Gestão financeira e econômica da propriedade rural com multiproduto
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFSCAR |
Texto Completo: | https://repositorio.ufscar.br/handle/ufscar/3404 |
Resumo: | Farmers have always neglected management procedures in their enterprises in detriment to initiatives regarding production technology. Overall, producers and technicians know the answer to what, how and when to produce, but they don t know the cost or profitability of this technology. The present study shows the importance of the sustainability of agricultural enterprises with reduced governmental intervention and the risk involved in a double crop production system. Therefore, the aim is to propose a model to support the decision-making process, focused on production planning in a representative multi-product farm under conditions of risk. Using quantitative applied research, a theoretical model of agricultural planning was combined with operational research to explain and understand different allocations of resources within the decision-making process. For that purpose, two production regions of Mato Grosso state in Brazil were selected: Sorriso (SRS) and Campo Novo do Parecis (CNP). In SRS, a production system with 76.9% early soybean (SP) and 23.1% soybean (SN) for the first harvest and 76.9% corn (MS) for the second harvest generated a high gross margin and risk. On the other hand, a production system with 90% SN and 10% SP implied less risk. Diversifying the cultivated area with SP and SN in the first crop and MS in the second crop is interesting for farmers; however, land allocation decisions depend on how much risk the producer is willing to take. Since this farm planning strategy reduces SP and MS areas in the production system, gross margin and risk are also decreased. The following distribution of arable land produced the maximum gross margin value in CNP: 62.5% SP, 18.8% SN and 18.7% cotton (ALG) in the first harvest and 62.5% MS for the second harvest. The resulting maximum gross margin of the farm was R$754,260.77, which was R$122,525.78 under high risk conditions. As the area of cotton production is reduced, the representative exposure to risk is protected. In this case, a production system with multiple products does not exactly mean reduced risk for the farm, since the addition one particular product in the production portfolio generates a specific cost, called the sunk cost. Thus, a production system becomes feasible when the use of specific machinery and equipment is maximized, but in the end this procedure penalizes the performance of other products. The decision to allocate land for these products should remunerate the opportunity cost of soybean and corn. The efficient frontier curves correspond to the most efficient investment strategies for the two farms.. The frontier curve for SRS was the allocation of average land used in the last six seasons (2004/05 to 2009/10), showing that the production system adopted (32.5% SP and 67.5% SN for the first crop and 32.5% MS for the second crop) has productive efficiency to minimize risks for a certain income level. This decision corresponds to an aversion rate to risk of 1.05. In the case of CNP, the average combination of crop area used was very close to the efficient frontier curve, indicating that the farm planning production system with 28% SP, 54% SN, 18% ALG for the first harvest, and 28% MS for the second harvest also minimizes risk for a certain income level. On the other hand, the aversion rate to risk corresponds to 3.71. |
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Osaki, MauroBatalha, Mario Otáviohttp://lattes.cnpq.br/1015001063418091http://lattes.cnpq.br/9357773852218630e568e0b6-617f-4fca-9236-fb7c35b0b16c2016-06-02T19:50:17Z2012-10-052016-06-02T19:50:17Z2012-08-27OSAKI, Mauro. Gestão financeira e econômica da propriedade rural com multiproduto. 2012. 253 f. Tese (Doutorado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2012.https://repositorio.ufscar.br/handle/ufscar/3404Farmers have always neglected management procedures in their enterprises in detriment to initiatives regarding production technology. Overall, producers and technicians know the answer to what, how and when to produce, but they don t know the cost or profitability of this technology. The present study shows the importance of the sustainability of agricultural enterprises with reduced governmental intervention and the risk involved in a double crop production system. Therefore, the aim is to propose a model to support the decision-making process, focused on production planning in a representative multi-product farm under conditions of risk. Using quantitative applied research, a theoretical model of agricultural planning was combined with operational research to explain and understand different allocations of resources within the decision-making process. For that purpose, two production regions of Mato Grosso state in Brazil were selected: Sorriso (SRS) and Campo Novo do Parecis (CNP). In SRS, a production system with 76.9% early soybean (SP) and 23.1% soybean (SN) for the first harvest and 76.9% corn (MS) for the second harvest generated a high gross margin and risk. On the other hand, a production system with 90% SN and 10% SP implied less risk. Diversifying the cultivated area with SP and SN in the first crop and MS in the second crop is interesting for farmers; however, land allocation decisions depend on how much risk the producer is willing to take. Since this farm planning strategy reduces SP and MS areas in the production system, gross margin and risk are also decreased. The following distribution of arable land produced the maximum gross margin value in CNP: 62.5% SP, 18.8% SN and 18.7% cotton (ALG) in the first harvest and 62.5% MS for the second harvest. The resulting maximum gross margin of the farm was R$754,260.77, which was R$122,525.78 under high risk conditions. As the area of cotton production is reduced, the representative exposure to risk is protected. In this case, a production system with multiple products does not exactly mean reduced risk for the farm, since the addition one particular product in the production portfolio generates a specific cost, called the sunk cost. Thus, a production system becomes feasible when the use of specific machinery and equipment is maximized, but in the end this procedure penalizes the performance of other products. The decision to allocate land for these products should remunerate the opportunity cost of soybean and corn. The efficient frontier curves correspond to the most efficient investment strategies for the two farms.. The frontier curve for SRS was the allocation of average land used in the last six seasons (2004/05 to 2009/10), showing that the production system adopted (32.5% SP and 67.5% SN for the first crop and 32.5% MS for the second crop) has productive efficiency to minimize risks for a certain income level. This decision corresponds to an aversion rate to risk of 1.05. In the case of CNP, the average combination of crop area used was very close to the efficient frontier curve, indicating that the farm planning production system with 28% SP, 54% SN, 18% ALG for the first harvest, and 28% MS for the second harvest also minimizes risk for a certain income level. On the other hand, the aversion rate to risk corresponds to 3.71.Agricultores sempre negligenciaram a administração de seus empreendimentos em detrimentos de iniciativas ligadas às tecnologias de produção. Em geral, produtores e técnicos sabem responder o que, como e quando produzir, mas eles tem dificuldade de responder quanto custa ou qual é a rentabilidade dessa tecnologia. Este trabalho mostra a importância do planejamento na sustentabilidade dos empreendimentos agrícolas, com intervenção governamental reduzido e sistema de produção agrícola com duas safras em condição de risco. Para isso, esta tese propõe um modelo de apoio à tomada de decisão, voltado ao planejamento de produção em uma propriedade representativa com multiproduto em condição de risco. A metodologia utilizou pesquisa aplicada quantitativa, que combina modelo teórico de planejamento agrícola com pesquisa operacional para explicar e compreender as diferentes alocações de recursos no processo de decisão. Para tanto, foram escolhidas duas regiões produtoras de Mato Grosso: Sorriso (SRS) e Campo Novo do Parecis (CNP). Em SRS, o modelo mostrou que o sistema de produção com 76,9% de soja precoce (SP) e 23,1% de soja normal (SN) na área de cultivo na primeira safra e 76,9% de milho na segunda safra (MS) obtém maior margem bruta e risco. Por outro lado, a área de produção com predomínio de SN (90%) e SP (10%) assume menor risco. A diversificação da área de cultivo com SP e SN na primeira safra e MS na segunda safra mostrou-se uma alocação interessante para o produtor, mas a decisão da proporção de uso da área agrícola dependerá do quanto de risco o produtor está disposto a assumir. Nesse planejamento agrícola, conforme reduz a área de SP e MS no sistema de produção tem-se uma diminuição da margem bruta e do risco. Em CNP obtém-se o valor máximo de margem bruta média quando a área total de cultivo fica ocupada com 62,5% de SP, 18,8% de SN e 18,7% de algodão (ALG) na primeira safra e com 62,5% de MS, o que motiva a margem bruta máxima da propriedade (R$ 754.260,77) em alta condição de risco (R$ 122.525,78). À medida que o uso da área de cultivo com o algodão na estrutura produtiva é reduzido, protege-se a propriedade representativa da exposição ao risco. Neste caso, o sistema de produção com multiproduto não significou exatamente a redução do risco da propriedade rural, pois a adição de um produto particular na carteira de produção acabou gerando um custo específico sunk cost. Assim, o sistema de produção da propriedade torna viável quando se busca a maximização do uso das máquinas e dos equipamentos específicos, mas isso acaba penalizando o desempenho dos demais produtos. A decisão de alocar o uso da terra com esses produtos deve remunerar o custo de oportunidade da soja e milho. As curvas de fronteira de eficiência revelaram que as duas propriedades representativas maximizam os fatores de produção. Em SRS, a alocação média da área de cultivo nas últimas seis safras (2004/05 a 2009/10) ficou na curva de fronteira, mostrando que o sistema de produção escolhido pelos produtores (32,5% de SP e 67,5% de SN na primeira safra e 32,5% de MS) tem mostrado a eficiência produtiva dos agricultores no sentido de minimizarem o risco para determinado nível de renda. Essa decisão corresponde a uma taxa de aversão ao risco de 1,050. No caso de CNP, a combinação média da área de cultivo ficou muito próxima da curva de fronteira, sinalizando que o planejamento agrícola do sistema de produção (28% de SP, 54% de SN e 18% de ALG na primeira safra, e 28% de MS) também minimiza o risco para determinado nível de renda, mas a uma taxa de aversão ao risco corresponde a 3,71.application/pdfporUniversidade Federal de São CarlosPrograma de Pós-Graduação em Engenharia de Produção - PPGEPUFSCarBREngenharia de produçãoEconomia agrícolaAdministração ruralRisco agrícolaRisco MOTADFarm planningMotadRiskENGENHARIAS::ENGENHARIA DE PRODUCAOGestão financeira e econômica da propriedade rural com multiprodutoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesis-1-113fa4966-9404-4793-9cb1-99f7855bbc85info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINAL4569.pdfapplication/pdf2774038https://repositorio.ufscar.br/bitstream/ufscar/3404/1/4569.pdf78f34cb28f3d27e0d82767631a1e03b1MD51TEXT4569.pdf.txt4569.pdf.txtExtracted texttext/plain0https://repositorio.ufscar.br/bitstream/ufscar/3404/2/4569.pdf.txtd41d8cd98f00b204e9800998ecf8427eMD52THUMBNAIL4569.pdf.jpg4569.pdf.jpgIM Thumbnailimage/jpeg6102https://repositorio.ufscar.br/bitstream/ufscar/3404/3/4569.pdf.jpgb6462215614a14dc333959048b630403MD53ufscar/34042023-09-18 18:31:32.773oai:repositorio.ufscar.br:ufscar/3404Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:32Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.por.fl_str_mv |
Gestão financeira e econômica da propriedade rural com multiproduto |
title |
Gestão financeira e econômica da propriedade rural com multiproduto |
spellingShingle |
Gestão financeira e econômica da propriedade rural com multiproduto Osaki, Mauro Engenharia de produção Economia agrícola Administração rural Risco agrícola Risco MOTAD Farm planning Motad Risk ENGENHARIAS::ENGENHARIA DE PRODUCAO |
title_short |
Gestão financeira e econômica da propriedade rural com multiproduto |
title_full |
Gestão financeira e econômica da propriedade rural com multiproduto |
title_fullStr |
Gestão financeira e econômica da propriedade rural com multiproduto |
title_full_unstemmed |
Gestão financeira e econômica da propriedade rural com multiproduto |
title_sort |
Gestão financeira e econômica da propriedade rural com multiproduto |
author |
Osaki, Mauro |
author_facet |
Osaki, Mauro |
author_role |
author |
dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/9357773852218630 |
dc.contributor.author.fl_str_mv |
Osaki, Mauro |
dc.contributor.advisor1.fl_str_mv |
Batalha, Mario Otávio |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/1015001063418091 |
dc.contributor.authorID.fl_str_mv |
e568e0b6-617f-4fca-9236-fb7c35b0b16c |
contributor_str_mv |
Batalha, Mario Otávio |
dc.subject.por.fl_str_mv |
Engenharia de produção Economia agrícola Administração rural Risco agrícola Risco MOTAD |
topic |
Engenharia de produção Economia agrícola Administração rural Risco agrícola Risco MOTAD Farm planning Motad Risk ENGENHARIAS::ENGENHARIA DE PRODUCAO |
dc.subject.eng.fl_str_mv |
Farm planning Motad Risk |
dc.subject.cnpq.fl_str_mv |
ENGENHARIAS::ENGENHARIA DE PRODUCAO |
description |
Farmers have always neglected management procedures in their enterprises in detriment to initiatives regarding production technology. Overall, producers and technicians know the answer to what, how and when to produce, but they don t know the cost or profitability of this technology. The present study shows the importance of the sustainability of agricultural enterprises with reduced governmental intervention and the risk involved in a double crop production system. Therefore, the aim is to propose a model to support the decision-making process, focused on production planning in a representative multi-product farm under conditions of risk. Using quantitative applied research, a theoretical model of agricultural planning was combined with operational research to explain and understand different allocations of resources within the decision-making process. For that purpose, two production regions of Mato Grosso state in Brazil were selected: Sorriso (SRS) and Campo Novo do Parecis (CNP). In SRS, a production system with 76.9% early soybean (SP) and 23.1% soybean (SN) for the first harvest and 76.9% corn (MS) for the second harvest generated a high gross margin and risk. On the other hand, a production system with 90% SN and 10% SP implied less risk. Diversifying the cultivated area with SP and SN in the first crop and MS in the second crop is interesting for farmers; however, land allocation decisions depend on how much risk the producer is willing to take. Since this farm planning strategy reduces SP and MS areas in the production system, gross margin and risk are also decreased. The following distribution of arable land produced the maximum gross margin value in CNP: 62.5% SP, 18.8% SN and 18.7% cotton (ALG) in the first harvest and 62.5% MS for the second harvest. The resulting maximum gross margin of the farm was R$754,260.77, which was R$122,525.78 under high risk conditions. As the area of cotton production is reduced, the representative exposure to risk is protected. In this case, a production system with multiple products does not exactly mean reduced risk for the farm, since the addition one particular product in the production portfolio generates a specific cost, called the sunk cost. Thus, a production system becomes feasible when the use of specific machinery and equipment is maximized, but in the end this procedure penalizes the performance of other products. The decision to allocate land for these products should remunerate the opportunity cost of soybean and corn. The efficient frontier curves correspond to the most efficient investment strategies for the two farms.. The frontier curve for SRS was the allocation of average land used in the last six seasons (2004/05 to 2009/10), showing that the production system adopted (32.5% SP and 67.5% SN for the first crop and 32.5% MS for the second crop) has productive efficiency to minimize risks for a certain income level. This decision corresponds to an aversion rate to risk of 1.05. In the case of CNP, the average combination of crop area used was very close to the efficient frontier curve, indicating that the farm planning production system with 28% SP, 54% SN, 18% ALG for the first harvest, and 28% MS for the second harvest also minimizes risk for a certain income level. On the other hand, the aversion rate to risk corresponds to 3.71. |
publishDate |
2012 |
dc.date.available.fl_str_mv |
2012-10-05 2016-06-02T19:50:17Z |
dc.date.issued.fl_str_mv |
2012-08-27 |
dc.date.accessioned.fl_str_mv |
2016-06-02T19:50:17Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/doctoralThesis |
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doctoralThesis |
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publishedVersion |
dc.identifier.citation.fl_str_mv |
OSAKI, Mauro. Gestão financeira e econômica da propriedade rural com multiproduto. 2012. 253 f. Tese (Doutorado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2012. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/ufscar/3404 |
identifier_str_mv |
OSAKI, Mauro. Gestão financeira e econômica da propriedade rural com multiproduto. 2012. 253 f. Tese (Doutorado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2012. |
url |
https://repositorio.ufscar.br/handle/ufscar/3404 |
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openAccess |
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Universidade Federal de São Carlos |
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Programa de Pós-Graduação em Engenharia de Produção - PPGEP |
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UFSCar |
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BR |
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Universidade Federal de São Carlos |
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