Modern Applied Science, Volume (11), No (4), Year (2017-1) , Pages (13-22)

Title : ( Modeling the Effective Factors on Bank Loans Default Rate UsingDelphi, SEM and Tobit Techniques (Evidence from Iran) )

Authors: hamid safay nikoo , Mohammad Taher Ahmadi Shadmehri , Ahmad Sabahi , Seyed Mohammad Javad Razmi ,

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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.

Keywords

, SME, loan default rate (DR), Delphi, SEM,
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@article{paperid:1061471,
author = {Safay Nikoo, Hamid and Ahmadi Shadmehri, Mohammad Taher and Sabahi, Ahmad and Razmi, Seyed Mohammad Javad},
title = {Modeling the Effective Factors on Bank Loans Default Rate UsingDelphi, SEM and Tobit Techniques (Evidence from Iran)},
journal = {Modern Applied Science},
year = {2017},
volume = {11},
number = {4},
month = {January},
issn = {1913-1844},
pages = {13--22},
numpages = {9},
keywords = {SME; loan default rate (DR); Delphi; SEM; Tobit},
}

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%0 Journal Article
%T Modeling the Effective Factors on Bank Loans Default Rate UsingDelphi, SEM and Tobit Techniques (Evidence from Iran)
%A Safay Nikoo, Hamid
%A Ahmadi Shadmehri, Mohammad Taher
%A Sabahi, Ahmad
%A Razmi, Seyed Mohammad Javad
%J Modern Applied Science
%@ 1913-1844
%D 2017

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