فهرست مطالب سیاب ممی پور

Pricing gasoline and optimal allocation of resources have always been topics of interest for governments and experts. The increasing jump in the exchange rate has created a significant difference between the nominal and real prices of gasoline. Therefore, in the present study, a solution is proposed to narrow the existing gap by introducing a floating tax proportional to gasoline consumption, and its effect on household income distribution is examined. On the other hand, the regressive feature is a weakness of the consumption tax system that leads to undesirable effects on income distribution by imposing a higher tax burden on vulnerable classes. Therefore, the proposed scenario in this study is similar to the current pricing system and is in the form of two-tiered rates (quota-based and non-quota-based rates). The quota-based section is exempt from taxes and is similar to the past procedure, while the non-quota-based gasoline price is calculated based on individuals' consumption, considering a 5% tax for each liter of consumption exceeding the monthly quota. If the consumption increases, instead of receiving more subsidies, the higher expenses will accompany the consumer. In this regard, by using an almost ideal demand system model, the effects of implementing the proposed scenario on inequality and income distribution among urban households were studied, and categorized into four gasoline consumption groups (less than 60 liters, 60 to 80 liters, 80 to 120 liters, and more than 120 liters) during the years 2017-2020, considering some demographic variables such as household size, gender, age, marital status, employment, education, and household head's ownership of housing. Price and income elasticities were extracted, and the compensatory variation (CV) index of changes was calculated. Assuming the implementation of the proposed scenario and the constancy of prices for all commodity groups except gasoline, the household expenditure data was simulated, and inequality was calculated using the Gini coefficient. The results show that if the above-mentioned scenario is implemented by the government, assuming the constancy of prices for other commodity groups, a relative improvement in the Gini coefficient is obtained, indicating a reduction in inequality.

Climate change has emerged as a significant global challenge, with its impact increasing rapidly in recent decades. The consumption of fossil fuels, which leads to the emission of greenhouse gases like CO2, is a major contributor to climate change. Iran, ranked as the sixth most polluted country in the world, emitted a staggering 745 million tons of CO2 in 2020. Notably, the power plants sector in Iran accounts for roughly 30% of its total carbon emissions. As a result, the main objective of this paper is to engage in long-term planning for electricity supply and demand in Iran, aiming to reduce carbon emissions in line with the country's obligations under the Paris Agreement. To achieve this goal, we utilized the MESSAGE model to design an electricity generation system that takes into account the potential of renewable sources from 2021 to 2050. Additionally, the ARDL model was employed to estimate electricity demand under various scenarios, including subsidy reforms. These predictions were then incorporated into the long-term planning process for Iran's electricity supply system. The findings of the ARDL model highlight that the subsidy reform strategy leads to a 10% decrease in electricity demand throughout the planning period, indicating effective control over the demand side. On the other hand, the MESSAGE model's findings reveal that Iran's ability to fulfill its responsibilities under the Paris Agreement heavily relies on the utilization of renewable potentials across different regions in power supply planning. While carbon dioxide emissions in Iran's electrical sector are not expected to be reduced in the near future (2020 to 2030). However, in the long term (2040 to 2050), significant reductions in CO2 emissions can be achieved. According to the findings, if the electricity system in Iran is designed in accordance with a chosen scenario that incorporates green technologies and subsidy reforms, the share of renewable technologies can increase from 6% in 2020 to 15%, 50%, and 78% in 2030, 2040, and 2050, respectively. Consequently, carbon emissions in the power generation sector can be reduced by 20% and 54% in 2040 and 2050, respectively, compared to 2020 levels.

The issue of climate change has become a significant global concern over the past few decades. Greenhouse gas emissions, specifically carbon dioxide (CO2), resulting from the combustion of fossil fuels, are a primary contributor to this phenomenon. Of the various types of fossil fuels, natural gas and petroleum products are the most widely used. Specifically, gas oil, fuel oil, and gasoline have been the most commonly utilized petroleum products in Iran over the last five decades. To examine the relationship between fossil fuel consumption and total carbon dioxide emissions in Iran from 1955 to 2018, the current study employs the autoregressive distributed lag (ARDL) model. The findings reveal that fossil fuel use has multiple impacts on carbon dioxide emissions. Specifically, a one percent increase in the consumption of gas oil, fuel oil, natural gas, and gasoline results in a corresponding increase in carbon dioxide emissions of 0.55%, 0.32%, 0.32%, and 0.18%, respectively. The analysis of long-term elasticities reveals that a one percent increase in fossil fuel consumption corresponds to a 0.83%, 0.49%, 0.09%, and 0.34% increase in carbon emissions, respectively. The study's results demonstrate that the utilization of gas oil has the greatest negative impact on the environment and carbon dioxide emissions in Iran, both in the short and long term. Fuel oil and gasoline follow closely behind. In contrast, consuming natural gas has the least negative effect on carbon dioxide emissions and the environment in the long run. However, due to supply-side constraints and increasing natural gas consumption, switching from other fossil fuels to natural gas cannot be sustained as a long-term policy to reduce carbon dioxide emissions. Therefore, it is recommended that policymakers pay attention to both price and non-price policies, such as reforming price subsidies and advancing fossil fuel-related machinery and technology.

The main purpose of this study is to investigate the effect of economic indicators, institutional quality and energy efficiency on the ecological footprint (as an indicator to evaluate the degree of environmental degradation). For this purpose, the annual data of 15 MENA countries (Middle East and North Africa) for the period from 1990 to 2021 have been used with the quantile panel approach. The quantile panel model provides the possibility of investigating the effect of research variables on the ecological footprint during different quantiles. The findings indicate the effect of the coefficients of the variables on the ecological footprint in accordance with the expected theoretical foundations; In such a way that the gross domestic product per capita, the ratio of foreign direct investment, and the degree of urbanization and political instability have a positive and significant effect on the ecological footprint, while the index of trade openness, corruption control, the index of democracy, and energy efficiency have a negative and significant effect on the ecological footprint. This effect has not been constant in different quantiles; In such a way that the effect of the variables of GDP per capita, energy efficiency, foreign direct investment ratio, degree of urbanization, and political instability in the high quantiles is far more than the low quantiles, and the effect of the variables of trade openness index, control Corruption and democracy index in low quantiles are more than in high quantiles.

In addition to intensified nonoptimal consumption, the accelerated rise of fuel consumption in the transportation sector is also followed by other hazards in domains such as the environment and national energy security and supply. Therefore, policymakers are particularly interested in improving the productivity of energy consumption with the intention of fuel saving. Such an approach, however, is faced with the rebounded effect in reality, and its positive impacts on reducing energy consumption are counteracted to a large extent.Aiming to estimate the direct rebound effect of improving gasoline consumption efficiency among urban households in four classes of consumption (less than 60 L, 60 to 80 L, 80 to 120 L, and more than 120 L) from 2017 to 2020, the present study applies the almost ideal demand system (AIDS) model and the seemingly unrelated regression (SUR) method.The results indicate that the direct rebound effect of improving gasoline consumption efficiency in four classes of consumption, i.e., less than 60 L, 60 to 80 L, 80 to 120 L, and more than 120 L is 0.73, 0.94, 0.63, and 0.47, respectively. These findings imply that the higher the non-rationed gasoline consumption, the more the saving. In fact, the gasoline pricing mechanism, which has been subject to ongoing criticism, is a significant factor in the extent of the rebound effect, and further amendments are required in this regard. 

Pricing of gasoline and the necessity of reforms in this area are perpetual concerns among experts and policymakers of the country. By allocating a large volume of subsidy to gasoline, not only has the main goal of supporting the poor classes of the society remained unrealized, but it has also created various problems such as excessive consumption, smuggling, and the spread of pollution. In this study, an effort is made to propose a new pricing policy for gasoline with the aim of reducing poverty in the society. In this scenario, a certain allocation (60 liters per month at a fixed price of 15000 Rials) will be preserved, and only non-allocated gasoline will be subject to a floating price and a 5% tax based on consumption. This study introduces a scenario and examines its effects on various types of poverty (absolute and relative) compared to the current situation.

The gasoline consumption data of 78255 households residing in the provinces of the country during the years 2017-2020 were collected and categorized into four groups (less than 60 liters, 60 to 80 liters, 80 to 120 liters, and more than 120 liters). This was based on the view that the amount of gasoline consumption is a part of the household income. The data were derived from expenditure surveys conducted by the Statistical Center of Iran. By employing an ideal demand system model and seemingly unrelated regression method, the share of nine selected commodity groups from the household consumption basket, including (food, clothing and footwear, housing, water, sewage, fuel, lighting, health and medical services; gasoline; transportation excluding gasoline; cultural and recreational services, prepared foods, hotels, and restaurants, and other goods and services) were examined while taking into account demographic variables including household size, gender, age, marital status, employment status, education, and home ownership of the heads of households. Price and income elasticities were extracted, the Compensating Variation (CV) measure of changes was calculated, and household cost information, poverty (absolute and relative) simulation and estimation were conducted, assuming the implementation of the proposed scenario.

The income elasticity of gasoline demand is less than one for all consumption categories. This elasticity has the highest value for consumption categories of less than 60 liters per month (the monthly allocation) and indicates a higher sensitivity of this category compared to other gasoline consumption categories. With the increase of income, the gasoline consumption of this group, as it has not yet reached its saturation point, increases more than other groups. For non-rationed consumption, there is a positive income elasticity trend alongside an increase in gasoline consumption, indicating that gasoline consumption also increases with increasing income. The elasticity of gasoline price showed that this commodity is essential for households, and an increase in its price has no significant effect on their consumption. Nevertheless, gasoline consumers within the monthly rationed range (60 liters) have a stronger reaction to price changes, and any price change affects the basic needs of households belonging to this consumption category. Households belonging to the consumption category of more than 120 liters have the lowest price elasticity, and it is necessary to change the pricing method to make them sensitive to the price of gasoline. Implementing the proposed scenario and imposing taxes on the consumption exceeding the allocated ration for households will result in changes in the welfare of households based on their level of consumption. To estimate the Compensating Variation (CV), the percentage change in the allocated budget share of the commodity group, the approximate relative price changes, and Hicksian price elasticity (compensation) were calculated. By implementing the policy of imposing taxes on excess consumption, households that consume between 60 to 80 liters of gasoline monthly will receive an additional 800,467 Rials for their welfare, and households with consumption between 80 to 120 liters and over 120 liters monthly will lose 5,843,089 Rials and 21,361,290 Rials of welfare, respectively. After adding and subtracting the calculated welfare to household expenses, simulations were performed, and poverty (absolute and relative) was recalculated. The results showed that adding welfare to low-consumption households reduces the poverty rate compared to the current situation. Among the demographic variables examined, except for the virtual age variable, which has an inverse relationship with gasoline consumption, the other demographic variables including household size, home ownership, gender, education, employment, income ownership, and marital status of the heads of households have significant and direct relationships with gasoline consumption.

Conclusion and Policy Implications:

 Currently, the policy of stabilizing gasoline prices in a two-tiered system (allocated and non-allocated prices) is being implemented, which will not be a logical solution in inflationary conditions. A solution needs to be proposed to partially amend and control the gasoline consumption pattern while taking into account the social-political dimensions of pricing reforms. Therefore, in this study, the scenario of non-allocated gasoline pricing proportional to the level of consumption was analyzed as a proposed solution. The results showed that implementing the proposed scenario leads to a reduction in poverty (absolute and relative). This finding has a significant impact on the decision-making of policymakers in order to improve the level of welfare in the society.

Gasoline pricing policy has always been a challenging issue and it has wide economic, political and social dimensions in Iran. In this study, first, the current policy of gasoline pricing has been examined based on analytical and descriptive approach. Then, new pricing scenario is proposed to reduce the harm caused by the current policy. The results show that the current gasoline pricing policy is separate from the economic situation and leads to over-consumption of gasoline, increased polluting emissions, more unfair distribution of subsidies, and increased incentives to smuggle fuel. To address the current price disadvantages and the social consequences of price reforms, a consumption tax policy is recommended as a suggested solution. Under the proposed policy, the price of gasoline is completely affected by the quantity consumed and the more fuel consumed is associated with higher costs rather than larger subsidies. In this policy, the incentive to smuggle fuel, which is associated with high fuel consumption, is greatly reduced because higher fuel consumption is provided at regional prices. Furthermore, consumers with low consumption (less than 80 liters per month) earn more well-being than the current policy and the proposed scenario is expected to be socially acceptable to people.

Achieving reality-based valuation of innovative companies is an undeniable challenge for the founders and investors of innovation. The purpose of this study is to model a logical, innovative and scalable approach to valuing innovative companies. In this way, by selecting the Earning Before Interest and Tax (EBIT) of the studied innovative company, as a state variable and simulating its future income flows based on Arithmetic Brownian Motion (ABM) standard and using the framework of Real Option Valuation (ROV) method, the valuation model was created. The accuracy and efficiency of this model was proved by extracting the data of the fiscal years from 1392 to 1395 of Gamron Petro Industry Exchange Company and comparing the results of the model with the market value of the company in Tehran Stock Exchange. On the other hand, in order to test the effect of real interest rate on the model results, by defining three different values of real interest rate, the effect of real interest rate fluctuation on the model evaluation results was investigated. Thus, the high flexibility of the model using the method of real option valuation is fully reflected in the research results.

Considering the increasing use of storage as one of the effective methods of peak demand management and increasing the reliability of the electricity network, it is necessary to prioritize the use of storages.The purpose of this study was to prioritize selected sub-distributive substations of Tehran for peak load, curve leveling and economic criteria using battery storage. First, we introduce different types of storage and considering the location of the storage in this study, the substations are power distribution. After prioritizing the posts and identifying the first priority posts, we determine the appropriate size of the storage and determine the delay time and the amount of benefit from delaying the development of the post when using the electrical energy storage. The method used is based on multi-criteria decision making with Shannon entropy weighting method and SAW implementation method. In this study, we used real data obtained from Tehran Regional Electricity and the data used for the 63 to 20 kW substations Ekbatan, Azadi, Azerbaijan, Abuzar, Sina, Depo and Yakhchi Abad on July 20, 2016. It is the hottest day of the year. The results of this study show that the maximum installed storage capacity calculated for the first priority post is 119.66 MWh and the maximum storage capacity is 18MW. the most suitable storage size for installing is 120MWh / 18MW. Using the storage at the selected post will delay the development of the post for 7 years and the benefit of underdevelopment is 40% of the investment cost.

The current trend of rising energy consumption in the world has hit mankind with two major crises: first, environmental pollution, and second, the acceleration of finishing energy supplies. Energy storage and reduction of pollutants in the city plays a crucial role in the process of maintaining existing energy. Meanwhile, the transportation sector needs attention due to its importance and position, and can annually bring significant amounts of economic savings to the people and governments by reducing energy consumption and adverse environmental effects, and reducing travel time and unwanted delays brought up. Therefore, in the present research, the most important parameters of environmental pollutant emissions in urban transport sector were determined and system dynamics model of Tehran's urban transport was developed. Based on quantitative analysis, six scenarios, Business As Usual, Priority to the Development of Public Transport, Technical Progress, Administrative Rules and Regulations Management, Travel Demand Management and comprehensive policy are evolved. According to the results, CP scenario has the best performance, and by simultaneously implementing the scenarios, each of them will play a role in improving the situation and significantly reducing energy consumption and CO2 emissions.

The main purpose of this study is to identify and prioritize different gasoline pricing policies in Iran based on sustainable development indicators using the Delphi method and Analytical Hierarchy Process (AHP). To this end, first, various types of gasoline pricing options along with evaluation indicators of these options were extracted separately in economic, social, and environmental terms by the Delphi method based on reviewing studies and interviews with specialists and experts. In this section, four pricing options for gasoline pricing were extracted entitled (i) “Double pricing of gasoline or continuation of the current trend; (ii) “Single rate gasoline price and cash payment of subsidies to cars; (iii) “Proportional pricing for gasoline consumption; (iv) “Single price of gasoline and allocation of quotas to people instead of cars. Then, these options were evaluated and prioritized in terms of economic, social, and environmental indicators in the framework of the AHP method. The results show that pricing commensurate with gasoline consumption or consumption tax (third option) is the best pricing option among the mentioned options. In this option, environmental and economic indicators are of great importance, and the price of gasoline between the quota price and FOB is determined in proportion to the consumption of individuals and sudden price changes do not occur for all consumers and the price of gasoline is completely dependent on the consumption behavior of individuals. Thus high consumption is always faced with higher taxes and allows for a fairer distribution of subsidies and reduced smuggling incentives for this fuel.

The restructuring of Iranian electricity industry allowed electricity price to be determined through market forces in 2005. The main purpose of this paper is to present a method for modeling and forecasting the electricity prices based on complex features such as instability, nonlinear conditions, and high fluctuations in Iran during the spring 2013 and winter 2018. For this purpose, time-series data of the daily average electricity price was decomposed into one approximation series (low frequency) and four details series (high frequency) utilizing the wavelet transform technique. The approximation and details series are estimated and predicted by ARIMA and GARCH models, respectively. Then, the electricity price is predicted by reconstructing and composing the forecasted values of different frequencies as a proposed method (Wavelet-ARMA-GARCH). The results demonstrated that the proposed method has higher predictive power and can forecast volatility of electricity prices more accurately by taking into consideration different domains of the time-frequency; although, more errors are produced if the wavelet transform process is not used. The mean absolute percentage error values of the proposed method during spring 2017 to winter 2018 are significantly less than that of the alternative method, and the proposed method can better and more accurately capture the complex features of electricity prices.

The main purpose of this study is to investigate the impacts of price, efficiency and income factors on energy intensity of Iran's thermal power plants. To meet this end, while using SVAR method and Blanchard-Quah approach, the impacts of power plants efficiency, revenue from power sales and the fuel price on energy intensity of thermal power plants was investigated for the e period 1986-2018. The results based on Impulse-Response analysis show that the response of energy intensity of power plants to an incremental impulse on efficiency is negative. This finding is consistent with the theoretical expectation of a reducing effect of efficiciency improvement on energy intensity. Moreover, energy intensity in power plants decreases following an incremental impulse in power plant revenues. This finding is in line with the theoretical expectation that in the long run, with increasing firm revenue, they tend to use energy saving technology which leads to reduce energy consumption. In addition, an impulse to energy prices (fuels prices), result in a decrease in energy intensity, which is in line with the theoretical expectation that with rising energy prices, there is an incentive to increase efficiency as well as decrease the energy intensity. Based on findings, it is recommended to improve the efficiency of power plants by converting gas power plants into combined cycle, using new technologies and removing fuel price subsidies.

Because of the importance of the state of financial stability in the economy and its impact on economic growth, we tried to test the fiscal sustainability in Iran by using the nonlinear Markov Switching unit root test from 1973 to 2017. The results obtained from the linear and nonlinear unit root tests show that the fiscal state is unstable in two different regimes entitled high and low fluctuations, and the fiscal policy during the studied period has been experienced an unstable situation. In other words, increasing government debt at a given period has not declined over time and has accumulated in the coming years, and government fiscal policies, regardless of accumulated debt compensation, expands spending policies. Therefore, serious consideration of this issue and formulation of fiscal policy, especially budgeting and strengthening of long-term government debt repayment paths to achieve financial sustainability status, is one of the policy recommendations of this paper for economic planners and decision-makers in Iran. Also, it is expected that, regardless of these considerations, the Iranian economy has always suffered from the accumulation of government debts over time.

Todays, energy consumption for experts and economists is one of the components of the performance evaluation of governments and countries, and energy intensity is considered as one of the indicators for assessing energy efficiency. The main purpose of this paper is to study some of the influential factors of energy intensity, such as GDP per capita, industrialization and transportation infrastructure which has been studied considering the spatial links between the provinces during the period from 2008 to 2014. For this purpose, the spatial panel econometric method has been used to estimate the model. The results of Spatial Autoregressive Model with Auto Regressive disturbances (SAC) show that the energy intensity was influenced by the spatial factor in Iran. So, the energy intensity in a province is not only influenced by the internal factors of the province but is also influenced by the energy intensity of the adjacent province. In other words, any external shock to a province will lead to a reduction in energy intensity in adjacent provinces. Also, the results show that GDP per capita has a negative and significant effect and industrialization and transport infrastructure variables have a positive and significant effect on energy intensity in Iran's provinces.

The economies of the world are always affected by the oil price, because oil is considered as the largest energy source of countries. As a result, oil price changes will have a main role in goods and services price changes. The main purpose of this paper is studying the dynamics of oil price pass-through into domestic Prices index in Iran over time. For this purpose, two models i.e. “Auto-Regressive Distributed Lag (ARDL)”, and “State-Space” Models are used during the period of 1990 to 2017 with seasonal frequency. The results of the ARDL model show that the oil price pass-through into the prices index is positive and significant in the long run, while oil price pass-through into the consumer price index is insignificant in short run, but it is positive and significant into producer price index in short run. Also, the results show that after 1995 as a structural break point, the oil price pass-through into consumer price index has declined, but producer price index has increased after 2011. The results of the state-space model indicate that the oil price pass-through into the consumer and producer index is not same over time. So, the oil price pass through was higher and fluctuating during the 1995 to 1997, but after 2000, the pass through into the producer price index are a pretty mild and positive trend, and this pass through has happened at a higher level in comparison with the consumer price index. Therefore, in general, global oil price volatility has affected the inflation of Iran's economy as an oil exporting country, and its intensity depends on how oil revenues are managed within the country. As the role of establishing a Foreign Exchange Reserves in 2000 and the National Development Fund in 2011 is evident to control the intensity of fluctuations oil prices pass through into inflation. Therefore, the emphasis on the stabilization role of the National Development Fund in preventing the transfer of inflationary surges of oil price changes to inflation is one of the policy recommendations of this paper for economic planners and decision makers.

Due to the importance of limited energy resources in the world, researchers and policy makers pay more attention to energy intensity. The purpose of the paper is to study the effect of structural break on factors influencing energy intensity in Iran during the period of 1979-2013. The Fully Modified Ordinary Least Squares (FMOLS) method was used to estimate co-integrating relationships among variables under study. The results showed that energy price and foreign direct investment had negative effects, and share of industrial value added had a significant positive effect on energy intensity. Then structural break was included in the model as a dummy variable. Findings indicate that 1987’s structural break has reduced the impact of energy price and industrial value added, which points to a decrease in the price elasticity of energy intensity and an increase in productivity of the industrial sector after structural break. However, such break had no significant effect on the relationship between direct foreign investment and energy intensity.

Financial markets are sensitive to exchange rate fluctuations of the Iran’s economy. Changes in the foreign exchange market affect household, businesses, and government spendings. Exchange rate management policy helps stock market to be protected from the effects of exchange rates. As for investment strategies, investors can invest without considering the exchange rate in the short run investments, but exposure to asymmetric exchange rate is very important in long run.
This study explores the asymmetric exchange rate exposure of stock returns building upon the capital asset pricing model (CAPM) framework, using monthly returns of Iranian industry indices. In accordance with the existing literature, industry returns are subject to lagged exposure effects, but the asymmetries vary across industries, which could be due to the discrepancies of trade balance and ownership of certain industries.
Furthermore, the dynamic multipliers depict that industry returns quickly respond to changes in the exchange rate and correct the disequilibrium within a short time, making the long run exposure to be symmetric or very small (Cuestas & Tang, 2015). The main aim of this study is, hence, to investigate the asymmetric exchange rate exposure of stock returns in the Iranian stock market at the industry level. Specifically, we introduce the conventional CAPM for measuring exchange rate exposure. We construct the dynamic nonlinear model to investigate both the long run and short run asymmetric exposure effects, which is carried out by means of estimating a nonlinear autoregressive distributed lag (NARDL) model introduced by Shin and Greenwood-Nimmo (2014).
Building upon the CAPM structure, this paper contributes to a growing literature on the analysis of exchange rate exposure of Iran's stock market on the following grounds. First, compared to linear regression models, the NARDL model demonstrates its competence and efficiency in estimating the exchange rate exposure. The disparities in the exposure effect depend on the ownership of these companies and the expansion of their global operations. Second, industry returns strongly and quickly respond to exchange rate changes in the very short run, while most of the long run exposures are symmetric or very small.
In fact, this paper studies the effects of positive and negative shocks of exchange rate on the return of various industries in stock market based on CAPM model and NARDL approach to estimate parameters during the period of April 2012 to March 2015.
To evaluate the efficiency of asymmetric effects of exchange rate on active industries in Tehran stock market, first exchange rates decompose to positive and negative shocks and then its asymmetric effects on stock market is analyzed using NARDL model. To do it, we use the Wald test for the symmetry or asymmetry effects of positive and negative exchange rate on return of active industries in the short run and long run. The results indicate that most industries of stock market are under the influence of positive and negative shocks of exchange rate and these effects are different for industries. Hence, the effects of positive and negative exchange rate shocks for the industries such as agriculture, textile, rubber, engineering, leather, communication, steel products, radio, chemical materials, and multi-disciplinary industries are symmetric while the effect of exchange rate shocks on return of industries like bank, automobile, basic metals, publishing and printing, electrical devices, computer , tool medical, cement, finance, non finance, investments, paper, non-metallic minerals, and machinery industries are asymmetric in short run, and for industries of ceramic tiles, they are asymmetric in the long run. Additionally, in industries like mass production, oil, transport, coal, drugs, wood, sugar, food ingredients except sugar, they are asymmetric in the short run and long run.
Thus, the results of this study can be useful for investors and shareholders in predicting the short and long term effects of exchange rate shocks on the stock prices.
Therefore, it can be argued that sudden shocks exchange rate can affect about 70 percent of returns of active industries in Tehran Stock market. Therefore, avoiding sudden shocks and maintaining relative stability in exchange market are the main suggestions for policymakers. Also, given that the exchange rate shocks are exogenous variables for firm managers, investors should further evaluate the performance of companies and their profitability, and consider long run vision in analysis and making decisions.

The main aim of this paper is to evaluate the energy efficiency in 30 provinces of Iran by applying the different methods of DEA and Anderson and Peterson during the period of 2009-2013. Also, since classical analysis models do not differentiate efficient cases, the AP method (Anderson-Peterson) was used to rank efficient units for evaluating efficiency correctly. So that combination of input variables (including total energy consumption, labor, capital stock, fossil fuel consumption and renewables consumption) and economic outputs (including GDP, Industry, value-added and services), has been used. The main empirical results of present study indicate that efficiency scores for models that consider total energy consumption and economic outputs in a comprehensive manner ((model M4) compared to simpler models that consider only aggregate energy and GDP data) are higher. In addition, assessment Malmquist index (MI) among Iranian provinces indicate that the efficiency in the Isfahan, Tehran, Bushehr, Ilam, Khorasan Razavi, Khuzestan, Qazvin, Markazi, Kohgiluyeh and Boyer Ahmad and Hormozgan provinces is improved.In addition, the results of this study can significantly help policymakers in decision-making process, for example, observations indicating that the change in the economic structure leads to efficiency improvement or the fact that the use of renewable resources should be gradually replaced the fossil fuel consumption, can lead to the adjustment of the Supportive policies from specific economic sectors or the expansion of specific energy sources.

The business cycles are one of the most important economic indicators that they show the changes in economic activities during time. The study of business cycles is important because the understanding fluctuations in GDP and effective factors on these fluctuations help policy makers to plan better and more efficient. The main purpose of this paper is to investigate the effects of oil price shocks on business cycles dynamics in Iranian economy during period of 2005 to 2017 by using non-linear Markov switching model with the time varying transitional probabilities (MS-TVTP). So, first, the oil price shocks were extracted in four different modes, and then the effect of them on recession and boom regimes are investigated. The results of MS-TVTP model show that business cycles are affected by oil price fluctuations and shocks in Iran’s economy. The results indicate that, in all four modes which oil price shocks were calculated, the positive shocks in oil price increase the probability of staying in boom regime. Also positive oil price shocks increase the probability of transition from the recession regime in Iran’s economy. Also, with relative comparison of the coefficients of oil price shocks in the probability of staying in boom regime and transition from recession to boom regime, it can be argued that positive oil price shocks in recession period increases the probability of transition from recession more than the boom regime. In other words, oil price shocks in recession periods have a greater effect on rotation of economic situation and increase the probability of transition from recession regime, but in the boom regime, the positive oil price shock lead to increases the probability of staying in boom regime a little.

This paper aims to study the role of gold, stock and foreign currency as hedges against inflation in Iran based on monthly data over period 2000-2016 by using a novel approach with nonlinear autoregressive distributed lags (NARDL). To achieve this goal, the effect of positive and negative inflation shocks  on price of these assets is estimated separately. The results show that all assets (foreign currency, gold and stock) are hedges against inflation in Iranian economy. As inflation rate increases, the prices of these assets also increase, but the magnitude and type of their hedge against inflation vary in different time horizons. The results show that the effects of both positive and negative inflation shocks on gold price are symmetric in the short-run, but in the long run, the effect of positive inflation shocks on gold price are more than negative shocks. The results of the inflationary coverage of foreign currency show that the effects of the positive and negative inflation shocks on it are asymmetric in the short-run and long-run; while these effects are symmetric for stocks in both short- and long-term. Furthermore, stocks is a proper hedge against inflation in the long run and not only it maintains purchasing power, but also it increases value of investors’ assets. Moreover, the inflationary coverage of foreign currency and gold are the same and less than rising inflation, but exchange rate is a hedge in the short-run and gold plays the role of hedge against inflation in the long-run.

The adoption of appropriate foreign exchange policies has always been one of the main issues in the developing countries, including Iran. The exchange rate volatility plays a key role in the economic performance. The consumption sector as one of the components of total demand is one of the key sectors in the economy that affects the exchange rate and its fluctuations. Therefore, the main purpose of this paper is to identify the main factors influencing on private consumption with the emphasis on exchange rate volatility and its asymmetry effects. To do it, firstly, real exchange rate volatility is estimated by IGARCH model and then it is decomposed for positive and negative shocks. Finally, the asymmetric effects of positive and negative shocks of exchange rate volatilities on private consumption behavior are estimated using the nonlinear ARDL model during the period 1960-2016.
In general, the results show that private consumption behavior is a function of fluctuations and uncertainties of exchange rate, rather than being influenced by the absolute level of the real exchange rate. Also the level of real exchange rate volatility (decreasing and increasing) also has a different effect on private consumption. The findings show that effect of positive and negative shocks of real exchange rate on the private sector consumption is symmetric in the short run but is asymmetric in the long run. Also, national income and inflation have a positive and negative effect on the consumption of the private sector, respectively. Therefore, the controlling the volatility of the real exchange rate rather than its absolute level targeting is the policy recommendation of this study for policy makers.

The main purpose of this paper is to investigate the effects of monetary and fiscal policies on the business cycles in the Iranian economy during the period 2004-2016. Markov Switching model has been used with time varying transitional probabilities for the recognition of the business cycle and identifying the influencing factors on the probability of staying in a period of recession and boom or the transition from one situation to another. The results of the MSIH(2)-AR(2)[1] model show that both expansionary monetary and fiscal policies increase expansion period, but expansionary monetary policy is more effective in expansionary fiscal policy. During the recession regime, fiscal policy has a greater impact than a monetary policy in the transition from the recession regime. Also, findings show that business cycles in Iranian economy have comovements with changes of oil revenues, but the effect of changes in oil revenues has a different effect on the staying or transition of business cycles. Thus, the increase of oil revenues reduces the probability of staying economic boom regime, but it will increase the transition probability of recession to boom regime. In fact, these results indicate that oil revenues are not managed well during the boom period but there is the relatively good management in the recession regime

The inverse relationship between economic growth and unemployment rate is known as Okun’s law in the economic literature. According to the importance of Okun's law on economic policy, investigating the relationship between unemployment rate and economic growth is very important at provincial level. Also, with regard to labor mobility between provinces based on economic conditions, spatial and spillover effects are essential in regional studies; therefore, the main objectives of this paper are to investigate Okun's law in Iran's provinces with spatial econometric approach and whether Okun’s law can be used as a rule of thumb for surveying the labor market response to changes in regional economic growth, in Iran's provinces. A panel data set for 30 provinces during period of 2005 to 2013. The results show that unemployment rates and economic growth of provinces have spatial dependence and labor market performance is influenced by macroeconomic situation and its features the economic situation in neighboring provinces. Hence, in this study spatial panel is employed to investigate Okun’s law. The results of spatial panel (SAC) approve accuracy of Okun's law in Iran's provinces; and the development of regional labor market is not limited to the provincial borders and spillovers to other provinces.