پديد آورندگان :
كوهي ليلان، بابك دانشگاه مفيد - گروه اقتصاد، قم، ايران , دباغ، رحيم دانشگاه صنعتي اروميه - گروه مهندسي صنايع، اروميه، ايران , كياالحسيني، ضياءالدين دانشگاه مفيد - گروه اقتصاد، قم، ايران , رهبر، فرهاد دانشگاه تهران - گروه اقتصاد، تهران، ايران
كليدواژه :
ثبات بانكي , رگرسيون آستانه‌اي پانل , ريسك اعتباري , كشورهاي منطقه منا
چكيده لاتين :
Objective: Banking, by its very nature, involves a wide range of risks. Banking supervisors
should identify their risks and evaluate and manage them. Therefore, the factors affecting
banking stability should be identified and applied in proportion to the importance of each
relevant strategy.
Methods: The method of the present research is descriptive and applied and using descriptive
and inferential methods, the data have been analyzed and then the obtained results have been
analyzed. It has been used to identify the impact of credit and liquidity risks on banking stability
in selected member countries of the Mena region using the Panel Gentle Transfer Regression
(PSTR) model, which is one of the prominent regime change models.
Results: According to the results of MATLAB software, it was found that the variables of
liquidity risk and credit risk in both regimes have the greatest impact on the stability of the
banking system of MENA member countries and also the impact of credit risk in both regimes is
greater than liquidity risk. Therefore, formulating appropriate policies to manage credit risk
reduction can lead to the stability of the country's banking system, which in turn will strengthen
the monetary system. Analyzing the relationship between economic factors and risks on banking
stability is an important issue that has been addressed in this study. The thresholds of credit risk
as a turning point and distinguishing point of the two regimes expressed in the PSTR model, for
these equations, have been estimated according to the Akaik and Schwartz tests (3.36 and 3.83),
respectively. The results of parameter slope estimation showed that the adjustment speed from
one regime to the second regime was equal to 0.194, which indicates their gentle adjustment
speed. In the first regime before the threshold, ie the linear part of the PSTR model, the variables of credit risk, payment facilities, inflation and crisis and shocks to countries have a negative and
significant effect on the banking system. In contrast, the variables of facility to deposit ratio,
liquidity risk, bank size, return on assets, efficiency of banks and GDP have a positive and
significant effect on the banking system. In the second regime, the nonlinear part of the PSTR
model, the variables of facility to deposit ratio, bank size, inflation, capital to asset ratio, facilities
and crises and shocks that have hit a country have a negative and significant effect on the
banking system. In contrast, the variables of liquidity risk, credit risk, return on assets, efficiency
of banks, gross national product and payment facilities of banks have a positive and significant
effect on the banking system.
Conclusion: According to the results of this study (first and second scenarios), liquidity risk, in
addition to a positive effect on banking stability, intensifies its positive effect on the banking
stability of countries. Credit risk also has a significant effect on off-line banking stability, which
has been confirmed. In other words, according to the results of the estimated model, the variables
of liquidity risk and credit risk in both regimes have the greatest impact on the stability of the
banking system of MENA member countries, so that the effect of credit risk in both regimes is
greater than liquidity risk. Therefore, formulating strategies to reduce instability in the country's
banking system, credit risk management can be an important factor to increase banking stability,
which will strengthen the monetary system.
