:: Volume 5, Issue 20 (9-2015) ::
2015, 5(20): 55-72 Back to browse issues page
Forecastingof the Value Added Tax from Tobacco Consumption Using Neural Network Method
Elham Gholami , Yegane Mousavi Jahromi
Abstract:   (5006 Views)
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.
Keywords: Tobacco consumption, VAT, Forecasting, Neural Network Method, Back - Propagation Algorithm
     
Type of Study: Applicable | Subject: بخش عمومی
Received: 2013/12/11 | Accepted: 2015/04/27 | Published: 2015/09/19


XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 5, Issue 20 (9-2015) Back to browse issues page