Determinants of agricultural diversification in Brazil: a spatial econometric analysis

IF 1.8 Q2 GEOGRAPHY Letters in Spatial and Resource Sciences Pub Date : 2022-01-03 DOI:10.22004/AG.ECON.315290
J. Parré, A. Chagas
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引用次数: 3

Abstract

This research has as main objective to analyze the behavior and the importance of agricultural diversification for Brazil, considering its States, for the period from 2002 to 2018. We will propose an analytical model to make it possible to identify the determinants of agricultural diversification in Brazil. Empirically, the study estimates an SLX model using panel data and considers the spillover effects, highlighting the importance of location and neighborhood. The study's findings indicate a continued decline in crop diversity with a strong tendency to productive specialization in Brazilian agriculture, mainly in the states located in the Midwest and South regions of the country. The average growth rates of the indices presented negative values for the analysis period: − 0.41% per year for the Simpson index, − 0.58% per year for the Shannon index, and − 0.91% per year for the effective number of crops. It is important to note that some states are allocating practically the entire agricultural area to three or four dominant crops. As for the determinants of agricultural diversification, the results for Brazil are in line with the specialized literature.
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巴西农业多样化的决定因素:空间计量经济学分析
本研究的主要目的是分析2002年至2018年期间巴西农业多样化的行为和重要性,考虑到其各州。我们将提出一个分析模型,以确定巴西农业多样化的决定因素。在实证方面,本文采用面板数据估计了SLX模型,并考虑了溢出效应,强调了区位和邻里关系的重要性。研究结果表明,巴西农业的作物多样性持续下降,生产专业化趋势强烈,主要集中在该国中西部和南部地区的各州。在分析期内,各指数的平均生长率均为负值:辛普森指数为- 0.41% /年,香农指数为- 0.58% /年,有效作物数为- 0.91% /年。值得注意的是,一些州实际上把整个农业面积分配给三到四种主要作物。至于农业多样化的决定因素,巴西的结果与专业文献一致。
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来源期刊
CiteScore
2.30
自引率
11.10%
发文量
30
期刊介绍: Letters in Spatial and Resource Sciences (LSRS) publishes high-quality, shorter papers on new theoretical or empirical results and on models and methods in the social sciences that contain a spatial dimension. Coverage includes environmental and resource economics, regional and urban economics, spatial econometrics, regional science, geography, demography, agricultural economics, GIS and city and regional planning. Examples of topics include, but are not limited to, environmental damage, urbanization, resource allocation, spatial-temporal data use, regional economic development and the application of existing and new methodologies.LSRS contributes to the communication of theories and methodologies across disciplinary borders. It offers quick dissemination and easy accessibility of new results. Officially cited as: Lett Spat Resour Sci
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