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Modelling smooth and uneven cross-sectoral growth patterns: an identification problem

Author

Listed:
  • Sandro Sapio

    (Sant'Anna School of Advanced Studies, Pisa, Italy)

  • Andrea Roventini

    (University of Modena and Reggio Emilia, Italy, and Sant'Anna School of Advanced Studies, Pisa, Italy)

  • Mauro Napoletano

    (Chair of Systems Design, ETH Zurich, 8092 Zurich, Switzerland, and SantAnna School of Advanced Studies, Pisa, Italy)

Abstract

This paper shows that the available stylized facts on productivity dynamics, such as persistent cross-sectoral heterogeneity, do not allow to solve an identification problem regarding the impact of common drivers - such as General Purpose Technologies (GPTs) - on economic growth. The evidence of persistently heterogeneous productivity performances is consistent both with a GPT-driven model, and with a model characterized by purely independent and idiosyncratic sectoral dynamics. These results are obtained within a simple theoretical framework, and illustrated with reference to measures of concentration of the sectoral contributions to aggregate total factor productivity growth.

Suggested Citation

  • Sandro Sapio & Andrea Roventini & Mauro Napoletano, 2006. "Modelling smooth and uneven cross-sectoral growth patterns: an identification problem," Economics Bulletin, AccessEcon, vol. 15(7), pages 1-8.
    • Handle: RePEc:ebl:ecbull:eb-06o40003
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    References listed on IDEAS

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    1. Nathan Rosenberg & Manuel Trajtenberg, 2001. "A General Purpose Technology at Work: The Corliss Steam Engine in the late 19th Century US," NBER Working Papers 8485, National Bureau of Economic Research, Inc.
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    5. Giovanni Dosi & Marco Grazzi, 2006. "Technologies as problem-solving procedures and technologies as input--output relations: some perspectives on the theory of production," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 15(1), pages 173-202, February.
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    8. David, Paul A, 1990. "The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox," American Economic Review, American Economic Association, vol. 80(2), pages 355-361, May.
    9. Sandro Sapio & Grid Thoma, 2006. "The Growth of Industrial Sectors: Theoretical Insights and Empirical Evidence from U.S. Manufacturing," LEM Papers Series 2006/09, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
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    Cited by:

    1. Castaldi, Carolina & Sapio, Sandro, 2006. "The Properties of Sectoral Growth: Evidence from Four Large European Economies," GGDC Research Memorandum GD-88, Groningen Growth and Development Centre, University of Groningen.
    2. Mark Knell & Simone Vannuccini, 2022. "Tools and concepts for understanding disruptive technological change after Schumpeter," Jena Economics Research Papers 2022-005, Friedrich-Schiller-University Jena.
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    4. Uwe Cantner & Holger Graf & Ekaterina Prytkova & Simone Vannuccini, 2018. "The Compositional Nature of Productivity and Innovation Slowdown," Jena Economics Research Papers 2018-006, Friedrich-Schiller-University Jena.
    5. Carolina Castaldi & Sandro Sapio, 2008. "Growing like mushrooms? Sectoral evidence from four large European economies," Journal of Evolutionary Economics, Springer, vol. 18(3), pages 509-527, August.

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    More about this item

    Keywords

    Growth General Purpose Technologies Real Cost Reduction Total Factor Productivity.;

    JEL classification:

    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • D2 - Microeconomics - - Production and Organizations

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