Forecastingof the Value Added Tax from Tobacco Consumption Using Neural Network Method

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.