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Economic Growth and Innovation Complexity: An Empirical Estimation of a Hidden Markov Model

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Over the past decades, research effort in high income countries has substantially increased. Meanwhile, the growth rates of per capita output have been rather stable. The contribution of this paper is twofold. The first is to provide a theoretical explanation for such trends by developing an R&D-based growth model which accounts for dilution, difficulty and duplication effects. The second is to show empirically that the occurrence of different phases in the economic growth dynamics traces back to the interplay between complexity and specialization in production. To do this we estimate a Hidden Markov Model in which countries can switch across different growth regimes. We identify four distinct growth regimes.

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  • Alberto Bucci & Lorenzo Carbonari & Pedro Mazeda Gil & Giovanni Trovato, 2020. "Economic Growth and Innovation Complexity: An Empirical Estimation of a Hidden Markov Model," CEIS Research Paper 483, Tor Vergata University, CEIS, revised 12 Nov 2021.
  • Handle: RePEc:rtv:ceisrp:483
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    Cited by:

    1. Zhu, Chen & Xia, Yuqing & Liu, Qing & Hou, Bojun, 2023. "Deregulation and green innovation: Does cultural reform pilot project matter," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 84-105.

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    More about this item

    Keywords

    Economic growth; Population growth; Complexity; Hidden Markov Model;
    All these keywords.

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • J1 - Labor and Demographic Economics - - Demographic Economics

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