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Radical technologies, recombinant novelty and productivity growth: a cliometric approach

Author

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  • Marianna Epicoco

    (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - Université de Haute-Alsace (UHA) - Université de Haute-Alsace (UHA) Mulhouse - Colmar - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Magali Jaoul-Grammare

    (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - Université de Haute-Alsace (UHA) - Université de Haute-Alsace (UHA) Mulhouse - Colmar - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Anne Plunket

    (RITM - Réseaux Innovation Territoires et Mondialisation - Université Paris-Saclay)

Abstract

Using inventions with a high degree of recombinant novelty as proxy for radical technologies, this work provides a long-run quantitative analysis of the relationship between radical technologies and productivity growth. The empirical analysis is based on a cliometric approach and relies on Granger's causality to test the sign and direction of causality between the flow of radical technologies and productivity levels, in the USA between 1920 and 2000. At the aggregate level, results show that radical technologies cause a temporary acceleration of productivity growth and explain a considerable part of productivity variations. At technology-field level, the analysis indicates that productivity growth is driven by a few technological fields, mainly concentrated in science based sectors and in the sectors of specialized suppliers of capital equipment. Finally, with respect to the controversial issue of the endogeneity of radical technologies, at the aggregate level we find no causal relationship running from productivity to radical technologies, suggesting that these are exogenous. However, at technology-field level, we find a few endogenous technologies. Most of these are "demand-driven" as their flow increases when productivity grows, but they have no impact on productivity. Only in one technological field, the flow of radical technologies increases when productivity decreases and, at the same time, has a positive impact on productivity. This latter case may explain why technological revolutions and the whole process of longrun economic development are partly endogenous.

Suggested Citation

  • Marianna Epicoco & Magali Jaoul-Grammare & Anne Plunket, 2022. "Radical technologies, recombinant novelty and productivity growth: a cliometric approach," Post-Print halshs-03765637, HAL.
  • Handle: RePEc:hal:journl:halshs-03765637
    DOI: 10.1007/s00191-022-00768-5
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-03765637v1
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    Cited by:

    1. Jangho Yang & Brian Cozzarin & Torsten Heinrich, 2025. "Productivity dispersion and firm growth in Canada," Journal of Evolutionary Economics, Springer, vol. 35(1), pages 35-70, January.
    2. Giorgi, Julien & Plunket, Anne & Starosta de Waldemar, Felipe, 2025. "Inter-regional highly skilled worker mobility and technological novelty," Research Policy, Elsevier, vol. 54(1).
    3. Joonkyu Choi & Serguey Braguinsky & Yuheng Ding & Karam Jo & Seula Kim, 2023. "Mega Firms and New Technological Trajectories in the U.S," NBER Working Papers 31460, National Bureau of Economic Research, Inc.

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    Keywords

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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • N12 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - U.S.; Canada: 1913-

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