A continuidade do processo de desconcentração regional da indústria brasileira nos anos 2000
The article continues the debate on the changes in the regional distribution of Brazilian industry in recent decades. Based on industry data for employment and wages for the period 1997/2007, it identifies an intense process of regional decentralization. Using classical indices of concentration, it appears that the trend identified affects all types of industries, whether traditional, commodities, diffuser or durable goods. The article also proposes the use of a new density index, highlighting some meso-regions where it is relatively high. From the values encountered for the density index some meso-regions located in different regions of the country are selected and their results discussed, which illustrates various situations of apparent success.
A nova configuração regional brasileira e sua geografia econômica
The aim of this paper is to identify the new regional pattern of the Brazilian economy by defining its economic poles and their areas of polarization, which will provide an economic regionalization for Brazil. The methodological tools to assign this objective will be an adapted version of the gravitational model using the Geographic Information System - GIS. This procedure will allow the identification of the influence areas for each regional pole, based on the potential interaction among the spatial units and their hierarchy in terms of economic power of attraction. The microregion of the Brazilian Statistics Bureau (IBGE) will be the spatial unit of this study, which will rely on microdata of the 1991 Demographic Census. The digital cartographic base is the Brazilian Municipal Digital Network converted into the MapInfo. The results will provide a hierarchical spatial structure of macro regions, mesoregions, microregions, and municipalities. In addition, we will make a basic economic characterization of the regions related to their agglomeration capability and economic activities.
UM PROCEDIMENTO PARA CALCULAR ÍNDICES A PARTIR DE UMA BASE DE DADOS MULTIVARIADOS
This paper presents a solution to the problem of finding an index number I for ranking a set of n objects, according to criteria defined by a set of m variables. In general, it is necessary to choose a suitable set of variables, and weights for each variable. Cluster Analysis is used for variable selection, and Principal Component Analysis is used to attain weights. Two applications are presented.