Identification of clusters to boost the productive chains of meat in Mexico.
DOI:
https://doi.org/10.15517/am.v27i2.24388Keywords:
spatial autocorrelation, exploratory data analysis, regional production, Moran’s Index, LISA test.Abstract
The aim of this study was to analyze the regional spatial correlation of meat carcass production by species in Mexico. The study was carried out between 2000-2012. Through exploratory data analysis, the estimation of the Moran Index and LISA test, the study tried to find evidence of spatial dependence and to identify clusters that promote the integration of productive chains. The exploratory analysis provided evidence that the northern states can generate clusters to boost production of beef, pork, and chicken; and that the increase in the production of sheep and goat meat may occur in the central and northern states, respectively. The positive indexes for beef, sheep, and goat meat showed that the neighborhood between producer states would not affect the creation of clusters to increase production; while the negative autocorrelation for pork and chicken suggests that the neighborhood of a producer state would be affected by its neighbors’ regional clusters. LISA test allowed to identify statistically significant groups that support the evidence that spatial concentration of production benefits the creation of clusters and the integration of productive chains only for beef, sheep, and goat meat.
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