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The characterization of memory effects in crude oil markets is an interesting issue that has attracted the attention of researchers from different disciplines, from econophysics to more classical economics. The importance of the problem relies in the fact that the departure from uncorrelated behavior would imply the presence of not-random effects which, in principle, can be exploited for arbitrage. This paper tries to contribute into the issue by estimating the memory effects by means of different parametric, semi-parametric, and non-parametric methods. In the other words, this paper provides analysis on the memory of the oil markets measured via the fractional integration parameter (d) by estimating it with various methods such as the MLE, NLS, GPH, Whittle, Lo, Hurst Exponent and Wavelet. To achieve this goal, we use the daily time series for WTI and Brent spot crude oil prices as well as 3-month futures, and further divide them into yearly subsections to obtain the historical series of memories. Results of the whittle and wavelet estimations, which are better suitted for this analysis, show no evidence of a long memory process. However, the oil price time series exhibits a nonstationary mean-reverting behaviour. Note that in this paper the behaviour of memory is our concern instead of the memory value itself. The results of memory changes trend shows that memory of international oil markets does not have an important trend change. In the other words, in our study period the efficiency of the market does not have an important decline or increase.

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  The power sector in Iran accounts for a share of 28.2 percent of the total CO2 emissions, so it is the biggest emitter of greenhouse gases. This study uses Logarithmic Mean Divisia Index (LMDI) technique to examine the role of five factors (economic growth, fuel intensity, electricity intensity, structure and quality of fuel) influencing CO2 emissions of the Power Plant sector in the period 1997-2008. Thermal efficiency and the fuel mix effects have been analyzed to determine the factors affecting changes in CO2 emissions index. The results show that the economic growth has the highest effect on the increase of CO2 emissions in the power sector during the whole period of study. Then, fuel quality effect, fuel intensity effect and the structure of production effect respectively, have influenced the growth of CO2 emissions. Changes in fuel mix have had the greatest effect on the increase of CO2 emission index, especially for the period 1387-83. Emission index displays that combined cycle power plant has the least emission index among all types of thermal power plants and hence it is the most suitable thermal power plant for the environment amongst thermal power plants .

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This article seeks to modeling social welfare functions, for assessment of how distribution of transfer payment among socio-economic levels. We consider providing social welfare functions two scenarios, first the each socio-economic levels receives amount of transfer payment equal to others, and second the each socio-economic levels receives that with weighted preferences. The four basic functions determine optimal value of how distribution, and then calculate actual value of that by transforming COICOP to ISIC . Finally the difference between optimal and actual values is determined for rural and urban society and for first and second scenario. At the first scenario the difference between optimal and actual value is smaller than second and this difference at rural society is greater than urban society. The other hand the welfare distribution at the former is worse than later.

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The Iranian electricity market is undergoing the first decade of restructuring. Effective competition in wholesale electricity market is a necessary feature of successful electricity industry restructuring. The paper examines the degree of competition in the Iranian electricity market during March to September 2009. The competitive benchmark analysis has been used to simulate producer’s behavior as a price taker firms and compare the competitive market results with actual market outcomes. The competitive benchmark has been calculated through generation costs of producers. Moreover, the possibility of execution market power has been considered by structural index. The finding indicates that the Iranian electricity market has a considerable potential to exercise power market and there were significant departure from competitive behavior during 2009.

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Increase in environmental pollutions of fossil fuels calls for policies stimulating clean technology deployment especially in the transportation sector. To evaluate the efficacy of these policies we should explore the preferences of consumers regarding different technologies. In this paper we use a discrete choice approach used in “Canadian Integrated Model system” (SIMS) to identify the behavioral components. This model has a hybrid top-down bottom-up structure. For this purpose we estimate a multi-nominal logit model (MNL) for different automobile technologies and different transportation modes based on preferences revealed by a sample of 250 Tehran citizens. Then, we evaluate the effects of economic, technological and environmental policies on market share of different automobile technologies and air pollution in Tehran. These policies include gasoline price increase, pollution tax, limitations on single passenger cars and limitations on use of gasoline driven cars. According to this analysis, technology based policies can effectively correct the market shares towards clean traffic technologies

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The crude oil is both a commodity and a financial asset. As there are many factors affecting the crude oil spot and futures markets, the analysis of the relationship between major factors of these markets is complicated. The main objective of this paper is to investigate the relationship between the price of crude oil in spot and futures market and identify the effect of the crude oil inventory and the interest-adjusted basis risk on these price changes. The monthly data of WTI spot and futures prices, WTI crude oil inventory and interest-adjusted basis risk are from EIA (Energy Information Administration) database. The data period is from January 1986 to December 2010. Due to the unpredictable volatilities and uncertainties in variables, the GARCH error process models are used. Empirical results show that there is a positive, strong and significant relationship between the spot crude oil price changes and futures prices. Additionally, the basis risk changes can affect the spot and futures crude oil prices up to three lags. Also, crude oil inventory changes have a negative effect on the spot crude oil price changes with one lag.

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  Environmental Kuznets Curve ( EKC) theory has evolved over several decades from its initial intuitive conception to the complex theoretical models of today. Through successive steps of empirical and theoretical debate, a quadratic relationship between income and environmental degradation has been proposed, criticized, defended, and criticized again.

  Along the way, each finding have new look at the subject. Critic that is provided by Mazzanti et al. (2007) and Stern (1998) is that instead of attempting to gain insight into the underlying mechanics of an EKC theoretical foundation, there are undue focus on exploring empirical regularities among a large set of variables. These critics from opponent and supporter cause researcher to review their approach and take more concerns on details and methodology of EKC theory that make the way of theoretical works.

In this paper, a microeconomics model is provided in which household confront with decision about consumption of dirty and clean goods. It is showed that household make decision in the way that, as income increases, environment pollution rise at first and then fall when household substitute dirty goods by clean goods.

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This paper aims to determine the optimum price of electricity during restructuring process. We maximized social welfare function subject to market equilibrium, maximum production capacity of each group of power plants, maximum demand of each consumer type and the potential of electricity export and import. The model was run using 2007 monthly and annual data by means of GAMS optimization software. The calculated electricity shadow price for the year 2007 was 371.2 per KWh. To get more exact results we run the model for each month separately. The results show that the price of electricity in spring and summer is lower than fall and winter, for marginal cost of power provision in winter rises. This is due to substitution of gas by gasoil and other liquid fuels and also reduction of hydropower production. For both intervals the actual price has a significant deviation from optimum price in Iranian power market.

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Informal economy i.e. unrecorded economy, is one of the important problems in developing countries which affects the efficiency of economic activities in formal sector. Informal economy is also an important source of air pollution. This paper aims at estimating informal economy in Iran over the period 1980-2009 based on the mount of CO2 emissions and the country forest areas and using Kalman Filter approach. The results indicate that: 1) there is a significant and long run relationship between CO2 emissions, the size of forest areas and firm’s industrial activities and total national product, 2) Total national product is more than recorded data in the study period so the existence of informal economy can’t be rejected during this period. 3) The average share of informal economy in total GDP is about 35.6 %.

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  Storing the electrical energy in large scale is impossible. So, it is necessary to identify the factors affecting the electricity demand. Researchers have used different methods to forecast the future demand of electricity, among them intelligent methods and fuzzy based methods are more popular. Since ANFIS structure is based on researcher’s experience about phenomenon, the created structure may not have the best result. Therefore, we used PSO-ANFIS structure.

  In this paper long term electricity demand is forecasted until the year 2025 by hybrid PSO-ANFIS algorithm. The results confirm the high power of the Adaptive Neural based Fuzzy Inference System in forecasting the electricity demand. Results also indicate that the forecasted electricity demand will be 401 billion KWh in 2025. The prediction performance of the proposed technique is more accurate than the ARIMA model.

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  The aim of this study is to calculate the marginal private and social costs of two thermal power plants in Isfahan region for a particular day in January 2010. For this purpose a nonlinear planning model with linear constraints has been used. The objective function (social cost) which is a twofold objective function is calculated by the summation of variable costs and external costs of power plants in the above mentioned region.

  The results of minimizing the objective function of private cost and also minimizing objective function of social cost indicate a significant difference between marginal social cost and marginal private cost. This difference is considered as marginal external cost in peak hours of electricity consumption and has had an obvious increase to the off-peak hours of electricity consumption in the region of the study. Taking into account the social costs of electricity generation, green power generation technologies can compete with thermal power plants.

 

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  Today the quantitative assessment of economic and social impacts of petroleum products supply constraints is one of the main policy issues in Iran. This issue arises from the fact that importing gasoline, gasoil and liquefied petroleum gas (LPG) is restricted by international sanctions. In this paper, we showed that a demand driven Social Accounting Matrix (SAM) is not a suitable tool for answering the above question. So, a modified SAM, known as mixed supply driven SAM is suggested. For this purpose the energy SAM of 2006 is used.

  The overall results reveal that: 1) Petroleum products supply constraints have the most impacts on crude oil and natural gas, retail and wholesale, chemical and agricultural sectors.2) Operating surplus has the most reduction among the other production factors. Results also showed that the fall of urban income as a consequence of supply constraints is more than rural labor either relatively or absolutely.

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This paper presents an AHP and FLP model for the allocation of energy subsidies to different economic sectors. To do so, we defined a group of socio-economic criteria that may affected by the allocation of energy subsidies. These criteria are: economic growth, energy intensity, labor intensity, inflation, social cost of air pollutions and distribution of energy subsidy among socio-economic levels. According to calculated weights, we determined the priority of the above mentioned criteria. Also, according to the optimum overall rank of economic sectors, the commercial sector has the highest rank followed by industrial, agricultural and household and transportation sectors. After determining the final coefficients of AHP approach, we determined the allocation of energy subsidies using linier programming approach. We also considerd the change in technology and consumption patterns of household and transportation sectors. Results show that the share of energy subsidies allocated to commercial and transportation sectors should increase to 30.4 and 28.6 percent respectively.

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Although fossil fuels consumption may causes to rapid economic growth, but due to related pollutants and its consequences, the world has suffered from climate changes. Moreover, fossil fuel resources such as petroleum, gas, coal and uranium are being exhausted rapidly in the last decades. Therefore, seeking an appropriate as well as low-cost alternative for the above-mentioned energy carriers is one of the most important research topics. Regarding this situation, the utilization of renewable energy sources especially solar and wind energies is very important. In this study, the social welfare is maximized and optimal trajectory of solar and wind energy substitution is derived by using an optimal control approach. The model is solved empirically by genetic algorithm using MATLAB software. The results show that assuming social discount rate of 5% and no reduction in solar and wind energy conversion cost during next years, transition from fossil energy to solar and wind energy must occur in 2089 while assuming a 50 % reduction in solar and wind energy conversion cost in every 10 years period, this transition must take place in 2032.

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The purpose of this paper is to introduce the “Natural Resources Perpetuity Rule” in the allocation of resources revenue. We also analyzed the potential impacts of implementing this rule on oil and gas revenues in Iran. To do so, we employed a Computable General Equilibrium Model which is calibrated based on 2010 Micro Consistent Matrix. We assumed an open economy with different sectors such as oil and gas, public services and other activities. Assuming exhaustibility, we measure the impact of different saving rates from Resources Revenue (SR) on welfare, size of public sector, activity levels and exports. We found that the more the SR, the more the welfare loss in first years, the higher the long-run welfare path, the more the non-oil export and the less the size of public sector.

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Dominance of arid and semiarid climate in a vast area of Iran along with the water consumption growth necessitates a more sophisticated planning, a more efficient operation towards an optimal allocation and conservation of water resources in the country. In recent decades many countries, including Iran, have adopted increasing block tariffs for domestic water management. This policy is based on a progressive tariffs applied to control and manage the residential water consumption. In this paper, we developed a panel data model to investigate the impact of increasing block pricing on the residential water consumption during 2004-2008. The average and marginal price models of demand for residential water have been estimated to examine the effects of households’ income and the climate conditions on the residential water consumption. Results show that the increasing block pricing system has not efficiently controlled the residential water consumption in Iran.

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Price shocks lead to oil price volatility in world oil markets. In response to this volatility, economic growth may take different regime and behavior patterns in different situation. Investigating this multi behavior patterns can be useful for policymakers to reduce the effect of oil price volatility. In this study, an EGARCH model has developed using the seasonal data of OPEC oil basket nominal prices during 1367:Q1-1389:Q4. Markov switching models is also applied to investigate the multi behavior patterns of economic growth in response to oil price volatility in Iran. The results show that positive oil price shocks sharply lead to formation of oil price volatility, but, the negative price shocks will slightly reduce oil price volatility. Iranian economic growth is affected by this volatility under three different behavior regimes. If the economy switch to one of the regimes (low, medium, high economic growth), the probability of transition between these regimes and their duration is different. So, oil price volatility as a reason for low economic growth in Iran may cause the economy switch to its lower situation.

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In this study, we designed and simulated a system dynamic model to analyze the impacts of energy intensity changes on environmental and economic indicators in Iran. Results show that if the current situation is continued, the industrial sector energy intensity will increase from 2.67 in the base year to 2.704 at the end of planning horizon. So, the sector will consume 540 million oil barrels to create a value added equals 490627 billion Rials in 2025. Accordingly, the amount of environmental pollutants will increase from 59 million tons in the first year to 267 million tons in 2025 and social costs of producing this pollution would be equal to 67, 449 billion Rials. These findings indicate that regarding the limitation of the production and the increasing costs of energy supply in the future, the country's industrial policies should concentrate on technological changes to increase the efficiency of energy consumption. Also, results indicate that industrial energy consumption has destructive effects on the environment and society in the future and the costs in this sector will not be reversible.

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This report investigates the dominant factors influencing the price gap and the symmetry principle’s evaluation between the crude oil’s price and gasoline. In this regard, the Brent’s crude oil price, gasoline price in six European countries and the fluctuations of the euro vs. US dollar’s exchange rate over the period of 1/1/1999 to 8/25/2011 in weekly intervals are studied. For this purpose, linear models and nonlinear models, such as artificial neural network and wavelet transformation, are implemented. The results indicate insignificant impact of the mentioned parameters in short period price gap both for linear and nonlinear simulations, but nonlinear modeling explicates 92% of long period fluctuations in price gap. According to linear/nonlinear models the symmetry principle is accepted for short period fluctuations in crude oil’s price, but not for long periods.

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The Iranian electricity industry has been restructured following the global experiences. The main objective of restructuring is transition from natural monopoly towards competition in order to improve efficiency. Currently, the Iranian electricity market is performing as imperfect competition and Pay-as-Bid (PAB) auctions are the major trade mechanism in this market. This paper proves that Supply Function Equilibrium (SFE) is an appropriate approach to analyze behavior of the Iranian electricity market. Isfahan electricity market has been considered as a case study in which SFE is applied (regarding marginal cost estimation as well as demand uncertainty). The derived SFE indicates that there is major difference between SFE and Nash equilibrium.