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Credit Risk Models For Five Major Sectors In Indonesia

Author

Listed:
  • Ndari Surjaningsih

    (Bank Indonesia)

  • Ina Nurmalia Kurniati

    (Bank Indonesia)

  • Reni Indriani

Abstract

This paper analyze Nonperforming Loan ratio to total credit (NPL), as a proxy for credit risk, for five major economic sectors by utilizing panel data of 117 commercial banks in Indonesia over period 2000Q1 to 2016Q3. Our empirical analysis shows that real economic growth is the main driver that is negatively correlated with credit risks in all sectors. The inverse relation is also found in commodity and housing price. Commodity price inflation affects NPL in manufacturing industry and trade sectors, meanwhile housing price inflation influences NPL in manufacturing industry, trade, and construction sectors. In addition, decreased in policy rate will decline credit risk in commodity, trade, and other sectors, meanwhile nominal exchange rate only affects credit risks in the other sector. Our assessment shows that credit risks in commodity and other sectors are more sensitive to real economic growth than those on manufacturing industry and trade sectors. Real economic growth elasticities to credit risk for commodity and other sectors are almost twice higher than for manufacturing industry and trade sectors. Thus, during economic contraction phase, NPL in commodity and other sectors will increase higher than NPL in manufacturing industry and trade sectors.

Suggested Citation

  • Ndari Surjaningsih & Ina Nurmalia Kurniati & Reni Indriani, 2018. "Credit Risk Models For Five Major Sectors In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 20(4), pages 1-20, April.
    • Handle: RePEc:idn:journl:v:20:y:2018:i:4:p:1-20
    DOI: https://doi.org/10.21098/bemp.v20i4.900
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    Cited by:

    1. Darjana Darjana & Sudarso Kadero Wiryono & Deddy Priatmodjo Koesrindartoto, 2022. "Does Credit Performance Change In The Post- Covid-19? Evidence From Java Island, Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 25(2), pages 257-272, August.

    More about this item

    Keywords

    Banking; Panel Data Models;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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