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The canonical correlation complexity method

Author

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  • Nomaler, Önder

    (UNU-MERIT, Maastricht University)

  • Verspagen, Bart

    (UNU-MERIT, Maastricht University)

Abstract

A relatively recent, yet rapidly proliferating strand of literature in the so-called econophysics domain, known as 'economic complexity' , introduces a toolkit to analyse the relationship between specialization, diversification, and economic development. Different methods that aim at reducing the high dimensionality in data on the empirical patterns of co-location (be it nations or regions) of specializations have been proposed. In terms of the concepts of machine learning, the existing algorithms follow the framework of 'unsupervised learning'. The competing alternatives (e.g., Hidalgo and Hausmann, 2009 vs. Tacchella et al, 2012) have been based on very different assessments of which products depend on more complex capabilities, and accordingly yield highly different estimations of complexity at the product level. The approach that we developed avoids this algorithmic 'confusion' by drawing on a toolkit of more transparent and long-established methods that follow the 'supervised learning' principle where the data on trade/specialization and development are processed together from the very beginning in order to identify the patterns of mutual association. The first pillar of the toolkit, Principal Component Analysis (PCA), serves dimensionality reduction in co-location information. The second pillar, Canonical Correlation Analysis (CCA), identifies the mutual-association between the various patterns of (co-)specialization and more-than-one dimension of economic development. This way, we are able to identify the products or technologies that can be associated with the level or the growth rate of per capita GDP and CO2 emissions.

Suggested Citation

  • Nomaler, Önder & Verspagen, Bart, 2022. "The canonical correlation complexity method," MERIT Working Papers 2022-015, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Handle: RePEc:unm:unumer:2022015
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    File URL: https://www.merit.unu.edu/publications/wppdf/2022/wp2022-015.pdf
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    References listed on IDEAS

    as
    1. Cesar A. Hidalgo & Ricardo Hausmann, 2009. "The Building Blocks of Economic Complexity," Papers 0909.3890, arXiv.org.
    2. Bronwyn H. Hall & Nathan Rosenberg (ed.), 2010. "Handbook of the Economics of Innovation," Handbook of the Economics of Innovation, Elsevier, edition 1, volume 1, number 1.
    3. Saleh Albeaik & Mary Kaltenberg & Mansour Alsaleh & C'esar A. Hidalgo, 2017. "729 new measures of economic complexity (Addendum to Improving the Economic Complexity Index)," Papers 1708.04107, arXiv.org.
    4. Saleh Albeaik & Mary Kaltenberg & Mansour Alsaleh & Cesar A. Hidalgo, 2017. "Improving the Economic Complexity Index," Papers 1707.05826, arXiv.org, revised Jul 2017.
    5. Raymond Vernon, 1966. "International Investment and International Trade in the Product Cycle," The Quarterly Journal of Economics, Oxford University Press, vol. 80(2), pages 190-207.
    6. Matthieu Cristelli & Andrea Tacchella & Luciano Pietronero, 2015. "The Heterogeneous Dynamics of Economic Complexity," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-15, February.
    7. Fagerberg, Jan & Srholec, Martin & Verspagen, Bart, 2010. "Innovation and Economic Development," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 833-872, Elsevier.
    8. Abramovitz,Moses, 1989. "Thinking about Growth," Cambridge Books, Cambridge University Press, number 9780521333962, January.
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    Cited by:

    1. Nomaler, Önder & Verspagen, Bart, 2022. "Canonical correlation complexity of European regions," MERIT Working Papers 2022-016, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

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    More about this item

    Keywords

    Economic complexity; economic development; supervised learning; canonical correlation analysis; principal component analysis;
    All these keywords.

    JEL classification:

    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development

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