Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/285015 
Year of Publication: 
2023
Series/Report no.: 
Texto para Discussão No. 2893
Publisher: 
Instituto de Pesquisa Econômica Aplicada (IPEA), Brasília
Abstract (Translated): 
Food production remains one of the biggest challenges for humankind in this century, and Brazil is one of the largest food-producing countries that have yet some land for economically or technically profitable farming expansion. Therefore, knowing which areas constitute the Brazilian agricultural frontier is crucial for improving public policies and logistics infrastructure decisions. Data from the Brazilian Institute of Geography and Statistics from 1995 to 2020 were used in this study. We aimed to map and measure the expansion of agricultural areas in Brazil from 1995 to 2020 for permanent crops according to their mesoregions. We applied a four-stage methodology, compared the results of two agglomerative clustering methods, and identified similar mesoregions based on their share trends in the Brazilian agricultural harvesting destined area. Some mesoregions must be highlighted in terms of trend values for their share of the Brazilian agricultural harvesting destined area: Minas' South/Southwest (MG), Triângulo Mineiro/Paranaíba Upstream (MG), Paraense Southwest (PA), Bauru (SP), Woodland Zone (MG), Rio-grandense Northeast (RS), Pernambucano San Francisco (PE) and Minas' North (MG). Other areas such as the Espírito-santense North Coast (ES), Bahia's San Franciscano Valley (BA), Cearense North (CE), Cearense Northwest (CE), Alagoano East (AL), and Paranaense Southeast (PR) constituted a second leading group, and Minas' West (MG), Paraense Northeast (PA), and Doce River Valley (MG) should be emphasized as clusters by themselves. Policy implications are discussed and further research is suggested, especially running top-down analysis targeting microregions or municipalities in the identified mesoregions.
Subjects: 
agricultural frontier
Brazil
permanent crops
Spearman&#x2019
s correlation coefficient
clustering
JEL: 
Q10
Q15
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Working Paper

Files in This Item:
File
Size
1.43 MB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.