Non-performing loans decision making in the Romanian banking system

Non-Performing Loans (NPLs) are representing nowadays one of the main challenges for the banking systems all over the world. Therefore, a sustainable decision-making process should be implemented, for minimizing the effects of credit risk. The current paper uses a dynamic panel regression model to p...

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Main Authors: Pop Ionuț-Daniel, Chicu Nicoleta, Răduțu Andrei
Format: Article
Language:English
Published: Sciendo 2018-03-01
Series:Management şi Marketing
Subjects:
Online Access:https://doi.org/10.2478/mmcks-2018-0004
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spelling doaj-a55fa61610c74748b49cb48cec728c3b2021-09-06T19:22:34ZengSciendoManagement şi Marketing2069-88872018-03-0113176177610.2478/mmcks-2018-0004mmcks-2018-0004Non-performing loans decision making in the Romanian banking systemPop Ionuț-Daniel0Chicu Nicoleta1Răduțu Andrei2The Bucharest University of Economic Studies – ASE, Bucharest, RomaniaThe Bucharest University of Economic Studies – ASE, Bucharest, RomaniaThe Bucharest University of Economic Studies – ASE, Bucharest, RomaniaNon-Performing Loans (NPLs) are representing nowadays one of the main challenges for the banking systems all over the world. Therefore, a sustainable decision-making process should be implemented, for minimizing the effects of credit risk. The current paper uses a dynamic panel regression model to present the determinants of NPLs for the largest five banks of the Romanian Banking System during 2007-2016. A Generalized Method of Moments (GMM) regression is used and defined under three different types of variables: bank specific indicators, macroeconomic indicators and qualitative variables. Other studies illustrated also the determinants of NPLs in various banking systems from all around the world, such as Japan, China or several CEE countries (especially the emergent ones). After an in-depth analysis of the literature and Romanian market, the following variables were found to be relevant and were introduced into a dynamic data panel model: unemployment rate, annual average growth rate of gross domestic product, return on equity (ROE), loan to deposit ratio (LTD). The existing literature presents ROE as having a negative impact on NPLs, unemployment rate being positive correlated with NPLs and a negative relationship between economic growth and such loans. Our contribution to the current literature is represented by the introduction of two additional qualitative variables (Board Risk Management Ratio (BRMR), as the proportion of risk managers within the Board of Directors of each bank in question and the Expert Aggregate Priority Vector (EAPV), as the aggregated perceived risk regarding the NPLs). The decision of introducing these variables relies on previous research made in this area, results being validated by experts from the Romanian Banking System, according to the BASEL III and NBR criteria. The results of the current paper are consistent with the existent literature, the correlations and impact of the variables being relevant for the subject matter.https://doi.org/10.2478/mmcks-2018-0004non-performing loansdecisional processesbanking performancerisk evaluationanalytic hierarchy process (ahp)generalized method of momentsdynamic panel data model
collection DOAJ
language English
format Article
sources DOAJ
author Pop Ionuț-Daniel
Chicu Nicoleta
Răduțu Andrei
spellingShingle Pop Ionuț-Daniel
Chicu Nicoleta
Răduțu Andrei
Non-performing loans decision making in the Romanian banking system
Management şi Marketing
non-performing loans
decisional processes
banking performance
risk evaluation
analytic hierarchy process (ahp)
generalized method of moments
dynamic panel data model
author_facet Pop Ionuț-Daniel
Chicu Nicoleta
Răduțu Andrei
author_sort Pop Ionuț-Daniel
title Non-performing loans decision making in the Romanian banking system
title_short Non-performing loans decision making in the Romanian banking system
title_full Non-performing loans decision making in the Romanian banking system
title_fullStr Non-performing loans decision making in the Romanian banking system
title_full_unstemmed Non-performing loans decision making in the Romanian banking system
title_sort non-performing loans decision making in the romanian banking system
publisher Sciendo
series Management şi Marketing
issn 2069-8887
publishDate 2018-03-01
description Non-Performing Loans (NPLs) are representing nowadays one of the main challenges for the banking systems all over the world. Therefore, a sustainable decision-making process should be implemented, for minimizing the effects of credit risk. The current paper uses a dynamic panel regression model to present the determinants of NPLs for the largest five banks of the Romanian Banking System during 2007-2016. A Generalized Method of Moments (GMM) regression is used and defined under three different types of variables: bank specific indicators, macroeconomic indicators and qualitative variables. Other studies illustrated also the determinants of NPLs in various banking systems from all around the world, such as Japan, China or several CEE countries (especially the emergent ones). After an in-depth analysis of the literature and Romanian market, the following variables were found to be relevant and were introduced into a dynamic data panel model: unemployment rate, annual average growth rate of gross domestic product, return on equity (ROE), loan to deposit ratio (LTD). The existing literature presents ROE as having a negative impact on NPLs, unemployment rate being positive correlated with NPLs and a negative relationship between economic growth and such loans. Our contribution to the current literature is represented by the introduction of two additional qualitative variables (Board Risk Management Ratio (BRMR), as the proportion of risk managers within the Board of Directors of each bank in question and the Expert Aggregate Priority Vector (EAPV), as the aggregated perceived risk regarding the NPLs). The decision of introducing these variables relies on previous research made in this area, results being validated by experts from the Romanian Banking System, according to the BASEL III and NBR criteria. The results of the current paper are consistent with the existent literature, the correlations and impact of the variables being relevant for the subject matter.
topic non-performing loans
decisional processes
banking performance
risk evaluation
analytic hierarchy process (ahp)
generalized method of moments
dynamic panel data model
url https://doi.org/10.2478/mmcks-2018-0004
work_keys_str_mv AT popionutdaniel nonperformingloansdecisionmakingintheromanianbankingsystem
AT chicunicoleta nonperformingloansdecisionmakingintheromanianbankingsystem
AT radutuandrei nonperformingloansdecisionmakingintheromanianbankingsystem
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