Author:
Lima Márcio Dias de,Gomes Alan Keller,Souza Daniel Soares de,Oliveira Lucas Santos de,Santos Paulo Henrique dos,Lopes Cassiomar Rodrigues,Silva José Carlos Barros,Batista Karla de Aleluia
Abstract
The agricultural and livestock industry is a cornerstone of Brazil’s economy, wielding substantial influence over the nation’s GDP and food security. Within this framework, the Ministry of Agriculture and Livestock (MAPA) plays an essential role in shaping and implementing policies geared towards fostering the sustainable growth of these critical sectors through public agreements. In this context, the equitable and efficient allocation of resources requires a thorough understanding of these agreements’ geographical distribution and temporal dynamics. This study meticulously scrutinizes the geographic spread, temporal progression, and inherent characteristics of the agreements signed by MAPA from 2019 to 2023. It examines the agreements using data mining techniques, encompassing clustering and statistical analyses. The research unveiled a pronounced regional distribution in the agreements, with Brazil’s Southern region emerging as the primary destination of grants, closely shadowed by the Southeast. Consequently, the study offers a holistic comprehension of the geographical dispersion, temporal evolution, and intrinsic traits of the agreements brokered by MAPA. Such insights serve as invaluable assets, empowering policymakers to formulate more efficient and targeted strategies for nurturing Brazil’s agricultural and livestock industry concerning the allocation of resources and the elaboration of agreements.
Publisher
South Florida Publishing LLC
Reference34 articles.
1. AGUIAR, P. A. d. A., SANTANA JÚNIOR, C. J., & BASTOS FILHO, C. J. A. (2018). Aplicação de algoritmos de clusterização em uma base de dados de reservas de hotéis. Revista de Engenharia e Pesquisa Aplicada, 3.
2. ALONSO-BETANZOS, A., & BOLÓN-CANEDO, V. (2018). Big-data analysis, cluster analysis, and machine-learning approaches. Sex-specific analysis of cardiovascular function, 607–626.
3. BORGES, M. J., & PARRÉ, J. L. (2021). O impacto do crédito rural no produto agropecuário brasileiro. Revista de Economia e Sociologia Rural, 60.
4. BRAGA, M. J., VIEIRA FILHO, J. E. R., & de FREITAS, C. O. (2019). IMPACTOS DA EXTENSÃO RURAL NA RENDA PRODUTIVA. In Diagnóstico e desafios da Agricultura Brasileira (chapter Impactos d, p. 340). IPEA, Rio de Janeiro.
5. CAPANO, G., & HOWLETT, M. (2020). The knowns and unknowns of policy instrument analysis: Policy tools and the current research agenda on policy mixes. Sage Open, 10(1):2158244019900568.