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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Payame Noor University</PublisherName>
				<JournalTitle>Economic Growth and Development Research</JournalTitle>
				<Issn>2228-5954</Issn>
				<Volume>6</Volume>
				<Issue>21</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>12</Month>
					<Day>22</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Forecasting Value Added Tax on Gasoline Consumption</ArticleTitle>
<VernacularTitle>Forecasting Value Added Tax on Gasoline Consumption</VernacularTitle>
			<FirstPage>119</FirstPage>
			<LastPage>107</LastPage>
			<ELocationID EIdType="pii">2108</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Yeganeh</FirstName>
					<LastName>Mousavi Jahromi</LastName>
<Affiliation>Faculty member, Payame Noor University</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2014</Year>
					<Month>09</Month>
					<Day>13</Day>
				</PubDate>
			</History>
		<Abstract>In the VAT Acts in order to control gasoline consumption as one of the environment- polluting and also to earn revenue resources for environment protection, higher tax rate than the standard rate is levied on its consumption. In this paper, forecasting income receivable from the tax base using the two-stage approach has been considered. In the first stage, tax base (gasoline consumption expenditure) has been forecasted in the period 2013 to 2016 and then gasoline consumption tax, using multiplying the tax rates in gasoline consumption expenditure predicted, has been calculated for the mentioned period. In this regard, for precise prediction of the tax revenue, supervised neural networks method and for networks training, error back-propagation algorithm are used. The results indicate that during the mentioned period gasoline price changes (as the most effective variable) arising from VAT will have no serious impact on gasoline consumption. Also, VAT revenue of gasoline consumption will increase by an average annual rate of 35 %.</Abstract>
			<OtherAbstract Language="FA">In the VAT Acts in order to control gasoline consumption as one of the environment- polluting and also to earn revenue resources for environment protection, higher tax rate than the standard rate is levied on its consumption. In this paper, forecasting income receivable from the tax base using the two-stage approach has been considered. In the first stage, tax base (gasoline consumption expenditure) has been forecasted in the period 2013 to 2016 and then gasoline consumption tax, using multiplying the tax rates in gasoline consumption expenditure predicted, has been calculated for the mentioned period. In this regard, for precise prediction of the tax revenue, supervised neural networks method and for networks training, error back-propagation algorithm are used. The results indicate that during the mentioned period gasoline price changes (as the most effective variable) arising from VAT will have no serious impact on gasoline consumption. Also, VAT revenue of gasoline consumption will increase by an average annual rate of 35 %.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Gasoline</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Neural Network Method</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Polluting Goods</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Value Added Tax</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Chaos Theory</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://egdr.journals.pnu.ac.ir/article_2108_2d6b711aa5057a5a246157eedb5680e9.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
