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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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Cigarette and tobacco products in the VAT Law is considered as one of the particular goods and in order to contorlingit’s consumption by price tools, higher tax rates than the standard rate will be levied on it. In this paper, forecasting of revenues of this tax using an approach based on the estimating of tax base has been considered. Thus the first stage, tax base (consumption expenditure) is forecasted for the period 2012 to 2015 and then tax related years by applying the tax rates, will be calculated. In this regard, Because of concerns that policy makers have access to accurate predictions of tax revenues, Supervised neural networks Method to prediction and back-propagation algorithm to train is used. The results indicate that the average annual growth of revenue from value added tax on Cigarette consumption will have 20 percent during the forecasting years.

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As one of the important energy forms, natural gas consumption has an upward trend in recent years. Therefore management and planning for provision of it requires prediction of the future consumption. But many of prediction procedures are inherently stochastic therefore it is important to have better knowledge about the robustness of prediction procedures. This paper compares robustness of two prediction procedures Artificial Neural Networks as a nonlinear and ARIMA as a linear model. using resampling method to predict the monthly consumption of natural gas in the household sector. Data spans from 2001-4 to 2012-3, to train the networks, we used genetic algorithms and Particle Swarming Optimization then results were compared using 10-fold method. According to the results, the particle swarm optimization (PSO) outperforms the genetic algorithm. Then we used data from 2001-4 to 2010-3, with resampling by 2000 to predict the  natural gas consumption for the 2001 -4 to 2012-3 and to form critical values. Results show that prediction by a mixed method using ANN and PSO is more robust than ARIMA method.