<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Decomposition of Environmental Total Factor Productivity Growth Using Distance Function in the Provinces of Iran</ArticleTitle>
<VernacularTitle>Decomposition of Environmental Total Factor Productivity Growth Using Distance Function in the Provinces of Iran</VernacularTitle>
			<FirstPage>1</FirstPage>
			<LastPage>24</LastPage>
			<ELocationID EIdType="pii">1328</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Paria</FirstName>
					<LastName>Parsa</LastName>
<Affiliation>Student in Energy Economics, Shahid Bahonar University of Kerman</Affiliation>

</Author>
<Author>
					<FirstName>Zeynalabedin</FirstName>
					<LastName>Sadeghi</LastName>
<Affiliation></Affiliation>
<Identifier Source="ORCID">0000-0002-6591-6090</Identifier>

</Author>
<Author>
					<FirstName>Abdolmajid</FirstName>
					<LastName>Jalaee</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>06</Month>
					<Day>30</Day>
				</PubDate>
			</History>
		<Abstract>This paper extends recently developed parametric hyperbolic distance functions to the analysis of energy and environmental efficiency for a panel data of 30 provinces in Iran from 2006-2011, and then decomposes the growth of environmental total factor productivity into two component measures, namely, environmental technology change and environmental technical efficiency change based on the estimated hyperbolic distance functions. In this period of time, the results show that environmental total factor productivity change has decreased average 8/47 percent, because of high decreases in the environmental technical efficiency and increases emission of CO&lt;sub&gt;2&lt;/sub&gt;. With increases emission of CO&lt;sub&gt;2&lt;/sub&gt;, the environmental total factor productivity change has been smaller than total factor productivity change and means that in this period of time, the environment is faced with the phenomenon of destruction rather than improving.</Abstract>
			<OtherAbstract Language="FA">This paper extends recently developed parametric hyperbolic distance functions to the analysis of energy and environmental efficiency for a panel data of 30 provinces in Iran from 2006-2011, and then decomposes the growth of environmental total factor productivity into two component measures, namely, environmental technology change and environmental technical efficiency change based on the estimated hyperbolic distance functions. In this period of time, the results show that environmental total factor productivity change has decreased average 8/47 percent, because of high decreases in the environmental technical efficiency and increases emission of CO&lt;sub&gt;2&lt;/sub&gt;. With increases emission of CO&lt;sub&gt;2&lt;/sub&gt;, the environmental total factor productivity change has been smaller than total factor productivity change and means that in this period of time, the environment is faced with the phenomenon of destruction rather than improving.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">The provinces of Iran</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Energy efficiency</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Environmental Efficiency</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Environmental total factor productivity</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Distance function</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1328_4c22bd444899d3b6047a10b20a2f26db.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Economic factors affecting the volatility of tax revenues</ArticleTitle>
<VernacularTitle>Economic factors affecting the volatility of tax revenues</VernacularTitle>
			<FirstPage>25</FirstPage>
			<LastPage>42</LastPage>
			<ELocationID EIdType="pii">1329</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Ebrahim</FirstName>
					<LastName>Nasiroleslami</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Teimoor</FirstName>
					<LastName>Rahmani</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Hamid</FirstName>
					<LastName>Abrishami</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>09</Month>
					<Day>20</Day>
				</PubDate>
			</History>
		<Abstract>Diversification of income sources is a strategic policy application in economics and management. Deal with the diversity makes it possible to access a more stable financial management objectives and its performance. In this paper, the effects of some variables such as fluctuations in GDP, tax diversification index, the share of indirect taxes, the tax to GDP ratio, oil income growth rate, GDP per capita, the share of agriculture value added, Gini coefficient on government tax income fluctuations are examined by using ARDL regression model.&lt;br /&gt; The results of estimating the regression model show that tax structure and the structure of the economy are important to bring stability for the combination of government tax revenue. In addition the tax structure and tax consequences affects on performance.</Abstract>
			<OtherAbstract Language="FA">Diversification of income sources is a strategic policy application in economics and management. Deal with the diversity makes it possible to access a more stable financial management objectives and its performance. In this paper, the effects of some variables such as fluctuations in GDP, tax diversification index, the share of indirect taxes, the tax to GDP ratio, oil income growth rate, GDP per capita, the share of agriculture value added, Gini coefficient on government tax income fluctuations are examined by using ARDL regression model.&lt;br /&gt; The results of estimating the regression model show that tax structure and the structure of the economy are important to bring stability for the combination of government tax revenue. In addition the tax structure and tax consequences affects on performance.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">tax</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">stable and sustainable income</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">ARDL</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1329_01e9565cecc4e989123f9620c1d09c09.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Decomposing the Influencing Factors of CO2 Emissions in Iranian Non-Metallic Mineral Products Industries</ArticleTitle>
<VernacularTitle>Decomposing the Influencing Factors of CO2 Emissions in Iranian Non-Metallic Mineral Products Industries</VernacularTitle>
			<FirstPage>43</FirstPage>
			<LastPage>57</LastPage>
			<ELocationID EIdType="pii">1330</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohsen</FirstName>
					<LastName>Pourbadollahan Covich</LastName>
<Affiliation>University of Tabriz</Affiliation>
<Identifier Source="ORCID">0000-0003-2755-5703</Identifier>

</Author>
<Author>
					<FirstName>Mohahmadmehdi</FirstName>
					<LastName>Barghi Oskooee</LastName>
<Affiliation>University of Tabriz</Affiliation>

</Author>
<Author>
					<FirstName>Hossein</FirstName>
					<LastName>Panahi</LastName>
<Affiliation>University of Tabriz</Affiliation>

</Author>
<Author>
					<FirstName>Khadijeh</FirstName>
					<LastName>Salehi Abar</LastName>
<Affiliation>University of Tabriz</Affiliation>

</Author>
<Author>
					<FirstName>Iraj</FirstName>
					<LastName>Ghasemi</LastName>
<Affiliation>University of Tabriz</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2014</Year>
					<Month>10</Month>
					<Day>15</Day>
				</PubDate>
			</History>
		<Abstract>Carbon Dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) resulting from the combustion of fossil fuels has the highest share of greenhouse gas emissions. Non-metallic mineral products industries with a share of 25.8 per cent had a significant role in CO&lt;sub&gt;2&lt;/sub&gt; emissions of Iranian ten people or more industries at 2011. In order to have knowledge about the changes of such pollutions, the recognition of the influencing factors of emissions of them is required. In this study, using the LMDI approach, the changes in total CO&lt;sub&gt;2&lt;/sub&gt; emissions in Iranian non-metallic mineral products industries are traced back to changes in activity level, structural change between sectors, structural change within sectors, energy intensity, fuel mix and emission factors, over the period of 2000 – 2011. The results indicate that the changes in the activity level, structural change between sectors and emission factors are the major factors of increasing CO&lt;sub&gt;2&lt;/sub&gt;, respectively. In contrast, changes in the energy intensity, structural change within sectors and fuel mix factors have decreased the CO&lt;sub&gt;2&lt;/sub&gt; emissions of such industries.</Abstract>
			<OtherAbstract Language="FA">Carbon Dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) resulting from the combustion of fossil fuels has the highest share of greenhouse gas emissions. Non-metallic mineral products industries with a share of 25.8 per cent had a significant role in CO&lt;sub&gt;2&lt;/sub&gt; emissions of Iranian ten people or more industries at 2011. In order to have knowledge about the changes of such pollutions, the recognition of the influencing factors of emissions of them is required. In this study, using the LMDI approach, the changes in total CO&lt;sub&gt;2&lt;/sub&gt; emissions in Iranian non-metallic mineral products industries are traced back to changes in activity level, structural change between sectors, structural change within sectors, energy intensity, fuel mix and emission factors, over the period of 2000 – 2011. The results indicate that the changes in the activity level, structural change between sectors and emission factors are the major factors of increasing CO&lt;sub&gt;2&lt;/sub&gt;, respectively. In contrast, changes in the energy intensity, structural change within sectors and fuel mix factors have decreased the CO&lt;sub&gt;2&lt;/sub&gt; emissions of such industries.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Index Decomposition Analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">CO2 Emissions</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Non-Metallic Mineral Products Industries</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">LMDI Method</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Iran</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1330_fe51510c80bfd6e5d78a164cd5b1f688.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Survey on the Relationship between Economic Growth, Poverty, and Inequality in Iran during Five-Year Development Plan</ArticleTitle>
<VernacularTitle>Survey on the Relationship between Economic Growth, Poverty, and Inequality in Iran during Five-Year Development Plan</VernacularTitle>
			<FirstPage>59</FirstPage>
			<LastPage>79</LastPage>
			<ELocationID EIdType="pii">1331</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Hossein</FirstName>
					<LastName>Raghfar</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Mitra</FirstName>
					<LastName>Babapour</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Mohadese</FirstName>
					<LastName>Yazdanpanah</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2014</Year>
					<Month>12</Month>
					<Day>15</Day>
				</PubDate>
			</History>
		<Abstract>This study focuses on the relationship of poverty with economic growth and inequality during different socio-economic development programs in Iran between1989-2013. To this end, the elasticity of poverty was decomposed into growth and inequality effects; then the outcome of the economic growth is calculated using Kakwani and Son’s (2008) Poverty Equivalent Growth Rate index. This index demonstrates how the benefits of growth are distributed between the poor and the non-poor people. Study of the poverty equivalent growth rate can be an important tool for the governments to reduce poverty.
Poverty changes decomposition to the neutral effects of the growth and inequality in rural and urban area shows that the effect of neutral growth on poverty is negative, whilst the neutral effect of inequality has positive and negative fluctuation. Iran’s economic and political evolvement during the years which our study focused on, can explain these fluctuations. Calculating Poverty Equivalent Growth Rate index and its comparison with the economic and social development programs in Iran, show that there were not any effective policies to achieve sustainable welfare.</Abstract>
			<OtherAbstract Language="FA">This study focuses on the relationship of poverty with economic growth and inequality during different socio-economic development programs in Iran between1989-2013. To this end, the elasticity of poverty was decomposed into growth and inequality effects; then the outcome of the economic growth is calculated using Kakwani and Son’s (2008) Poverty Equivalent Growth Rate index. This index demonstrates how the benefits of growth are distributed between the poor and the non-poor people. Study of the poverty equivalent growth rate can be an important tool for the governments to reduce poverty.
Poverty changes decomposition to the neutral effects of the growth and inequality in rural and urban area shows that the effect of neutral growth on poverty is negative, whilst the neutral effect of inequality has positive and negative fluctuation. Iran’s economic and political evolvement during the years which our study focused on, can explain these fluctuations. Calculating Poverty Equivalent Growth Rate index and its comparison with the economic and social development programs in Iran, show that there were not any effective policies to achieve sustainable welfare.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Poverty</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Inequality</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Growth</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Poverty Equivalent Growth Rate</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Iran</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1331_e077e1a544eec4f0307cf5c3c721d944.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Impact of Human Capital Dimensions on Total Factor Productivity of Production in Iran&#039;s Economy</ArticleTitle>
<VernacularTitle>The Impact of Human Capital Dimensions on Total Factor Productivity of Production in Iran&#039;s Economy</VernacularTitle>
			<FirstPage>81</FirstPage>
			<LastPage>106</LastPage>
			<ELocationID EIdType="pii">1332</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohammad Ali</FirstName>
					<LastName>Falahi</LastName>
<Affiliation></Affiliation>
<Identifier Source="ORCID">0000-0001-7442-4269</Identifier>

</Author>
<Author>
					<FirstName>Fereshteh</FirstName>
					<LastName>Jandaghi Meybodi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Zohreh</FirstName>
					<LastName>Eskandaripoor</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2014</Year>
					<Month>09</Month>
					<Day>27</Day>
				</PubDate>
			</History>
		<Abstract>In this study, using time series analysis, the long-run relationship between human capital dimensions (education and health) and total factor productivity of production in Iran’s economy is estimated during 1978 to 2010. Along with human capital indicators, other variables such as accumulation of domestic R&amp;D capital and capital stock per workers are used as control variables. Cointegration analysis with estimating Unrestricted Error Correction Model (UECM) based on Bounds Test is performed. The Long-run and short-run coefficients, using Autoregressive Distributed Lag (ARDL) method, are estimated. The results confirm that the human capital indicators and capital stock per workers have significant and positive effect on the productivity level. The results of Granger-causality test based on Error Correction Model (ECM), show that there exist a bi-directional causal relation between the human capital (education) and total factor productivity of production in the long-run.</Abstract>
			<OtherAbstract Language="FA">In this study, using time series analysis, the long-run relationship between human capital dimensions (education and health) and total factor productivity of production in Iran’s economy is estimated during 1978 to 2010. Along with human capital indicators, other variables such as accumulation of domestic R&amp;D capital and capital stock per workers are used as control variables. Cointegration analysis with estimating Unrestricted Error Correction Model (UECM) based on Bounds Test is performed. The Long-run and short-run coefficients, using Autoregressive Distributed Lag (ARDL) method, are estimated. The results confirm that the human capital indicators and capital stock per workers have significant and positive effect on the productivity level. The results of Granger-causality test based on Error Correction Model (ECM), show that there exist a bi-directional causal relation between the human capital (education) and total factor productivity of production in the long-run.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">total factor productivity of production</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Human Capital</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Auto Regressive Distributed Lag (ARDL)</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Bounds test</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">causality test</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Iran</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1332_28e209b61a52482a0ae1cb9f5959c792.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Effects of Demographic Changes on Income and Consumption Taxes in Iranian Economy: Microsimulation Approach</ArticleTitle>
<VernacularTitle>The Effects of Demographic Changes on Income and Consumption Taxes in Iranian Economy: Microsimulation Approach</VernacularTitle>
			<FirstPage>107</FirstPage>
			<LastPage>134</LastPage>
			<ELocationID EIdType="pii">1333</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Ebrahim</FirstName>
					<LastName>Rezaee</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>29</Day>
				</PubDate>
			</History>
		<Abstract>This paper investigates the relationship between demographic changes and tax revenues, as a prominent economical subject which can be transformed to an economic problem, potentially. So, the two tax bases, which have the closest relation with population changes, have been considered. To continue analysis, a microsimulation framework is employed which itself involves several stages: Firstly, income profiles of individuals have estimated. Then, using multi-rate tax function the tax revenue of every age group has been estimated. After aggregation and projection of total income tax revenues based on multi-rate function output, sensitivity analysis of each group&#039;s income against demographic changes has performed. Also, tax on consumption has estimated based on multi stage process and applying several estimator tools and input-output coefficients. Results show that, at the present, income&#039;s tax revenues of younger groups is affecting by demographic changes and other old age groups will be affect until 2030s decade. Tax on consumption will be affect slower than tax on income. </Abstract>
			<OtherAbstract Language="FA">This paper investigates the relationship between demographic changes and tax revenues, as a prominent economical subject which can be transformed to an economic problem, potentially. So, the two tax bases, which have the closest relation with population changes, have been considered. To continue analysis, a microsimulation framework is employed which itself involves several stages: Firstly, income profiles of individuals have estimated. Then, using multi-rate tax function the tax revenue of every age group has been estimated. After aggregation and projection of total income tax revenues based on multi-rate function output, sensitivity analysis of each group&#039;s income against demographic changes has performed. Also, tax on consumption has estimated based on multi stage process and applying several estimator tools and input-output coefficients. Results show that, at the present, income&#039;s tax revenues of younger groups is affecting by demographic changes and other old age groups will be affect until 2030s decade. Tax on consumption will be affect slower than tax on income. </OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Demographic changes</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Tax on consumption</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Tax on income</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Microsimulation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Multi- rate tax function</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1333_ff49cc40a8890e6a60f40ff3026d2730.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Asymmetric and Symmetric Effects of Changes in Price and Income on Natural Gas Demand in Iran Industry Sector</ArticleTitle>
<VernacularTitle>The Asymmetric and Symmetric Effects of Changes in Price and Income on Natural Gas Demand in Iran Industry Sector</VernacularTitle>
			<FirstPage>135</FirstPage>
			<LastPage>155</LastPage>
			<ELocationID EIdType="pii">1334</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Vida</FirstName>
					<LastName>Varahrami</LastName>
<Affiliation></Affiliation>
<Identifier Source="ORCID">0000-0002-1869-8852</Identifier>

</Author>
<Author>
					<FirstName>Rassam</FirstName>
					<LastName>Moshrefi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Jaber</FirstName>
					<LastName>Layegh Gigloo</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>06</Month>
					<Day>28</Day>
				</PubDate>
			</History>
		<Abstract>Aim of this paper is to survey asymmetric effects of natural gas price on it&#039;s demand in industrial sector and demand function of natural gas in this sector is derived. This paper surveyed existence of asymmetric effects of natural gas price in koyck model for period of 1991-2013. Results of this paper revealed that effects of natural gas price on it&#039;s demand in industry sector is symmetric in this period and effect of income changes on natural gas demand in this sector is asymmetric. In this period, as estimation results long run and short run elasticties of natural gas are -0.56 and -0.33 and long run and short run income elasticities of natural gas demand is 16/59. </Abstract>
			<OtherAbstract Language="FA">Aim of this paper is to survey asymmetric effects of natural gas price on it&#039;s demand in industrial sector and demand function of natural gas in this sector is derived. This paper surveyed existence of asymmetric effects of natural gas price in koyck model for period of 1991-2013. Results of this paper revealed that effects of natural gas price on it&#039;s demand in industry sector is symmetric in this period and effect of income changes on natural gas demand in this sector is asymmetric. In this period, as estimation results long run and short run elasticties of natural gas are -0.56 and -0.33 and long run and short run income elasticities of natural gas demand is 16/59. </OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Asymmetric Effects</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Koyck Model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Price Elasticity and Income Elasticity of Natural Gas Demand</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1334_8edd72158ccd2a879f79cb2538568fdc.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Comparative analysis of the energy efficiency of Iran province&#039;s large industries using data envelopment analysis in the period 2008-2011</ArticleTitle>
<VernacularTitle>Comparative analysis of the energy efficiency of Iran province&#039;s large industries using data envelopment analysis in the period 2008-2011</VernacularTitle>
			<FirstPage>157</FirstPage>
			<LastPage>178</LastPage>
			<ELocationID EIdType="pii">1335</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Vahid</FirstName>
					<LastName>ShahabiNejad</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>04</Month>
					<Day>30</Day>
				</PubDate>
			</History>
		<Abstract>There are two well-known indicators used to study how energy inputs are efficiently used: One is energy intensity which measures the amount of energy consumption for every economic output produced in the economy, and the other is energy efficiency (or energy productivity) defined as economic output divided by energy input. These two indices only take energy into account as a single input to produce GDP output. In contrast, total-factor energy efficiency index (TFEEI) incorporates other key inputs such as capital and labor as multiple inputs so as to produce economic output. This article estimates TFEEI of Iranian provinces large industries using total-factor frameworks based on data envelopment analysis (DEA) in the period 1387-1390. Results indicate that Total average of TFEE in The Iranian provinces large industries is 0.4 percent. Furthermore Hormozgan, Tehran, Bushehr, Azerbayjan Sharghi and Kerman provinces have the greatest value of TFEE, while the lowest value of TFEE index considered in Khorasan Shomali, Chaharmohal Bakhtiari, Sistan and Baluchestan, Khorasan Jonubi and Lorestan provinces. Also, according to the computation results, the average of TFEE in large industries in Iran decreased during 1387-1389 and due to recent plan subsidies and energy price reform improved in 1390. </Abstract>
			<OtherAbstract Language="FA">There are two well-known indicators used to study how energy inputs are efficiently used: One is energy intensity which measures the amount of energy consumption for every economic output produced in the economy, and the other is energy efficiency (or energy productivity) defined as economic output divided by energy input. These two indices only take energy into account as a single input to produce GDP output. In contrast, total-factor energy efficiency index (TFEEI) incorporates other key inputs such as capital and labor as multiple inputs so as to produce economic output. This article estimates TFEEI of Iranian provinces large industries using total-factor frameworks based on data envelopment analysis (DEA) in the period 1387-1390. Results indicate that Total average of TFEE in The Iranian provinces large industries is 0.4 percent. Furthermore Hormozgan, Tehran, Bushehr, Azerbayjan Sharghi and Kerman provinces have the greatest value of TFEE, while the lowest value of TFEE index considered in Khorasan Shomali, Chaharmohal Bakhtiari, Sistan and Baluchestan, Khorasan Jonubi and Lorestan provinces. Also, according to the computation results, the average of TFEE in large industries in Iran decreased during 1387-1389 and due to recent plan subsidies and energy price reform improved in 1390. </OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Total-Factor Energy Efficiency Index (TFEEI)</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Data Envelopment Analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Iranian provinces large industries</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1335_9cb67ffb59554ab1dabb65bcb370ddd9.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A Study on the Effect of Education Inequality on Income Distribution in Iran</ArticleTitle>
<VernacularTitle>A Study on the Effect of Education Inequality on Income Distribution in Iran</VernacularTitle>
			<FirstPage>179</FirstPage>
			<LastPage>203</LastPage>
			<ELocationID EIdType="pii">1336</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Morteza</FirstName>
					<LastName>Afghah</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Maeede</FirstName>
					<LastName>Gharafi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Mahdi</FirstName>
					<LastName>Basirat</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>06</Month>
					<Day>02</Day>
				</PubDate>
			</History>
		<Abstract>Study on factors affecting income distribution is one of the most important goals of social scientists in developing countries. The role of education on income distribution, among others, is an issue that many social scientists have concentrated on it. In Iran, too, Income distribution is an important issue for many researchers and policy makers. In this paper, thus, it is tried to examine the effect of inequality in education on income distribution of Iran in the period of 1981-2011. Using Johansen-Juselius Approach and variables such as education Gini coefficient of labor force, and average schooling years as indices for inequality of education, we have examined the effect of unequal education on income distribution. Furthermore, the ratio of government expenditures on education, government size and per capita income are explanatory variables that are used in research models of this paper.
This study showed that Gini coefficient of education is a better variable explaining the effect of unequal education on income distribution, indicating a direct relationship between unequal education and unequal income distribution. However, there is an indirect relationship between the ration of government expenditures on education and Gini coefficient of Income. This study shows that moving toward equality in education will result in a better income distribution. Furthermore, an increase in education ratio of government expenditures has led to a better condition in income distribution, i.e. decrease in Gini coefficient.</Abstract>
			<OtherAbstract Language="FA">Study on factors affecting income distribution is one of the most important goals of social scientists in developing countries. The role of education on income distribution, among others, is an issue that many social scientists have concentrated on it. In Iran, too, Income distribution is an important issue for many researchers and policy makers. In this paper, thus, it is tried to examine the effect of inequality in education on income distribution of Iran in the period of 1981-2011. Using Johansen-Juselius Approach and variables such as education Gini coefficient of labor force, and average schooling years as indices for inequality of education, we have examined the effect of unequal education on income distribution. Furthermore, the ratio of government expenditures on education, government size and per capita income are explanatory variables that are used in research models of this paper.
This study showed that Gini coefficient of education is a better variable explaining the effect of unequal education on income distribution, indicating a direct relationship between unequal education and unequal income distribution. However, there is an indirect relationship between the ration of government expenditures on education and Gini coefficient of Income. This study shows that moving toward equality in education will result in a better income distribution. Furthermore, an increase in education ratio of government expenditures has led to a better condition in income distribution, i.e. decrease in Gini coefficient.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Unequal Education</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Income Distribution</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Average Years of Schooling</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Education Gini coefficient</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Johansen-Juselius Approach</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1336_3d779cae2d46cf6a8a99a35ba4167977.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>bu ali sina university</PublisherName>
				<JournalTitle>Journal of Applied Economics Studies in Iran</JournalTitle>
				<Issn>2322-2530</Issn>
				<Volume>4</Volume>
				<Issue>16</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Introducing an appropriate forecasting system to estimate the treatment demand at Imam Reza hospital of Urmia</ArticleTitle>
<VernacularTitle>Introducing an appropriate forecasting system to estimate the treatment demand at Imam Reza hospital of Urmia</VernacularTitle>
			<FirstPage>205</FirstPage>
			<LastPage>232</LastPage>
			<ELocationID EIdType="pii">1337</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Kiuomars</FirstName>
					<LastName>Shahbazi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Akbar</FirstName>
					<LastName>Pilevar Soltanahmadi</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>04</Month>
					<Day>20</Day>
				</PubDate>
			</History>
		<Abstract>The hospitals are responsible for maintaining the health of the population and devote himself a large part of health expenditure. Evidence shows that there is a vast prospect to improve and promote hospitals resources (financial and human). Awareness of the amount of future demand highly ensures optimal management of resources and quality of services in the health field. The aim of this study is to investigate the linear (ARIMA) and nonlinear (neural network MLP) models to estimate the treatment demand at Imam Reza hospital of Urmia, using data at different time intervals such as daily, weekly and monthly in different sections of the hospital. The results of this study indicate that ANN MLP nonlinear model has a good performance in predicting treatment demand and it is capable to provide more accurate forecasts than ARIMA model. Neural network MLP model with an average error of 24.96% compared to ARIMA model with an average error of 26.73% has a high predictive power. Also the estimation results of pediatric ward indicate that the ARIMA model compared to Neural network MLP model has more predictive power, the reason for this inconsistency with research hypotheses must be sought in low variance of this section.</Abstract>
			<OtherAbstract Language="FA">The hospitals are responsible for maintaining the health of the population and devote himself a large part of health expenditure. Evidence shows that there is a vast prospect to improve and promote hospitals resources (financial and human). Awareness of the amount of future demand highly ensures optimal management of resources and quality of services in the health field. The aim of this study is to investigate the linear (ARIMA) and nonlinear (neural network MLP) models to estimate the treatment demand at Imam Reza hospital of Urmia, using data at different time intervals such as daily, weekly and monthly in different sections of the hospital. The results of this study indicate that ANN MLP nonlinear model has a good performance in predicting treatment demand and it is capable to provide more accurate forecasts than ARIMA model. Neural network MLP model with an average error of 24.96% compared to ARIMA model with an average error of 26.73% has a high predictive power. Also the estimation results of pediatric ward indicate that the ARIMA model compared to Neural network MLP model has more predictive power, the reason for this inconsistency with research hypotheses must be sought in low variance of this section.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Treatment demand forecasting</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Emergency Department</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">ARMA Model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Neural –Networks</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://aes.basu.ac.ir/article_1337_e48e13207341b6bffb7fb1622282247b.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
