Compromise solution for economic-environmental decisions in agriculture
Identifieur interne : 000768 ( Istex/Corpus ); précédent : 000767; suivant : 000769Compromise solution for economic-environmental decisions in agriculture
Auteurs : P. G. Lakshminarayan ; Jay Dee Atwood ; Stanley R. Johnson ; Vince A. SpositoSource :
- Journal of Environmental Management [ 0301-4797 ] ; 1991.
English descriptors
Abstract
Least-cost production versus the environmental on- and off-site erosion damage of agriculture is evaluated in a policy context for a major Corn Belt watershed. Compromise programming, previously utilized in firm-level multi-criteria decision-making problems, is applied to a regional agricultural production model with environmental policy goal trade-offs. The crop sector model allocates land, water, labor, capital and commodity-program base acres to crop production. Production options include four conservation practices, three tillage methods and several crop rotations. Crop yield and fertilizer levels are dependent upon erosion. Cropping options selected allow for both wind and water erosion.The vector of objectives include three minimization functions: current production cost, future value of productivity loss and sediment damage. Vector optimization technique was used to generate the payoff matrix containing efficient but simultaneously unobtainable solutions. Given the ideal but infeasible solution vector we generated efficient solutions in the compromise subset corresponding to the L1, L2 and L∞ metrics. Trade-off relations were developed using the non-inferior set estimation technique.
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DOI: 10.1016/S0301-4797(05)80047-7
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<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Compromise solution for economic-environmental decisions in agriculture</title><author><name sortKey="Lakshminarayan, P G" sort="Lakshminarayan, P G" uniqKey="Lakshminarayan P" first="P. G." last="Lakshminarayan">P. G. Lakshminarayan</name><affiliation><mods:affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</mods:affiliation></affiliation></author><author><name sortKey="Atwood, Jay Dee" sort="Atwood, Jay Dee" uniqKey="Atwood J" first="Jay Dee" last="Atwood">Jay Dee Atwood</name><affiliation><mods:affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</mods:affiliation></affiliation></author><author><name sortKey="Johnson, Stanley R" sort="Johnson, Stanley R" uniqKey="Johnson S" first="Stanley R." last="Johnson">Stanley R. Johnson</name><affiliation><mods:affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</mods:affiliation></affiliation></author><author><name sortKey="Sposito, Vince A" sort="Sposito, Vince A" uniqKey="Sposito V" first="Vince A." last="Sposito">Vince A. 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G." last="Lakshminarayan">P. G. Lakshminarayan</name><affiliation><mods:affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</mods:affiliation></affiliation></author><author><name sortKey="Atwood, Jay Dee" sort="Atwood, Jay Dee" uniqKey="Atwood J" first="Jay Dee" last="Atwood">Jay Dee Atwood</name><affiliation><mods:affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</mods:affiliation></affiliation></author><author><name sortKey="Johnson, Stanley R" sort="Johnson, Stanley R" uniqKey="Johnson S" first="Stanley R." last="Johnson">Stanley R. Johnson</name><affiliation><mods:affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</mods:affiliation></affiliation></author><author><name sortKey="Sposito, Vince A" sort="Sposito, Vince A" uniqKey="Sposito V" first="Vince A." last="Sposito">Vince A. Sposito</name><affiliation><mods:affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Journal of Environmental Management</title><title level="j" type="abbrev">YJEMA</title><idno type="ISSN">0301-4797</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1991">1991</date><biblScope unit="volume">33</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="51">51</biblScope><biblScope unit="page" to="64">64</biblScope></imprint><idno type="ISSN">0301-4797</idno></series><idno type="istex">889B1B62B1EFEDDDE2A5EC914CAF0F0781634924</idno><idno type="DOI">10.1016/S0301-4797(05)80047-7</idno><idno type="PII">S0301-4797(05)80047-7</idno><idno type="ArticleID">05800477</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0301-4797</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>compromise program</term><term>multi-criteria</term><term>soil erosion</term><term>vector optimization</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Least-cost production versus the environmental on- and off-site erosion damage of agriculture is evaluated in a policy context for a major Corn Belt watershed. Compromise programming, previously utilized in firm-level multi-criteria decision-making problems, is applied to a regional agricultural production model with environmental policy goal trade-offs. The crop sector model allocates land, water, labor, capital and commodity-program base acres to crop production. Production options include four conservation practices, three tillage methods and several crop rotations. Crop yield and fertilizer levels are dependent upon erosion. Cropping options selected allow for both wind and water erosion.The vector of objectives include three minimization functions: current production cost, future value of productivity loss and sediment damage. Vector optimization technique was used to generate the payoff matrix containing efficient but simultaneously unobtainable solutions. Given the ideal but infeasible solution vector we generated efficient solutions in the compromise subset corresponding to the L1, L2 and L∞ metrics. Trade-off relations were developed using the non-inferior set estimation technique.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>P.G. Lakshminarayan</name><affiliations><json:string>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</json:string></affiliations></json:item><json:item><name>Jay Dee Atwood</name><affiliations><json:string>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</json:string></affiliations></json:item><json:item><name>Stanley R. Johnson</name><affiliations><json:string>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</json:string></affiliations></json:item><json:item><name>Vince A. 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Compromise programming, previously utilized in firm-level multi-criteria decision-making problems, is applied to a regional agricultural production model with environmental policy goal trade-offs. The crop sector model allocates land, water, labor, capital and commodity-program base acres to crop production. Production options include four conservation practices, three tillage methods and several crop rotations. Crop yield and fertilizer levels are dependent upon erosion. Cropping options selected allow for both wind and water erosion.The vector of objectives include three minimization functions: current production cost, future value of productivity loss and sediment damage. Vector optimization technique was used to generate the payoff matrix containing efficient but simultaneously unobtainable solutions. Given the ideal but infeasible solution vector we generated efficient solutions in the compromise subset corresponding to the L1, L2 and L∞ metrics. 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Compromise programming, previously utilized in firm-level multi-criteria decision-making problems, is applied to a regional agricultural production model with environmental policy goal trade-offs. The crop sector model allocates land, water, labor, capital and commodity-program base acres to crop production. Production options include four conservation practices, three tillage methods and several crop rotations. Crop yield and fertilizer levels are dependent upon erosion. Cropping options selected allow for both wind and water erosion.The vector of objectives include three minimization functions: current production cost, future value of productivity loss and sediment damage. Vector optimization technique was used to generate the payoff matrix containing efficient but simultaneously unobtainable solutions. Given the ideal but infeasible solution vector we generated efficient solutions in the compromise subset corresponding to the L1, L2 and L∞ metrics. Trade-off relations were developed using the non-inferior set estimation technique.</p></abstract><textClass xml:lang="en"><keywords scheme="keyword"><list><head>Keywords</head><item><term>compromise program</term></item><item><term>multi-criteria</term></item><item><term>soil erosion</term></item><item><term>vector optimization</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="1991">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/889B1B62B1EFEDDDE2A5EC914CAF0F0781634924/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Elsevier doc found" wicri:toSee="Elsevier, no converted or simple article"><istex:xmlDeclaration>version="1.0" encoding="utf-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//ES//DTD journal article DTD version 5.0.1//EN//XML" URI="art501.dtd" name="istex:docType"></istex:docType><istex:document><article version="5.0" xml:lang="en" docsubtype="fla"><item-info><jid>YJEMA</jid><aid>05800477</aid><ce:pii>S0301-4797(05)80047-7</ce:pii><ce:doi>10.1016/S0301-4797(05)80047-7</ce:doi><ce:copyright type="unknown" year="1991">Academic Press Limited</ce:copyright></item-info><head><ce:article-footnote><ce:label>*</ce:label><ce:note-para>Journal Paper No. J-13957 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa. Project No. 2872.</ce:note-para></ce:article-footnote><ce:title>Compromise solution for economic-environmental decisions in agriculture</ce:title><ce:author-group><ce:author><ce:given-name>P.G.</ce:given-name><ce:surname>Lakshminarayan</ce:surname></ce:author><ce:author><ce:given-name>Jay Dee</ce:given-name><ce:surname>Atwood</ce:surname></ce:author><ce:author><ce:given-name>Stanley R.</ce:given-name><ce:surname>Johnson</ce:surname></ce:author><ce:author><ce:given-name>Vince A.</ce:given-name><ce:surname>Sposito</ce:surname></ce:author><ce:affiliation id="aff1"><ce:textfn>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</ce:textfn></ce:affiliation></ce:author-group><ce:date-received day="12" month="3" year="1990"></ce:date-received><ce:abstract id="ab1" class="author" xml:lang="en"><ce:abstract-sec><ce:simple-para>Least-cost production versus the environmental on- and off-site erosion damage of agriculture is evaluated in a policy context for a major Corn Belt watershed. Compromise programming, previously utilized in firm-level multi-criteria decision-making problems, is applied to a regional agricultural production model with environmental policy goal trade-offs. The crop sector model allocates land, water, labor, capital and commodity-program base acres to crop production. Production options include four conservation practices, three tillage methods and several crop rotations. Crop yield and fertilizer levels are dependent upon erosion. Cropping options selected allow for both wind and water erosion.</ce:simple-para><ce:simple-para>The vector of objectives include three minimization functions: current production cost, future value of productivity loss and sediment damage. Vector optimization technique was used to generate the payoff matrix containing efficient but simultaneously unobtainable solutions. Given the ideal but infeasible solution vector we generated efficient solutions in the compromise subset corresponding to the <ce:italic>L<ce:inf loc="post">1</ce:inf>, L<ce:inf loc="post">2</ce:inf></ce:italic> and <ce:italic>L</ce:italic><ce:inf loc="post">∞</ce:inf> metrics. Trade-off relations were developed using the non-inferior set estimation technique.</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords class="keyword" xml:lang="en"><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>compromise program</ce:text></ce:keyword><ce:keyword><ce:text>multi-criteria</ce:text></ce:keyword><ce:keyword><ce:text>soil erosion</ce:text></ce:keyword><ce:keyword><ce:text>vector optimization</ce:text></ce:keyword></ce:keywords></head><tail><ce:bibliography><ce:section-title>References</ce:section-title><ce:bibliography-sec><ce:bib-reference id="bib1"><ce:label>AAEA, 1986</ce:label><sb:reference><sb:comment>Occasional Paper No. 2</sb:comment><sb:contribution langtype="en"><sb:authors><sb:author><ce:surname>AAEA</ce:surname></sb:author></sb:authors></sb:contribution><sb:host><sb:edited-book><sb:book-series><sb:series><sb:title><sb:maintitle>Soil Erosion and Soil Conservation Policy in the United States</sb:maintitle></sb:title></sb:series></sb:book-series><sb:date>1986</sb:date><sb:publisher><sb:name>American Agricultural Economic Association. Soil Conservation Policy Task Force</sb:name></sb:publisher></sb:edited-book></sb:host></sb:reference></ce:bib-reference><ce:bib-reference id="bib2"><ce:label>Braden, et al, 1989</ce:label><sb:reference><sb:contribution langtype="en"><sb:authors><sb:author><ce:surname>Braden</ce:surname><ce:given-name>J.B.</ce:given-name></sb:author><sb:author><ce:surname>Johnson</ce:surname><ce:given-name>G.</ce:given-name></sb:author><sb:author><ce:surname>Bouzaher</ce:surname><ce:given-name>A.</ce:given-name></sb:author><sb:author><ce:surname>Miltz</ce:surname><ce:given-name>D.</ce:given-name></sb:author></sb:authors><sb:title><sb:maintitle>Optimal spatial management of agricultural pollution</sb:maintitle></sb:title></sb:contribution><sb:host><sb:issue><sb:series><sb:title><sb:maintitle>American Journal of Agricultural Economics</sb:maintitle></sb:title><sb:volume-nr>71</sb:volume-nr></sb:series><sb:date>1989</sb:date></sb:issue><sb:pages><sb:first-page>404</sb:first-page><sb:last-page>413</sb:last-page></sb:pages></sb:host></sb:reference></ce:bib-reference><ce:bib-reference id="bib3"><ce:label>Burt, 1981</ce:label><sb:reference><sb:contribution langtype="en"><sb:authors><sb:author><ce:surname>Burt</ce:surname><ce:given-name>O.</ce:given-name></sb:author></sb:authors><sb:title><sb:maintitle>Farm level economics of soil conservation in the Palouse area of the Northwest</sb:maintitle></sb:title></sb:contribution><sb:host><sb:issue><sb:series><sb:title><sb:maintitle>American Journal of Agricultural Economics</sb:maintitle></sb:title><sb:volume-nr>63</sb:volume-nr></sb:series><sb:date>1981</sb:date></sb:issue><sb:pages><sb:first-page>83</sb:first-page><sb:last-page>91</sb:last-page></sb:pages></sb:host></sb:reference></ce:bib-reference><ce:bib-reference id="bib4"><ce:label>Clark, et al, 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type="family">Lakshminarayan</namePart><affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jay Dee</namePart><namePart type="family">Atwood</namePart><affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Stanley R.</namePart><namePart type="family">Johnson</namePart><affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Vince A.</namePart><namePart type="family">Sposito</namePart><affiliation>Center for Agricultural and Rural Development, Department of Economics, Iowa State University, Ames, Iowa 50011, U.S.A.</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="Full-length article"></genre><originInfo><publisher>ELSEVIER</publisher><dateIssued encoding="w3cdtf">1991</dateIssued><copyrightDate encoding="w3cdtf">1991</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Least-cost production versus the environmental on- and off-site erosion damage of agriculture is evaluated in a policy context for a major Corn Belt watershed. Compromise programming, previously utilized in firm-level multi-criteria decision-making problems, is applied to a regional agricultural production model with environmental policy goal trade-offs. The crop sector model allocates land, water, labor, capital and commodity-program base acres to crop production. Production options include four conservation practices, three tillage methods and several crop rotations. Crop yield and fertilizer levels are dependent upon erosion. Cropping options selected allow for both wind and water erosion.The vector of objectives include three minimization functions: current production cost, future value of productivity loss and sediment damage. Vector optimization technique was used to generate the payoff matrix containing efficient but simultaneously unobtainable solutions. Given the ideal but infeasible solution vector we generated efficient solutions in the compromise subset corresponding to the L1, L2 and L∞ metrics. Trade-off relations were developed using the non-inferior set estimation technique.</abstract><note>Journal Paper No. J-13957 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa. Project No. 2872.</note><subject lang="en"><genre>Keywords</genre><topic>compromise program</topic><topic>multi-criteria</topic><topic>soil erosion</topic><topic>vector optimization</topic></subject><relatedItem type="host"><titleInfo><title>Journal of Environmental Management</title></titleInfo><titleInfo type="abbreviated"><title>YJEMA</title></titleInfo><genre type="journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">199107</dateIssued></originInfo><identifier type="ISSN">0301-4797</identifier><identifier type="PII">S0301-4797(05)X8043-4</identifier><part><date>199107</date><detail type="volume"><number>33</number><caption>vol.</caption></detail><detail type="issue"><number>1</number><caption>no.</caption></detail><extent unit="issue pages"><start>1</start><end>104</end></extent><extent unit="pages"><start>51</start><end>64</end></extent></part></relatedItem><identifier type="istex">889B1B62B1EFEDDDE2A5EC914CAF0F0781634924</identifier><identifier type="DOI">10.1016/S0301-4797(05)80047-7</identifier><identifier type="PII">S0301-4797(05)80047-7</identifier><identifier type="ArticleID">05800477</identifier><accessCondition type="use and reproduction" contentType="copyright">©1991 Academic Press Limited</accessCondition><recordInfo><recordContentSource>ELSEVIER</recordContentSource><recordOrigin>Academic Press Limited, ©1991</recordOrigin></recordInfo></mods></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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