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Developing models for accurate natural gas spot price forecasting is critical because these forecasts are useful in determining a range of regulatory decisions covering both supply and demand of natural gas or for market participants. A price forecasting modeler needs to use trial and error to build mathematical models (such as ANN) for different input combinations. This is very time consuming since the modeler needs to calibrate and test different model structures with all the likely input combinations. In addition, there is no guidance about how many data points should be used in the calibration and what accuracy the best model is able to achieve. In this study, the Gamma Test has been used for the first time as a mathematically nonparametric nonlinear smooth modeling tool to choose the best input combination before calibrating and testing models. Then, several nonlinear models have been developed efficiently with the aid of the Gamma test, including regression models Local Linear Regression (LLR), Dynamic Local Linear Regression (DLLR) and Artificial Neural Networks (ANN) models. We used daily, weekly and monthly spot prices in Henry Hub from Jan 7, 1997 to Mar 20, 2012 for modeling and forecasting. Comparing the results of regression models show that DLLR model yields higher correlation coefficient and lower MSError than LLR and will make steadily better predictions. The calibrated ANN models specify the shorter the period of forecasting, the more accurate results will be. Therefore, the forecasting model of daily spot prices with ANN can interpret a fine view. Moreover, the ANN models have superior performance compared with LLR and DLLR. Although ANN models present a close up view and a high accuracy of natural gas spot price trend forecasting in different timescales, its ability in forecasting price shocks of the market is not notable.

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The shares of state-owned or public companies are supplied in privatization plan. If the financial market be clear and efficient, it is expected that discovered price of supplied shares be efficient too. However, there is no guarantee for the fulfillment of this condition. Specially, implementation of those policies that, for example, a shock to exchange rate or the price of inputs (such as fuel), can affect market efficiency to discover efficient price of shares. In this study, the factors that cause the deviation of the actual share price have been identified, at first. After that a computable system has been designed by implementation error corrector filters. The input of this system is biased variable and corrected variable is the output. In this study, comparing previous studies, is generalized. So computable designed model can evaluates a wide range of factors. This system has been used to calculate the share of Tehran Regional Electricity Company. The outcomes show that the value of its shares is change from a negative amount (based on bias variables) to 2445 billion Rials (after passing based variable from correction filters). This difference, in addition of information asymmetry, maybe causes, in special in energy and electricity sectors, some opportunities to rent.

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Abstract

 Forecasting of crude oil price plays a crucial role in optimization of production, marketing and market strategies. Furthermore, it plays a significant role in government’s policies, because the government sets and implements its policies not only according to the current situation but also according to short run and long run predictions of important economic variables like oil price. The main purpose of this study is modeling and forecasting spot oil price of Iran by using GARCH model and A Gravitational Search Algorithm. Performed forecasts of this study are based in static and out-of-sample forecasting and each subseries data is divided in to two parts: data for estimation and data for forecasting. The forecast horizon is next leading period and its length is one month. In this study the selected models for forecasting spot oil of Iran are GARCH(2,1) and a Cobb Douglas function which is functional of prices of 5 days ago. Finally, the performances of these models are compared. For comparison of these models MSE, RMSE, MAE, and MAPE criteria are used and the results indicate that except in MAPE criterion, the mentioned criteria are smaller for GARCH model in comparison to GSA algorithm.

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This study aims to evaluate the status of Iranian gas industry and to formulate appropriate policies in order to attain the objectives of Iran’s Vision 2025. A dynamic model including exploration, production, consumption and demand sub-systems is designed based on the system dynamics approach and is simulated for the period 2010-2025. In this model, factors affecting natural gas exploration, demand and consumption as well as production, export and import of all other fuels in energy supply are identified and their dynamic interactions are investigated. The results of solving the basic model indicated that except for a 75 % share of gas consumption, none of Vision’s objectives would be attained, if current policies were followed. Accordingly, new policies are formulated and included in the model in the form of some scenarios. The results of simulating such scenarios suggest that other than coordinating the subdivisions of gas industry, production and exploration rates should be increased and significant technological exploration and production advances should be made in order to attain the objectives considered in the gas industry. Furthermore, clean energies such as water, wind and solar resources should be utilized increasingly in order to supply a part of domestic consumption. The results of model validation tests indicate the validity of the model as acceptable.

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The unavoidable consequences of increased demand and decreasing water resources and Deduction rainfall and drought is caused to arise disutes among water user in recent years.

On the other hand, vital need of agriculture sector to water and developing industry sector in Isfahan, have increased competition between water users of industry sector and agriculture sector. In this paper, we use game theory for optimal allocation water resources zayande rud basin. Amount of optimal allocation from zayande rud basin determine by using optimal pareto curve and four conflict solutions For each of sector with enivironment and for game two persons between mentioned sectors over 1379-1388 years. in three games ''industy sector and environment'' and ''agriculture sector and environment'' and ''agriculture sector and industry sector'' find out that allocation water resources isn't optimal between mentioned sectors over 1379-1388 years. After deduction of drinking water, the resulting of game two persons between agriculture and industry sector is share of industry and share of agriculture sector is 85.82% and 14.18%, ,respectively in order to maximize total benefit Isfahan. on the other hand, estimation economic value of water in two sector determine water price in Agricultural sector 13010 rials per M³ and in Industry sector 6001.95 rials per M³ by application linear programming and residual imputation approach. According to the large difference between the actual price of water and tariff set by Ministry of Power for agriculture sector and the results of game theory, it is proposed that give more value to the industry sector, Because it consume less water than agriculture and we use innovative methods for irigation in agriculture sector, so that we prevent from wastage of water resources in this sector.

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This article measures the market power in the loan and deposit markets in banking industry of Iran, including 10 state-owned and 4 private banks, during 1380-1389 (2001-2010) based on the evaluating of Lerner indices. To achieving this objective, a stochastic frontier cost function has been applied then market power was calculated. The main results of paper show over the observed period although market power in loan market has reduced, in deposit market it has increased. Outcome of calculations indicates some fluctuations in Lerner indices especially during (2005-10). So, it shows importance of economic policy aimed at removing the barriers of entry to market and regulation of them in order to make these markets more competitive.

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Establishment of the Gas Exporting Countries Forum in Tehran in 2001 has proved to be one of the most important changes in the gas market. Establishment of the forum has sparked the concern among the consuming countries that a cartel is being formed in the gas market, resulting in the disturbance of supply security and gas price rise. Evidence so suggests the forum is facing fundamental obstacles to form a cartel or any other influential institution. On the other hand, considering the remarkable fall in gas prices during last months, it is necessary to present a model for determining the GECF Members Gas Export Quotas to decrease the gas supply and to increase gas prices. In this paper, we present a model which if it is applied by the GECF members we can expect that gas prices will increase. Hence in this paper first we present two mechanisms for determining the GECF member’s quotas, then considering the current situation of the members in natural gas market the optimal rationing mechanism selected. Besides, for determining the total optimal amount of production in each period as optimal total export of forum two different methods present. The first is more complicated but more accurate.

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IN ACCORDANCE TO DEVELOPMENT OF INFORMATION AND COMMUNICATION TECHNOLOGY IN IRAN, ELECTRONIC BANKING HAS BEEN DEVELOPED IN RECENT DECADE.‌A MEANINGFUL TRANSFORMATION HAS BEEN PLACED IN THE STYLE OF EXISTING BANKING SYSTEM SERVICES, BY SIGNIFICANT INCREASE IN THE USE OF ELECTRONIC BANKING TOOLS IN TEN YEARS. THE REFLECTION OF THIS PHENOMEN IS CLEAR IN THE BEHAVIOR OF PEOPLE AND BANKING SYSTEM WHO CARE ABOUT CASH, MONEY DEMAND PREFRENCES AND VARIATION IN THE COMPOSITION OF BANK RESOURCES.THEREFORE EFFECTIVENESS OF E-BANKING ON VARIABLES SUCH AS MONEY DEMAND IS A TOPIC WHICH APPEARS ESSENTIAL TO STUDY. DEMAND MONEY FUNCTION IS ONE OF THE MAIN IMPORTANT PARTS OF MONETARY SYSTEM AND PLAY CRUCIAL ROLE IN TRANSMISSION OF MONETARY POLICY TO THE REAL ECONOMIC SECTION. THE IMPACT OF THIS ON OTHER COMPONENT OF ECONOMIC SYSTEM, BOTH MONETARY AND NON-MONETARY IS INEVITABLE. IN OTHER WORDS, TO ANALYZE MONETARY ISSUES AND SOLVING THE PROBLEMS, IT IS NECESSARY TO UNDERSTAND THE NATURE OF MONEY DEMAND. IN THIS PAPER, THE DEMAND FUNCTION HAS BEEN ESTIMATED BY USING AR METHOD AND ENTERING EXOGENOUS VARIABLES IN MARKOV SWITCHING VECTOR AUTO REGRESSION MODEL. FOR MODELING OF MONEY DEMAND FUNCTION, SEASONAL DATA BETWEEN 2002‌ TO 2011 HAVE BEEN USED. ALSO THE EFFECT OF TRANSACTION VOLUME THROUGH POINT OF SALE(POS) AND AUTOMATIC TELLER MACHINE (ATM) AS EN-BANKING INDEX HAS BEEN DETERMINED. ACCORDING TO STABILITY TESTS, ESTIMATING THE MONEY DEMAND WICHE CONTAIN EN-BANKING VARIABLES IS UNSTABLE. THERFOR, IT CAN BE STATED THAT THE RESULTS OF FISCAL AND MONETARY POLICIES OF THE CENTRAL BANK AND THE GOVERNMENT TO ACHIEVE ITS GOALS DUE TO UNCERTAIN DEMAND MONEY POSITION, SOMETIMES IS REVERSED.

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One of the issues discussed in economy is the socioeconomic inequality in the society. Income mobility is another measure which indicates the degree of inequality of opportunity in a society. The extent of income mobility depends on socio-economic status of the individuals. Different socio-economic status leads to further inequality and increases inequality of opportunity. Such inequalities lead to the formation of Poverty which can be reproduced and transmitted from one cohort to the other, if not utilize the appropriate method. income mobility is measured as either conditional or absolute one. In Conditional mobility fixed effects are considered, however in absolute mobility it is not so. Fixed effect parameter that indicates the heterogeneity between individuals. According to the importance of the issue of poverty and the relation it has with inequality, this paper studies the conditional mobility in the economy of  Iran. In this study Household Survey Data collected by Iran Statistical Center from 1988 till 2011 is used. The method of nonlinear dynamic pseudo-panel has been used in order to measure income inequality dynamics. Nonlinear dynamics of income inequality for urban areas in Iran are estimated. This method enables us to track the performance of each cohort over time. The main results of this study indicate that the conditional income mobility is low and dine quality in the country has increased over time. Facing negative shocks, households cannot quickly improve their situation and return to the initial income, and at the same time, the market operation in itself cannot fix the problem. This means that the market provides more favorable conditions for people who have higher power and wealth. This leads the inequality to spread to the higher level.

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The growth of non-communicable diseases, and the enormous costs of health care, has led policy makers to focus on “education”, as an effective instrument to improve the public health. Recent empirical studies show that education can improve health and increase life expectancy via ameliorating the life style. The main objective of this paper is to investigate the effect of ‌education on health in‌ Iran over the period of 1974- 2010. Health ‌production function is defined based on the Grossman (1972) model.‌‌ The empirical model has been estimated by using co-integration technique and error correction model.‌ Separation of short and long-term effects and estimate of impact‌ by education’s temporary and permanent lag time changes on health is considered the  innovation aspect of  this research. The results of model estimation indicate that there is a positive and long-term equilibrium relationship between health and education. Based on evidence obtained, education plays a key role in health improvement. Empowering people by investment in their education can prevent many non-communicable diseases. Diseases that are imposed by our incorrect life style. Today we believe that an active participation of elementary and high schools, higher education, and mass media can ameliorate the health statue of society.

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Energy carrier’s subsidization has placed a significant pressure on government budget in Iran thus, energy price increase is performed in order to ameliorate this case. One of the main challenges that policymakers need to consider is the impact of energy prices increase on the labor market especially, when the national unemployment rate is high. This paper utilizes a computable general equilibrium model based on a Micro Consistent Matrix for 2006 in order to evaluate the impact of energy price increase on the Iranian labor market during 2006. The empirical results are based on two scenarios: Baseline and FOB price increase scenarios. They show that the activity level and demand for labor in “crude oil, natural gas, and coal” as well as “other services” sectors will increase in short-run while the energy carriers’ prices increase. However, in long-run, the labor increment will be lower. Furthermore, the model results indicate that in short-run, the activity level and demand for labor in the other sectors will decrease. On the other hand, the policy will result in a larger decrement in the activity level and demand for labor in these sectors in long-run.

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This paper based on the new empirical industrial organization model (NEIO) examines the impact of market concentration and cost efficiency on bank's profit rate margin in Iran. The study uses the model developed by Azzam (1997) to evaluate the market power and cost efficiency for 15 active banks in the banking industry. The empirical findings indicate a decrease in the market power of banks during the period 2001-2011. It is also shown that the conjectural variations index associated with the loans is -0.96, while demand for the loans is completely inelastic where its value is near to 0.087. Additionally, The market power and cost efficiency in the banking industry have been estimated 0.37 and -0.30 respectively meaning a decrease about 0.3 percent for the bank's profit rate due to the efficiency of cost and an increase about 0.07 percent due to the concentration.

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Due to the potentiality of the accumulation of atmospheric carbon dioxide and its permanent nature, the actual amount of carbon dioxide in the atmosphere, the accumulation of effective per capita carbon dioxide and the accumulation of effective per capita of this pollutant in the steady state has been estimated estimated through Kalman filter approach in a Ramsey equilibrium model over the period of 1991- 2007 for Iran. Thereby the researchers were able to estimate parameters such as the coefficient of environment cleaning for carbon dioxide, the share of fossil resources in production, the rate of time preference and the elasticity of emission function with respect to reduction activities.
   The empirical results of the study concerning the minimum, equilibrium & maximum rate of the coefficient of environment cleaning, indicate that for 1991 to 2007 in Iran the elasticity of fossil energy in production function is 0.4475, the rate of time preference is 0.12, the elasticity of emission function with respect to reduction activities is 4.45 and the coefficient of environment cleaning for carbon dioxide is 0.02. The effective per capita accumulated co2 & effective per capita accumulated co2 in steady state with the coefficient of seasonal cleaning of 0.02 respectively have the average of 50.45, 52.97 metric ton based on constant 2005 (PPP). Also the average of effective per capita consumption of the fossil fuel energy and the effective per capita capital in steady state are respectively 4.468 kg and 6.56  $ based on constant 2005 (PPP). The surpassing of the average value of the accumulation of carbon dioxide in steady state compared to its accumulation average value indicates that the accumulation path of co2 will have an increasing trend in next years.

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Natural resources as wealth in general and oil and natural gas in particular can have a potentially beneficial impact on the economic prosperity. However, economic experience implies that many of the major oil exporting countries are facing instability in economic growth, Dutch Disease, corruption and under- development. Owing to the fact that natural resources can play a vital role in development, the present study tries to investigate the econometrics relationship between export of natural resources (as a proxy for abundance) and governance indicators (as alternative variables for institutional development) in selected oil-exporting and OECD countries through the application of Generalized Moment of Method (GMM), for the period lasting from 1996 to 2011. Findings of the study revealed that the strong and statistically significant evidence confirms the negative impact of the export of natural resources on the governance index, quality of regulations, rule of law and control of corruption in the selected OPEC’s member countries. Nevertheless, such a negative impact does not have any statistically significant strength in developed countries. This is due to the improvement made in the surveillance, technical and executive mechanisms of the institutions in the selected OECD countries. It seems that the enormous incomes accrued from the export of natural resources in the oil producing countries in question will induce a decrease in transparency and accountability, instability and frequent changes in economic policies, extension of rent-seeking, corruption and authoritarianism.

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Iran’s share of world exports has not been great in recent years and the development of non-oil exports such as exports of industrial goods in order to reduce the economy's dependence on oil revenues made necessary. The real exchange rate is one of the most important variables affecting exports. In this context, investigate the effect of the real exchange rate volatility on different variables such as the export is important. The main objective of this paper is to investigate the impact of real exchange rate volatility on exports of Iran Industrial goods over the period of 1968-2010. To that end, The real exchange rate volatility index has been estimated incorporating with EGARCH (0,1)  model than we using co-integration of  Saikkonen & Lutkepohl and FMOLS to investigate the impact of the real exchange rate volatility index, along with other variables of model exports of industrial goods have been evaluated.
The main empirical finding of this paper show that the real exchange rate volatility variables and export prices have negative and significant effects on exports of industrial goods and variables GDP’s world, GDP’s Iran and trade  of openness  have positive and significant effects on exports of industrial goods. The empirical findings of this paper, The beneficial implications for investors and Policy makers needs to recognize the exact effects of exchange rate volatility on exports of industrial goods are provided.

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The main objective of this study is to investigate the effects of oil shocks on GDP, prices level, money and exchange rates in Iran by using the structural vector error correction (SVEC) approach model covering the period 1980Q2-2010Q1. The findings of this study reveal that positive shock in oil real price has significant and positive effect on the real GDP in the short, medium and long. The impact of oil price shocks on domestic prices in the short, medium and long term is negative and significant, such as creating a positive shock to the real price of crude oil, reduce the domestic price. In addition, a positive shock to the real price of crude oil has the negative effect of the exchange rate in the short, medium and long term. However, the impact of oil price shock on the real exchange rate is permanent. Imports also will increase, due to the increase in wealth and demand for intermediate products. On the other hand, a positive shock to the real residual money in the short run cause to immediate increases in real out put.

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Symmetry or asymmetry of the business cycle is an important issue in order to select the behavior patterns and prediction of macroeconomic fluctuations. Factors such as oil prices, the financial crisis, uncertainty, the delay on learning, etc., Can cause lack of symmetry in the cycle. Decomposition of the business cycle by wavelet transform, which is strong instrument for processing data, and reviews of the presence or absence of symmetry at each decomposed level, will allow to obtain more information about different frequencies of business cycle. This helps policy makers to adopt appropriate counter-cyclical policies. Wavelet analysis enabled us to investigate symmetry of high and low frequency components of seasonal GDP during 1989-2011. Using Wavelet Symlet was observed, which at least in the low-frequency component, there is asymmetry. Another advantage of this study is selecting model for prediction of each decomposed level separately. This would reduce forecast error.

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The main objective of this study was to investigate weak efficient market hypothesis of Tehran stock exchange. For this purpose, total  price index, financial index, industry index and the index's top 50 companies data for the period 2013:7-2009:5 daily basis as well as data on prices and yields for the period 2013:2 - 2000:3 are applied on a monthly basis. In this study, the hypothesis of the poor performance of the Tehran stock exchange, using wavelets and fractional Brownian motion is investigated. The results show the aforementioned hypotheses are rejected.

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The fluctuations in the oil price with uncertainty, as an exogenous variable, is the most important factor affecting the fluctuations in the GDP of the countries especially OPEC. This study examines the effect of oil price uncertainty on the Iran’s GDP growth using the seasonal data for the period 1988(1)-2011(4). The model used in this study is the asymmetric VARMA, MVGARCH-M and the estimated method is quasi maximum likelihood (QML). The results indicated that there is a negative and significant relationship between oil price and economic growth over the period. Furthermore, the results show that the conditional variance-covariance process underlying output growth and change in oil price exhibits non-diagonality and asymmetry.

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Women as half of the workforce in society can be an effective lever to promote economic and social development goals. In recent years, participation of women in development activities has increased. But the participation of women has been associated with discrimination against them. In recent years with increasing participation of women in the labor market, the income gap between men and women in the labor market is one of the most important discrimination they are facing with it. Understanding the factors affecting women's employment and the impact of these factors on the wage level and understanding the factors affecting the gender gap, can be very useful in reducing discrimination and achieving sustainable desirable development.
With attention, in this study, we tried to analyze influence employment, productivity, education and educating of men and women on decrease gender gap in wages paid to an econometric model. Theoretical basis of this model is based on Blinder- Oaxaca gender gap (1974) and in the period 1370 to 1390. The experimental results with model coefficients using panel data and with using Stata and Eveiws software is obtained and then analyzed.
Based on the results, however, productivity and employment increase wages of men and women but it Increase the gender income gap. Education increases wages of men and women but it reduces the gender income gap. Educating reduces wages of women and gender income gap too.