Distribution of farmers by dead animal disposal methods, broiler production, 2003 (percent) 6.8 Distribution of farmers by dead animal disposal methods, egg production, 2003 (percent) 6.9 Distribution of farmers by dead animal disposal methods, swine production, 2003 (percent) 6.10 Environmental expenditures per kilogram output of liveweight broiler or eggs from poultry production, 2003 6.11 Environmental expenditures per kilogram output from swine production, 2003 6.12 Environmental expenditures per unit output from milk production, 2003 6.13 Determinants of farm expenditure on mitigation of environmental externalities from swine production, Thailand, 2002-03 6.14 Determinants of farm expenditure on mitigation of environmental externalities from broiler production, Thailand, 2003 6.15 Determinants of farm expenditure on mitigation of environmental externalities from broiler production, Philippines, 2002-03 6.16 Determinants of farm expenditure on mitigation of environmental externalities from swine production, Philippines, 2002-03 7.1 Mean relative profit efficiency of broiler farms across farm sizes by country, 2002 7.2 Mean relative profit efficiency of layer farms across farm sizes by country, 2002 7.3 Mean relative profit efficiency of swine farms across farm sizes by country, 2002 7.4 Mean relative profit efficiency of dairy farms across farm sizes by country, 2002 7.5 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Philippine broiler farms 7.6 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Thai broiler farms 7.7 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Indian broiler farms 7.8 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Brazilian layer farms 7.9 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Indian layer farms 7.10 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Philippine swine farms tables v 7.11 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Brazilian swine farms 7.12 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Indian dairy farms 7.13 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Thai dairy farms 7.14 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Brazilian dairy farms 7.15 Summary of empirical results vi tables summary xi xii summary 3 Monogastrics are animals with one stomach compartment; examples are pigs and poultry. settled export-certified zone spend more per unit than smaller farms, and dairy farmers in Thailand, where the larger-scale farmers have more crop land per animal than do the smallerscale farmers in the sample. Results are backed up by a second, more conventional procedure that estimates mass balances of nutrients per hectar...

AGRADECIMENTOS Ao professor Geraldo Sant'Ana de Camargo Barros sou especialmente grata pela orientação segura, e pelas inúmeras vezes em que me indicou com clareza os caminhos a seguir. Sua leitura criteriosa e valiosos comentários durante as várias etapas da pesquisa foram responsáveis pelo engrandecimento do trabalho. Em seu nome agradeço ao Centro de Pesquisa em Economia Aplicada (CEPEA), pelo suporte financeiro que possibilitou a realização das entrevistas. Da mesma forma, a bolsa de estudo recebida pela CAPES durante o curso foi de fundamental importância para a realização desta tese. Luciene -pela colaboração e amizade. À Maielli, que sempre sorridente me socorreu dos apuros com as datas e prazos, um agradecimento especial. Falando em prazos, sou grata à Helena e à Ligiana, que na fase final do trabalho prontamente me ajudaram a vencê-los.Agradeço a colaboração das pessoas entrevistadas, que dispuseram de seu tempo nas agendas apertadas, em reuniões que algumas vezes duraram mais de três horas, sem as quais a realização desta tese não teria sido possível.Isto me faz lembrar da Dra. Elizabeth Serodio, que ao término de nossa entrevista, às 22:30, depois de um dia exaustivo da atividades, ainda achou tempo para me levar aos principais pontos turísticos da cidade.Ao Caio, além do precioso tempo dispendido, sou grata por ter me presenteado com o tema desta tese, há três anos atrás, quando vislumbrou os enormes desafios a serem enfrentados pelo setor. Em nome da Denise e da Nívea, agradeço também a 7CONCLUSÕES .

Although the Brazilian agribusiness sector’s relevance to the country has been widely recognized nowadays, to date, no study has been developed to evaluate the level of employment in this sector as a whole for Brazil. Therefore, the first objective of this study is to access the Brazilian agribusiness labor market, and to measure it, analyze its structure and characterize its workers. Agribusiness worker income differentials were also contrasted with income differentials in the aggregated non-agribusiness labor force. The main results from the study are as follows: a) in 2017, 18.2 million individuals, 20.1% of the country’s labor force, worked in the Brazilian agribusiness sector; b) agribusiness workers were predominately unskilled or semi-skilled with a low level of schooling; c) a large proportion of the sector’s labor force were not formally employed; and d) the average income of agribusiness employees was lower than that of individuals in other economic sectors. There is also extreme labor market heterogeneity among agribusiness sector segments – with the primary segment presenting a noticeably dissimilar profile – and a significant income differential associated with different labor market statuses, economic sub-sectors and locations, and with individual characteristics such as level of schooling, skin tone and gender.

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Códigos JEL: C32; E32; O13; O33; O41; O47.O objetivo principal deste trabalho é examinar o padrão de crescimento da produção de algodão no Brasil desde os anos 1960 até os dias atuais, período em que se materializa a expansão da cultura para novas regiões do país, num novo sistema produtivo. Desenvolve-se um modelo econômico para aferir o crescimento do setor em termos de choques de oferta e de demanda. Os resultados apontaram que a produtividade da lavoura explica aproximadamente 30% do crescimento da produção e quase um quarto da evolução da exportação de algodão do Brasil. Outros 15% do aumento da produção podem ser atribuídos à evolução do preço. Os resultados sugerem que, configurado um cenário de rentabilidade, o setor tende a ajustar a área e a produção durante um período de uma década ou mais, num processo auto-regressivo característico. This paper is intended to analyze the growth pattern of the Brazilian cotton production after 1960. During this period the cotton crop expanded to new regions based on a new productionsystem. An economic model is developed to * O presente artigo é baseado na tese de doutorado do primeiro autor. Os autores agradecem a contribuição do(s) parecerista(s). Possíveis erros remanescentes são de inteira responsabilidade dos autores. † Professor Doutor do

Este estudo dimensiona o mercado de trabalho do agronegócio mineiro, identifica a estrutura deste mercado e o perfil dos trabalhadores nele inseridos, e analisa de forma exploratória aspectos relacionados aos rendimentos das pessoas ocupadas no setor. Utiliza-se como principal base de informações os microdados da PNAD Continua e, de forma auxiliar, informações do CEPEA/ESALQ/USP e da RAIS. Estimou-se que, em 2014, o agronegócio representou 26% das ocupações de Minas Gerais. Verificou-se que o mercado de trabalho do setor é em geral marcado por trabalhadores com baixa escolaridade e elevada informalidade, resultado bastante influenciado pelo segmento primário. Verificou-se ainda que, em média, as pessoas ocupadas no agronegócio auferiram rendimentos 31% menores que os ocupados no demais setores da economia do estado. E, dentro do agronegócio: as mulheres ganharam em média 29% menos que os homens; os empregados com carteira assinada cerca de 67% a mais que os sem carteira assinada e 27% a mais que aqueles que atuam por conta-própria; os empregadores, por sua vez, auferiram rendimentos 264% maiores que os empregados com carteira assinada; os ocupados com ensino superior tiveram rendimentos 352% superiores àqueles sem instrução, 218% superiores àqueles com até ensino fundamental, e 119% superiores àqueles com até ensino médio.

In the last decades the Brazilian agriculture had a strong growth. Our hypothesis is that most of that growth may be attributed to two general factors, which may conveniently be related to two types of shocks acting upon agriculture: demand-related and technological supply-related shocks. Demand shocks are originated both from domestic economy and from external markets. We use Blanchard and Quah (1989) type of economic model to test the relative importance of supply and demand shocks on Brazilian agricultural growth. Our results indicate that supply and demand shocks have permanent effects upon agricultural output and prices. We estimate that the agricultural output growth in Brazil is attributed in large proportion to yield increases and that integration to international markets was important to assure the profitability of continuous use of new technology that led to yield improvements. This is why exchange rate plays is relevant in explaining the performance of the Brazilian agriculture. We anticipate that, if investments in science and technology are maintained and international integration expanded, Brazil will be able to substantially increase its supply of agricultural products both for domestic and foreign markets. Nas últimas décadas a agricultura brasileira teve um forte crescimento.

This study assessed the risk exposure of the production system of a typical farm in southern Brazil. Five possible production systems were analyzed, combining three crops (soybeans, corn seasons and wheat) in different crop-year combinations, for example: "Summer soybeans followed by corn" and "Autumn corn followed by winter wheat". Five different production systems were created based on the intensity of land use for each of the crops. Primary data were collected from a typical farm in the producing region over eight seasons (2006/07 to 2013/14). The Monte Carlo simulation technique was used to evaluate negative Net Operating Revenue (NOR) risk. The results showed that the production system with soybean and first season corn had a higher NOR and lower risk when compared with the other four production systems, which intensified the land use in the second season. When the production system had a higher rate of corn and/or wheat, the NOR and the risk to the production system increased for the first or second crop. Both corn and wheat in the second crop increased the risk to the production system on the typical farm in Cascavel, in the state of Parana (PR).