Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data
Identifieur interne : 000790 ( Istex/Corpus ); précédent : 000789; suivant : 000791Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data
Auteurs : Seong-Hoon Cho ; Zhuo Chen ; Steven T. Yen ; Burton C. EnglishSource :
- Papers in Regional Science [ 1056-8190 ] ; 2007-03.
English descriptors
- KwdEn :
Abstract
Abstract. An agricultural production function is estimated using a Chinese county‐level dataset along with associated geographic information. County‐specific output‐input elasticities are computed using the geographically weighted regression (GWR) and mapped with the geographical information system (GIS). A comparison of the ordinary least squares and GWR estimates confirms that allowing spatial variation in the parameters improves model fit of the agricultural production function, and provides valuable insights into the relative importance of inputs in different regions. Moran's indices reveal the spatial dependence of output per unit of land, and four inputs across regions. Mappings of GWR estimates help to detect a few clusters of high output‐input elasticities: for labour in the Northeast, North, Southwest and Northwest China, for land in the Central and Southwest, for mechanical power in the North, Northwest and coastal area of the East and South and for fertiliser in the East. The county‐specific scale elasticities suggest constant return to scale is likely to hold in the Central, East, Southwest and South.
Url:
DOI: 10.1111/j.1435-5957.2007.00113.x
Links to Exploration step
ISTEX:9E6B06D2F41C7C3716A22848EC64171F33C9E80DLe document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data</title><author><name sortKey="Cho, Seong Oon" sort="Cho, Seong Oon" uniqKey="Cho S" first="Seong-Hoon" last="Cho">Seong-Hoon Cho</name><affiliation><mods:affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</mods:affiliation></affiliation></author><author><name sortKey="Chen, Zhuo" sort="Chen, Zhuo" uniqKey="Chen Z" first="Zhuo" last="Chen">Zhuo Chen</name><affiliation><mods:affiliation>Chicago Center of Excellence in Health Promotion Economics, University of Chicago, Chicago, IL 60637, USA (e‐mail: zchen1@cdc.gov)</mods:affiliation></affiliation></author><author><name sortKey="Yen, Steven T" sort="Yen, Steven T" uniqKey="Yen S" first="Steven T." last="Yen">Steven T. Yen</name><affiliation><mods:affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</mods:affiliation></affiliation></author><author><name sortKey="English, Burton C" sort="English, Burton C" uniqKey="English B" first="Burton C." last="English">Burton C. English</name><affiliation><mods:affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:9E6B06D2F41C7C3716A22848EC64171F33C9E80D</idno><date when="2007" year="2007">2007</date><idno type="doi">10.1111/j.1435-5957.2007.00113.x</idno><idno type="url">https://api.istex.fr/document/9E6B06D2F41C7C3716A22848EC64171F33C9E80D/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000790</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000790</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data</title><author><name sortKey="Cho, Seong Oon" sort="Cho, Seong Oon" uniqKey="Cho S" first="Seong-Hoon" last="Cho">Seong-Hoon Cho</name><affiliation><mods:affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</mods:affiliation></affiliation></author><author><name sortKey="Chen, Zhuo" sort="Chen, Zhuo" uniqKey="Chen Z" first="Zhuo" last="Chen">Zhuo Chen</name><affiliation><mods:affiliation>Chicago Center of Excellence in Health Promotion Economics, University of Chicago, Chicago, IL 60637, USA (e‐mail: zchen1@cdc.gov)</mods:affiliation></affiliation></author><author><name sortKey="Yen, Steven T" sort="Yen, Steven T" uniqKey="Yen S" first="Steven T." last="Yen">Steven T. Yen</name><affiliation><mods:affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</mods:affiliation></affiliation></author><author><name sortKey="English, Burton C" sort="English, Burton C" uniqKey="English B" first="Burton C." last="English">Burton C. English</name><affiliation><mods:affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Papers in Regional Science</title><idno type="ISSN">1056-8190</idno><idno type="eISSN">1435-5957</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><pubPlace>Oxford, UK</pubPlace><date type="published" when="2007-03">2007-03</date><biblScope unit="volume">86</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="139">139</biblScope><biblScope unit="page" to="157">157</biblScope></imprint><idno type="ISSN">1056-8190</idno></series><idno type="istex">9E6B06D2F41C7C3716A22848EC64171F33C9E80D</idno><idno type="DOI">10.1111/j.1435-5957.2007.00113.x</idno><idno type="ArticleID">PIRS113</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1056-8190</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Agricultural production</term><term>China</term><term>O18</term><term>Q10</term><term>R12</term><term>geographically weighted regression</term><term>output‐input elasticity</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract">Abstract. An agricultural production function is estimated using a Chinese county‐level dataset along with associated geographic information. County‐specific output‐input elasticities are computed using the geographically weighted regression (GWR) and mapped with the geographical information system (GIS). A comparison of the ordinary least squares and GWR estimates confirms that allowing spatial variation in the parameters improves model fit of the agricultural production function, and provides valuable insights into the relative importance of inputs in different regions. Moran's indices reveal the spatial dependence of output per unit of land, and four inputs across regions. Mappings of GWR estimates help to detect a few clusters of high output‐input elasticities: for labour in the Northeast, North, Southwest and Northwest China, for land in the Central and Southwest, for mechanical power in the North, Northwest and coastal area of the East and South and for fertiliser in the East. The county‐specific scale elasticities suggest constant return to scale is likely to hold in the Central, East, Southwest and South.</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Seong‐Hoon Cho</name><affiliations><json:string>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</json:string></affiliations></json:item><json:item><name>Zhuo Chen</name><affiliations><json:string>Chicago Center of Excellence in Health Promotion Economics, University of Chicago, Chicago, IL 60637, USA (e‐mail: zchen1@cdc.gov)</json:string></affiliations></json:item><json:item><name>Steven T. Yen</name><affiliations><json:string>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</json:string></affiliations></json:item><json:item><name>Burton C. English</name><affiliations><json:string>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>O18</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Q10</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>R12</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Agricultural production</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>China</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>geographically weighted regression</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>output‐input elasticity</value></json:item></subject><articleId><json:string>PIRS113</json:string></articleId><language><json:string>eng</json:string></language><originalGenre><json:string>technicalNote</json:string></originalGenre><abstract>Abstract. An agricultural production function is estimated using a Chinese county‐level dataset along with associated geographic information. County‐specific output‐input elasticities are computed using the geographically weighted regression (GWR) and mapped with the geographical information system (GIS). A comparison of the ordinary least squares and GWR estimates confirms that allowing spatial variation in the parameters improves model fit of the agricultural production function, and provides valuable insights into the relative importance of inputs in different regions. Moran's indices reveal the spatial dependence of output per unit of land, and four inputs across regions. Mappings of GWR estimates help to detect a few clusters of high output‐input elasticities: for labour in the Northeast, North, Southwest and Northwest China, for land in the Central and Southwest, for mechanical power in the North, Northwest and coastal area of the East and South and for fertiliser in the East. The county‐specific scale elasticities suggest constant return to scale is likely to hold in the Central, East, Southwest and South.</abstract><qualityIndicators><score>6.968</score><pdfVersion>1.2</pdfVersion><pdfPageSize>430.866 x 649.134 pts</pdfPageSize><refBibsNative>true</refBibsNative><abstractCharCount>1131</abstractCharCount><pdfWordCount>5679</pdfWordCount><pdfCharCount>36410</pdfCharCount><pdfPageCount>19</pdfPageCount><abstractWordCount>164</abstractWordCount></qualityIndicators><title>Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data</title><genre><json:string>other</json:string></genre><host><volume>86</volume><publisherId><json:string>PIRS</json:string></publisherId><pages><total>19</total><last>157</last><first>139</first></pages><issn><json:string>1056-8190</json:string></issn><issue>1</issue><genre><json:string>journal</json:string></genre><language><json:string>unknown</json:string></language><eissn><json:string>1435-5957</json:string></eissn><title>Papers in Regional Science</title><doi><json:string>10.1111/(ISSN)1435-5957</json:string></doi></host><categories><wos><json:string>social science</json:string><json:string>geography</json:string><json:string>environmental studies</json:string><json:string>economics</json:string></wos><scienceMetrix><json:string>applied sciences</json:string><json:string>built environment & design</json:string><json:string>urban & regional planning</json:string></scienceMetrix></categories><publicationDate>2007</publicationDate><copyrightDate>2007</copyrightDate><doi><json:string>10.1111/j.1435-5957.2007.00113.x</json:string></doi><id>9E6B06D2F41C7C3716A22848EC64171F33C9E80D</id><score>0.0399037</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/9E6B06D2F41C7C3716A22848EC64171F33C9E80D/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/9E6B06D2F41C7C3716A22848EC64171F33C9E80D/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/9E6B06D2F41C7C3716A22848EC64171F33C9E80D/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a" type="main" xml:lang="en">Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>Blackwell Publishing Ltd</publisher><pubPlace>Oxford, UK</pubPlace><availability><p>WILEY</p></availability><date>2007</date></publicationStmt><notesStmt><note type="content">*The authors thank, without implicating, the Editor‐in‐Chief and three anonymous referees for helpful comments and suggestions.</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data</title><author xml:id="author-1"><persName><forename type="first">Seong‐Hoon</forename><surname>Cho</surname></persName><affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</affiliation></author><author xml:id="author-2"><persName><forename type="first">Zhuo</forename><surname>Chen</surname></persName><affiliation>Chicago Center of Excellence in Health Promotion Economics, University of Chicago, Chicago, IL 60637, USA (e‐mail: zchen1@cdc.gov)</affiliation></author><author xml:id="author-3"><persName><forename type="first">Steven T.</forename><surname>Yen</surname></persName><affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</affiliation></author><author xml:id="author-4"><persName><forename type="first">Burton C.</forename><surname>English</surname></persName><affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</affiliation></author></analytic><monogr><title level="j">Papers in Regional Science</title><idno type="pISSN">1056-8190</idno><idno type="eISSN">1435-5957</idno><idno type="DOI">10.1111/(ISSN)1435-5957</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><pubPlace>Oxford, UK</pubPlace><date type="published" when="2007-03"></date><biblScope unit="volume">86</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="139">139</biblScope><biblScope unit="page" to="157">157</biblScope></imprint></monogr><idno type="istex">9E6B06D2F41C7C3716A22848EC64171F33C9E80D</idno><idno type="DOI">10.1111/j.1435-5957.2007.00113.x</idno><idno type="ArticleID">PIRS113</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2007</date></creation><langUsage><language ident="en">en</language></langUsage><abstract><p>Abstract. An agricultural production function is estimated using a Chinese county‐level dataset along with associated geographic information. County‐specific output‐input elasticities are computed using the geographically weighted regression (GWR) and mapped with the geographical information system (GIS). A comparison of the ordinary least squares and GWR estimates confirms that allowing spatial variation in the parameters improves model fit of the agricultural production function, and provides valuable insights into the relative importance of inputs in different regions. Moran's indices reveal the spatial dependence of output per unit of land, and four inputs across regions. Mappings of GWR estimates help to detect a few clusters of high output‐input elasticities: for labour in the Northeast, North, Southwest and Northwest China, for land in the Central and Southwest, for mechanical power in the North, Northwest and coastal area of the East and South and for fertiliser in the East. The county‐specific scale elasticities suggest constant return to scale is likely to hold in the Central, East, Southwest and South.</p></abstract><textClass xml:lang="en"><keywords scheme="keyword"><list><head>keywords</head><item><term>O18</term></item><item><term>Q10</term></item><item><term>R12</term></item></list></keywords></textClass><textClass xml:lang="en"><keywords scheme="keyword"><list><head>keywords</head><item><term>Agricultural production</term></item><item><term>China</term></item><item><term>geographically weighted regression</term></item><item><term>output‐input elasticity</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2007-03">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/9E6B06D2F41C7C3716A22848EC64171F33C9E80D/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Wiley, elements deleted: body"><istex:xmlDeclaration>version="1.0" encoding="UTF-8" standalone="yes"</istex:xmlDeclaration><istex:document><component version="2.0" type="serialArticle" xml:lang="en"><header><publicationMeta level="product"><publisherInfo><publisherName>Blackwell Publishing Ltd</publisherName><publisherLoc>Oxford, UK</publisherLoc></publisherInfo><doi origin="wiley" registered="yes">10.1111/(ISSN)1435-5957</doi><issn type="print">1056-8190</issn><issn type="electronic">1435-5957</issn><idGroup><id type="product" value="PIRS"></id><id type="publisherDivision" value="ST"></id></idGroup><titleGroup><title type="main" sort="PAPERS IN REGIONAL SCIENCE">Papers in Regional Science</title></titleGroup></publicationMeta><publicationMeta level="part" position="03001"><doi origin="wiley">10.1111/pirs.2007.86.issue-1</doi><numberingGroup><numbering type="journalVolume" number="86">86</numbering><numbering type="journalIssue" number="1">1</numbering></numberingGroup><coverDate startDate="2007-03">March 2007</coverDate></publicationMeta><publicationMeta level="unit" type="technicalNote" position="8" status="forIssue"><doi origin="wiley">10.1111/j.1435-5957.2007.00113.x</doi><idGroup><id type="unit" value="PIRS113"></id></idGroup><countGroup><count type="pageTotal" number="19"></count></countGroup><titleGroup><title type="tocHeading1">RESEARCH NOTES</title></titleGroup><eventGroup><event type="firstOnline" date="2007-03-20"></event><event type="publishedOnlineFinalForm" date="2007-03-20"></event><event type="xmlConverted" agent="Converter:BPG_TO_WML3G version:2.3.2 mode:FullText source:FullText result:FullText" date="2010-03-04"></event><event type="xmlConverted" agent="Converter:WILEY_ML3G_TO_WILEY_ML3GV2 version:3.8.8" date="2014-02-07"></event><event type="xmlConverted" agent="Converter:WML3G_To_WML3G version:4.1.7 mode:FullText,remove_FC" date="2014-11-03"></event></eventGroup><numberingGroup><numbering type="pageFirst" number="139">139</numbering><numbering type="pageLast" number="157">157</numbering></numberingGroup><linkGroup><link type="toTypesetVersion" href="file:PIRS.PIRS113.pdf"></link></linkGroup></publicationMeta><contentMeta><unparsedEditorialHistory>Received: 15 May 2005 / Accepted: 3 October 2006</unparsedEditorialHistory><countGroup><count type="figureTotal" number="7"></count><count type="tableTotal" number="5"></count><count type="formulaTotal" number="6"></count><count type="referenceTotal" number="37"></count><count type="wordTotal" number="6166"></count><count type="linksPubMed" number="0"></count><count type="linksCrossRef" number="0"></count></countGroup><titleGroup><title type="main">Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data<link href="#fn6">*</link></title><title type="shortAuthors">S.‐H. Cho et al.</title><title type="short">Spatial variation of output‐input elasticities</title></titleGroup><creators><creator creatorRole="author" xml:id="cr1" affiliationRef="#a1"><personName><givenNames>Seong‐Hoon</givenNames><familyName>Cho</familyName></personName></creator><creator creatorRole="author" xml:id="cr2" affiliationRef="#a2"><personName><givenNames>Zhuo</givenNames><familyName>Chen</familyName></personName></creator><creator creatorRole="author" xml:id="cr3" affiliationRef="#a1"><personName><givenNames>Steven T.</givenNames><familyName>Yen</familyName></personName></creator><creator creatorRole="author" xml:id="cr4" affiliationRef="#a1"><personName><givenNames>Burton C.</givenNames><familyName>English</familyName></personName></creator></creators><affiliationGroup><affiliation xml:id="a1" countryCode="US"><unparsedAffiliation> Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {<email>scho9@utk.edu</email>, <email>syen@utk.edu</email> and <email>benglish@utk.edu</email>)</unparsedAffiliation></affiliation><affiliation xml:id="a2"><unparsedAffiliation> Chicago Center of Excellence in Health Promotion Economics, University of Chicago, Chicago, IL 60637, USA (e‐mail: <email>zchen1@cdc.gov</email>)</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup xml:lang="en"><keyword xml:id="k1">O18</keyword><keyword xml:id="k2">Q10</keyword><keyword xml:id="k3">R12</keyword></keywordGroup><keywordGroup xml:lang="en"><keyword xml:id="k4">Agricultural production</keyword><keyword xml:id="k5">China</keyword><keyword xml:id="k6">geographically weighted regression</keyword><keyword xml:id="k7">output‐input elasticity</keyword></keywordGroup><abstractGroup><abstract type="main" xml:lang="en"><p><b>Abstract. </b> An agricultural production function is estimated using a Chinese county‐level dataset along with associated geographic information. County‐specific output‐input elasticities are computed using the geographically weighted regression (GWR) and mapped with the geographical information system (GIS). A comparison of the ordinary least squares and GWR estimates confirms that allowing spatial variation in the parameters improves model fit of the agricultural production function, and provides valuable insights into the relative importance of inputs in different regions. Moran's indices reveal the spatial dependence of output per unit of land, and four inputs across regions. Mappings of GWR estimates help to detect a few clusters of high output‐input elasticities: for labour in the Northeast, North, Southwest and Northwest China, for land in the Central and Southwest, for mechanical power in the North, Northwest and coastal area of the East and South and for fertiliser in the East. The county‐specific scale elasticities suggest constant return to scale is likely to hold in the Central, East, Southwest and South.</p></abstract></abstractGroup></contentMeta><noteGroup><note xml:id="fn6"><label>* </label><p> The authors thank, without implicating, the Editor‐in‐Chief and three anonymous referees for helpful comments and suggestions.</p></note></noteGroup></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>Spatial variation of output‐input elasticities</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data*</title></titleInfo><name type="personal"><namePart type="given">Seong‐Hoon</namePart><namePart type="family">Cho</namePart><affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Zhuo</namePart><namePart type="family">Chen</namePart><affiliation>Chicago Center of Excellence in Health Promotion Economics, University of Chicago, Chicago, IL 60637, USA (e‐mail: zchen1@cdc.gov)</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Steven T.</namePart><namePart type="family">Yen</namePart><affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Burton C.</namePart><namePart type="family">English</namePart><affiliation>Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996, USA (e‐mail: {scho9@utk.edu, syen@utk.edu and benglish@utk.edu)</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="other" displayLabel="technicalNote"></genre><originInfo><publisher>Blackwell Publishing Ltd</publisher><place><placeTerm type="text">Oxford, UK</placeTerm></place><dateIssued encoding="w3cdtf">2007-03</dateIssued><edition>Received: 15 May 2005 / Accepted: 3 October 2006</edition><copyrightDate encoding="w3cdtf">2007</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="figures">7</extent><extent unit="tables">5</extent><extent unit="formulas">6</extent><extent unit="references">37</extent><extent unit="words">6166</extent></physicalDescription><abstract>Abstract. An agricultural production function is estimated using a Chinese county‐level dataset along with associated geographic information. County‐specific output‐input elasticities are computed using the geographically weighted regression (GWR) and mapped with the geographical information system (GIS). A comparison of the ordinary least squares and GWR estimates confirms that allowing spatial variation in the parameters improves model fit of the agricultural production function, and provides valuable insights into the relative importance of inputs in different regions. Moran's indices reveal the spatial dependence of output per unit of land, and four inputs across regions. Mappings of GWR estimates help to detect a few clusters of high output‐input elasticities: for labour in the Northeast, North, Southwest and Northwest China, for land in the Central and Southwest, for mechanical power in the North, Northwest and coastal area of the East and South and for fertiliser in the East. The county‐specific scale elasticities suggest constant return to scale is likely to hold in the Central, East, Southwest and South.</abstract><note type="content">*The authors thank, without implicating, the Editor‐in‐Chief and three anonymous referees for helpful comments and suggestions.</note><subject lang="en"><genre>keywords</genre><topic>O18</topic><topic>Q10</topic><topic>R12</topic></subject><subject lang="en"><genre>keywords</genre><topic>Agricultural production</topic><topic>China</topic><topic>geographically weighted regression</topic><topic>output‐input elasticity</topic></subject><relatedItem type="host"><titleInfo><title>Papers in Regional Science</title></titleInfo><genre type="journal">journal</genre><identifier type="ISSN">1056-8190</identifier><identifier type="eISSN">1435-5957</identifier><identifier type="DOI">10.1111/(ISSN)1435-5957</identifier><identifier type="PublisherID">PIRS</identifier><part><date>2007</date><detail type="volume"><caption>vol.</caption><number>86</number></detail><detail type="issue"><caption>no.</caption><number>1</number></detail><extent unit="pages"><start>139</start><end>157</end><total>19</total></extent></part></relatedItem><identifier type="istex">9E6B06D2F41C7C3716A22848EC64171F33C9E80D</identifier><identifier type="DOI">10.1111/j.1435-5957.2007.00113.x</identifier><identifier type="ArticleID">PIRS113</identifier><recordInfo><recordContentSource>WILEY</recordContentSource><recordOrigin>Blackwell Publishing Ltd</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Agronomie/explor/SisAgriV1/Data/Istex/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000790 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Istex/Corpus/biblio.hfd -nk 000790 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Agronomie
|area= SisAgriV1
|flux= Istex
|étape= Corpus
|type= RBID
|clé= ISTEX:9E6B06D2F41C7C3716A22848EC64171F33C9E80D
|texte= Spatial variation of output‐input elasticities: Evidence from Chinese county‐level agricultural production data
}}
| This area was generated with Dilib version V0.6.28. |  |