فصلنامه راهبرد اقتصادی
پیاپی 34 (پاییز 1399)

In recent years, electronic banking and the use of electronic payment tools have expanded, and this has led to changes in monetary variables that can have many economic effects. In this regard, in this study, the effect of electronic banking on selected economic variables in Iran has been investigated using modeling and simulation of system dynamics. The designed model includes two parts, monetary and real, which also includes electronic banking. After simulating and validating the model, in the form of designed scenarios, the effects of electronic banking on economic variables are investigated. The results of applying different scenarios showed that the increase of ATMs has reduced the volume of liquidity, price index, capital accumulation and production and the increase of sales terminals has increased the mentioned variables. Simultaneous increase in ATMs and sales terminals also increased liquidity and price index and had no effect on capital accumulation and production. The results also showed that in this case, increasing the volume of legal reserves as a control policy can neutralize some of the effects of these instruments on liquidity.

Unemployment rate is one of the economic indicators that has always been considered by policy makers and economists. Numerous factors and economic variables affect this index. Given the economic conditions of Iran as an oil exporter and the imposition of economic sanctions as well as the Islamic banking system, it is necessary to study the impact of oil prices and interest rate as two key variables. In this study, in order to investigate the effects of oil price changes and interest rates on employment, the linear autoregressive distributed lag (ARDL) of Pesaran et al. (2001) and the asymmetric nonlinear NARDL model of Shin et al. (2013) were used. Asymmetry in the nonlinear model is represented via positive and negative partial sum decomposition of oil price and interest rate. ARDL suggests that although oil price and interest rate changes have minor short run effects but they have significant long run effects in all the cases. The NARDL model presents a different picture of the effects of changes in oil prices and interest rates on the unemployment rate. While in the short run, the changes of oil price have no effect on the unemployment rate and only changes in interest rates affect it, in the long run, in addition to interest rates, rising oil prices also affect the unemployment rate. The results of the study show that in the short and long term, falling interest rates have more effects than increasing it and increasing oil prices have more effects than reducing it.

The main objective of this study is to answer this important and basic question whether demand management policies can affect the energy consumption in Iran economy or not? Energy consumption management policies will be effective only if the energy consumption time series contains a unit root or in other words if it is nonstationary. The main problem with conventional unit root tests like ADF, … is that when there is a structural break or nonlinearities like asymmetric adjustment in the underlying series these tests can result in incorrect results. Consequently, in this paper instead of conventional tests like ADF we have used three alternative tests including Zivot and Andrews (1992), Lee and Strazicich (2003) and Kapetanios et al. (2003). The first two, incorporate structural break in unit root test and the latter assumes nonlinear exponential smooth transition autoregressive (ESTAR) process as an alternative in the unit root test. In this paper we have used annual data for per capita energy consumption (in Residential, Industry, Transportation, Agriculture sectors and overall economy) over the 1967-2016 period. The results show that the energy consumption in Residential sector is stationary which means that the energy consumption management policies have no permanent effect on energy consumption in this sector. On the other hand, based on ZA, LS and ESTAR test results, the energy consumption in the Industry, Transportation, Agriculture sectors and overall economy are all nonstationary and shocks to energy consumption have longrun and permanent effect in these sectors.

In this paper, we examined the effects of financing on various activities of Iran’s economy using an input-output table. To this end, the input-output table of 2017 used and by applying modern methods of input-output analysis, the relationship between financing activity and other activities measured. In the new approach, hypothetical extraction and field of influence approaches were used, from which we find different results. For the hypothetical method, the results indicated that banking and financial institutions have the greatest impact on themselves. After that, in the second level, the non-residential construction activity and in the third level, the administrative and supportive activities are affected by the banking finance. However, the results of the field of influence method indicated that the banking activity has the most influence on the wholesale and retail activity, and the strength and weakness of financing, make more changes in this activity. After that, in the second level, the manufacturing of chemical materials and products is located. In the third level, the crude oil and natural gas extraction lies in the ranking of the field of influence.

Choosing the best method of financing about projects is the most important factor in industries functions. Nowadays global economics’ general constraints, fiscal resources scarcity and non – optimum method of allocation in resources had appeared the necessity of introducing new titles in finance. Since bitcoin was introduced, theorists began to studying the feasibility of designing and establishing new financing patterns on the blockchain platform and the use of cryptocurrencies. The establishment of platforms based on blockchain and its replacement with existing mechanisms will have undeniable effects on reducing operating costs and enhancing transparency in various industries and businesses. This research, focused on the upstream sectors of the oil and gas industry. The results show that the use of emerging blockchain technology capabilities, provides the possibility of using new generation of international financing method using cryptocurrency. The oil-backed cryptocurrency is the main crypto asset in this framework. This cryptocurrency's value is equal the barrel of crude oil.

The mechanism of money creation and other inflationary measures of central banks, which often prefer the short-term interests of governments to the rationality and long-term stability required by the market, are among the most important reasons for the new monetary system architecture and the widespread acceptance of cryptocurrencies such as Bitcoin in the last decade. In this paper, we solve a DSGE model to investigate the impact of Bitcoin encryption on the money demand and seigniorage. To do so, the data of seasonal time series 1989 to 2018 have been used. In the model designed in this study, it is assumed that due to the use of money cryptocurrencies, the government revenue from money printing decreases; This will lead the government to reconsider the price of the energy (especially the energy used to extract cryptocurrencies) and supply it at the price that maximizes its profits. In this study, the shock caused by the price and the volume of Bitcoin transactions is considered as an indicator for the demand of cryptocurrencies. Our main finding is that as the demand for cryptocurrencies increases, the demand for the formal money decreases, the inflation decreases, and consequently the seigniorage revenue decreases. The results also indicate that the shock to the cryptocurrency from the channel of changes in the energy prices will compensate part of the government revenues, although in the long run the welfare effects of this policy have been significant.