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An Application of Canonical Correlation Analysis in Regional Science: TheInterrelationships Between Transport and Development in China's Zhujiang Delta

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  • Becky P.Y. Loo

Abstract

Canonical correlation analysis (CCA) has the ability to deal with two sets of multivariate variables simultaneously and to produce both structural and spatial meanings. In view of the valuable insights to be gained, in this paper I examine the potential applications of CCA in regional science by describing its algorithm in a regional or spatial context. Next, I apply CCA to explore the mutually interdependent relationship between transport and development inChina's Zhujiang Delta. The results highlight the utility of CCA in revealing the structural and spatial patterns of two dominant and four subdominant transport‐development relationships in this growing region of China.

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  • Becky P.Y. Loo, 2000. "An Application of Canonical Correlation Analysis in Regional Science: TheInterrelationships Between Transport and Development in China's Zhujiang Delta," Journal of Regional Science, Wiley Blackwell, vol. 40(1), pages 143-171, February.
    • Handle: RePEc:bla:jregsc:v:40:y:2000:i:1:p:143-171
    DOI: 10.1111/0022-4146.00168
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    Cited by:

    1. Loo, Becky P.Y. & Banister, David, 2016. "Decoupling transport from economic growth: Extending the debate to include environmental and social externalities," Journal of Transport Geography, Elsevier, vol. 57(C), pages 134-144.
    2. Loo, Becky P. Y., 2002. "The potential impacts of strategic highways on new town development: a case study of Route 3 in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(1), pages 41-63, January.

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