Journal of Economic Modeling Research

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The foreign direct investment is one of the economic variables that can positively affect the economic growth, but according to some researches this does not apply to some countries. These researches implicate that this lack of positive effect is due to domestic qualification of the home country. One of the essential qualifications for positive effectiveness of foreign direct investment on the economic growth is the existence of developed financial market. Therefore, in this research we intend to examine the role of financial market in the effectiveness of foreign direct investment on the economic growth. To do this we made use of the data from 57 countries in the period 1990-2005 and the econometric technique of panel data. The results show that in developed countries because of their financial market, the effect of foreign direct investment on economic growth is positive and significant whereas in developing countries this effect is not significant.

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Value Added Tax (VAT) as a method of tax charging with creating a new tax base broad has been interest of many countries. Also Value Added Tax in our country in order to reform the structure of tax and increasing government revenues was approved by the House after a relatively long time and in the second quarter of year 1387 was carried out. Given that this law as an experiment and for five year was carried out study of effects of this tax on macroeconomic variables is of particular importance. In this study has tried to use the analytical relationships Input-Output and production of technical coefficient matrix constant assumption of fixed economic conditions and economic variables and limiting assumptions of this study to the price effects resulting from applying VAT on cost of whole different departments to deal with the country's economy. By using of model price of input - output and applying tax rates issue of Article 12 on exemption for goods and services and ultimately applying export exemption issue of Article 13 on value added tax the price effects of each section of economy is calculated and with and with considering of share of each section from the whole output the price effects is calculated. Results show that implementation of VAT has had very low price effects.

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Life insurance as an investment and assurance tool provides a great source of investment financing in different economies. Despite life insurance development in advanced countries and in many developing economies, it could not get its appropriate share in Iranian family’s basket. This paper investigates factors that affect life insurance demand in Iran. So, random sampling used to get required information in three provinces of Iran (Tehran, East Azerbayjan and Mazandaran). Factors are divided into two main groups: Socioeconomics and psychological. Required data were gathered using questionnaire. Results show that life insurance demand has negative relationship with individual expected health condition, premium, expected inflation, degree of risk aversion and income. Bequest, economic optimism, age, employment of partner and reading has positive relation with life insurance demand. Based on the sample, result show that life insurance demand is not affected by advertisements but is affected by others recommendations.

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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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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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This paper aims at estimating Geometric Brownian Motion (GBM) Model, based on two central parameters in this model (volatility and drift), and forecasting Henry Hub natural gas daily spot prices (07/01/1997-20/03/2012). Researches reveal that two mentioned parameters estimation can be satisfied with different approaches and in various time scales. Therefore, two approaches of backward looking and forward looking have been used in different time scales and sub-periods. Results show that the volatility and drift values are highly dependent on the time scale and backward results are lower than the forward ones. Moreover, along with increasing the number of random runs of the model although the fluctuating range decreases, the predicted line slope is very close to the actual line. Ultimately, the performance evaluation criteria yields that forward method, clearly in 2009, has the best performance. The sub-periods of 2001-2004 in backward and forward methods have the next best performances, respectively. These sub-periods can be used as a basis for calculating the central parameters of the model. In addition, the results suggest that relying on data used in the most recent period is not sufficiently accurate. Also, it is observed that sub-periods or time scales with higher volatility show better performance evaluation criteria, therefore they can be applied in price forecasting with GBM model.

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One of the greatest challenges of renewable resources is unpredictable nature of these resources. Nevertheless use of fossil-renewable integrated hybrid system, which uses some renewable resources rather than a single source, for the supply of power, is the most affordable and the most reliable method. In this study by use of analytical programming approach and 2012 base year statistics, production system of Khorasan Regional Electricity CO. has been simulated and the maximum renewable electricity potential, entered into power generation system. Results show that among all of solar, wind, biomass, geothermal and hydro, only solar power have enough capacity and potential to be substituted with fossil power. The comprehensive system, which uses all renewable potential power capacity, causes 6.38 TWh reduction in fossil power, 4.28 million tons emission, 10-fold increase in spot-hourly price and 21% reduction in grid stability which shows necessity of using stabilizer and storage equipment in the hybrid integrated production system and Technical and financial support from the government to reduce the cost of solar equipment.