Theories on the relationship between money and inflation had largely been shaped around the positive relationship and money causality for inflation before the PostKeynesians. Since the 1980s, this idea emerged that there might be no correlation between money growth and inflation. In the case of existence, the causality is reversed, so money is endogenous somehow. However, practically there is a suspicion that the causality between money growth and inflation is not fixed and linear. According to the experience of Turkey in the last seven decades, which has experienced fluctuated inflation rates, it is supposed that the causal relationship between Broad Money Growth (BMG) and inflation is not constant. This paper examines this idea over 1961–2019 using a Markov Switching Vector Autoregressive model (MS-VAR), which allows for regime shifts. Findings show that the causal relationship between BMG and inflation has not been constant, and different regimes have generated different causality orientations. There was a one-way causality from inflation to BMG during 1971–2001 that inflation rates were high. Whereas, during 1961–70 and 2002–19, when the Turkish economy experienced milder inflation rates, there was a one-way causal relationship from BMG to inflation.
{"title":"Investigating the Relationship between Money Growth and Inflation in Turkey: A Nonlinear Causality Approach","authors":"E. Eltejaei, Jalal Montazeri Shoorekchali","doi":"10.52547/jme.16.3.305","DOIUrl":"https://doi.org/10.52547/jme.16.3.305","url":null,"abstract":"Theories on the relationship between money and inflation had largely been shaped around the positive relationship and money causality for inflation before the PostKeynesians. Since the 1980s, this idea emerged that there might be no correlation between money growth and inflation. In the case of existence, the causality is reversed, so money is endogenous somehow. However, practically there is a suspicion that the causality between money growth and inflation is not fixed and linear. According to the experience of Turkey in the last seven decades, which has experienced fluctuated inflation rates, it is supposed that the causal relationship between Broad Money Growth (BMG) and inflation is not constant. This paper examines this idea over 1961–2019 using a Markov Switching Vector Autoregressive model (MS-VAR), which allows for regime shifts. Findings show that the causal relationship between BMG and inflation has not been constant, and different regimes have generated different causality orientations. There was a one-way causality from inflation to BMG during 1971–2001 that inflation rates were high. Whereas, during 1961–70 and 2002–19, when the Turkish economy experienced milder inflation rates, there was a one-way causal relationship from BMG to inflation.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121463520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mehdi Haghighi Kaffash, A. Moradpoor, Shahram Khalilnezhad, M. Keimasi
Despite the importance of the business model in implementing strategy, this issue is less addressed than strategy. This important issue regarding banks' business model has received less attention, and research in Iran and other countries has caused a deprivation of knowledge. In addition to the scientific pathology of the business model in Iranian commercial banks, the present article seeks to determine the weights of importance and prioritization of the main categories. It also prioritizes and determines the importance of each of the concepts of the main categories of the commercial banking business model. The research method is applied in terms of results and descriptive in terms of purpose and quantitative-qualitative from the data dimension. The research method's strategy in the qualitative part is the grounded theory, and in the quantitative part is the process of hierarchical analysis. The data analysis method in the qualitative part is the coding method, and the quantitative part is based on pairwise comparisons and incompatibility rate analysis. The research community is the experts of commercial banks, and its examples are Mellat, Tejarat, Melli, Sepah, Saderat, Shahr, Eghtesad-eNovin, and Ayandeh banks. The sampling method is a purposeful judgment with the snowball method and data collection tools in the qualitative part of the interview and review of documents in the quantitative part of the questionnaire. The research findings led to identifying the pathology of Iranian commercial banks' business model in 7 categories and 36 concepts, which are prioritized and contributed based on the importance and role of each of them in the business model.
{"title":"Pathology of Business Model of Iranian Commercial Banks","authors":"Mehdi Haghighi Kaffash, A. Moradpoor, Shahram Khalilnezhad, M. Keimasi","doi":"10.52547/jme.16.3.348","DOIUrl":"https://doi.org/10.52547/jme.16.3.348","url":null,"abstract":"Despite the importance of the business model in implementing strategy, this issue is less addressed than strategy. This important issue regarding banks' business model has received less attention, and research in Iran and other countries has caused a deprivation of knowledge. In addition to the scientific pathology of the business model in Iranian commercial banks, the present article seeks to determine the weights of importance and prioritization of the main categories. It also prioritizes and determines the importance of each of the concepts of the main categories of the commercial banking business model. The research method is applied in terms of results and descriptive in terms of purpose and quantitative-qualitative from the data dimension. The research method's strategy in the qualitative part is the grounded theory, and in the quantitative part is the process of hierarchical analysis. The data analysis method in the qualitative part is the coding method, and the quantitative part is based on pairwise comparisons and incompatibility rate analysis. The research community is the experts of commercial banks, and its examples are Mellat, Tejarat, Melli, Sepah, Saderat, Shahr, Eghtesad-eNovin, and Ayandeh banks. The sampling method is a purposeful judgment with the snowball method and data collection tools in the qualitative part of the interview and review of documents in the quantitative part of the questionnaire. The research findings led to identifying the pathology of Iranian commercial banks' business model in 7 categories and 36 concepts, which are prioritized and contributed based on the importance and role of each of them in the business model.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134426394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Valipour Pasha, Rasool Khansari, A. Ahmadian
As a mechanism to enhance financial system stability and a process that allows banks to change their role from traditional lenders to originators and distributors of loans, securitization reduces the dependence on customer deposits. Also, it expands lending capacity, manages banks credit risk, and transforms illiquid assets into saleable securities. In this research, GMM method in three formats is used for the 16 selected Iranian banks. Results show that real sector growth positively and significantly increase financial stability in the Iranian economy. This is because of the economic scale augmentation and its impact on creating new financial resources. Meanwhile, the non-performing loans ratio significantly diminishes banking stability as well as it lowers banks' capacity to generate revenues from intermediary activities. Moreover, return is affected by the inflationary conditions which heightens revenue making and equity factors in banks' balance sheets. In order to generate higher revenues and gain upper profits, banking resources are occasionally withdrawn to enter other financial markets. Loans to deposits ratio, representing the credit risk in banking systems, denotes that higher risk in credit areas exacerbates financial stability due to the higher probability of risk appetite in generating loans to the general public. Also, security size highlights that although it is expected that securitization augments the financial stability in the banking system, other indicators would also be influential on financial stability. In other words, the higher the security size, the bigger its impact on banking stability. Furthermore, Lending capacity augments as a result of risk management and transforming illiquid assets into saleable securities.
{"title":"Can Securitization Enhance Financial Stability? (Case of the I.R. of Iran)","authors":"Mohammad Valipour Pasha, Rasool Khansari, A. Ahmadian","doi":"10.52547/jme.16.3.323","DOIUrl":"https://doi.org/10.52547/jme.16.3.323","url":null,"abstract":"As a mechanism to enhance financial system stability and a process that allows banks to change their role from traditional lenders to originators and distributors of loans, securitization reduces the dependence on customer deposits. Also, it expands lending capacity, manages banks credit risk, and transforms illiquid assets into saleable securities. In this research, GMM method in three formats is used for the 16 selected Iranian banks. Results show that real sector growth positively and significantly increase financial stability in the Iranian economy. This is because of the economic scale augmentation and its impact on creating new financial resources. Meanwhile, the non-performing loans ratio significantly diminishes banking stability as well as it lowers banks' capacity to generate revenues from intermediary activities. Moreover, return is affected by the inflationary conditions which heightens revenue making and equity factors in banks' balance sheets. In order to generate higher revenues and gain upper profits, banking resources are occasionally withdrawn to enter other financial markets. Loans to deposits ratio, representing the credit risk in banking systems, denotes that higher risk in credit areas exacerbates financial stability due to the higher probability of risk appetite in generating loans to the general public. Also, security size highlights that although it is expected that securitization augments the financial stability in the banking system, other indicators would also be influential on financial stability. In other words, the higher the security size, the bigger its impact on banking stability. Furthermore, Lending capacity augments as a result of risk management and transforming illiquid assets into saleable securities.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116142775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although gold is no longer a central cornerstone of the international monetary and financial system, it still attracts considerable attention from researchers and investors. Nowadays, many investors manage their risk with valuable assets such as gold. This paper examines the dynamic relationships between gold and stock markets in the Tehran Stock Exchange. We have applied the Markov switching method to study the role of gold as a hedge or safe haven for the Tehran Stock Exchange risk from 1998 to 2018. The high dependence and low dependence regimes used in the Markov switching model are based on empirical results that show two regimes for all markets under investigation: a low volatility regime and a high volatility regime. The study's findings show that gold can act as a strong hedge and cannot act as a safe haven for risk of The Tehran stock exchange.
{"title":"Study on Gold as a Hedge or Safe Haven for the Stock Market by a Markov Switching Approach","authors":"Aghil Ariannejad, R. Tehrani","doi":"10.52547/jme.16.3.377","DOIUrl":"https://doi.org/10.52547/jme.16.3.377","url":null,"abstract":"Although gold is no longer a central cornerstone of the international monetary and financial system, it still attracts considerable attention from researchers and investors. Nowadays, many investors manage their risk with valuable assets such as gold. This paper examines the dynamic relationships between gold and stock markets in the Tehran Stock Exchange. We have applied the Markov switching method to study the role of gold as a hedge or safe haven for the Tehran Stock Exchange risk from 1998 to 2018. The high dependence and low dependence regimes used in the Markov switching model are based on empirical results that show two regimes for all markets under investigation: a low volatility regime and a high volatility regime. The study's findings show that gold can act as a strong hedge and cannot act as a safe haven for risk of The Tehran stock exchange.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125626949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Botshekan, Amir Takaloo, Reza H. soureh, Mohammad Sadegh Abdollahi Poor
{"title":"Global Economic Policy Uncertainty (GEPU) and Non-Performing Loans (NPL) in Iran's Banking System: Dynamic Correlation using the DCC-GARCH Approach","authors":"M. Botshekan, Amir Takaloo, Reza H. soureh, Mohammad Sadegh Abdollahi Poor","doi":"10.52547/jme.16.2.187","DOIUrl":"https://doi.org/10.52547/jme.16.2.187","url":null,"abstract":"","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133761854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aims at getting a better performance for optimal stock portfolios by modeling stocks prices dynamics through a continuous paths Levy process. To this end, the share prices are simulated using a multi-dimensional geometric Brownian motion model. Then, we use the results to form the optimal portfolio by maximizing the Sharpe ratio and comparing the findings with the outputs of the conventional model. To examine the robustness of the results, we have evaluated its performance for different investment horizons and various volumes of price information over a long period (approximately twenty years) in the Tehran Stock Exchange (TSE). Findings indicate that within the trading dates spanning the interval 24-Mar-2001 to 19-Sep-2020, the return of the portfolios obtained from applying this simulation scheme for maximization of Sharpe ratio is (244% on average) higher and their risk (standard deviation) are lower (1227% on average) than those realized by the conventional methods. Additionally, a comparison of the simulation approach with a performance of the actual market portfolios indicates that the Sharpe ratios of the simulation method are higher (0.055% on average) than those resulting from the total market performances. The results of the stochastic dominance test show that our proposed strategy has a first-order stochastic dominance (FSD) over the conventional one and market portfolios, that means at each level of cumulative distribution, the Sharpe ratio of our method is higher, and as FSD test makes no assumptions about the curvature of investors' utility functions, these results do not depend on the degree of risk aversion of investors, and as long as investors prefer a higher Sharpe ratio, they would be better off if they follow our proposed strategy.
{"title":"Outperformance Testing of a Dynamic Assets Portfolio Selection Supplemented with a Continuous Paths Levy Process","authors":"Mohammad Feghhi Kashani, Ahmadreza Mohebimajd","doi":"10.52547/jme.16.2.253","DOIUrl":"https://doi.org/10.52547/jme.16.2.253","url":null,"abstract":"This study aims at getting a better performance for optimal stock portfolios by modeling stocks prices dynamics through a continuous paths Levy process. To this end, the share prices are simulated using a multi-dimensional geometric Brownian motion model. Then, we use the results to form the optimal portfolio by maximizing the Sharpe ratio and comparing the findings with the outputs of the conventional model. To examine the robustness of the results, we have evaluated its performance for different investment horizons and various volumes of price information over a long period (approximately twenty years) in the Tehran Stock Exchange (TSE). Findings indicate that within the trading dates spanning the interval 24-Mar-2001 to 19-Sep-2020, the return of the portfolios obtained from applying this simulation scheme for maximization of Sharpe ratio is (244% on average) higher and their risk (standard deviation) are lower (1227% on average) than those realized by the conventional methods. Additionally, a comparison of the simulation approach with a performance of the actual market portfolios indicates that the Sharpe ratios of the simulation method are higher (0.055% on average) than those resulting from the total market performances. The results of the stochastic dominance test show that our proposed strategy has a first-order stochastic dominance (FSD) over the conventional one and market portfolios, that means at each level of cumulative distribution, the Sharpe ratio of our method is higher, and as FSD test makes no assumptions about the curvature of investors' utility functions, these results do not depend on the degree of risk aversion of investors, and as long as investors prefer a higher Sharpe ratio, they would be better off if they follow our proposed strategy.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127993277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mehran Zarei, M. Esfandiari, Seyed Hossein Mirjalili
Shadow banking is a term that came out of the financial crisis of 2007-2009. There is a belief that shadow banking was one of the crisis reasons. Because the excessive expansion of shadow banking endangers the financial stability of countries, this paper examines the impact of shadow banking on financial stability using data from 14 countries of the G20 during 2002-2018. We divided countries into four groups according to the level of shadow banking activity; then, we employed the quantile regression method. The results indicated that shadow banking hurts financial stability (positive impact on financial instability) in countries with a high shadow banking index (fourth group countries). One unit of increase in the shadow banking index increases financial instability in the fourth group countries (high shadow banking) by 1.6 units. But in countries where shadow banking is not very strong (other three groups), shadow banking does not significantly affect financial stability.
{"title":"The Impact of Shadow Banking on the Financial Stability: Evidence from G20 Countries","authors":"Mehran Zarei, M. Esfandiari, Seyed Hossein Mirjalili","doi":"10.52547/jme.16.2.237","DOIUrl":"https://doi.org/10.52547/jme.16.2.237","url":null,"abstract":"Shadow banking is a term that came out of the financial crisis of 2007-2009. There is a belief that shadow banking was one of the crisis reasons. Because the excessive expansion of shadow banking endangers the financial stability of countries, this paper examines the impact of shadow banking on financial stability using data from 14 countries of the G20 during 2002-2018. We divided countries into four groups according to the level of shadow banking activity; then, we employed the quantile regression method. The results indicated that shadow banking hurts financial stability (positive impact on financial instability) in countries with a high shadow banking index (fourth group countries). One unit of increase in the shadow banking index increases financial instability in the fourth group countries (high shadow banking) by 1.6 units. But in countries where shadow banking is not very strong (other three groups), shadow banking does not significantly affect financial stability.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129555542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper aims to estimate the Value-at-Risk (VaR) using GARCH type models with improved return distribution. Value at Risk (VaR) is an essential benchmark for measuring the risk of financial markets quantitatively. The parametric method, historical simulation, and Monte Carlo simulation have been proposed in several financial mathematics and engineering studies to calculate VaR, that each of them has some limitations. Therefore, these methods are not recommended in the case of complications in financial modeling since they require considering a series of assumptions, such as symmetric distributions in return on assets. Because the stock exchange data in the present study are skewed, asymmetric distributions along with symmetric distributions have been used for estimating VaR in this study. In this paper, the performance of fifteen VaR models with a compound of three conditional volatility characteristics including GARCH, APARCH and GJR and five distributional assumptions (normal, Student’s t, skewed Student’s t and two different Lévy distributions, include normal-inverse Gaussian (NIG) and generalized hyperbolic (GHyp)) for return innovations are investigated in the chemical, base metals, automobile, and cement industries. To do so, daily data from of Tehran Stock Exchange are used from 2013 to 2020. The results show that the GJR model with NIG distribution is more accurate than other models. According to the industry index loss function, the highest and lowest risks are related to the automotive and cement industries.
{"title":"Estimation of Value at Risk (VaR) Based On Lévy-GARCH Models: Evidence from Tehran Stock Exchange","authors":"Hossein Amiri, Mahmood Najafi Nejad, Seyede Mohadese Mousavi","doi":"10.52547/jme.16.2.165","DOIUrl":"https://doi.org/10.52547/jme.16.2.165","url":null,"abstract":"This paper aims to estimate the Value-at-Risk (VaR) using GARCH type models with improved return distribution. Value at Risk (VaR) is an essential benchmark for measuring the risk of financial markets quantitatively. The parametric method, historical simulation, and Monte Carlo simulation have been proposed in several financial mathematics and engineering studies to calculate VaR, that each of them has some limitations. Therefore, these methods are not recommended in the case of complications in financial modeling since they require considering a series of assumptions, such as symmetric distributions in return on assets. Because the stock exchange data in the present study are skewed, asymmetric distributions along with symmetric distributions have been used for estimating VaR in this study. In this paper, the performance of fifteen VaR models with a compound of three conditional volatility characteristics including GARCH, APARCH and GJR and five distributional assumptions (normal, Student’s t, skewed Student’s t and two different Lévy distributions, include normal-inverse Gaussian (NIG) and generalized hyperbolic (GHyp)) for return innovations are investigated in the chemical, base metals, automobile, and cement industries. To do so, daily data from of Tehran Stock Exchange are used from 2013 to 2020. The results show that the GJR model with NIG distribution is more accurate than other models. According to the industry index loss function, the highest and lowest risks are related to the automotive and cement industries.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122680123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Generally, international flows of capital and foreign direct investment attraction are challengeable issues in the literature of economic growth and development in emerging market countries. However, the fluctuations in foreign direct investment, including sudden flood and stop, will affect emerging markets' output and macroeconomic variables. Using an econometric model with unbalanced panel data during 1990-2014 for 38 emerging countries, this study tries to evaluate the determinants of output losses from the sudden stop of foreign direct investment and consider the role of macroeconomic policies. The results show that the sudden stop phenomena and the financial crises have been identified as the main explanatory variables for the output collapse in the selected countries. Moreover, the role of macroeconomic policies is important, and the output losses can be controlled by using active monetary and exchange rate policies.
{"title":"Output Loss from Sudden Stop of FDI and the Role of Macroeconomic Policies","authors":"M. Yazdani, E. Daryani","doi":"10.52547/jme.16.2.213","DOIUrl":"https://doi.org/10.52547/jme.16.2.213","url":null,"abstract":"Generally, international flows of capital and foreign direct investment attraction are challengeable issues in the literature of economic growth and development in emerging market countries. However, the fluctuations in foreign direct investment, including sudden flood and stop, will affect emerging markets' output and macroeconomic variables. Using an econometric model with unbalanced panel data during 1990-2014 for 38 emerging countries, this study tries to evaluate the determinants of output losses from the sudden stop of foreign direct investment and consider the role of macroeconomic policies. The results show that the sudden stop phenomena and the financial crises have been identified as the main explanatory variables for the output collapse in the selected countries. Moreover, the role of macroeconomic policies is important, and the output losses can be controlled by using active monetary and exchange rate policies.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132649523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The present study investigates the impact of macroeconomic and bank-specific variables on non-performing loans (NPLs). To avoid the identification problem, two models are employed to address this impact. The first one tests the effect of macroeconomic variables including the growth of oil revenues, inflation, and the growth of GDP without the oil sector on the growth of NPLs. Data is quarterly over the period 2004:3 to 2019:3. The transition variable in this setup is the growth of oil revenues and its threshold is 9 percent, which divides the sample into oil booms and oil recessions. According to the results, inflation has a significant positive effect on NPLs. During the oil boom, oil revenues decrease the NPLs. Due to the immense size of the government and its current and capital expenditures, when oil revenues are lower, the government forces banks to allocate loans to finance projects with long maturity. Furthermore, the present study used PSTR to test the impact of bank-specific variables consisting of interest rate spread, loan loss provision, loan to deposit ratio, and NPLs. To do so, monthly data of 10 banks is used over 2016:04 to 2020:12. The transition variable is the interest rate spread at 1 percent, which categorizes the banks into two groups of good and bad. Good banks collect deposits with a low-interest rate and allocate high-rate loans with less chance of default. So, interest spread is the most important prominent determinant of decreasing NPLs, while the loan to deposit ratio is dependent on the banks belonging to which group. For good banks, the loan to deposit ratio decreases the NPLs, while for bad banks, it worsens the growth of NPLs.
{"title":"The Impact of Macroeconomic and Banking Variables on Non-Performing Loans in Oil Cycles: Evidence from Iran","authors":"F. Rahbar, Mohsen Behzadi Soufiani","doi":"10.52547/jme.16.2.135","DOIUrl":"https://doi.org/10.52547/jme.16.2.135","url":null,"abstract":"The present study investigates the impact of macroeconomic and bank-specific variables on non-performing loans (NPLs). To avoid the identification problem, two models are employed to address this impact. The first one tests the effect of macroeconomic variables including the growth of oil revenues, inflation, and the growth of GDP without the oil sector on the growth of NPLs. Data is quarterly over the period 2004:3 to 2019:3. The transition variable in this setup is the growth of oil revenues and its threshold is 9 percent, which divides the sample into oil booms and oil recessions. According to the results, inflation has a significant positive effect on NPLs. During the oil boom, oil revenues decrease the NPLs. Due to the immense size of the government and its current and capital expenditures, when oil revenues are lower, the government forces banks to allocate loans to finance projects with long maturity. Furthermore, the present study used PSTR to test the impact of bank-specific variables consisting of interest rate spread, loan loss provision, loan to deposit ratio, and NPLs. To do so, monthly data of 10 banks is used over 2016:04 to 2020:12. The transition variable is the interest rate spread at 1 percent, which categorizes the banks into two groups of good and bad. Good banks collect deposits with a low-interest rate and allocate high-rate loans with less chance of default. So, interest spread is the most important prominent determinant of decreasing NPLs, while the loan to deposit ratio is dependent on the banks belonging to which group. For good banks, the loan to deposit ratio decreases the NPLs, while for bad banks, it worsens the growth of NPLs.","PeriodicalId":151574,"journal":{"name":"Journal of Money and Economy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115556331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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