Showing 4 results for Nazari
Dr Iman Haqiqi, Dr Hasan Aqanazari, Dr Gholamali Sharzei,
Volume 4, Issue 11 (3-2013)
Abstract
The purpose of this paper is to introduce the “Natural Resources Perpetuity Rule” in the allocation of resources revenue. We also analyzed the potential impacts of implementing this rule on oil and gas revenues in Iran. To do so, we employed a Computable General Equilibrium Model which is calibrated based on 2010 Micro Consistent Matrix. We assumed an open economy with different sectors such as oil and gas, public services and other activities. Assuming exhaustibility, we measure the impact of different saving rates from Resources Revenue (SR) on welfare, size of public sector, activity levels and exports. We found that the more the SR, the more the welfare loss in first years, the higher the long-run welfare path, the more the non-oil export and the less the size of public sector.
Marzieh Khakestari, Navid Nazari Adli,
Volume 6, Issue 21 (10-2015)
Abstract
Monetary wide range of sanctions has been established against Iran in recent years by European :::::union::::: and United States. These sanctions have been targeted Iran energy and oil industry. Although, these types of sanctions are not new on Iran and Iran is familiar whit them since oil nationalization movement. This paper studies these sanctions effects on Iran in recent years and tries to assess the possible strategies with game theory. In order to achieve this proposed, three players are introduced: Iran, Saudi Arabia and United States, and then a model have been established. At the following, the model was solved and Nash equilibrium obtained for each one. Each of three players , United States , Saudi Arabia and Iran choose their strategy, respectively, pressure reduction, cooperation and cooperation. At the end of this study, the impact of oil sanction on Iran's sales, has been shown. Eventually, it was seen even with great increasing in world oil prices, Iran's in come has been downward.
Ali Falahati, Soheyla Nazari, Maryam Poshtehkeshi,
Volume 11, Issue 39 (3-2020)
Abstract
Natural resource rent affects countries’ economies through various channels. Revenues from the natural resources sales are expected to boost countries' economic growth, but the economic experience of recent decades reveals the numerous economic problems in these countries, the most important of which may be the increase in the shadow economy size. Moreover, the institutions specify the significant economic axes like resources and assets distribution in the community, so that the level of institutional quality brings about the optimal resource directing and their allocation through economic stability and affects the shadow economy volume by increasing economic stability and reducing uncertainty. The purpose of the present study was to examine the effect of natural resource rent and institutional quality on the shadow economy in 87 countries with high and low inflation rates from 2000 to 2018. The analysis method was system generalized-method of moments (System GMM). Smart PLS software was used to estimate the shadow economy. The results indicated that in both low-inflation and high-inflation countries, the increase in institutional quality has reduced the size of the shadow economy, and the rent of natural resources has had a positive relationship with the volume of the shadow economy
Nasrin Motedayen, Rafik Nazarian, Marjan Damankeshideh, Roya Seifi Pour,
Volume 12, Issue 45 (11-2021)
Abstract
Credit risk is the probability of default of the borrower or the counterparty of the bank in fulfilling its obligations, according to the agreed terms. In other words, uncertainty about receiving future investment income is called risk, which is of great importance in banks. The purpose of this article was to estimate the credit risk of Mellat Bank's legal customers. In this study, the statistical information of 7330 real customers was used. In this regard, the results of neural network model and support vector machine model have been compared. The obtained results have shown that the components considered in this study based on personality, financial and economic characteristics had significant effects on the probability of customer default and credit risk calculation. Also, the results of this study showed that the application of control policies at the beginning of the repayment period suggests facilities that have the highest probability of default with long life and high repayment. Comparing the results obtained from the prediction accuracy of different models, it was observed that the explanatory power of the support vector machine model and the use of the survival probability function was higher than that of the simple neural network model for the studied groups of real customers.
