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

Bruno Pegorare Alexander | Zendy; Paula Martin de Moraes | Zendy; Reginaldo Brito da Costa | Zendy; Gomes Pinto de Abreu Urbano | Zendy; Dany Rafael Fonseca Mendes | Zendy; Belchior Silva Moreira Tito | Zendy; George Henrique de Moura Cunha | Zendy; Constantino Michel | Zendy

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

Author(s) -

Bruno Pegorare Alexander,

Paula Martin de Moraes,

Reginaldo Brito da Costa,

Gomes Pinto de Abreu Urbano,

Dany Rafael Fonseca Mendes,

Belchior Silva Moreira Tito,

George Henrique de Moura Cunha,

Constantino Michel

Publication year - 2018

Publication title -

african journal of agricultural research

Language(s) - English

Resource type - Journals

ISSN - 1991-637X

DOI - 10.5897/ajar2017.12730

Subject(s) - gross domestic product , livestock , agriculture , spatial econometrics , spatial analysis , econometric model , geography , agricultural science , statistic , spatial dependence , agricultural economics , sugar cane , spatial variability , forestry , econometrics , environmental science , statistics , mathematics , economics , economic growth , remote sensing , archaeology

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.

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