Objective: Income inequality affects consumption structure via changes in the composition of expenditure basket. Shocks, fluctuations, disparities, and dispersions of Income inequality, is expected to be transmitted to consumption expenditures. These shocks might induce inequalities in consumption expenditures. This paper tries to measure the amount of such consumption expenditures inequalities that are derived from Income inequality.Method: To measure the consumption expenditures inequality and Income inequality, the variance of logs is employed. For this purpose, Iranian urban households' data of the period of 1982 to 2007 is used. To analyze relations between variables, panel data methodology is applied. Findings: All fluctuations of Income distribution do not translate in consumption expenditure distribution. Conclusion: The distribution of households' consumption expenditure in comparison to the distribution of Income is less subjected to fluctuations and variations.

Objectives: The main objective of this research is to estimate Income inequality in IRAN using the statistical data on household budgets. This is due to the fact that budget distribution has less fluctuation and is more uniformed. Measuring changes in inequality helps us determine the effectiveness of polices aimed at affecting inequality, and gives us data necessary to use inequality as an explanatory variable in social analysis.However, similar to several other developing countries one of the most common problems in analyzing the Income distribution in IRAN, raises from inaccuracy in statistical data. This inaccuracy can be due to several factors such as lack of precision in data acquisition process, misunderstanding the statistical concepts or mistakes in measuring methods. This problem causes the acquired data to be inconsistent over the time.Method: In the first step, a discrete set of distribution samples from 30,000 households gathered by Statistical Center of IRAN is processed. This data set is part of the household budget microdata for both urban and rural areas for the time period 1984-2004. This data is then used to estimate the Income inequality in rural and urban areas for the specified period. To this point, three indices of the Gini coefficient, Atkinson and Theil and are calculated by STATA.Result: calculated by Atkinson and thei and Gine measures can be summarized as fallows:The two main factors in the evaluation of Atkinson measures are coefficient   and estimation of Atkinson index. The findings calculated by Atkinson measure indicate that in urban areas the maximum levels of inequality appear in the years 1988, 1990 and 1991 and the minimum level in 2003-04. In rural areas, these maximum levels occurred in 1987, 1990 and 1991 and the minimum is in 2003-04. The optimum range for coefficient   in the Atkinson index is estimated between 0 and 1 in both rural and urban areas meaning that the rates of inequalities are consistent in these areas. In estimation of theil measure indicate that in urban areas the maximum levels of inequality appear in the years 1988, 1990 and 1991 and the minimum level in 2003-04. In rural areas, these maximum levels occurred in 1987, 1990 and 1991 and the minimum is in 2003-04.In estimation of Gini coefficient, the highest levels of inequality are observed in the years 1987, 88 and 91 and the minimum levels have been occurred in years 2003-04. This level is measured to be lower than 63 in both rural and urban areas in the year 2004.The most concerning observable fact in the analysis of these results are the strong fluctuations in the rate of change of inequality rather than its absolute value. These fluctuations result in social and economical instability. It is worthwhile to mention that although evaluation the Income distributions are very crucial, no statistical data is available on Income distribution at the moment. The only statistical available data is on distribution of household spending.

The main objective of this paper is to examine causality between ICT indicators and Income inequality in Iran during the period 1994-2013. In other words, does the information and communication technologies, increasing Income inequality in Iran or vice versa, Income inequality is causality the availability of information and communication technology? And is there a feedback between them? To analyze, we use annual time series including unit root test and two methods: casual bounds test approaches based on unrestricted error correction model (UECM) (Pesaran et al. (2001)) as well as Toda and Yamamoto's Granger non-causality test (1995). Findings show a one-way causality from Income inequality to all ICT indicators. This means that Income inequality in the country will lead to the expansion of the digital divide.