درخت حوزه‌های تخصصی

Inflation targeting framework has become a predominant monetary approach across the globe. Williams (2015) believes that in a very real sense, almost all economies are inflation targeters -either explicit or implicit- now.(1) Due to the increasing spread of this policy, it is necessary to consider the way it affects macroeconomic variables. using prevalent economic models for evaluating the effectiveness of inflation targeting causes bias selection which for solving this problem, it is proposed propensity score matching model. the goal of this paper is to evaluate the effect of the adoption of Inflation Targeting policy on indirect taxes and its components in two selected groups of oil exporter and oil importer countries during 1990-2016 by using propensity score matching model. our results have shown that inflation targeting adoption in average has a positive and significant effect on indirect tax revenues in oil importer countries group but its effect on indirect tax revenues in oil exporter countries is insignificant. JEL Classification: E5, H2, C21.

The aim of this study was to investigate the asymmetric effects of exchange rate fluctuations on Stock index of Tehran Stock Exchange. For this purpose, we first calculated the exchange rate fluctuations using model General Autoregressive Conditional Heteroskedastic (GARCH), and then the effect of these fluctuations on the Stock index of Tehran Stock Exchange was estimated using the Generalized Method of Moments (GMM). The data were used daily during the period 2010-2017. Also, the effect of positive and negative fluctuations were separated and included as independent variables in the model. The results of fitting the model indicate that the effect of exchange rate and oil price fluctuations on the Stock index of Tehran Stock Exchange is direct. The results of the model estimation showed that the effect of the positive and negative fluctuations of the exchange rateon Stock Index of Tehran Stock Exchange is asymmetric, so that the effect of the exchange rate increase on the Stock index of stock exchange is far greater than the effect of its reduction. Oil price fluctuations have a direct relationship with the Stock index of Tehran stock exchange. JEL Classification: D82, C51,E32, G00.

Foreign trade expansion plays an important role in economic growth and development. Since Iran’s single-product economy is facing tight sanctions, among trading partners, Turkey benefits from special place, and political independence in international relations because of its large population, rising per capita income, high economic growth rate, geographical and cultural proximity to Iran. Many opportunities and substantial capacities have been established for expanding foreign trade between these two countries. To do this, it is necessary to determine the maximum export capacity of Iran to Turkey and whether this capacity has actually been deployed and realized or not. The next question is what the bases of Iran’s export development to Turkey are, and the goods which should be focused on to develop trading. Therefore, the aim of this study was to estimate the maximum export capacity of Iran to Turkey and to determine the commodities with the highest export capacity. The Revealed Comparative Advantage (RCA) index, the Cosine Index, and the General Model of the gravity model were used to evaluate Iran’s export potential and to determine commodities in which Iran has export advantage. Iran’s export potential to Turkey was investigated in various years and in different commodity groups by comparing the rate of export volume of each commodity to total volume of its import by Turkey. Research findings indicated that the highest Iranian export potential value to Turkey was $9,339 million, and just 7.2% of that ($669 million) has been realized. Also, 11 commodity groups formed more than 66% of Iranian potential exports to Turkey. Among them, ‘mineral products’ with $2,730 million, ‘plastics and natural rubber and artifacts made from them’ with 1,185 million, ‘common metals and artifacts made from them’ with $918 million, and ‘products of the chemical industry and its related industries’ with $879 million were respectively the four commodity groups with the highest export potential. JEL Classification: F14]

In 2010, the World Bank categorized countries by GDP (at Purchasing Power Parity) per capita (at constant 1990 prices) in three categories: low, middle (low and high), and high. If a country falls in a trap at least 28 years in the low middle income and at least 14 years in the high middle income group, then it is included in low and middle income groups, respectively .In this paper, using the experience of successful countries in avoiding the trap, we investigated the impact of investment, human capital, high-tech exports, total factor productivity, exports of goods and services, and the value added of service sectors on per capita GDP growth during 1991-2014, using panel data. Research findings in the literature indicated that in selected Asian countries, human capital and total factor productivity growth with positive and significant effects have the greatest impact on avoiding the trap. In the case of Iran, human capital and the total factor productivity growth have positive and significant effects on the economic growth, but such effects have not been so great to help escaping Iran’s economy from the middle- income trap. Therefore, Iran has remained in the middle- income trap over the past 58 years. JEL Classification: J24, D24, E22, C33.

Nowadays, financial markets in Iran have attracted the attention of many managers, investors and financial policymakers. Therefore, in order to make the optimal decision and reduce the risks in such a market, it is important to identify and analyze the network behavior of the financial markets at different times to obtain the optimal decision. The current study aims to answer the following research question; how is it possible to use the minimum spanning tree and hierarchical clustering in the network analysis of the Tehran Stock Exchange? The period examined was 2013 to 2018. The population consisted of all the companies accepted in Tehran Stock Exchange. The sampling was selected purposefully and contained the companies which had at least one trading day in the time span from the beginning of 2013 to the end of 2018. The stock of the investigated companies was considered as the vertexes of one graph and the coherent information criterion was considered as the weight of the edge. First, the minimum spanning tree of the graph was calculated. The results revealed that the stocks of DarooAbuReihan, DarooPakhsh and Alborzdaroo had a high influence on directing the prices of the other stocks. Furthermore, the results of hierarchical clustering classified the stocks of the companies into 8 clusters. This study presents a viewpoint about the modern method designed for the analysis of complex financial networks. Moreover, the study offers an analysis of Iran's stock market structure which can be the center of finance researchers and analysts' attention.