Mohammadgholi Yousefi; Bahman Khadam
Abstract
The purpose of this study is to find the main determinants of stagflation in Iranian manufacturing sector during 1982-2012. We have used the data of manufacturing industries, categorizing them into three groups of resource base, low technology and medium and high technological industries. We have used ...
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The purpose of this study is to find the main determinants of stagflation in Iranian manufacturing sector during 1982-2012. We have used the data of manufacturing industries, categorizing them into three groups of resource base, low technology and medium and high technological industries. We have used logit regression with fixed effect, taking industries utilizing less than 50 percent of their nominal capacity and having more than 20 percent disguised unemployment in addition with having capital–output ratio of over 3o percent as industries suffering from stagflation. If a manufacturing industry was suffering stagflation, its dependent variable was given a value of 1 and the dependent variable of other industries was set to zero. Our explanatory variables include the imports of intermediate goods, wage costs, labor productivity, interest rates, exchange rate and oil revenue. Our findings show that all the variables with the exception of labor productivity had expected signs and their coefficients were statistically significant. The results show that, while as expected, the coefficient of labor productivity was negative, however, the coefficients of other variables were positive and significant implying positive impact on stagflation.
Saeed Moshiri; Mohammad Nadali
Volume 13, Issue 48 , April 2013, , Pages 1-27
Abstract
The banking structure in Iran has undergone dramatic changes for the past three decades going from a mixed private-public banking system to a complete state-owned banking system. Although banking crisis such as bank panic and bank run has never been observed in Iran, the money market pressure index ...
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The banking structure in Iran has undergone dramatic changes for the past three decades going from a mixed private-public banking system to a complete state-owned banking system. Although banking crisis such as bank panic and bank run has never been observed in Iran, the money market pressure index shows that the banking system has experienced crisis in various times. In this paper, we use the banking crisis data derived by Moshiri and Nadali (2010) to estimate the determinants of the banking crisis in Iran, using a Logit model for the period 1971-2008. The estimation results show that inflation, short term interest rate, and the ratio of domestic credit to private sector to GDP are the main factors affecting banking crisis in Iran. Moreover, the results indicate that the relationship between inflation rate and the banking crisis is U shape. The exchange rate does not have a significant effect on the banking crisis as the Iranian banking system is not heavily involved in the international financial markets and is not strongly connected to the international banking system.
Reza Raei; Aboozar Soroush
Volume 12, Issue 44 , April 2012, , Pages 131-145
Abstract
Defaulted loans are biggest challenges in Iranian bank system. One of the major reasons for this phenomenon is the lack of validate scoring systems for loan payment in the banks. The banks can predict default risks of the borrowers, by using these systems.
However, a data base has been established for ...
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Defaulted loans are biggest challenges in Iranian bank system. One of the major reasons for this phenomenon is the lack of validate scoring systems for loan payment in the banks. The banks can predict default risks of the borrowers, by using these systems.
However, a data base has been established for gathering borrowers' information and providing validates reports in previous years, but, there are defects to use these reports in the bank system comprehensively.
This research aims to design a practical validate scoring model.
We have used the information 290 legal (small and medium size) borrowers in three banks. The results show the suggested model is significant. In addition, the model was tested on the basis the information of another sample of 40 legal borrowers; the results confirmed the before ones.
