African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6638

Full Length Research Paper

Spatial econometric analysis of the main agricultural commodities produced in Central-West Region, Brazil

Alexander Bruno Pegorare
  • Alexander Bruno Pegorare
  • Agricultural Research Supervision, IBGE/MS Brazilian Institute of Geography and Statistics, Campo Grande, MS, Brazil.
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Paula Martin de Moraes
  • Paula Martin de Moraes
  • Catholic University of Brasília (UCB), Brasília, DF, Brazil.
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Reginaldo Brito da Costa
  • Reginaldo Brito da Costa
  • Catholic University of Brasília (UCB), Brasília, DF, Brazil.
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Urbano Gomes Pinto de Abreu
  • Urbano Gomes Pinto de Abreu
  • Brazilian Agricultural Research Corporation - Embrapa Pantanal, Corumbá, MS, Brazil.
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Dany Rafael Fonseca Mendes
  • Dany Rafael Fonseca Mendes
  • University Center of Brasília (UniCEUB), Brasília, DF, Brazil Brazil.
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Tito Belchior Silva Moreira
  • Tito Belchior Silva Moreira
  • Catholic University of Brasília (UCB), Brasília, DF, Brazil.
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George Henrique de Moura Cunha
  • George Henrique de Moura Cunha
  • Catholic University of Brasília (UCB), Brasília, DF, Brazil.
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Michel Constantino
  • Michel Constantino
  • Catholic University of Brasília (UCB), Brasília, DF, Brazil.
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  •  Received: 16 September 2017
  •  Accepted: 21 December 2017
  •  Published: 25 January 2018

Abstract

The aim of this paper is to present novel variables in the Brazilian Central-West Region to evaluate the spatial dependence of the Gross Domestic Product of agriculture and livestock (GDPagri) and the Gross Value of Production (GVP) on the main agricultural and livestock commodities in order to identify clusters of high and low spatial correlations. Data on the municipalities of Mato Grosso do Sul State (MS) between 2000 and 2010 is used. Initially, a spatial exploratory data analysis is performed to verify the hypothesis of global spatial randomness of the evolution of GDPagri and GVP, with Moran's I statistic as the instrumental measurement. In addition, econometric and spatial models were utilized. The results of the three spatial models used indicated that the SAR model (Spatial Auto Regressive) is most appropriate for the evaluation of GDPagri in MS. Despite beef cattle having presented the greatest GVP, the culture of sugar cane allowed for a greater increase in GDPagri.

Key words: Agribusiness, gross domestic product, spatial econometrics, Brazil.