فصلنامه اقتصاد مقداری
سال هجدهم شماره 4 (پیاپی 71، زمستان 1400)

Financial institutions, especially the banking system, play a key role in the economic system; on the one hand, they provide economic growth and development and on the other hand, they may lead to the conditions of disorder and collapse in an economic system. Therefore, the existence of an efficient and stable banking system to prevent or reduce the likelihood of financial and consequently economic crisis is critical. For this reason, Western governments try to affect our economy through financial sanctions. This increases the business risk and costs of the banking system and economic activists, disrupting all international businesses and financial transactions. sanctions as an external shock can potentially have destabilizing effects on the financial system, especially on the banking system and consequently the economy of a country (in terms of revenue and expenditure). In contrast, some economists believe that sanctions do not affect Iran's banking system. In this case, the inefficiency of Iran's banking system regarding international regulations, as well as high credit risk at the international level, is pseudo-sanctioned, causing the unwillingness of foreign banks to cooperate with Iran. Due to this disagreement, the main purpose of this study is to investigate the effect of banking sanctions and their channels on the financial instability of Iran banks using the Z-score index.

To obtain the purposes of this research, a hypothesis has been formulated that bank sanctions have a significant negative effect on banks' financial stability. To test the hypothesis, the financial data relating to a sample of 18 Iranian banks are collected for the period 2007-2017. Dynamic panel data approach especially two-stage system-generalized method (SYS-GMM) is used. This can dynamically present the results with less error.Specifying research model The model is specified based on Kayaza et al. (2014) as follows: In this model i: Banks, t: time, α: intercept and b: the coefficients of the explanatory variables, banking stability index: (Z). Dummy Variable Sanctions: (SANC), Credit Risk: (CR), Liquidity Risk: (LR), Market Risk: (MR), Inefficiency: (INEFFI), Bank Size: (size), GDP per capita: (GDP), Inflation rate: (INF), current account (DCA).

Sanctions have a significant negative effect on the banking stability of Iran. In addition, inefficiency, credit risk, and liquidity have led to a decline in bank stability but the size of the bank and market risk have a significant positive effect on banking stability. Also, inflation and GDP have significant negative effects and the current account is significantly positively associated with banking stability.

The research hypothesis, that sanctions have a significant negative effect on the stability of Iranian banks, can not be rejected. It may be interpreted that banking sanctions lead to international invalidity and increase the credit risk, resulting in banking instability due to increasing financial costs through bypassing sanctions and finance at a higher cost. Therefore, the central bank is recommended to adopt policies to reinforce the banking system against sanctions, including the use of a SWIFT's alternative messenger system or new financial technologies, especially Blockchain and digital currencies with decentralized supervision.

Nowadays, countries should consider the expansion of the knowledge-based economy to witness endogenous and extroverted growth. So, the government and central bank’s policies should be designed to support the new factors of production, like human capital, R&D, and Innovation. To do so, this study tries to illustrate if monetary policies implemented by the central bank of I.R. Iran between 1978 and 2016 were aligned with the expansion of the innovation market, as one of the prominent factors of a knowledge-based economy.

In this study, we used a simultaneous equation system to investigate the monetary policy effect on GDP through innovation channel in the period of 1978 to 2016. The data was extracted from the central bank of I.R. Iran, and since this study tries to investigate the monetary policy effect on GDP through innovation channel, its spatial scope is national. Specifying research model To investigate the study’s hypotheses following equations were used:(1) (2) In these equation IN, L, K, , and M refer respectively to Innovation, Labor force, Physical capital stock, Physical capital Intensity, and Monetary policy index. It should be noted that since four different monetary indexes were used, four systems of the simultaneous equation were estimated too.

The results show that monetary policies with money stock as a proxy had a negative and significant effect on Innovation in Iran. However, the influence of Innovation on GDP was positive and significant. Therefore, the monetary policy harmed GDP through the Innovation channel.

By implementing a change to relative prices of production factors, it is expected to see rational producers substitute less expensive combination of factors of production. In that case, the implemented policies will determine which factors will be used more in the production process. Interestingly, in our study period, the effect of monetary policy on GDP and GDP without Oil thorough innovation was negative. Therefore, these policy recommendations can be suggested:·I.R.Iran Central bank should be careful about its policies on the innovation market and should implement policies to change the current situation. Also, Central bank’s consultants should recommend policies that aim at knowledge-based economy expansion without any political consideration.

Regardless of different theoretical views regarding the impact of monetary policies on the economy, these policies are currently considered tools to influence variables and the structure of the economy. The main objectives of implementing such economic policies, similar to other policy instruments, are to control adverse economic fluctuations, establish relative stability in price levels, and maintain production within its optimal path. With such goals in mind, it is clear that following the detection of any adverse economic fluctuation, monetary instruments are one of the options available to policymakers to control such fluctuations.On the other hand, academic literature on monetary policies and the difference in adopting monetary instruments in response to business cycles disregard the distinction among countries (for instance based on their level of development etc.). The accepted advice in the economic literature is that countries should adopt counter-cyclical monetary policies. In other words, in times of economic prosperity, it is recommended that monetary authorities eliminate inflation by increasing interest rates and reducing interest rates in times of economic recession to stimulate production to return to its sustainable path. This recommendation is attributed to the study by Wexel (1907). Despite all the developments in the field of monetary theories in the last century, this recommendation has remained unchallenged and was part of Chicago's plan that emerged from the Great Depression of 1933. Keynesian IS and LM models support counter-cyclical monetary policies. However, Fisher (1977) and Phelps and Taylor (1977) (in the presence of rational expectation), along with Keynesians Woodford (2001) and Giannoni and Woodford (2002), opposed monetary policies as a cycle to stabilizean  active economy and recommend it.

Note that this emphatic policy recommendation does not consider any specific classification among countries. However, there is evidence that countries have adopted monetary instruments differently in response to similar business cycles, depending on their level of development (or other economic indicators). In other words, there are a number of empirical studies indicating that in the presence of business cycles, developed countries have implemented counter-cyclical (or often cycle-independent) monetary policies, while developing ones have adopted this approach and implemented pro-cyclical monetary policies.In this regard, the present study investigates the cyclical situation of monetary and fiscal policies in Iran. To achieve this goal, a structural vector autoregression (SVAR) model with three variables has been estimated using data derived from 1352 to 1396.

The results of the study show that correlation coefficient between fiscal and monetary structural movements are very low and approximated to zero. T test show that none of these coefficients had any statistical difference with zero. These findings show that proxies(equipments) for fiscal and monetary policy in Iran are changing independent of business cycles.

The results from model estimation confirm that monetary and fiscal policies in Iran demonstrate a behavior independent of the cycles.The results also show that these policies, despite the independent nature of the cycle, have the potential for economic stabilization.

The main objective of this study is to analyze the impact of changes in the real exchange rate on the export performance of the non-oil sector. Export earnings are assumed of vital importance not only for developing but also for developed countries. Developed countries mainly export capital and final goods, while the main part of developing countries export consists of mining-industry goods especially natural resources. In this context, there are some challenges for countries with natural resource abundance, such as oi,l in comparison with other countries. The main point is that in parallel with the windfall of oil revenues these countries have to pay more attention to the development of the non-oil sector as well as its export performance ;because in most cases oil-driven economic development leads to some undesirable consequences such as Dutch Disease in oil-rich countries. In oil-dependent countries, the export of other goods can help reduce the effect of oil revenues on the country's trade basket. Several factors affect non-oil exports, one of which is exchange rate variable. exchange rate which is the price of a foreign currency in terms of domestic currencies, has an important effect on macroeconomic variables; Such as production, exports, the balance of payments, etc. By affecting the relative prices of domestic and imported goods, this rate can also affect other economic sectors of the country. Accordingly, exchange rates and shocks of this variable are one of the main factors affecting non-oil exports.

Today, because many countries are experiencing continuous changes in politics and economics, it is expected that modeling macroeconomic variables with linear models and fixed parameters are not appropriate, so nonlinear models and temporal parameters have a comparative advantage. This study examines the impact of the exchange rate on non-oil exports in Iran from 1978-2017 by using nonlinear Markov-switching (MS) and Smooth Transition Regression (STR) models. Therefore, these two models are used to estimate the regime transfer rate due to the asymmetric exchange rate on non-oil exports. The studied variables have been collected from the websites of the Central Bank of Iran and the Bank of Commercial Partners. They include non-oil exports, exchange rates, Iran's GDP, GDP, and price index.

The results of a sudden change of Markov-switching model (MS) show that the effect of exchange rate in the first regime is about 8.6 times the second regime, both of which have a positive effect on non-oil exports, So, the results of this method show the nonlinear, asymmetric, and positive effect of exchange rate on non-oil exports in Iran.However, in the Smooth Transition Regression model (STR), exchange rate coefficientsshowed different effects in the two regimes in a way that exchange rate in the first regime has a negative, insignificant effect on non-oil exports, but in the second regime it has a positive and significant effect on non-oil exports.

Overall, the results show that the effect of exchange rate on non-oil exports is nonlinear and asymmetric and this effect changes with the change in transfer rate of the regime;i.e. if the rate of transfer from a regime to another is immediate, the effect of exchange rate on non-oil exports changes rapidly, but if the transition rate is slow, it can reverse the effect of exchange rate on non-oil exports and even completely change the effect. In addition, the findings of this study can be useful for policymakers in the monetary and real sectors in Iran, especially in terms of exchange rate policy implementation and its impact on non-oil exports.

Tax is the main and most stable source of government funding, but governments in most developing countries face institutional and structural barriers, such as poor quality of governance and high levels of corruption, in providing tax revenues. Accordingly, strengthening government accountability and effectiveness can increase the willingness to pay taxes. The trust created in individuals as a result of improving the quality of governance leads to the timely receipt of tax revenues and this leads to strengthening the economic structure. Thus, improvements in institutional quality can lead to public confidence, reduced tax evasion, increased government tax revenues, and ultimately improved tax system performance. One of the important indicators of the tax system performance in different countries is the ratio of tax revenues to GDP in each country. Accordingly, a higher value of this index in a country indicates better performance of its tax system.

In this study, the tax evasion trend is first estimated using Multiple Causes-Multiple Indicators (MIMIC) method. Finally, the simultaneous effect of institutional quality and tax evasion on the performance of the tax system of selected MENA countries in the period (2002-2007) is investigated using the panel data method. In the following, theoretical principles are used to specify the econometric model, in which simultaneous effects of government efficiency and accountability and tax evasion on the performance of the tax system in selected countries of Mena in the period (2017-2002) are discussed: (1)Where, is the ratio of government tax revenues to GDP,  is growth rate of GDP, is value added ratio of services sector to value added of industry sector (structural conversion index), is the share of value added of agricultural sector in GDP, is the ratio of imports of goods and services To GDP, is the government efficiency index and  is the tax evasion index in the i-th country at time t and  is the error term. In the second model, the multiplier effects of tax evasion and GDP growth on the ratio of government tax revenues to GDP are examined:   (2)

Increasing government efficiency and accountability paves the way for greater public participation in financing government expenditures and increases government tax revenues while reducing tax evasion. Also, increasing trade restrictions expand the underground economy, increase illegal imports and smuggling, and reduce government tax revenues. Also, structural transformation, as a representative of the change in the composition of economic sectors, affects the government's ability to collect taxes, the composition and type of taxes it can impose on the economy.

The results show that improving the quality of governance leads to a reduction in tax evasion. Also, the results show that government efficiency and accountability, structural transformation in the economy, the share of imports of goods and services in GDP have a positive effect but the share of value added in agriculture in GDP has a negative effect on the ratio of tax revenues to GDP. In addition, the effect of tax evasion and the multiplier effect of tax evasion and GDP growth rate on the ratio of tax revenues to GDP are not significant.

One of the most important economic problems in Iran during the last few decades is the phenomenon of inflation, to an extent that improving the conditions caused by inflation has always been one of the important goals of developmental plans in Iran. Achieving this goal requires the creation of a rigorous and purposeful mechanism for the economic policymaking process, which in its standard form involves forecasting, targeting and policy analysis. Given that inflation affects many macroeconomic indicators, therefore, explaining and forecasting inflation rates based on econometrics models can help improve policy making.

In this study, 108 quarterly variables from 1990-2017 were used. The variables included the consumer price index as a dependent variable and 107 independent variables (predictors) which were included in nine blocks in order to extract the factors. Thus, 1) the price block included different values ​​of the producer price index, GDP deflator and wage indexes (including 13 variables); 2) the demand block included components of GDP on the demand side and some other indexes related to capital stock (including 7 variables); 3) the fiscal block included all types of government revenues and expenditures (including 13 variables); 4) the international block included exports, imports, exchange rates, as well as the inflation and exchange rates of China and Germany (as Iran's largest trading partners) (including 17 variables); 5) the output block, where different types of production variables were used (including 14 variables); 6) the money block included liquidity and monetary base components (including 21 variables); 7) the financial block, including stock market and insurance variable (including 6 variables); 8) the energy block included various variables related to crude oil, electricity and energy (including 7 variables); and 9) the labor force block which included various variables of unemployment, employment and productivity (including 9 Variables). All the variables of this paper were seasonally adjusted using X-13, TRAMO or STL. Also, the statics of the variables were investigated by the use of unit root tests without seasonal integration (Dickey Fuller and KPSS tests) and a unit root test with seasonal and semi-annual integration (HEGY test). In addition, all variables were standardized by differentiating from the mean and dividing by the standard deviation. Principal Component Analysis (PCA) was used to extract the factors using all the variables in each block.The main purpose of this study was to compare DMA and DMS models (9 block factor methodes) with BMA, BVAR, TVP and AR. In addition, the interruptions of each model were determined using BIC. Similar to the study of Koop and Korobilis (2012), the predictions were considered with a short-run horizon (h = 1), a medium-run horizon (h = 4) and a long-run horizon (h = 8).In order to assess the prediction performance, Mean Squared Forecast Error (MSFE), Mean Absolute Forecast Error (MAFE), Mean Absolute Percentage Error (MAPE), the bias of the prediction error, the variance of the prediction error and the sum of log predictive likelihoods (PL) were used. In addition, the Diebold-Mariano (1995) test was used to compare the prediction accuracy.

The results show that the prediction of DMS and DMA is more efficient than other traditional predictive methods to predict the inflation rate in Iran. Findings indicated that in all forecast horizons, money and price blocks were the highest in using the optimal model over time and the fiscal block was the lowest. In general, it can be said that the DMA model is the average of many models and does not only use a single factor block (there is also no irrelevant factor block) and this is the most important feature of DMA / DMS use.

Due to the fact that variables can be changed in DMA / DMS in any time period, so their use for economic policy is recommended.

Despite the growing trend of renewable energy production in the world, that will significantly reduce dependence on fossil fuel  in major energy comsuming countries, the IAEA forecasts during the next 30 years all industrialized countries, including menbers of the EU, will be increasingly dependant on the importation of oil and gas. Thereforethe security of energy supply will be a core issue in the EU.  According to forecasts by the European Commission's Energy Office, energy supply within the European Union will decline by about 20% in2030compared to 2005, so that Europe will need to import more than 55%of its energy. Meanwhile, gas is the main source of energy on which there wiil be the most dependence. Gas cooperation between the EU and Russia has existed since 1960. It has passed a variety of challenges successfully and is now an important aspect of the overall EU-Russia relationship. Russia is the largest exporter of natural gas to the European Union, so as the revenues from exports to the EU accounts for a large share of Russia's GDP. However, current EU-Russia energy policies do not appear to becooperative, and implementation of previous initiatives has slowed. There are a number of studies on the interdependence between Russia and the European Union in terms of energy, especially gas trade, as well as the analysis of misunderstandings and conflicts in this regard. However, the way in which such interdependence can affect Iran has not been well explored. None of the studies has considered Iran as an important player or even a solution to the "crisis" in EU-Russia energy relations.

In this research, statistical, descriptive, analytical and historical research methods have been used. Information was also collected through library and Internet resources and using news databases based on objective-historical data, and an attempt was made to use the most reliable and up-to-date statistical and descriptive information of domestic, regional and international study centers. The libraries of the Ministry of Foreign Affairs, the Library of the University of Science and Research, the Library of the Center for Middle East Studies and Research of the Ministry of Foreign Affairs, the National Library and domestic and international virtual libraries have been used to obtain library information.

The inability of some members of the European Union to supply energy resources or their monopoly, and high dependence on Russian gas and lack of trust in that country, insufficient gas resources in the Caspian Sea and a 25 percent reduction in energy production within the EU by 2030 (compared to 2000(, the Union's main challenges in ensuring energy security have made the EU adopt a "collective energy security" approach. In line with theories of reciprocity and neo-functionalism, EU-Russia cooperation in the field of energy can reduce the conflict and accelerate cooperation in other areas and establish peace in relations between the two sides. One of the requirements of the EU Collective Security Strategy is the diversification of the EU's energy supply, and in this strategy, the Islamic Republic of Iran, as the holder of the world's first energy reserves (total oil and gas), can play a key role in the EU's energy supply. If this is achieved, further stabilization will accelerate Iran's economic development from two perspectives of Iran's security and the region, as well as the provision of economic benefits.

Despite various challenges in reducing the share of Russian gas in the European energy basket, Iran can play a special role in this process due to its abundant gas resources and strategic geographical location. Although the establishment of a special program for strategic cooperation between the EU and Iran regarding energy has always been a serious challenge due to the  US economic sanctions, the strong mutual desire to establish economic relations, especially after the 2013 nuclear deal, confirms that the concept of interdependence can be used for bilateral relations in this regard. This study discusses  how this dependence regarding energy, can ultimately lead to explaining the role of Iran in the future energy supply of Europe. According to the results, Iran will be able to meet 10% of global consumer needs in the long run if it overcomes the political challenges of international relations and lift sanctionsThis will lead to a strategic partnership between the EU andIran that will improve international investment and trade as well as technology transfere. With the rapid,stable improvement in Iran, this can be an advantage.