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Brazilian spatial dynamics in the long term (1872–2000): “path dependency” or “reversal of fortune”?

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Abstract

This paper analyzes the spatial dynamics of Brazilian regional inequalities between 1872 and 2000 using contemporary tools. The first part of the paper provides new estimates of income per capita in 1872 by municipality using census and electoral information on income by occupation. The level of analysis is the Minimum Comparable Areas 1872–2000 developed by Reis et al. (Áreas mínimas comparáveis para os períodos intercensitários de 1872 a 2000, 2007). These areas are the least aggregation of adjacent municipalities required to allow consistent geographic area comparisons between census years. In the second section of the paper, Exploratory Spatial Data Analysis, Markov chains and stochastic kernel techniques (spatially conditioned) are applied to the dataset. The results suggest that, in broad terms, the spatial pattern of income distribution in Brazil during that period of time has remained stable.

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Notes

  1. In fact, the New Economy Geography, in able hands, predicts much richer spatial dynamics (see Crafts and Venables 2001).

  2. Meisel and Bonet (2007) and Naritomi et al. (2007) tested for the long-run effects of colonial institutions within contemporary Colombia and Brazil, in that order.

  3. Reis (2008b) used data on wages of civil servants as a proxy for per capita income in the beginning of the period.

  4. This is around 3,000 pounds sterling at current price levels (adjusted by the GDP deflator of Britain. Source: EH.net 2009 and IPEADATA 2009).

  5. See Appendix for the list of electoral rolls that were used.

  6. The MCAs for the period from 1872 to 2000 for the northern region of Brazil and the state of Mato Grosso were either too wide-ranging or contained very small populations. Had they been included in the database, they would have distorted the spatial analysis, and for this reason they were excluded. As a result, for the purposes of this study the name “Brazil” refers only to the North-Eastern, South-Eastern and Southern regions of the country, and to the state of Goiás. The final number of MCAs in this paper is 410.

  7. Unfortunately, as Platt's “Mickey Mouse Numbers in World History” (1989) has shown, many widely used historical estimates of income are quite opaque.

  8. A simple queen adjacency matrix was used in the paper.

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Acknowledgments

This research was made possible by the support of Eustáquio Reis, the technical staff of IPEA, and Nemesis (Núcleo de Estudos e Modelos Espaciais Sistêmicos). I am grateful for the comments made by Colin Lewis (LSE- Department of Economic History). I am also grateful for the financial support of CNPq and Nemesis FAPERJ (Proc. E52 168.171/2006).

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  1. IPEA, Instituto de Pesquisas Econômicas Aplicadas, SBS Q.01 Ed. BNDES sala 307, Brasília, DF, 70076-900, Brazil

    Leonardo Monteiro Monasterio

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Correspondence to Leonardo Monteiro Monasterio.

Appendix

Appendix

See (Table 6).

Table 6 Source of the data on incomes
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Monasterio, L.M. Brazilian spatial dynamics in the long term (1872–2000): “path dependency” or “reversal of fortune”?. J Geogr Syst 12, 51–67 (2010). https://doi.org/10.1007/s10109-009-0094-8

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