Determinants of Non-Performing Loans and Non-Performing Financing level: Evidence in Indonesia 2008-2021

  • Received August 1, 2022;
    Accepted October 27, 2022;
    Published November 28, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.17(4).2022.10
  • Article Info
    Volume 17 2022, Issue #4, pp. 116-128
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This work is licensed under a Creative Commons Attribution 4.0 International License

Banking stability plays an important role as an intermediary in the economy. Both the economy and the banking sector affect each other. This study aims to investigate the effect and response of external variables and internal bank variables on Non-Performing Loans at Conventional Commercial Banks and Non-Performing Financing at Islamic Commercial Banks. This study uses macroeconomic variables such as economic growth and inflation, while a bank’s internal variables include the Loan to Deposit Ratio, Financing to Deposit Ratio, and Capital Buffer. This study employs Vector Autoregressive Regression (VAR) to examine the time series data. The results showed that the variable Economic Growth at lag-1, Loan to Deposit Ratio at lag-1, and Capital Buffer at lag-2 significantly affect Non-Performing Loans. While the variable that has a significant effect on Non-Performing Financing is only Economic Growth at lag-1. In addition, as can be seen from the Impulse Response Function curve, Non-Performing Financing tends to be more stable toward shocks from the variables used than Non-Performing Loans. The findings suggest that banks are encouraged to be more selective in loan disbursement and maintain minimal capital adequacy by taking into account the principle of prudence and referring to the bank’s health criteria.

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    • Table 1. IRF estimation results
    • Table A1. Stationarity test result
    • Table A2. Lag optimum test result
    • Table A3a. Polynomial test result (conventional)
    • Table A3b. Polynomial test result (Islamic)
    • Table A4. Cointegration test result
    • Table A5. Granger causality test result
    • Table A6. VAR estimation result (conventional)
    • Table A7. VAR estimation result (Islamic)
    • Conceptualization
      M. Safar Nasir
    • Funding acquisition
      M. Safar Nasir
    • Supervision
      M. Safar Nasir
    • Validation
      M. Safar Nasir
    • Writing – original draft
      M. Safar Nasir
    • Data curation
      Yolanda Oktaviani
    • Formal Analysis
      Yolanda Oktaviani
    • Methodology
      Yolanda Oktaviani
    • Software
      Yolanda Oktaviani
    • Visualization
      Yolanda Oktaviani
    • Investigation
      Nur Andriyani
    • Project administration
      Nur Andriyani
    • Resources
      Nur Andriyani
    • Writing – review & editing
      Nur Andriyani