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Quão distantes estão as regiões portuguesas? Uma aplicação de escalonamento multidimensional

Author

Listed:
  • Gertrudes Guerreiro

    (Departamento de Economia Universidade de Évora Portuga)

  • António Caleiro

    (Departamento de Economia Universidade de Évora)

Abstract

Apesar de ser um país pequeno, Portugal caracterizase por disparidades regionais significativas, as quais se tornam evidentes a partir da análise de numerosos indicadores como o nível de rendimento ou a taxa de desemprego. Estas disparidades regionais adquirem características que, em certo sentido, não respeitam o padrão tradicional que seria de esperar, o qual apontaria no sentido de uma diminuição das condições de vida, à medida que aumenta a distância de cada região, à região onde a prosperidade económica é mais elevada. De facto, isto significa que, para além do mapa geográfico, é possível construir um mapa alternativo das regiões de Portugal o qual, pelas suas características, é certamente muito mais interessante do ponto de vista da economia regional. Tal pode ser feito, recorrendo ao escalonamento multidimensional, o qual permite representar graficamente as unidades espaciais de maneira a reproduzir, tanto quanto possível, as distâncias económicas entre elas, medidas por indicadores tradicionais. A análise dos resultados do escalonamento multidimensional torna, então, possível, por um lado, verificar como as distâncias geográficas se relacionam com as distâncias económicas e, por outro lado, verificar se as políticas económicas regionais portuguesas contribuíram para uma diminuição daquelas disparidades regionais.

Suggested Citation

  • Gertrudes Guerreiro & António Caleiro, 2005. "Quão distantes estão as regiões portuguesas? Uma aplicação de escalonamento multidimensional," RPER, Associação Portuguesa para o Desenvolvimento Regional, issue 8, pages 47-59, March.
  • Handle: RePEc:apd:rper00:y:2005:i:8:id:190
    DOI: 10.59072/rper.vi8.190
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    References listed on IDEAS

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    1. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
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