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Technological advancements have transformed the payments industry. In the competition between banknotes and alternative instruments such as debit cards and mobile payments, the question of Central Bank Digital Currency (CBDC) has emerged in recent years and sparked much debate. This research examines the factors influencing public adoption of CBDC in two parts. From a macroeconomic perspective, demand for money encompasses the demand for the various functions of money—such as a means of payment and as a type of asset. Drawing on conventional theories of money demand, we analyze this demand over the long term. Since CBDC is essentially fiat money with characteristics similar to physical currency, but does not compete with cash due to the latter’s unique features (e.g., anonymity), it serves as a better substitute for demand deposits. With this view of CBDC, the findings related to demand deposits can be attributed to CBDC demand. In this study, using data on the number of point-of-sale (POS) terminals, debit cards, and ATMs, a logistic model is estimated to calculate a digital development index for Iran’s economy. One key result is the positive and significant effect of this digital development index on demand for demand deposits (as a proxy for CBDC demand), and its negative and significant effect on demand for banknotes. In the second part, CBDC is examined as a payment instrument. Here, the factors influencing CBDC adoption are categorized into four groups: technological, demographic, financial-economic, and operational.

Military expenditure is a key variable in various economic growth models, and its effects can vary depending on different conditions. However, there is no general consensus regarding the relationship between defense spending, economic growth, and other macroeconomic variables. Considering the significance role of defense expenditures for ensuring of a nation's security, it is essential to examine its impact on various economic sectors. This study aims to explore the relationship between defense expenditures and macroeconomic variables in Iran over the period 1980-2022, using the vector autoregression (VAR) technique and the Toda-Yamamoto causality test. The analysis examines the relationship between defense spending and several key economic variables, including economic growth, inflation, trade balance, employment, and imports. The results obtained from the causality test point towards a bi-directional causality between defense spending and economic growth, whilst, on the other hand, a uni-directional causality exists from defense spending to employment. The study did not find a causal relationship between defense expenditure and trade balance, inflation, or imports. Additionally, the reaction functions indicate that a positive shock in military spending can lead to an increase in economic growth, imports, and employment, whilst causing a decrease in inflation and trade balance in subsequent periods.

The abundant and numerous uses of steel in various industries have turned it into a strategic commodity, and its price has always been a concern of industrial owners. Therefore, access to accurate forecasts of the price trend of steel and its products is important. Therefore, in the present study, while identifying the determinant variables for the price of steel, an out-of-sample forecast for 2023:10 to 2024:06 has been made using the vector autoregression (VAR) model. At first, the results of the Johansen-Juselius cointegration test confirmed the long-term relationship. Also, the error correction coefficient (ECM) was -0.0842. We analyze impulse response functions. The unofficial exchange rate, and industrial producer price index (base metal manufacturing sub-group) (respectively with a positive effect of 6.8% and 6.5% percent in the standard form) have been more effective than other model variables on the fluctuations of steel price. In addition, the results of variance decomposition showed that the industrial producer price index (16.18%), and unofficial exchange rate (11.7%) after the price of steel itself had more effect on the price fluctuations of this product than other variables. Finally, we estimate the out-of-sample forecast. The price of steel is forecasted from 302,445 Rials in October 2023 to 321,552 Rials in June 2024 (with a 5% increase). Based on the forecast evaluation criteria, our model can accurately forecast the price trend of steel. According to the results, the most important policy recommendations include updating the technologies, equipment, and machinery used in the production of steel products to develop the production of steel products, saving energy consumption and production costs, adopting appropriate monetary and foreign exchange policies, And increasing exports by focusing on marketing and sales of steel products (to prevent raw sales), through the development of production, increasing the variety, quality, and durability of manufactured steel products can be provided

Examining the transfer of returns in the markets helps analysts to identify the reasons for the movement of liquidity ratio between the markets. In this study, the monthly data of the gold market price index, housing, stock exchange and the currency has been used in Iran for the past twenty years. Investigating the interactions between price returns The stock market, housing, currency and gold market and understanding the relationship structure between these markets based on liquidity ratio in the given period is one of the studies in this article. According to the significance of the variables of the VAR model with five variables; We will use the gold market price index, currency, housing and stock exchange and the liquidity ratio. The results of the causality test show that the returns of the housing market and the stock exchange are related. Based on the results of analysis of variance, the effect of the liquidity ratio in the long run on the stock market and the gold market is greater and less on other markets. The effect of foreign exchange market returns on all variables is positive. The effect of stock market returns on the liquidity ratio is more than other variables.

In monetary and financial literature, financial crises include a wide range of crises. But in general, there are three important types of financial crisis, including the currency crisis. The banking crisis and the debt crisis. The aim of this study is to simultaneously analyze the occurrence of banking, debt and currency crises, known as the three crises in Iran. For this purpose, first to determine the indicators related to banking crises, currency and debt payments and using logistics and self-regression vector models during the 1980 to 2017 seasonally, we have discussed the relationship between these three crises. The results show that the three banking crises, debt and currency, affect each other. The short-term results of the VAR model showed the effect of the banking crisis and the currency crisis on the debt crisis is positive and significant, indicating an increase in the likelihood of a banking crisis and the currency will increase the debt of the government and the country. Also, the effects of banking and debt crises on the currency crisis are positive and significant. This indicates the existence of causal relationship between banking crises and debt on the currency crisis. The results of the Logit model show that the effect of inflation variables, liquidity growth and the growth of the exchange rate on the indicators of the three crises that are significant and positive in most models.

Financial Stress Index as a measure of a systemic risk that quantify stress throughout the entire financial system and describes the contribution of each section of the financial market to the overall stress of the system. In this paper, a composite index for measuring the stress of the Iran’s financial system proposed using a portfolio approach. This indicator is a combination of stress variables in different parts of the Iran’s financial system (stock market, debt market, banking sector, money market and exchange rate market). To aggregate these variables, EWMA, dynamic conditional correlation (DCC-GARCH) and BEKK-GARCH used to examine the cross-correlations structure between the subindices during the period of March 2010 to March 2018. In the end, to determine which of the stress indicators designed for the financial system of Iran is more desirable, the results of the prediction of the VAR model used to explain the changes in GDP. The results of the comparison of the prediction criteria showed that differences in the performance of these indices are not significant, although the stress index produced by BEKK-GARCH method performed better and in comparison with the other two methods used to estimate subindices cross-correlation, better explains the changes in the economy activity.

The purpose of this study is to study the financial interactions between financial markets of selected financial partner of Iran, including China, France, Germany, Italy and the UAE. For this purpose, the VAR model has been used. Financial risk data is collected annually (from 1984 to 2017). The results indicated that there was a positive and two-side relationship between the financial risk fluctuations between Iran and China, the UAE and Italy, the United Arab Emirates and China during the period under review. In addition, financial risk aversion was observed one- side from Iran to Italy and the UAE to France and China to the UAE. Also, financial risk aversion from Germany to China, Iran, Italy, and the United Arab Emirates was seen one-side, in other cases, there was not Fluctuation overflow. Ultimately, it could be said that Germany was only country affected by risk of the other countries.

This paper investigates the role of the central bank and monetary policy in the occurrence of the business cycles in Iran’s economy. This is important since the effects of monetary policy on the business cycle and its dynamics are the main stage in understanding the role of financial markets in the economy. Therefore, in this study, using the quarterly data from, 1999-2013 the cycles in GDP and liquidity have been elicited (with the help of economic filters); then, using vector autoregressive model, it is shown that fluctuations in liquidity are leading the fluctuations in production.
The most important and crucial issue among modern economics is the existence of commercial cycles or economic fluctuations. The emergence of such business cycles, which in many cases caused problems for the economies and created a period of unintentional inflationary or recessionary events which could itself lead to other adverse economic conditions. Consequently, it seems the study of this phenomenon and the causes of its creation as well as finding options to deplete those problems are the most concerning issues of economic policies in every country. Commercial cycles are fluctuations which are defined in terms of frequency periods of boom and recession. Economic activities usually consist of two stages, recession and boom. When production and employment decrease and lead to poverty, they reduce the welfare and lower the living level of people; hence, it means that economic activities are in recession. Additionally, when production and employment rise, it brings about welfare and increases society’s living quality; this means economic is about to get better or boom. Although, these cycles occur frequently, none of two cycles are similar to each other. During later decades recognition of causes, predictions and economic fluctuations are the most important issues of macroeconomic and policy making economists. Among commercial cycles, usually parameters like production, employment, real income and real sale level decrease and increase together. On the other hand, some economic parameters before empowering a cycle are considered as pioneer indices, which indicate the existence of an economic cycle in future. Among these parameters, we can name those that are cooperating in changing of money, credits, crucial prices, order volume in production parts, personal contracts, number of started buildings and number of working hours. It can be said that, a group of economists believe that economics essentially has a problem which for some reasons will lead to commercial cycles. On the other hand, another group of them believe that some external intruding will lead to the creation or at least increase of these cycles. According to the second group, economics essentially has stability and since the external intruding of government, banks, and other sources do not exist, economics will not experience any commercial cycle, and as a result, the essential and crucial question is whether it is possible to get rid of the cycles.
Generally, we can study the reasons of growths in real volume of country’s economic activities in two aspects of changes in demand and supply. The considerable point is that, the existence of stability in a country’s economy could be useful in various aspects and essentially one of the duties of governments and planning systems is providing economic stability. Thus, with the recognition of fluctuation’s structure and cycles in economy, we should try to control and decrease the intensity of them. Severe economic fluctuations or cycles are natural, and instability growths in economy, households, and economic firms cannot make a bright prediction of future. In times of recession or moving towards a recession, unemployment has increased and production has declined, and some production units may even be out of business and prices are falling. What is important is to know what initially creates prosperity and then, after a period of economic activity, it will lead to slowdowns and stagnation. In other word, it seems that in economic cycles we must look for the reasons of appearance, duration, and power of these fluctuations. There are various theories and reasons which lead to commercial cycles in macroeconomic literatures. Some of these theories say that the origin of fluctuations and commercial cycles is in policies of the demand side. The theory of Keynesians, the monetary (Chicago School), and the theory of rational expectations and its subcategories, including the new classics (monetary branches) and the new Keynesians, are among these theories.
According to some theories, commercial cycles are related to supply spectrum theory. One of these is the Real Commercial Cycle Theory (RBC), which argues that fluctuations and business cycles are explained by the volatility of real variables in the economy . Whether the central bank can pursue active economic stabilization policies and, on the other hand, whether anti-cyclical monetary policies can be effective in controlling business cycles is a great help for economic policy-makers and policy makers. The answer to these questions will be very helpful to economic regulators and central banks’ policy makers. Consequently, it seems that the recognition and understanding of commercial cycles will be the first step in retrieving the role of central bank, and as a result, they will be considered in designing stability policies.
Based on the obtained results, on average, 23 periods are observed, with peak periods, the rate of liquidity change was about 9 months (6 months) from the peak of the level of economic activity.   Variance Dissection (VD)
The results of the dissection of variance in Table 10 show that in the short term (about three cycles ), the explanatory power of the growth of government expenditures from periods of stagnation and boom is higher than the explanatory power of liquidity growth, but, in the medium and long term, liquidity growth has a greater potential for expanding business cycles and periods of recession. In this paper, we tried to answer the above question using a theoretical explanation and designing a self-regression vector (VAR) model in order to analyze the experimental effect of this relationship. Based on the results, it is found that, on average, using 23 cycles, the peak of interest rates was about 9 months away from the peak of economic activity. This could indicate that fluctuations and changes in the rate of liquidity growth as an indicator for monetary policy in the Iranian economy are one of the factors that trigger business cycles in Iran's economy. To evaluate the dynamics among the model variables, the action-response functions were used. The results reflect the negative reaction of the business cycle to inflation. In other words, the inflation rate has a positive and significant effect on the duration of the recession, so by increasing it by one percent, the length of the recession or the risk of withdrawal from this period will be reduced. Therefore, with rising inflation, the length of the recession in Iran will increase

The economy of Iran has witnessed a couple of booms and busts in housing prices over the period of 1981(1)-2014(4). Since the fluctuations in housing prices affect household wealth, and consequentially, total consumption, saving and even banking, it is of crucial importance to analyze the impact of such fluctuations on real economy. This study, utilizing the MSIAH -VARX model, examines booms and busts in housing prices in Iran over the aforementioned period. This approach offers the possibility to identify different regimes in Iran’s housing market. Moreover, the probability of staying in one regime as well as that of transition from one regime to another could be estimated. The findings indicate that during the aforementioned period, there are two regimes of boom and bust in housing prices. Furthermore, the probability of staying in a bust regime is greater than that of a boom regime.

With due attention to distinguished role of oil in Iran’s economy, it is important to analyze oil market shocks on Iran’s economy. Based on various studies results and because of eliminated variables bias in VAR models, valuation of impulse response functions led to wrong results; such as price dilemma problem in empirical literature. In this paper, for more exact analyzing the effects of oil income growth shocks on Iran’s economy, we substitute VAR model with constant coefficients by TVP-VAR models during 1988 - 2012 period. So, variables such as industry and mine value added, informal exchange rate, inflation rate, government’s real consumption expenditures growth, real imports growth, real oil income growth and oil market shocks are used in the model. The results show that the relation between variables is time variant and depends on economic situation. Furthermore, real oil revenues shocks have positive effects on real imports and governments real expenditures costs. Beside this, these shocks have negative effects on industry and mine value added and it could be a sign of Dutch disease, and it is not a suitable condition for an economic. So the policy makers should choose a consistent substitute for oil revenues such as tax revenues and policies.

The Survey of relationship between the exchange rate and domestic price levels, that has been known as “exchange rate pass-through” in international finance literature, have been one of the key issues in the field of international economics in recent decades. Exchange rate pass-through is defined as "percentage change in the domestic price of imported goods for every one percent change in the exchange rate between the exporting and importing countries”. In this study we examined the positive and negative exchange rate shocks on Iranian inflation rate and other macroeconomic variables during the period from 1339 to 1392, and in the context of a VAR Approach. The results indicate that the reaction of inflation rate to positive exchange rate shock (devaluation of the national currency and increasing the nominal exchange rate) is much more of a negative shock (increase the value of the national currency and decreasing the nominal exchange rate) is. In other words we can say that the degree of exchange rate pass-through in the event of a positive exchange rate shock is more (complete). The analysis of variance decomposition also shows that the sensitivity of inflation to the increase in exchange rate (devaluation of the Rial), is far more than reducing it (strengthening the Rial). The average explanatory of inflation by positive exchange rate shock in different periods is 4.1 percent, while for negative shock is 1.8 percent.

Oil revenues play an important role in the political economy of Iran. In this study we analyze the asymmetric effects of oil price shocks on government expenditures and investment for the period of 1978-2008. We Apply the VAR model and impulse response functions (IRFs). The main result shows that oil shocks have asymmetric effects. It means that the effect of negative shocks on government expenditures and investment is larger than positive shocks. The results show that oil shocks have asymmetric effect on government expenditures and confirm the existence of Dutch-Disease and high dependency to oil revenues in Iranian economy. The use of stabilization and savings funds and diversification of the revenues of oil sector seems crucial to minimize the harmful effects of oil booms and busts.

GDP growth rate as a measure of economic progress is estimates on the basis of national accounts. Since the national accounts are recorded regardless of natural resource depletion، by estimating depreciation in the oil، gas، coal and other parts of the environment، depletion of natural resources can be accounted for which will provide the access to green GNP index. Green GNP shows increased economic growth stability. Among all natural resources، oil is the most important source of revenue for oil exporting countries and fluctuations in its price is a major factor for economic crisis in both the oil-exporting and importing countries. The main purpose of the present paper is to examine the impact of oil price shocks on green GNP. For this study، the first oil price shock are calculated using hoodrick - Prescott Filter method and then the effects of oil price shocks on green manufacturing was estimated using self regressing pattern. Based on the estimation results in the short term، oil price shocks have a negative impact on the green production. This is due to the oil extraction، depletion of natural resource is increased and it leads to decreasing the green production، and it has negative impact on green production in the long-run because an increase in oil production will lead to real growth of other sectors so that this growth offsets the depreciation.

Oil shocks have always had different effects on the oil exporting and importing countries. It seems that these effects have modified during the last four decades. In other words, the effects of the oil shocks of 1970s on the industrialized economies of the oil importing countries have been mostly followed by an overwhelming stagflation, although such severe effects have not appeared after the oil shocks of 1990s. In this paper, with the use of Autoregressive (VAR) model, the attempt is to investigate the critical effects of oil shocks on some oil exporting countries like Iran, Venezuela, Nigeria, Norway and Canada. Based on impulse response functions in these countries, we will arrive at the conclusion that just in Norway and Canada, the effects of oil shocks on growth rate, inflation and real exchange rate have been decreased. In this case, the paper will argue that the role of exchange rate systems, monetary policies and different macroeconomic structure of these countries have caused milder effects of oil shocks in 1990s.