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Technological opportunity, long-run growth, and convergence

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  • Jakub Growiec
  • Ingmar Schumacher

Abstract

We derive a R&D-based growth model where the rate of technological progress depends, inter alia, on the amount of technological opportunity. Incremental innovations provide direct increases to the knowledge stock but they reduce technological opportunity and thus the potential for further improvements. Technological opportunity is renewed by radical innovations, which have no direct impact on factor productivity. We study both the market equilibrium and the social planner allocation in this economy. Investigating the model for its implications on economic growth we find: (i) in the long run, a balanced growth path requires that the returns to radical innovations are at least as large as those of the incremental ones; (ii) the transition need not be monotonic. We show under which conditions our model generates endogenous cycles via complex dynamics without resorting to uncertainty; (iii) the calibrated model exhibits substantial quantitative differences between the market outcome and the social planner allocation. Copyright 2013 Oxford University Press 2012 All rights reserved, Oxford University Press.

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  • Jakub Growiec & Ingmar Schumacher, 2013. "Technological opportunity, long-run growth, and convergence," Oxford Economic Papers, Oxford University Press, vol. 65(2), pages 323-351, April.
  • Handle: RePEc:oup:oxecpp:v:65:y:2013:i:2:p:323-351
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    File URL: http://hdl.handle.net/10.1093/oep/gps022
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    Cited by:

    1. Pedro Mazeda Gil & André Almeida, & Sofia B.S.D. Castro,, 2015. "Flexible Transitional Dynamics in a Non-Scale Fully Endogenous Growth Model," CEF.UP Working Papers 1503, Universidade do Porto, Faculdade de Economia do Porto.
    2. Gil, Pedro Mazeda & Iglésias, Gustavo & Guimarães, Luís, 2023. "Endogenous growth and monetary policy: How do interest-rate feedback rules shape nominal and real transitional dynamics?," Journal of International Money and Finance, Elsevier, vol. 138(C).
    3. Daniel Nepelski & Giuditta De Prato, 2020. "Technological complexity and economic development," Review of Development Economics, Wiley Blackwell, vol. 24(2), pages 448-470, May.
    4. Gersbach, Hans & Sorger, Gerhard & Amon, Christian, 2018. "Hierarchical growth: Basic and applied research," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 434-459.
    5. Jakub Growiec, 2019. "The Hardware–Software Model: A New Conceptual Framework of Production, R&D, and Growth with AI," Working Paper series 19-18, Rimini Centre for Economic Analysis.
    6. Jakub Growiec, 2018. "The Digital Era, Viewed From a Perspective of Millennia of Economic Growth," KAE Working Papers 2018-034, Warsaw School of Economics, Collegium of Economic Analysis.
    7. Liu, Taoxiong & Liu, Zhuohao, 2022. "A growth model with endogenous technological revolutions and cycles," Journal of Mathematical Economics, Elsevier, vol. 103(C).

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    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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