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Dr Soheil Roudari, Dr Hamidreza Maghsoudi, Dr Farzaneh Ahmadian-Yazdi,
Volume 0, Issue 0 (12-2024)
Volume 0, Issue 0 (12-2024)
Abstract
Aim and Introduction
One of the most important issues in Iran's economy is related to managing the exchange rate, inflation and budget deficit. During tightening of the sanctions, the oil revenues are limited which potentially leads to an increase in the budget deficit as well as a decrease in the currency supply which accelerates the exchange rate. On the other hand, with the increase in the budget deficit, the probability of borrowing from the banking system and also the issuance of bonds increases, which in turn rise the monetary base and liquidity. In addition, inflationary expectations also increase, which can be effective in improving assets prices. With an increase in inflation, based on the inflation-currency spiral, there is a possibility of a grow in exchange rate in order to maintain the competitiveness of domestic production. This can accelerate the price of imported commodities and cause domestic inflation again. With the increase in inflation and households spending, nominal wages will have a higher growth compared to normal conditions in order to maintain minimum purchasing power, which can again face the government with limited resources and more borrowing to meet current expenses. From the monetarists’ point of view and the classical economics, in general, the main stimulator in increasing inflation is the growth of money and liquidity. However, from the post-Keynesian economists’ point of view, inflation increases the demand of money and subsequently liquidity. On the other hand, with an increase in the exchange rate, the government's expenses usually increase more than its income, which can lead to an increase in the government's budget deficit. Also, considering the existence of a monopoly in currency supply by the central bank, the hypothesis of using currency exchange revenues (the difference between free and budget-approved currency) will be applicable and this issue can raise the impact of the budget deficit on the exchange rate. Therefore, there has always been a serious challenge among economists as well as macroeconomic decision-makers about the connectedness between macroeconomic variables. What is the main driver of the network between macro variables? Is there a different way of communication in different thresholds of their growth rate? These cases show that it is very important to examine the time-varying interrelationships between these macroeconomic variables.
Accordingly, there is a complex connection between exchange rate, inflation, budget deficit and liquidity, which can be varied in different years. Therefore, in this research, using the TVP-TVAR technique, the time-varying connectedness across exchange rate, inflation, budget deficit and liquidity is examined during March, 2006 to August, 2023.
Methodology
In the current research, the relationship between exchange rate fluctuations, inflation, government budget deficit and liquidity based on monthly data using the TVP-TVAR technique is investigated. It should be noted that all the required information is extracted from the economic indicators of the central bank, and the government's budget deficit data from 2017 onward are extracted from Iran's Program and Budget Organization.
Findings
The results show that exchange rate and liquidity are, respectively, the largest net transmitter of volatilities in the network. Moreover, inflation rate and government budget deficit, respectively, are the largest net receivers of shocks from network. On average, the TCI is 23%, and more than 70% of this interrelationship between variables is explained by other factors such as political ones. Moreover, if the variables underestimated grow up to 36% annually (3% monthly), the connection between them will be cut off. In the conditions of decreasing the growth rate of variables up to -3% per month, the exchange rate has played a dominant role and its volatilities are transferred more strongly to inflation rate and less strongly to the budget deficit and liquidity.
If the growth rate of the variables is up to 24% annually (threshold of +2% monthly growth rate), the exchange rate volatilities are transferred to inflation and no interconnectedness between other variables is observed.
Discussion and Conclusion
Our results show that, on average, the total connectedness index from 2012 to 2016 has been upward, which is caused by the tightening of sanctions and the increase in inflationary expectations, psychological factors and emotions. Moreover, the connectedness between them is increased in 2018 and 2019, which is related to the intensification of sanctions and the reduction of currency supply and the increase in inflation and budget deficit and subsequently the increase in the issuance of debt securities in the capital market in order to manage the budget deficit and as a result increase liquidity. The results show that exchange rate is a main net transmitter of volatilities in most years and the inflation rate is a main net receiver of volatilities in many years. From 2016 onwards, the budget deficit is the net receiver of shocks from network in most periods, except for one period in 2019. It is interesting to note that in 2019, with the increase in the budget deficit and the issuance of debt securities, the budget deficit is transmitter, liquidity is receiver and inflation is more receiver variable than liquidity in the network. Totally, the results show that exchange rate is the major net transmitter of shocks to other macro variables.
Moreover, based on the results of the sensitivity analysis and thresholds effect, if the growth rate of variables is up to 24% annually (threshold of +2% monthly growth rate), the exchange rate fluctuations will be transferred to inflation and no connection between other components is observed. This shows that the macroeconomic management of the economy is very sensitive to the growth rate of the thresholds of the macroeconomic components, and before the political economy and also the factors of expectations and emotions dominated the economy, the macroeconomic management, especially the exchange rate, is required. Otherwise, it is impossible to manage the investigated variables with monetary and fiscal policies. Therefore, the managed floating exchange rate should be taken into consideration and if the goal is to manage the network using macroeconomic theories, the variables should not be allowed to increase by more than 24% annual growth. Other factors such as the political economy, and especially inflationary expectations will get the dominant role in the economy
One of the most important issues in Iran's economy is related to managing the exchange rate, inflation and budget deficit. During tightening of the sanctions, the oil revenues are limited which potentially leads to an increase in the budget deficit as well as a decrease in the currency supply which accelerates the exchange rate. On the other hand, with the increase in the budget deficit, the probability of borrowing from the banking system and also the issuance of bonds increases, which in turn rise the monetary base and liquidity. In addition, inflationary expectations also increase, which can be effective in improving assets prices. With an increase in inflation, based on the inflation-currency spiral, there is a possibility of a grow in exchange rate in order to maintain the competitiveness of domestic production. This can accelerate the price of imported commodities and cause domestic inflation again. With the increase in inflation and households spending, nominal wages will have a higher growth compared to normal conditions in order to maintain minimum purchasing power, which can again face the government with limited resources and more borrowing to meet current expenses. From the monetarists’ point of view and the classical economics, in general, the main stimulator in increasing inflation is the growth of money and liquidity. However, from the post-Keynesian economists’ point of view, inflation increases the demand of money and subsequently liquidity. On the other hand, with an increase in the exchange rate, the government's expenses usually increase more than its income, which can lead to an increase in the government's budget deficit. Also, considering the existence of a monopoly in currency supply by the central bank, the hypothesis of using currency exchange revenues (the difference between free and budget-approved currency) will be applicable and this issue can raise the impact of the budget deficit on the exchange rate. Therefore, there has always been a serious challenge among economists as well as macroeconomic decision-makers about the connectedness between macroeconomic variables. What is the main driver of the network between macro variables? Is there a different way of communication in different thresholds of their growth rate? These cases show that it is very important to examine the time-varying interrelationships between these macroeconomic variables.
Accordingly, there is a complex connection between exchange rate, inflation, budget deficit and liquidity, which can be varied in different years. Therefore, in this research, using the TVP-TVAR technique, the time-varying connectedness across exchange rate, inflation, budget deficit and liquidity is examined during March, 2006 to August, 2023.
Methodology
In the current research, the relationship between exchange rate fluctuations, inflation, government budget deficit and liquidity based on monthly data using the TVP-TVAR technique is investigated. It should be noted that all the required information is extracted from the economic indicators of the central bank, and the government's budget deficit data from 2017 onward are extracted from Iran's Program and Budget Organization.
Findings
The results show that exchange rate and liquidity are, respectively, the largest net transmitter of volatilities in the network. Moreover, inflation rate and government budget deficit, respectively, are the largest net receivers of shocks from network. On average, the TCI is 23%, and more than 70% of this interrelationship between variables is explained by other factors such as political ones. Moreover, if the variables underestimated grow up to 36% annually (3% monthly), the connection between them will be cut off. In the conditions of decreasing the growth rate of variables up to -3% per month, the exchange rate has played a dominant role and its volatilities are transferred more strongly to inflation rate and less strongly to the budget deficit and liquidity.
If the growth rate of the variables is up to 24% annually (threshold of +2% monthly growth rate), the exchange rate volatilities are transferred to inflation and no interconnectedness between other variables is observed.
Discussion and Conclusion
Our results show that, on average, the total connectedness index from 2012 to 2016 has been upward, which is caused by the tightening of sanctions and the increase in inflationary expectations, psychological factors and emotions. Moreover, the connectedness between them is increased in 2018 and 2019, which is related to the intensification of sanctions and the reduction of currency supply and the increase in inflation and budget deficit and subsequently the increase in the issuance of debt securities in the capital market in order to manage the budget deficit and as a result increase liquidity. The results show that exchange rate is a main net transmitter of volatilities in most years and the inflation rate is a main net receiver of volatilities in many years. From 2016 onwards, the budget deficit is the net receiver of shocks from network in most periods, except for one period in 2019. It is interesting to note that in 2019, with the increase in the budget deficit and the issuance of debt securities, the budget deficit is transmitter, liquidity is receiver and inflation is more receiver variable than liquidity in the network. Totally, the results show that exchange rate is the major net transmitter of shocks to other macro variables.
Moreover, based on the results of the sensitivity analysis and thresholds effect, if the growth rate of variables is up to 24% annually (threshold of +2% monthly growth rate), the exchange rate fluctuations will be transferred to inflation and no connection between other components is observed. This shows that the macroeconomic management of the economy is very sensitive to the growth rate of the thresholds of the macroeconomic components, and before the political economy and also the factors of expectations and emotions dominated the economy, the macroeconomic management, especially the exchange rate, is required. Otherwise, it is impossible to manage the investigated variables with monetary and fiscal policies. Therefore, the managed floating exchange rate should be taken into consideration and if the goal is to manage the network using macroeconomic theories, the variables should not be allowed to increase by more than 24% annual growth. Other factors such as the political economy, and especially inflationary expectations will get the dominant role in the economy
Dr Abolghasem Golkhandan,
Volume 0, Issue 0 (12-2024)
Volume 0, Issue 0 (12-2024)
Abstract
Aim and Introduction
Ecological footprint accounting is composed of two metrics, the “demand-side” (ecological footprint) and the “supply-side” (biocapacity). While the ecological footprint calculates the demand for natural assets in global hectares, biocapacity symbolizes the supply capacity of nature to meet this demand with the same unit of measurement. Ecological deficit also shows the difference between ecological footprint and biological capacity. Globally, the degree of ecological deficits continued to expand over the last decade due to the increase in EF and reduction in biocapacity, which is caused by the following: increasing consumption of fossil fuel energy, overexploitation of natural resources, unsustainable production methods, and economic activities.
Iran is one of the countries that has a weak environmental performance. According to the Global Footprint Network, Iran's ecological footprint exceeded 333% of its biological capacity in 2022. Iran's ecological deficit, which was - 0.55 global per capita hectares in 1961, has increased by 554% to 2.50 global per capita hectares in 2022, and the destruction and pollution of the environment in Iran have reached unsustainable levels. Therefore, the analysis of the determinants of environmental quality can provide insights into the design of appropriate environmental policies in Iran.
In this regard, the environmental effects of dependence on crude oil have attracted considerable attention. Crude oil is an important and largest source of energy, especially for developing countries such as Iran. It is a fossil-based fuel and a major source of carbon emissions in the world. Hence, many studies have linked oil price shocks to environment quality. In contrast to oil-importing economies, where oil price increases encourage a shift to cheaper and cleaner alternative energy sources, the environmental policy issue in oil-exporting countries is entirely different. Indeed, a fall in oil prices may be associated with a decreased investment in environmentally friendly energy sources. By comparison, an increase in oil prices revealed a reluctance to diversify the economy away from its reliance on non-eco-friendly fossil fuel energy.
Based on the explanations above, the main purpose of this article is to investigate the asymmetric impact of scaled oil price impulses on the environmental Load Capacity Factor (LCF) in Iran using the Non-linear Autoregressive Distributed Lag (MATNARDL) approach. The paper intends to make the following contributions to the literature. Firstly, this article is the first to look into the effect of oil prices on the LCF in Iran by applying asymmetric methodologies. Secondly, it is the first study with a reverse load capacity factor as an environmental sustainability indicator. Thirdly, this paper applied the advanced and newly developed MATNARDL for asymmetric and nonlinear analysis to provide a more robust result that exhibits relevant policy implications. Finally, this innovative study investigated the effects of oil prices on the LCF in Iran between 1961 and 2022 in the framework of the LCC hypothesis.
Methodology
The study compiles annual data for the period 1961-2022 for Iran from three different sources. According to Statista, OP represents average annual OPEC crude oil price (in US dollars per barrel). The data are obtained from the World Bank, GDP per capita, (constant 2015 dollars), Energy Consumption (EC) as kg of oil equivalent per capita, Ecological Footprint (per capita, gha) and LCF (the load capacity factor) are obtained from Global Footprint Network. Because the LCF includes biocapacity in the numerator and EF in the denominator, it allows for simultaneous environmental assessment on the supply and demand sides. A higher LCF indicates a better environment. The current paper's economic functions are illustrated in Equations (1):
2
The main objective of this study is to examine the major, medium and minimal scales of positive and negative changes in oil price on the environmental quality index in Iran. For this purpose, the MATNARDL is used as an estimator to examine the effect of minor to major adverse shocks and minor to major positive surprises in the explanatory variable on the explained variable.
Findings
The bounds cointegration test results confirm a long-term relationship in the asymmetric model. The estimation of the model has been performed by categorizing the positive and negative impulses of the oil price in three small (quantiles less than the τ30 threshold), medium (quantiles between the τ30 and τ70 thresholds), and large (quantiles greater than the τ70 threshold) scales in the form of MATNARDL approach. The results indicate that in the long term, small scale of positive (negative) oil price impulses had a positive (negative) and significant effect on the load capacity factor; while these impulses have a negative effect on the load capacity factor in the long term in both medium and large scales. Based on other results, energy consumption has a negative and significant effect on the load capacity coefficient, and the environmental hypothesis of the load capacity curve (LLC) in Iran is confirmed.
Discussion and Conclusion
Based on the obtained results, it can be said that the effect of oil price on the load capacity factor in Iran is asymmetric. Among positive impulses, only with increase in small scale of oil price, we can see an increase in load capacity factor and environmental sustainability in the country. Moreover, the positive impulses of the oil price on both medium and large scales lead to the increase of environmental instability by prioritizing economic achievements and activities over environmental issues
Ecological footprint accounting is composed of two metrics, the “demand-side” (ecological footprint) and the “supply-side” (biocapacity). While the ecological footprint calculates the demand for natural assets in global hectares, biocapacity symbolizes the supply capacity of nature to meet this demand with the same unit of measurement. Ecological deficit also shows the difference between ecological footprint and biological capacity. Globally, the degree of ecological deficits continued to expand over the last decade due to the increase in EF and reduction in biocapacity, which is caused by the following: increasing consumption of fossil fuel energy, overexploitation of natural resources, unsustainable production methods, and economic activities.
Iran is one of the countries that has a weak environmental performance. According to the Global Footprint Network, Iran's ecological footprint exceeded 333% of its biological capacity in 2022. Iran's ecological deficit, which was - 0.55 global per capita hectares in 1961, has increased by 554% to 2.50 global per capita hectares in 2022, and the destruction and pollution of the environment in Iran have reached unsustainable levels. Therefore, the analysis of the determinants of environmental quality can provide insights into the design of appropriate environmental policies in Iran.
In this regard, the environmental effects of dependence on crude oil have attracted considerable attention. Crude oil is an important and largest source of energy, especially for developing countries such as Iran. It is a fossil-based fuel and a major source of carbon emissions in the world. Hence, many studies have linked oil price shocks to environment quality. In contrast to oil-importing economies, where oil price increases encourage a shift to cheaper and cleaner alternative energy sources, the environmental policy issue in oil-exporting countries is entirely different. Indeed, a fall in oil prices may be associated with a decreased investment in environmentally friendly energy sources. By comparison, an increase in oil prices revealed a reluctance to diversify the economy away from its reliance on non-eco-friendly fossil fuel energy.
Based on the explanations above, the main purpose of this article is to investigate the asymmetric impact of scaled oil price impulses on the environmental Load Capacity Factor (LCF) in Iran using the Non-linear Autoregressive Distributed Lag (MATNARDL) approach. The paper intends to make the following contributions to the literature. Firstly, this article is the first to look into the effect of oil prices on the LCF in Iran by applying asymmetric methodologies. Secondly, it is the first study with a reverse load capacity factor as an environmental sustainability indicator. Thirdly, this paper applied the advanced and newly developed MATNARDL for asymmetric and nonlinear analysis to provide a more robust result that exhibits relevant policy implications. Finally, this innovative study investigated the effects of oil prices on the LCF in Iran between 1961 and 2022 in the framework of the LCC hypothesis.
Methodology
The study compiles annual data for the period 1961-2022 for Iran from three different sources. According to Statista, OP represents average annual OPEC crude oil price (in US dollars per barrel). The data are obtained from the World Bank, GDP per capita, (constant 2015 dollars), Energy Consumption (EC) as kg of oil equivalent per capita, Ecological Footprint (per capita, gha) and LCF (the load capacity factor) are obtained from Global Footprint Network. Because the LCF includes biocapacity in the numerator and EF in the denominator, it allows for simultaneous environmental assessment on the supply and demand sides. A higher LCF indicates a better environment. The current paper's economic functions are illustrated in Equations (1):
The main objective of this study is to examine the major, medium and minimal scales of positive and negative changes in oil price on the environmental quality index in Iran. For this purpose, the MATNARDL is used as an estimator to examine the effect of minor to major adverse shocks and minor to major positive surprises in the explanatory variable on the explained variable.
Findings
The bounds cointegration test results confirm a long-term relationship in the asymmetric model. The estimation of the model has been performed by categorizing the positive and negative impulses of the oil price in three small (quantiles less than the τ30 threshold), medium (quantiles between the τ30 and τ70 thresholds), and large (quantiles greater than the τ70 threshold) scales in the form of MATNARDL approach. The results indicate that in the long term, small scale of positive (negative) oil price impulses had a positive (negative) and significant effect on the load capacity factor; while these impulses have a negative effect on the load capacity factor in the long term in both medium and large scales. Based on other results, energy consumption has a negative and significant effect on the load capacity coefficient, and the environmental hypothesis of the load capacity curve (LLC) in Iran is confirmed.
Discussion and Conclusion
Based on the obtained results, it can be said that the effect of oil price on the load capacity factor in Iran is asymmetric. Among positive impulses, only with increase in small scale of oil price, we can see an increase in load capacity factor and environmental sustainability in the country. Moreover, the positive impulses of the oil price on both medium and large scales lead to the increase of environmental instability by prioritizing economic achievements and activities over environmental issues
Mr. Habib Mosavi, Dr Nader Mehregan, Dr Mohammedreza Yousefi Sheikh Robat,
Volume 21, Issue 3 (9-2021)
Volume 21, Issue 3 (9-2021)
Abstract
Financial markets, especially the capital market, may have strong links with other economic sectors. One of the most important aspects of investment is to determine the “optimal investment portfolio”. To date, some research has been conducted to determine the optimal portfolio with” artificial intelligence” and “Fuzzy Logic”. However, we determine the optimal portfolio based on Dynamic Stochastic General Equilibrium (DSGE) model. This study examines the design and calibration of the new Keynesian dynamic stochastic equilibrium model related to an optimal investment portfolio and the effect of shocks such as productivity shocks and foreign exchange earnings’ fluctuation shocks on macroeconomic variables. To this end, we design a DSGE model with sectors of households and firms, government and the central bank, and calibrate the model’s parameters after logarithm–Linearization using seasonal data of 1996-2016 and results of empirical studies. In the designed model, households maintain a portfolio of stocks, cash, securities, and other assets based on risk and return or an optimal portfolio. In the end, we assess the impulse response function of economic variables to shocks of productivity and foreign exchange earnings. Ultimately, the comparison of the present moments in the current study and moments of real data indicates the relative success of the model with regard to the realities of Iranian economy.
Mr. Morteza Dehghandorost, Dr Hassan Heidari, Dr Sahar Bashiri,
Volume 22, Issue 2 (6-2022)
Volume 22, Issue 2 (6-2022)
Abstract
This research examines the macroeconomic variables reaction and banking sector with the financial and monetary shocks using dynamic stochastic general equilibrium model (DSGE). Considering the banking facilities and utilization of seasonal data for the period 1991-2017, the banking sector behavior in the economic dynamics is studied. Therefore, the linear-logarithmic form of the equations is obtained after specifying the model, optimizing, and extracting the first-order conditions. The model is simulated under two different scenarios by considering bank facilities as two types of capital facilities and working capital, and not considering the facilities. The results show that by occurring financial and monetary shocks, the instant reaction of variables is consistent with the theoretical bases of the economy, which indicates the acceptable ability of the model in accurately fitting Iran's economy. Furthermore, comparing the moments of the simulated variables with the real data, the success of the model in simulating the governing facts of the economy is confirmed. Finally, the results show that banking facilities could reduce the range of economic fluctuations and increase the stability of the economy. This issue can be mentioned by the economic policymakers in order to reach economic sustainable development.
Mr. Abdolreza Iesvand Heidari, Dr Mir Hossein Mousavi, Dr Saleh Ghavidel, Esmaeel Safarzadeh,
Volume 22, Issue 3 (9-2022)
Volume 22, Issue 3 (9-2022)
Abstract
The purpose of this article is to investigate the effects of macroeconomic variables such as exchange rate, interest rate, economic growth and real money residual growth on the financial stability in the Iranian insurance industry. For this purpose, Markov switching method is used. The ability to account for changes in the relationship between macroeconomic variables and the financial stability of the insurance industry over time is one of the most important features of the Markov switching method. The period under study is from the first quarter of 2005 to the fourth quarter of 2015. The results show that the effects of macroeconomic variables during the first regime (including the first quarter of 2005 to the third quarter of 2008) and the second regime (including the fourth quarter of 2008 to the fourth quarter of 2015) on financial stability of the insurance industry are different. So that the effects of exchange rate, interest rate and economic growth on the financial stability of the insurance industry in the first regime are the opposite of those of the second regime. This is while the growth of the real balance of money has a direct link to the financial stability of the insurance industry in each round of the regime, but in the second regime, which is a recessionary regime, its effect on financial stability is insignificant. Also, the findings show that the stability of the first regime is more than the second regime, so that if the insurance industry is in regime one in the previous period, with a probability of 94% it will be again in regime one.
Dr Leila Torki, Baran Mazaheri,
Volume 22, Issue 4 (12-2022)
Volume 22, Issue 4 (12-2022)
Abstract
Aim and Introduction
Financial sanctions have long been a powerful tool for countries to achieve their political goals and secure their interests. Countries usually apply economic sanctions when they intend to force the target country to change certain policies that are not acceptable to the sending countries. The impact of financial sanctions may be far beyond the scope of a country's economy, so that in addition to affect the economy, it can also have a negative effect on the politics, culture, and social welfare of the target country. Iran has always been under the pressure of many sanctions. Therefore, due to the many sanctions that have been imposed on Iran over the years, the concern of many economists has always been how these sanctions affect Iran's economy. The economic and legal dimensions of sanctions as well as their diversity make it difficult to evaluate the implications related to sanctions on macroeconomic variables.
By examining the studies conducted in the field of financial sanctions and their effects on economic variables, it was found that most of these studies had investigated the effect of sanctions on two or more macro-economic variables, However, in the present study, the most important macroeconomic variables are included in the model and analyzed. Another innovation that distinguishes this research from other studies is the research method used in this research, which has not been used in Iran for the subject under study.
First, the optimal interval of the model is determined using the Hannan-Quinn statistic, then the Bayesian vector regression model is estimated using the optimal interval, and then the effect of financial sanctions on the variables of the model is investigated. In order to create a comparative framework, the results of the Bayesian VAR model are analyzed, and the results of both BVAR and VAR models are compared. It should be noted that Eviews 12 and 16, Excel and Matlab 2021 softwares were are used to estimate the model and analyze the results and form the instantaneous response function.
Findings
After estimating the Bayesian vector auto-regression model with the SSVS prior, the results of the instantaneous response functions are as follows:
The effect of the shock on the variable of fixed investments is negative and decreasing. The effect of the shock on the price index variable of consumer goods and services is positive and increasing. The effect of the shock on the export variable is negative and decreasing. The effect of the shock on the import variable is negative and decreasing. The effect of the shock on the GDP variable is negative and decreasing. The effect of the shock on the variable of overdue loans to the private sector is positive and increasing. The shock effect in the monetary base variable is negative and increasing. The effect of the shock on the country's external debt variable is negative and increasing. The effect of the shock on the variable of the currency market pressure index is negative and increasing.
After estimating the vector auto-regression model, the results of the instantaneous response functions are as follows:
The effect of the shock on the variable of fixed investments is negative and increasing. The effect of the shock in the price index variable of consumer goods and services is negative and increasing. The effect of the shock on the export variable cannot be investigated. The effect of the shock on the import variable cannot be investigated. The effect of the shock on the GDP variable is negative and variable. The effect of the shock on the variable of overdue loans to the private sector is negative and variable. The effect of the shock on the monetary base variable is negative and variable. The effect of the shock on the country's external debt variable is negative and increasing. The effect of the shock on the variable of the currency market pressure index is positive and variable.
As it is clear from the results, the information obtained from the auto-regression vector model is very inaccurate and with high variance, and the reason for this is, as previously stated, the existence of many parameters and the reduction of the degree of freedom of the model, which causes the accuracy to decrease. The estimate as well as the dispersion function becomes instantaneous. But Bayesian models solve this problem by shrinking the model and increase the estimation accuracy. As it is clear from the instantaneous response functions obtained by this method, the graphs have less dispersion and are much closer to the middle line, and also by examining the results, it can be said that the results are consistent with experimental studies and predictions taken is closer.
Discussion and Conclusion
The lack of appropriate quantitative indicators has caused most of the studies related to the investigation of the effects of sanctions to be focused on the explanation of the channels of the impact of the sanctions on the economic environment. Sanctions affect various economic sectors such as trade, investment, employment and economic growth regardless of success or failure in achieving the ultimate goal. Therefore, for accurate policies in these areas, it is necessary to evaluate the exact amount of the effects of sanctions on these sectors based on quantitative models, along with the influence channels.
According to the results of the auto-regression Bayesian vector model with SSVS prior, financial sanctions have a negative effect on the GDP and cause it to decrease. With the decrease in the productive capacity of the economy, fixed investments also decrease. A decrease in economic growth causes a recession. A decrease in private consumption, private investment, and a decrease in economic growth can greatly strengthen the recessionary conditions, therefore, it is recommended that the government, while managing the budget, avoid excessive reductions in construction costs, so that by strengthening the effective demand in the economy, it can bring it out of stagnation.
On the other hand, financial sanctions reduce the country's exports and imports and increase the country's foreign debt. Therefore, it is suggested that the import of luxury goods, which have a high value, should be put on the agenda in the conditions of prohibited sanctions and self-sufficiency in the production of some imported products. Besides, increasing the diversification of export goods can partially compensate for the decrease in exports. In this case, the policy of supporting domestically produced goods and export-oriented goods is recommended.
Since financial sanctions increase the pressure index of the currency market, it is suggested to prevent the entry of luxury goods and to put autarky in the production of these goods. In this regard, the creation of knowledge-based companies and the creation of career guidance and specialized employment offices in universities and the policies of training human resources in the specialties needed by society should be included in the goals of the country's vision.
Dr Parviz Davoodi, Dr Mohamadreza Sezavar,
Volume 22, Issue 4 (12-2022)
Volume 22, Issue 4 (12-2022)
Abstract
Introduction:
All economists believe that the most important goals of economic policy are achieving full employment, price stabilization and economic growth in the society. On the other hand, rendering the formation of the exchange rate to the market mechanism and increasing it disproportionately with the purchasing power of the rial has a negative effect on production and employment and causes an increase in prices and a decrease in the value of the national currency, which again provides the ground for the next increase in the exchange rate. For this purpose, in most societies, especially in developing countries, currency policies are used to achieve the mentioned goals. Changes in exchange rates affect economic performance in different ways. In this study, we will examine the effect of exchange rate changes on the performance of important macroeconomic variables, namely production, employment and the general level of prices. Taking into account the effects of sanctions against the country, the model considers the mechanism and channel of its effect on the foreign sector of the economy, while creating an index with monthly frequency for it, and its effect has been calculated directly on all macroeconomic variables of the foreign sector of the model.
Methodology:
During the last two decades, tremendous developments have taken place in the field of modeling time series variables and predicting the future values of economic variables, one of which is to specify and estimate equations where the variables involved in that equation, unlike usual, have different frequencies. Mixed-data sampling (MIDAS) has been specified and estimated with the help of time series data over the period 1959-2017. Mixed data sampling regressions are now commonly used to deal with time series data sampled at different frequencies.
A MIDAS regression is a direct forecasting tool which can relate future low-frequency data with current and lagged high-frequency indicators, and yield different forecasting models for each forecast horizon. It can flexibly deal with data sampled at different frequencies and provide a direct forecast of the low-frequency variable. It incorporates each individual high-frequency data in the regression, which solves the problems of losing potentially useful information and including mis-specification.
Results and Discussion:
The presented macro econometric model is developed in the framework of the aggregate supply-aggregate demand model. Total demand is made up of household consumption expenditures, investment expenditures separately from private and government, government current expenditures and net exports. The production function forms the supply side of the economy according to the utilization rate of the production capacity. The modeling of the two parts of supply and demand has been done in a completely consistent manner, so that after the estimation of the model, it is possible to solve and simulate the model to examine the effect of economic policies and predict macro variables. According to the results of the model, in relation to the policy of devaluation of the national currency in the Iranian economy, the increase in the exchange rate in the face of sanctions, in addition to reducing production, paves the way for employment and inflationary pressures. Indeed, The incorrect approach of increasing the exchange rate has not only limited economic growth due to the increase in production costs, but has also caused the impoverishment of the oppressed and the unfair distribution of income in the society.
Conclusion:
Because the model under study has better explanatory power than other time series models due to more complete information, it is expected that it will be possible to evaluate exchange rate policies more accurately. The model has sections on production, consumption and investment expenditures, foreign trade, government, employment, money and prices. In addition, according to the very good results obtained from the dynamic simulation of the model, the model can be a good representative of the mechanism of the Iranian economy. Finally, the results of the evaluation of foreign exchange policies in the context of sanctions can be reviewed.
Mr. Karami Karami Ardali, Dr Hussein Marzban, Dr Ali Hussain Samadi, Dr Amin Nazemi,
Volume 23, Issue 2 (5-2023)
Volume 23, Issue 2 (5-2023)
Abstract
Aim and Introduction
The development of financial markets is critical for economic growth. One of the most important financial markets is the capital and stock market, where the prosperity of the stock market and financing through the stock market can develop any country's economy. Capital market development requires the efficient performance of financial intermediaries, including mutual funds. Iran’s economy has always faced the problem of insufficient liquidity and financing for production sectors. As a financial tool, mutual funds can moderate this problem with their existing potential. Therefore, the study aims to investigate the probable effect of mutual funds on economic growth.
Methodology
In the previous studies that have been done in this field, the descriptive-analytical aspect of the subject has been discussed. But these studies didn't provide an appropriate framework for analyzing the effect of mutual funds on economic growth. For this purpose, in the present study, based on the theoretical literature, a general equilibrium model has been designed, and the output of this model is obtained according to the optimization of different sectors of the economy. Assume a closed economy where mutual funds are investors with information and allocate capital to high-productivity firms. The economy has a single period with two production components, a representative mutual fund, and a representative household. We assume a high-productivity firm (H) and a low-productivity firm (L) with an equal number of producers. Both firms can obtain funds by issuing new stocks in the primary market. There is one representative mutual fund in the economy that can invest on behalf of the representative household. Therefore, the fund can invest as much as the fund flows (F) received from the household at the beginning of the period. We assume the mutual fund has sufficient access to information and production technology and can detect high-productivity firms. The household seeks to maximize utility, and the proposed utility function consists of only consumption. As utility and consumption are positively related, utility maximization is equivalent to consumption maximization. However, since the present study adopted a single-period economy, consumption equals income. Thus, maximum utility is represented by maximum income. Initial capital (W) can be directly invested in the primary market or indirectly invested in the secondary market by the mutual fund. This framework is a new aspect and the main contribution of research in this field. The output of the model is estimated using the GMM method for the period 2010:2 to 2020:4.
Findings
According to Table 5, most coefficients are statistically significant. The first lag of GDP was expectedly found to have a positive, significant impact on the GDP level and, thus, economic growth. Mutual fund investment was observed to have a positive, significant impact on GDP; a 1% rise in fund investment, on average, leads to a 0.473% increase in GDP. This finding is consistent with our theoretical framework. We expect mutual funds’ investments in the primary market, positively impact GDP since mutual funds have an information advantage over individual investors. Thus, they can optimally allocate resources to high-productivity firms (i.e., mutual funds have a higher ability than individual investors to identify high-productivity firms in light of their information advantage). The household wealth coefficient was estimated to be 0.255, suggesting that a 1% increase in the household’s wealth raises GDP by 0.255% on average. This finding is consistent with economic theories. The interaction of wealth and fund investment was estimated to have a coefficient of 0.257, implying a significant relationship. This coefficient was expectedly found to be positive, consistent with modeling. The interaction of fund flows and fund investment significantly affects GDP with a coefficient of -0.174. This coefficient was expectedly found to be negative, consistent with modeling. Fund flows were estimated to have no significant impact on GDP. Although it was found to have the expected sign, it has an insignificant impact on GDP and thus cannot be interpreted. The coefficient of the secondary market return was found to be significant only at a confidence level of 90%.
Discussion and Conclusion
Overall, mutual funds have a positive impact on GDP. These funds may improve the performance of Iran’s financial markets if they acquire an appropriate position in the financial market. A large number of individual traders have begun to trade on Iran’s stock market without financial knowledge and suffered massive losses in 2020-2021. If the mutual fund sector is active in Iran, in addition to the optimal allocation of resources, it can also help people for investment in the stock market and prevent crises such as 2020-2021. Eventually, the policy recommendation is that policymakers pay more attention to the development of mutual funds in short- and long-term policies.
Keywords: Mutual fund, Capital market, Economic growth, Primary market, GMM
JEL Classification: G11, G23, G51
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