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Information technologies, embodiment and growth

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  • Boucekkine, Raouf
  • de la Croix, David

Abstract

This paper studies the conditions under which an IT revolution may occur and have permanent effects on long-term growth. To this end, we construct a multi-sectoral growth model with endogenous embodied technical progress. The R&D sector expands the range of softwares. The capital sector produces efficient capital combining hardware with available softwares. Technological progress is therefore embodied: New softwares can only be run on the most recent generations of hardware. The new softwares are copyrighted during a fixed period of time. First, we analytically characterize the balanced growth paths of the model. Then we focus on the dynamic response of the economy to technological shocks. Substitution effects favorable to the IT sectors are shown to arise when positive supply shocks affect the production of efficient capital and/or the creation of new softwares. Positive shocks specific to the capital sector are unable to produce effects on long-term growth, in contrast to the shocks specific to the R&D sector.
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  • Boucekkine, Raouf & de la Croix, David, 2003. "Information technologies, embodiment and growth," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2007-2034, September.
    • Handle: RePEc:eee:dyncon:v:27:y:2003:i:11-12:p:2007-2034
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    Cited by:

    1. Raouf Boucekkine & David de la Croix & Yiannis Vailakis, 2002. "Technological Shocks and IT Revolutions," Recherches économiques de Louvain, De Boeck Université, vol. 68(1), pages 75-89.
    2. Mattalia, Claudio, 2012. "Human capital accumulation in R&D-based growth models," Economic Modelling, Elsevier, vol. 29(3), pages 601-609.
    3. Keiichi Kishi, 2015. "Dynamic analysis of wage inequality and creative destruction," Journal of Economics, Springer, vol. 115(1), pages 1-23, May.
    4. Chatelain, Jean-Bernard & Ralf, Kirsten & Amable, Bruno, 2010. "Patents as Collateral," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 34(6), pages 1094-1104.
    5. Dan Su & Yang Yao, 2017. "Manufacturing as the key engine of economic growth for middle-income economies," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 22(1), pages 47-70, January.
    6. Bambi, Mauro & Gozzi, Fausto & Licandro, Omar, 2014. "Endogenous growth and wave-like business fluctuations," Journal of Economic Theory, Elsevier, vol. 154(C), pages 68-111.
    7. De, Supriyo, 2014. "Intangible capital and growth in the ‘new economy’: Implications of a multi-sector endogenous growth model," Structural Change and Economic Dynamics, Elsevier, vol. 28(C), pages 25-42.
    8. Ohki, Kazuyoshi, 2015. "Analysis of transition dynamics caused by technological breakthroughs: Cause of productivity slowdown and drop in existing firms’ stock prices," Structural Change and Economic Dynamics, Elsevier, vol. 35(C), pages 12-25.
    9. Rivas-Aceves, Salvador, 2013. "El sector público y el cambio tecnológico [The public sector and technological change]," MPRA Paper 58267, University Library of Munich, Germany, revised 2013.
    10. Yu. Yatsenko & N. Hritonenko, 2007. "Network economics and optimal replacement of age-structured IT capital," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 65(3), pages 483-497, June.
    11. Mattalia, Claudio, 2013. "Embodied technological change and technological revolution: Which sectors matter?," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 249-264.

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    More about this item

    JEL classification:

    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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