جستجوی مقالات مرتبط با کلیدواژه « مطالبات معوق » در نشریات گروه « اقتصاد »

The housing sector in Iran is considered one of the most important economic sectors, so that around 20-30% of the country's capital formation was allocated to this sector in the last decade. Price vibratilitys are one of the most important economic challenges of this sector. Examining the conditions governing the economy in the past years shows that the conditions of recession and inflation governing the country's economy have created one of the most difficult periods for the country, and in the meantime, the housing sector, as one of the economic sub-sectors, has not been protected from the Adverse effects of the conditions governing the macro economy. And it has experienced relatively long periods of recession and relatively high inflation before that. On the other hand, one of the basic problems that banks and financial and credit institutions are dealing with today is the problem of non-current claims and uncollected facilities. In addition to reducing the profitability of banks, this issue causes the slow circulation of liquidity in the economy, the lack of allocation of credits to productive requests on time, in the fields of industry, mining, trade and agriculture, and ultimately economic stagnation. One of the most important factors affecting the non-current claims of the banking system can be the business cycles and periods of the housing sector, since the civil partnership facilities of banks have a significant share, the booms and busts of the housing and non-residential buildings sectors can affect the ability to repay the received facilities. be influential. The boom in the housing sector and investors in this sector will help repay loans. While the stagnation of the housing sector and its expansion will reduce the willingness and ability of investors to repay loans; Therefore, examining the cycles of the housing sector as one of the factors affecting non-current claims is necessary and necessary. Also, it seems that the increase in demand is not the only factor affecting housing prices and the unfavorable conditions of other economic sectors of the country make the housing sector attractive to all investors (banks and non-banks). Considering the importance of the issue and considering that one of the effects and consequences of the monetary activities of credit institutions is the emergence of non-current claims that have negative effects on the cycle of resources and expenses of banks and can also affect housing prices; Therefore, the main goal of this research is to answer the question that to what extent does the investment of banks in real estate affect the price of housing? In this research, using the TVP-DMA method, the most important factors affecting housing prices have been identified. To examine a forecasting model or to choose the best model among different models for a time series, an index is needed to make the necessary decision regarding the acceptance or rejection of the forecasting model. In this study, two standard indices of the Mean Squared Forecast Error (MSFE) and the Mean Absolute Forecast Error (MAFE) are used. Based on the results, the most important variables affecting housing prices in Iran's economy are inflation variables; exchange rate; liquidity; Economic Growth; Bank payment facilities for housing; Overdue claims and increase in bank debt; the amount of fixed assets of banks; Land price index in Tehran; sanctions index; population; housing tax; Urbanization coefficient and price index of construction materials. Based on the results of inflation variables; exchange rate; liquidity; Bank payment facilities for housing; the amount of fixed assets of banks; Land price index in Tehran; sanctions index; population; Urbanization coefficient and price index of construction materials have a positive effect and economic growth variables; Overdue claims and increase in bank debt and housing tax have a negative effect on housing prices. Based on these results, inflation with the longest period of influence is the most important variable affecting housing prices in Iran. Based on the results, the following suggestions are made to improve the situation in the housing sector:Tax policies: According to the current conditions, the most effective way to deal with housing speculation is to apply effective taxes in the field of housing and real estate. These taxes can be placed in 5 areas: real estate capital gains tax, real estate transfer tax, annual real estate tax, real estate rental income tax, and real estate construction and sale income tax.Pending claims policies: Considering the results of the research and the significance of the effect of housing prices on non-current claims of banks in the period under review, it seems that policymakers and supervisors should consider housing prices as a key indicator affecting the stability of banks. In this context, it is desirable to provide a framework to control the relationship between housing prices, bank loans and loan losses.Facilitation policies: as a policy solution arising from the results and findings of this research and considering the existence of potential accumulated demand in the housing market and the existing imbalance, it is suggested to prevent the stimulation of potential demand and the increase of housing prices, the share of bank facilities granted for the purchase housing will be reduced and on the other hand, the share of bank facilities granted for housing construction will increase and then the facilities allocated for housing construction will be converted into long-term contracts for installment sales and rent as a condition of possession. It is worth mentioning that the interest rate of bank facilities can also be effective on housing prices from the cost aspect; Therefore, in the housing market, both supply and demand factors must be monitored and controlled.

Liquidity , as the most important variable of the money market , has a significant role in economic performance from various aspects and therefore it is important to identify the factors affecting liquidity. Considering that one of the channels to increase liquidity is loans paid by the banking network and the effective role of capital adequacy ratio in the payment of bank loans, in the present study we investigate the effect of capital adequacy ratio on volume of liquidity and its asymmetric effects in 2008:2 -2020:1 by using a nonlinear Autoregressive Distributed Lags model.The results show that increasing the capital adequacy ratio has a reducing effect on the volume of liquidity and compliance with the regulation on the capital adequacy ratio can be one of the key tools to curb the growth of liquidity in the Iranian economy. In addition, the effect of changing the capital adequacy ratio on liquidity is asymmetric. According to the results of the Wald test, increasing the capital adequacy ratio has a stronger effect on liquidity than reducing it.The results also showed that the increase in the amount of non performing loans of the banking network through the channel of reducing the lending capacity of the banking network in both short-term and long-term periods leads to a decrease in liquidity in the country. The increase in the exchange rate has also led to an increase in liquidity in the country in short-term and with two lags. Also, in order to curb the growth of liquidity, an increase in government expenditures should be financed through an increase in tax revenues, not borrowing from the banking network or the use of sovereignty revenues.

Credit risk assessment has always been one of the most important concerns of banks. Widely used models such as financial models have been used to assess credit risk so far. But increasing non-performing loans indicates that today these models cannot assess the credit risk of customers. Inconstant and uncertain environmental, social and political factors affect customer behavior and change customer behavior over time so that low risk customers become high risk customer. Hence a dynamic model had better to design for customers’ credit risk evaluation. Recognizing patterns of changes of customer behavior is a key factor in the bank's success in assessing and managing customer credit risk. Previous research has used conventional models such as financial and empirical data models. In this study, considering the dynamics of customers over time in different segments of low risk, medium risk and high risk and using big data analysis methods, dynamic customer behavior patterns have been extracted. In this study, the loans information of individual customers of three banks in a sample of 284,000 customers between 1389 and 1396 were examined and 30 variables were used to assess credit risk. The results showed that the model with a sensitivity of 92.1% and a detection of 89.1% has a high efficiency and performs better and has a higher efficiency compared to the probit, logit and neural network models. The result of this research is the recognition of dynamic patterns of customers' credit risk and using it. The bank has a more accurate assessment of customers' credit risk. Also in this method there is no need to retrain the data and run the algorithms again, therefore, this method saves time and money. Most importantly, the results of this study are significantly different from the results of the current bank model (static method).

In the present study, the effect of exchange rate and shadow banking along with the added value of different production sectors on the overdue receivables of the banking network in the period 2008: 2-2018: 4 has been investigated using the Markov regime change pattern. The results show that the effect of research variables in different regimes of overdue receivables is different, so that if deferred receivables are in their high regime, the growth of shadow banking has a negative and significant effect, and if in their low regime Has a positive and significant effect. The exchange rate has a positive and significant effect in the high regime of overdue receivables and has no significant effect in the low regime. The added value of the oil and services sectors in all arrears regimes leads to a reduction, which shows the importance of these sectors. However, the added value of the agricultural and industrial sectors can only be reduced if the overdue claims in the regime are high. Therefore, if the goal is to reduce the volume of delinquent receivables, the necessary policy should be implemented according to the regime in which the delinquent receivables are placed and also based on the influence of the economic and banking sectors.

Due to the importance of non-performing loan banking in the health of the banking system and the role of banks in financing the country's enterprises in this study was tried to use the study of Abid et al. (2014) in which the effect of economic and banking variables on non-performing loan banking of Tunisia has been studied, To evaluate the effect of macroeconomic variables (GDP, Government dept, exchange rate, and liquidity) and banking (bank size, moral hazard, and bad management) on the volume of non-preforming loans bankings, accepted banks in Tehran stock exchange during the period 1396-1386 to be paid. In this study, the two-step Generalized Method of Moments (GMM) and panel data have been used. Finally, the accuracy of the results was checked by Sargan tests and serial autocorrelation. The statistical population of the study is the banks accepted by tehran stock exchange (Saderat, Mellat, Tejarat, Sina, Sarmayeh, Saman, Parsian, Pasargad, Hekmat Iranian, Ansar, Eghtesad Novin, Dey, Khavaremianeh, Ayandeh, Gardeshgary, Shahr, Karafarin, Post Bank and Tosee Etebari). Macroeconomic variables such as liquidity, government debt and exchange rates have a significant effect on the volume of non-performing loan. The relationship between liquidity and government debt variables and the volume of non-performing loan is positive. The relationship between the exchange rate and the volume of non-performing loan was reported in most negative coefficients. Also, banking variables such as bank size have a negative relationship with the volume of non-performing loan and the relationship between bad management and the volume of non-performing loan is positive.

The purpose of this research is to measure the efficiency of selected Iranian banks from 2010 to 2016. We estimate efficiency, productivity and efficiency changes under the Bayesian setting. In this research, we consider the Non-Performing Loans (NPLs) of banks as bad outputs, while good outputs are loans, off balance sheet assets and securities. Also, variables such as number of employees, bank capital, fixed assets and deposits play inputs role. Results show that the productivity changes of selected Iranian banks are positive over the period of the study, which is mainly due to the improvement in technology like e-banking services, while efficiency changes continued to be negative over the same period. It is observed that the average efficiency for banks is 85 percent. The Karafarin bank has the largest efficiency among selected banks while Refah Kargaran bank efficiency has the smallest one. Results also show that, during the specified period, private banks have a few better efficiency estimate in comparison with the efficiency of state owned banks.

The purpose of this paper is to investigate the effect of macroeconomic factors on the ratio of non-performing loans of accepted banks in Tehran Stock Exchange. For this purpose, the data of 8 banks and credit institutions from 1391 to 1396 in Tehran Stock Exchange and data panel regression method were used. The results of the study showed that the inflation rate and GDP have a negative and significant effect on the bank's outstanding claims. Moreover, the results indicated that the interest rate of the facility had a positive and significant effect on non-performing loans.

The banking system as an essential foundation for the economy is affected by various factors both internal and external. Loan quality is one of the factors affecting the proper functioning of the system. Because the low quality of loans leads to rise in the ratio of non-performing loans and reduce profitability. Moreover, this can cause to withdrawals by clients that are rooted in fear of losing money and finally lead to a crisis due to a high level of uncertainty in deposits repayment by the banks. In this study, we evaluate the effects of some factors such as loan growth rate and credit risk of which measured by Non-Performing Loan ratio on loan quality in the banking system. We also examine the effect of macroeconomic variables on the loan quality. The results of GMM estimation came to the conclusion that there is a significant relationship between the independent variables and loan growth rate and NPL in the short and long term. According to the results, the relationship between return on asset and the loan quality is significant and positive. Additionally, the findings show a negative and significant relationship between capital adequacy ratio and NPL. Accordingly considering asset quality plays a key role in banks risk management.

As banks place in our country and aim of surveying their operations, this paper survey bank efficiency of Iran in 2010-2014. Main aim of this paper is to survey efficiency of 17 banks with Network Data Envelopment Analysis (NDEA). In this paper, the inputs used is fixed asset and employee number, bank deposit is intermediate variable , banks profit is desirable output and Non performing loans of banks is undesirable output. Variables are collected according to their roles in bank's structures. Results reveal that else of 2 banks, all banks of our sample operated less than efficient level in our period. Performance of some banks is so weak and some banks which have more Non Performing Loans have lower efficiency.Keywords: Efficiency, Banks, Network Data Envelopment Analysis (NDEA), Non Performing Loans, Intermediate variable

Banking system has been faced recently by none-performing Loan in Iran and it has many consequences such as lack of liquidity and reduction in the volumes of credit in Iran’s banking system. This study investigates the impact of banking and economic factors affecting on none-performing Loan in seven public banks in the framework of dynamic panel data model with using one-step generalized method of moment(GMM) estimator during the time period of 1380 until 1393 based on the importance role of none-performing Loan in the banking system. The results indicate that economic variables (economic growth, inflation rate, real interest rate and public debts) have a significant role in explaining long run and short run changes in public bank’s None-performing Loan, whereas management and efficiency among bank’s factors have a significant role in explaining changes in public bank’s None-performing Loan. Based on the results, changes in public bank’s None-performing Loan compare with economic and banking factors, are more sensitive to economic condition.

This paper examines the relationship between financial stability and macroeconomics variables and banking concentration in Iranian banking system for the period 1385-1393 (2006-2014).
In this study, Herfindal-Hirschman index (HHI) as a concenteration index and inverted non-performing loans ratio are used to measure banking concentration and financial stability respectively. In addition, inflation rate, GDP growth rate, bank lending rate and market share are considered as macroeconomics variables. In order to estimate the relationship, a balanced dynamic panel with generalized method of moments (GMM) is used. The result indicates that the banking concentration,inflation, GDP growth rate, interest rate and market share has a statistically significant impact on non-performing loans and therefore on the Bank's financial stability.

The increasing of non-performing loans, (NPLs) and consequently, instabilities that may happen in the future. Therefore, research in this issue causes some findings that rots of the problems in order to prevent the growth of non-performing loans in awarded facilities. The potential and actual collection of non-performing loans creates desirable condition for both banking system and Recipients of bank facilities. The present study stimulates and checks the relationship between financial distress Recipients of bank facilities and amount of bank non-performing loans of period by using system dynamics approaches. The model is designed using VENSIM Software. The result of Sceneries imitation at the end of the period of study shows that reduction in expected inflation, reduction in unemployment and reduction in interest rates will have significant effect in reducing the amount of bank non-performing loans.

Banking system is one of the main pillars of any economic system that is the source of a need of money persons and their correct performance of and principles can boom over growth and economic system. Undoubtedly, creation of Nonperformance Loans are looking for financing activities in banks and financial institutions so a heavy non-performing portfolio and default on part of the clients is a serious problem confronting the financial institutions all over the world including. Hence, this paper with quantitative analytical methods tries to have comparative comparison NPLs in Iranian banking system with other countries and resolve defaults or late payments in some Islamic countries. The comparative study result shows that situation of Iranian Banking system, despite using Ribafree banking, in comparison with other countries of the world is not appropriate and need to find immediate solution. At the end, paper offered proposed strategies in two sections of legal solutions and experience of Islamic countries.

It has been discussed that the expansion of the financial sector has complicated the management of macroeconomic policies so that the analysis and the management of business cycles would not be sufficient without considering the interactions of the financial and real sectors, mainly due to the effects of financial stances on the transmission mechanisms of the economic policies. In order to evaluate the linkages between business and financial cycles in Iran’s economy, we built a dynamic stochastic general equilibrium model within the new Keynesians framework which incorporates banking system, and in particular the distinguished characteristics of Iranian banking system such as high rate of NPLs and considerable share of fixed assets in its balance sheet are taken into account. By calibrating the parameters, the simulated moments of the model fits that of real data of Iran’s economy during 1369-1393 (AH). We find that the technological shocks effect the financial cycles. Moreover, the balance sheet of banks has a major role in explaining the macroeconomic fluctuations. In this regard the effects of frozen banking assets on the economic cycles are greater than those of NPLs. Therefore, it is highly suggested that the central bank puts a higher priority to decrease the fixed assets of banking system while perusing the reduction of NPLs.

One of the major problems of the Iranian banking industry is non-performing loans and facilities which are not collected nowadays. Most economists believe that the growth of nonperforming loans is a sign of non-optimal allocation of banking resources showing that the banking system is managed publicly and the emphasis on expanding share of private banks in the banking industry. Thus, with transferring state banks to the private sector in recent years, as well as the establishment of new private banks, it is necessary to investigate the effect of development of private banks on non-performing loans of the banking system in Iran. For this reason, the present paper attempts to test and analyze the effect of development of share of private banks in the banking system on nonperforming loans of all banking system by using seasonal data of 2001 to 2011 and by applying Auto Regressive Distributed Lag (ARDL) model. The results showed that there is a significant long-run relationship between development of share of private banks in the banking system and the whole nonperforming loans in the banking system. The research also emphasis that this correlation in Long-term will be negative.

The growing non-performing loans which are rooted in credit risk have increasingly intensified the importance of identification and resolution of this problem. Many systematic and unsystematic factors affect non-performing loans. By reviewing scientific sources، this study aims to identify these factors. As an initial step، approximately 90 factors from different sources were recognized as factors affecting the non-performing loans. After confirming and completing this list according to experts’ opinions، these factors were classified into 8 systematic and 7 unsystematic categories along with previous researches and conceptual similarity as well as banking experts’ opinions. To assess the extent of each factor’s impact on the non-performing loans and measuring inter-communication within a group the data was analyzed by using Multiple Criteria Decision Making techniques (Fuzzy TOPSIS and Fuzzy DEMATEL method). The results indicate that among other factors the following have the most significant impact on the increasing of non-performing loans: increase in inflation، devaluation of the national currency and weakness in the process of evaluation of loan application. Also factors such as political and economic risks، sanctions، rising inflation، devaluation of the national currency، the increase in parallel market efficiency، government ownership over banks and their centralization are the most central factors affecting other factors and the rest of the factors are mostly included in affected group of factors. In general، it can be concluded that the participation of systematic factors in increasing non-performing loans are more than unsystematic factors، because they are ranked higher than unsystematic factors and also these factors have been identified as factors affect other factors.

Among the problems of the banking system in the economy of Iran is the NPLs (non-performing loans or outstanding claims). Accumulation of NPLs is a serious challenge for liquidity management in banks, and to the other side due to banks requests on central bank to provide liquidity lack, thereby increasing the monetary base. This study analyzes the effects of NPLs on output and inflation using the dynamic system modeling and simulation. Thus, behavioral equations estimated by Auto-Regressive distributed Lag (ARDL) methodology, along with other relations structure the system dynamic model. The powerful system dynamic software, ithink applied for system simulation and after validation tests, 5 percentage point increase in NPL rate as a step shock introduced. Results show inflation increased and GDP did not response significantly. Added restriction on Central Bank Claims on Banks (CBCB), lead to production and inflation decrease.