this study also helps creditors, investors, and borrowers predict interest rates and thus manage their assets and liabilities more efficiently.

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    • Figure 1. Normality test
    • Table 1. Descriptive statistics
    • Table 2. Pairwise correlation matrix
    • Table 3. Variance inflation factor (VIF)
    • Table 4. Serial correlation (LM) test results
    • Table 5. Heteroskedasticity test results
    • Table 6. Regression model estimation
    • Conceptualization
      Ahmad Mohammad Obeid Gharaibeh
    • Formal Analysis
      Ahmad Mohammad Obeid Gharaibeh, Mohammad Omar Farooq
    • Investigation
      Ahmad Mohammad Obeid Gharaibeh
    • Methodology
      Ahmad Mohammad Obeid Gharaibeh, Mohammad Omar Farooq
    • Software
      Ahmad Mohammad Obeid Gharaibeh
    • Visualization
      Ahmad Mohammad Obeid Gharaibeh
    • Writing – original draft
      Ahmad Mohammad Obeid Gharaibeh
    • Supervision
      Mohammad Omar Farooq
    • Validation
      Mohammad Omar Farooq
    • Writing – review & editing
      Mohammad Omar Farooq