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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Payame Noor University</PublisherName>
				<JournalTitle>Economic Growth and Development Research</JournalTitle>
				<Issn>2228-5954</Issn>
				<Volume>1</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2012</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Survey of and Forecasting the Effect of Globalization on Urban Income Distribution in Iran Using Artificial Neural Network</ArticleTitle>
<VernacularTitle>The Survey of and Forecasting the Effect of Globalization on Urban Income Distribution in Iran Using Artificial Neural Network</VernacularTitle>
			<FirstPage>144</FirstPage>
			<LastPage>117</LastPage>
			<ELocationID EIdType="pii">62</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Seyyed Abdolmajid</FirstName>
					<LastName>Jalayee</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Omid</FirstName>
					<LastName>Sattari</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2011</Year>
					<Month>07</Month>
					<Day>27</Day>
				</PubDate>
			</History>
		<Abstract>Globalization, the process of considerable increase in international trade, global exchanges and markets’ integration as a fundamental characteristic, are emerging inevitably. Investigating the way in which this process affects economic variables, can be a guidance of decision making for policy makers. Considering structural economic differences between urban and rural societies in Iran and using 1350-1386 Iran’s economy dataset, first we compared the efficiency of VAR and VEC models with artificial neural network (ANN) approach in forecasting measure of income distribution inequality of urban societies and finally the best model (ANN) has used as an out-of-sample forecasting tool in different designed scenarios from 1387 to 1395. Choosing ANN model, decrease in urban societies’ income inequality during globalization process, is the main result.</Abstract>
			<OtherAbstract Language="FA">Globalization, the process of considerable increase in international trade, global exchanges and markets’ integration as a fundamental characteristic, are emerging inevitably. Investigating the way in which this process affects economic variables, can be a guidance of decision making for policy makers. Considering structural economic differences between urban and rural societies in Iran and using 1350-1386 Iran’s economy dataset, first we compared the efficiency of VAR and VEC models with artificial neural network (ANN) approach in forecasting measure of income distribution inequality of urban societies and finally the best model (ANN) has used as an out-of-sample forecasting tool in different designed scenarios from 1387 to 1395. Choosing ANN model, decrease in urban societies’ income inequality during globalization process, is the main result.</OtherAbstract>
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			<Object Type="keyword">
			<Param Name="value">globalization</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Income Distribution</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">VAR</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">artificial neural network</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://egdr.journals.pnu.ac.ir/article_62_82d44809591ddebde57e8a3306dec953.pdf</ArchiveCopySource>
</Article>
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