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Modeling the Effective Factors on Bank Loans Default Rate Using Delphi, SEM and Tobit Techniques (Evidence from Iran)

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  • Hamid Safaynikou
  • Mohammad Taher Ahmadi Shadmehri
  • Ahmad Sabahi
  • Mohammad Javad Razmi

Abstract

Banks entering a developing market face a lot of uncertainty about the risks involved in lending. This paper models the effective factors on default rate (DR) loans to small and medium size enterprises (SMEs) in Iran based on the case study of branches of Melli Bank in Khorasan Razavi province. For this purpose a set of data about loans made to 300 SMEs between years 2004 to 2015 and Delphi, SEM and Tobit models were applied. Results of Delphi technique indicated that 48 factors affect the DR. The structural equation model (SEM) estimations showed that between 10 latent variables which describe the DR, the “loans properties†latent variable have the most effect. Also, findings of Tobit econometric model stated that between 48 variables which affect the DR, “loan volume†variable has the most effect. These and other factors emphasize the need for SMEs credit scoring in developing countries.

Suggested Citation

  • Hamid Safaynikou & Mohammad Taher Ahmadi Shadmehri & Ahmad Sabahi & Mohammad Javad Razmi, 2017. "Modeling the Effective Factors on Bank Loans Default Rate Using Delphi, SEM and Tobit Techniques (Evidence from Iran)," Modern Applied Science, Canadian Center of Science and Education, vol. 11(4), pages 1-13, April.
    • Handle: RePEc:ibn:masjnl:v:11:y:2017:i:4:p:13
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    References listed on IDEAS

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    1. Fidrmuc, Jarko & Hainz, Christa, 2010. "Default rates in the loan market for SMEs: Evidence from Slovakia," Economic Systems, Elsevier, vol. 34(2), pages 133-147, June.
    2. Anderson, Dennis, 1982. "Small industry in developing countries: A discussion of issues," World Development, Elsevier, vol. 10(11), pages 913-948, November.
    3. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    4. Nada Mora, 2012. "What determines creditor recovery rates?," Economic Review, Federal Reserve Bank of Kansas City, vol. 97(Q II).
    5. Wajid Hasan Shah, 2014. "SME Loan Defaults in Bangladesh," ARTNeT Policy Briefs 41, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP).
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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