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The Heterogeneous Dynamics of Economic Complexity

Author

Listed:
  • Matthieu Cristelli
  • Andrea Tacchella
  • Luciano Pietronero
Abstract
What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method—the selective predictability scheme—in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0117174
    DOI: 10.1371/journal.pone.0117174
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    References listed on IDEAS

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    1. Fagerberg, Jan & Verspagen, Bart, 2009. "Innovation studies--The emerging structure of a new scientific field," Research Policy, Elsevier, vol. 38(2), pages 218-233, March.
    2. Cesar A. Hidalgo & Ricardo Hausmann, 2009. "The Building Blocks of Economic Complexity," Papers 0909.3890, arXiv.org.
    3. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    4. Matthieu Cristelli & Andrea Gabrielli & Andrea Tacchella & Guido Caldarelli & Luciano Pietronero, 2013. "Measuring the Intangibles: A Metrics for the Economic Complexity of Countries and Products," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-20, August.
    5. Simon Kuznets, 1946. "Introduction, National Income: A Summary of Findings," NBER Chapters, in: National Income: A Summary of Findings, pages 1-2, National Bureau of Economic Research, Inc.
    6. Samir Suweis & Filippo Simini & Jayanth R. Banavar & Amos Maritan, 2013. "Emergence of structural and dynamical properties of ecological mutualistic networks," Nature, Nature, vol. 500(7463), pages 449-452, August.
    7. Carmen M. Reinhart & Kenneth S. Rogoff, 2010. "Growth in a Time of Debt," American Economic Review, American Economic Association, vol. 100(2), pages 573-578, May.
    8. Guido Caldarelli & Matthieu Cristelli & Andrea Gabrielli & Luciano Pietronero & Antonio Scala & Andrea Tacchella, 2012. "A Network Analysis of Countries’ Export Flows: Firm Grounds for the Building Blocks of the Economy," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-11, October.
    9. Robert Costanza & Ida Kubiszewski & Enrico Giovannini & Hunter Lovins & Jacqueline McGlade & Kate E. Pickett & Kristín Vala Ragnarsdóttir & Debra Roberts & Roberto De Vogli & Richard Wilkinson, 2014. "Development: Time to leave GDP behind," Nature, Nature, vol. 505(7483), pages 283-285, January.
    10. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    11. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    12. Bowen, Harry P & Leamer, Edward E & Sveikauskas, Leo, 1987. "Multicountry, Multifactor Tests of the Factor Abundance Theory," American Economic Review, American Economic Association, vol. 77(5), pages 791-809, December.
    13. Simon Kuznets, 1946. "National Income: A Summary of Findings," NBER Books, National Bureau of Economic Research, Inc, number kuzn46-2.
    14. Tacchella, A. & Cristelli, M. & Caldarelli, G. & Gabrielli, A. & Pietronero, L., 2013. "Economic complexity: Conceptual grounding of a new metrics for global competitiveness," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1683-1691.
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