mostafa omidali

Factors such as expectations, lack of financial flexibility, the existence of uncertainties in the economic environment and other economic and non-economic indicators have an impact on the creation of business cycles. The large volume of government activities in Iran's economy indicates that the government has a fundamental influence on the stability and instability of business cycles in Iran. The purpose of the present study is to investigate the relationship between financial shocks and commercial periods of the Iranian economy during the period 1981-2021. First, by using Hadrick-Prescott filter method, business cycles of Iran's GDP are extracted, and by using VAR model, the causality relationship between financial shocks and business cycles is studied. The research results show that Iran's economy has experienced five periods of recession and five periods of prosperity during the studied period. These courses are symmetrical in terms of length and depth. The results of the VAR model show that there is a two-way causality relationship between the government expenditure shock and the tax shock with the business cycles of GDP. Therefore, the economic prosperity can reduce the financial shocks of the government and subsequently improve the budget forecast and reduce the budget deficit.

Factors such as expectations, lack of financial flexibility, uncertainties in the macroeconomic environment and other economic and non-economic indicators are influential in creating business cycles, none of which alone creates business cycles. The purpose of this study is to investigate the relationship between economic, financial, political and international risks with the economic business cycles of Iran during the period 2001-2009. To achieve this goal, the long-run trend will be separated from the cyclical GDP trend using the Hadrick-Prescott filter, and the data will be analyzed using the Structural Vector Distribution (SVAR) model. According to the results, the average of one business cycle in the Iranian economy is equal to 10 seasons, which are equal to 5.45 and 5 seasons for the recession and boom period, respectively. Economic risk of -0.354 percentage has immediate effects on the business cycles of the Iranian economy, which for financial risk, international risk and political risk, the figures show -0.315, -0.0031 and 0.0048 percentage, respectively. According to the Granger causality test, the two variables of economic risk and financial risk are the cause of business cycles in the Iranian economy, while political and international risks are not the cause of business cycles. Economic risks in the first period with an impact of about 6% have the most explanatory effect in creating business cycles of GDP, after which financial risk has the greatest impact on business cycles, on the other hand, political risks among the studied risks have the least impact on cycles.

Goal: Electricity consumption in Iran was reached to historical level of 255,724 million kwh in 2017 which shows 7.7 percent increase compared to the year 2016. Considering the dramatic increase in electrity use mainly due to population growth, urbanization, economic and industrial development, providing a better picture of the future electricity demand for policy makers seems necessary. In addition, specification of the most important variables and their effects on the electricity demand would help policy makers to decide which policy instrument, such as price or non price policies, to choose in order to manage electricity demand.
The aim of the present study is to propose and estimate per capita electricity demand function in Iran and forecast electricity consumption over the next 15 years (2015–2029).
To do so, via a dynamic partial adjustment model (DPAM), we first estimated the per capita electricity demand function using historical data over the years 1981-2014 to see the long term and short tem effects of independent variables such as real per capita gdp, real electricity price, real natural gas price as an alternative fuel, and population on electrity demand. Then based on estimated values of the independent variables from an ARIMA model in the hybrid dynamic partial adjustment and ARIMA model, we predicted the electricity consumption up to the year 2029. We used Augmented Dickey-Fuller test to check the unit root in the time series data and we found that none of the variables were stationary and we could not reject the null hypothesis at 5 percent statistical signigficance level. However, the first difference of the variables were stataionary at 5 percent level. We also did Engle-Granger and Cointegrating Regression Durbin Watson (CRDW) Tests and the results show that cointegration exists among the variables.
According to the results, short-term and long-term price elasticities of electricity demand are -0.014 and -0.026 percent respectively which indicate that electricity demand is inelastic with respect to price changes, thus electricity price increase would not lower electricity demand. Moreover, income elasticities both in short-run (0.192) and lon –run (0.36) had much higher effects on electricity demand. Among the independent variables, per capita gdp with coefficient equal to 1.47 had the strongest effect on the electricity demand. Finally, our estimation shows that the cross price elasticities in shor-run and long-run are 0.006 and 0.011 respectively which show that one percent natural gas price decrease would reduce electricity consumption less than one percent. Overally, these reults revealed that price policies are not effective to manage electrity demand.
Based on AIC and SBC criteria, we found that ARIMA (2,1,1), ARIMA(1,1,1), ARIMA (2,1.2) and ARIMA (2,1,2) are appropriate to predict per capita GDP, real electricity price, population, and real natural gar price repectively.The results from the hybrid dynamic partial adjustment and ARIMA mode also show that the average annual growth rate of the electricity consumption per capita between 2015 and 2029 was 2.03 percent and the electricity consumption in 2029 will be 4134.7 million kwh which is 45 percent higher comparing to the year 2015.
To test the credibility of our prediction, we compared the historical figures of per capita electricity consumptions with the predicted numbers by our hybrid model over the years 1981-2014 and realized that the average deviation of the prediction was only 1.3 percent which is in the range of acceptable error level.
To cope with this predicted electrity demand, appropriate energy policies including planning to increase electricity production and/or managing electricity demand side must be designed and implemented. Examples of such policies in supply side would be more investment on power plants and their productivity improvement. On the demand side, non-price policies such as consumers educatios and providing better coversion technologies like more energy efficient appliances to consumers are adviced.

The aim of this study is to estimate the domestic balance of natural gas per capita in the Iran, as well as its forecast for the period 2017 - 2037. In this study, with employing dynamic models Autoregressive Distributed Lag (ARDL), at first, long-term and short-term elasticity of per capita natural gas demand in Iran for the period 1981-2016 is estimated. Then with using a hybrid ARDL and ARIMA model, we predict the balance natural gas per capita up to the year 2037. The results show that amount of per capita natural gas demand will reach 4177.36 million cubic meters in 2037, as well as the amount of per capita natural gas supply will reach 3417.26 million cubic meters in this years. For responding this excess demand should be adopting policies to increase production or constrainting natural gas demand.

Isobutanol produced from the fermentation process has a low concentration and needs to be concentrated and purified for use in different applications. There are many separation processes for isobutanol recovery from the fermentation broth. A hydrophobic pervaporation process was employed to separate isobutanol from its dilute aqueous solutions. For this purpose, composite poly dimethyl siloxane (PDMS) membranes with various active layer thicknesses were used for the recovery of isobutanol and the effect of some operating parameters such as membrane thickness, feed concentration and feed temperature on the separation performance of pervaporation was investigated. The results indicated that the permeation flux and isobutanol selectivity increased by an enhancement in the feed concentration. For example, by increasing the isobutanol feed concentration from 2 to 5%wt., the total flux and membrane selectivity enhanced by more than 50%. When the membrane thickness varied from 2.3 to 12.9 μm, the permeation flux was reduced by about half, but the selectivity increased more than 2 times. Also, higher temperature led to higher permeation flux, while the selectivity decreased with an enhancement in the feed temperature.