Spatial Dimensions of Economic Growth in Brazil

Guilherme Resende

doi:10.1155/2013/398021

Abstract

The contribution of this paper is to explore time and spatial scale dimensions of economic growth in Brazil using alternative panel data techniques to provide a measure of the extent of spatial autocorrelation (in kilometres) over three decades (1970–2000) as well as discussing the determinants of economic growth at a variety of geographic scales (minimum comparable areas, micro-regions, meso-regions, and states). The magnitude and statistical significance of growth determinants such as schooling, population density, population growth, and transportation costs are dependent on the scale of analysis. Moreover, the extent of residual spatial autocorrelation showed that it seems to vary across spatial scales. Indeed, spatial autocorrelation seems to be bounded at the state level and it shows positive and statistically significant values across distances of more than 1,500 kilometres at the other three spatial scales. Among other results, the study suggests that the nonspatial panel data techniques are not able to deal with spatially correlated omitted variables across different spatial scales, except for the state level where nonspatial panel data models seem to be appropriate to investigate growth determinants and convergence process in the Brazilian states case.

Highlights

This paper explores time and spatial scale dimensions of economic growth in Brazil using alternative panel-data techniques to provide a measure of the extent of spatial autocorrelation over three decades (1970– 2000) and it discusses the determinants of economic growth at a variety of geographic scales
It is important to note that when conditioning variables were dropped from the models and only per capita income growth was regressed on initial per capita income, the values for spatial autocorrelation in the residuals for all spatial scales and methods increased as expected. (For the absolute β-convergence case, estimations at all spatial scales suffer from higher spatial autocorrelation than the conditional β-convergence ones, because the Moran’s I statistics in the residuals of former estimations present the highest values.) For instance, Silveira-Neto and Azzoni [40] found that after conditioning their models on variables with strong geographic patterns across states in Brazil, spatial dependence disappeared
This study provides empirical evidence that the Brazilian economic growth process between 1970 and 2000 varied according to the spatial scale under analysis

Summary

Introduction

This paper explores time and spatial scale dimensions of economic growth in Brazil using alternative panel-data techniques to provide a measure of the extent of spatial autocorrelation (in kilometres) over three decades (1970– 2000) and it discusses the determinants of economic growth at a variety of geographic scales (minimum comparable areas, micro-regions, meso-regions, and states). The focus is on a descriptive analysis of the extent of the spatial autocorrelation effects in the context of regional growth literature, by testing whether the residuals of traditional growth model estimates are spatially autocorrelated at different spatial scales using standard panel data models between 1970 and 2000 in Brazil. The empirical exercise conducted by Resende [3] shows that spatial autocorrelation appears only at finer scales With the exception this latter work, the studies far have only examined the existence of spatial autocorrelation in the process of economic growth at a single spatial scale to infer the consistency of spatial growth models with reality (e.g., [4,5,6,7,8]). This study of regional economic growth explores both time and spatial scale dimensions

Methods

Results

Conclusion