Regional Importance of the Agribusiness in the Brazilian Economy

Guilhoto, Joaquim José Martins

doi:10.2139/ssrn.2425747

Cited by 10 publications

(9 citation statements)

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“…Minas Gerais is bordered by states that are relevant to the Brazilian economy, such as Sao Paulo, Rio de Janeiro, and Bahia. As the second-largest contributor to Brazilian GDP, this southeast state has in its territory several economic and cultural characteristics [15], such as the historic cities of Mariana and Ouro Preto, listed as world heritage and at the same time the country's largest road network.…”

Section: Minas Gerais Statementioning

confidence: 99%

Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites

2019

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Featured Application: A hybrid model formed by neural network techniques and fuzzy systems that predicts rainfall and temperatures in the capital of Minas Gerais, Brazil, which contains several river sources essential for the Brazilian economy. The purpose of the paper is to construct a model capable of extracting knowledge from satellite data related to temperatures and rainfall forecast of the analyzed state.Abstract: The forecast for rainfall and temperatures in underdevelope countries can help in the definition of public and private investment strategies in preventive and corrective nature. Water is an essential element for the economy and living things. This study had a main objective to use an intelligent hybrid model capable of extracting fuzzy rules from a historical series of temperatures and rainfall indices of the state of Minas Gerais in Brazil, more specifically in the capital. Because this is state has several rivers fundamental to the Brazilian economy, this study intended to find knowledge in the data of the problem to help public managers and private investors to act dynamically in the prediction of future temperatures and how they can interfere in the decisions related to the population of the state. The results confirm that the intelligent hybrid model can act with efficiency in the generation of predictions about the temperatures and average rainfall indices, being an efficient tool to predict the water situation in the future of this critical state for Brazil. Appl. Sci. 2019, 9, 5476 2 of 30 watersheds critical nationally. Along with several great cities, it has suffered a strong impact from drought [4].In contrast to the lack of water, it has problems with excess: floods and landslides [2]. If a river or stream receives a considerable amount of water from rain and cannot support it, it ends up overflowing and causing floods, which bring with it destruction, damage, and even death.The facts cited above are just some of the impacts that rain has on society. Within this context, this work was developed for the use of neural networks in the forecast of volumetric rainfall, based on a fuzzy rule system, developing a precise forecast, and contributing to the anticipation of possible tragedies s in places that occur phenomena of greater magnitude, as well as helping in a better control of agriculture. Another purpose was to support air and sea transportation, avoiding accidents in their trajectories. Briefly, when anticipating a possible problem, it is also possible to anticipate solutions and reduce their impacts, such as evacuating areas at risk of landslides or flooding [5].Currently, many kinds of research are being developed to apply models of artificial neural networks in rain forecasts, river basins, and water studies. For example, it was applied to the problem of forecasting the flow of the Nile River in Egypt [6], using a temporal series as a reference to compare tests among several prediction methods of neural networks. Besides, there was a study using stochastic autoregressive mean m...

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Section: Minas Gerais Statementioning

confidence: 99%

Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites

2019

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“…A maioria dos autores relata a tendência declinante da participação da agropecuária na composição do PIB de grande parte dos países do mundo, como por exemplo, Schultz (1951), Ahumada (1967), Araújo (1975), Araújo e Schuh (1988), Syrquin 4 (1988), Stern (1994), Alexandratos (1999), Gollin et al (2000) e Guilhoto (2004), associando essa tendência ao processo de desenvolvimento econômico.…”

Section: Desenvolvimento Urbano-industrial E a Participação Decrescenunclassified

“…Isto implica o crescimento mais acelerado da produtividade do trabalho na agropecuária se comparado aos outros setores, pois a renda gerada por cada trabalhador na agropecuária é inferior à dos outros setores (WORLD BANK, 2005). Guilhoto (2004), utilizando dados cross-section e recentes, também mostra que países com renda per capita mais elevada tendem a apresentar menor participação da agropecuária no PIB. Alexandratos (1999) relata que os países subdesenvolvidos estão assumindo a produção de alimentos para a população dos países desenvolvidos, tornando a questão da segurança alimentar em insegurança ("food insecurity").…”

Section: Desenvolvimento Urbano-industrial E a Participação Decrescenunclassified

“…Embora o processo de desenvolvimento urbano-industrial leve à redução da importância da agropecuária na economia, segundo Furtuoso e Guilhoto (2003) e Guilhoto (2004), o agronegócio tem maior importância econômica que somente a agropecuária. Nos EUA, a agropecuária representou aproximadamente 1,6% do PIB em 1998, enquanto o agronegócio representou 8,1% do PIB.…”

Section: Desenvolvimento Urbano-industrial E a Participação Decrescenunclassified

“…Outros países desenvolvidos, como Japão, Inglaterra, França, Alemanha, Austrália e Canadá, também apresentam este comportamento declinante (Figura 1). Fonte: World Bank (2000Bank ( , 2005 A agropecuária norte-americana tem pouca importância relativa na composição do PIB (1,6% em 2001, de acordo com o World Bank, 2005), porém, este setor dinamiza os outros setores da economia (setores industrial e de serviços), sendo de extrema importância para o processo produtivo da economia (GUILHOTO, 2004), assim como pela geração de emprego (responsável por aproximadamente 2,5% do emprego dos EUA) e fornecimento de alimentos (em termos estraté-gicos). Esses fatores são fundamentais para defender o apoio governamental à produção agropecuária nos EUA.…”

Section: Introductionunclassified

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Análise da participação da agropecuária no PIB dos EUA de 1960 a 2001

Brugnaro¹,

Bacha

2008

Rev. Econ. Sociol. Rural

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Resumo: Este artigo faz uma análise da evolução da participação da agropecuária no PIB dos EUA de 1960 a 2001, dando destaque à análise econométrica das principais variáveis que determinam essa participação. A tendência geral, no período de 1960 a 2001, é a diminuição da participação da agropecuária no PIB. Porém, isto não ocorre de forma contínua, pois de 1971 a 1973 essa participação aumentou. O artigo prova, econometricamente, a quebra de tendência da participação da agropecuária no PIB de 1971 a 1973 e centra sua análise no período de 1973 a 2001. Através de gráficos, observa-se grande crescimento da produção física de cereais e de carnes no período de 1970 a 2001, que se explica pelo grande crescimento da produtividade da agropecuária e dos subsídios governamentais, dado que a tendência da relação de preços recebidos/ preços pagos pela agropecuária foi decrescente nesse período. Baseado em um modelo contábil que explicita as variáveis que determinam a participação da agropecuária no PIB, um modelo econométrico é definido e estimado. As principais variáveis determinando a participação da agropecuária no PIB dos EUA (em ordem decrescente de importância), no período de 1973 a 2001, são a relação de preços recebidos/preços pagos, o valor defasado dessa participação e a produtividade total dos fatores da agropecuária.

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Climate change in Brazil: future scenarios classified by Thornthwaite (1948)

Lima

Aparecido

Lorençone

et al. 2021

Theor Appl Climatol

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Climate Classification System (CCS) is an important tool for validating climate change models, subsidizing the characterization of new areas suitable or unfit for agricultural activity according to future climate change scenarios. This study aims to classify the climate of the Brazilian territory in the various climate change scenarios of the IPCC through the Thornthwaite system (1948). We used a 30-year historical series of climatic data of average air temperature (°C) and rainfall (mm), obtained from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources platform (NASA/POWER). Potential evapotranspiration (ETP) was estimated by the method of Camargo (1971); the climatological water balance (CWB) was calculated by the method of Thornthwaite and Mather (1955), using 100 mm of soil water storage capacity. CWB extracts were combined for classification by Thornthwaite (1948). The scenarios used were based on the IPCC (2014) projections and the study of Pirttioja et al. (2015). The Brazilian territory had an average air temperature of 22.20 °C (± 3.20) °C and annual precipitation of 1987 mm (± 725) mm. The climatic classification of Thornthwaite presented 108 climatic classes for the current scenario with a more significant predominance of the classes ArAʹaʹ, B4rAʹaʹ, and B3rAʹaʹ representing 20.54%, 15.62%, and 9.46% of the Brazilian territory, respectively. The climate class ArAʹaʹ had 39.20% in the North and 14.97% in the Midwest. The South region has a predominance of 24.31% for the class ArBʹ3aʹ. In the Southeast and Northeast, the climate classes B2rBʹ3aʹ and DdBʹ2aʹ represented 14.80% and 15.26% of the regions, respectively. The S5 scenario was considered more favorable to establishing crops, with 48.04% of Brazil represented by the climate class ArAʹaʹ. Furthermore, the most catastrophic scenarios for crops were S3 and S4, promoting Brazil a predominance of classes B3rAʹaʹ in 18.02% and B1rAʹaʹ in 21.04%, respectively, favoring the occurrence of arid and dry climates in large part of the Brazilian territory.

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Regional Importance of the Agribusiness in the Brazilian Economy

Cited by 10 publications

References 1 publication

Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites

Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites

Análise da participação da agropecuária no PIB dos EUA de 1960 a 2001

Climate change in Brazil: future scenarios classified by Thornthwaite (1948)

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