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Dynamic heterogeneous R&D with cross-technologies interactions

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  • Bondarev, Anton
  • Krysiak, Frank C.

Abstract

In many countries, inducing large-scale technological changes has become an important policy objective, as in the context of climate policy or energy transitions. Such large-scale changes require the development of strongly interlinked technologies. But current economic models have little flexibility for describing such linkages. We present a model of induced technological change that covers a fairly large set of cross-technology interactions and that can describe a wide variety of long-run developments. Using this model, we analyse and compare the development induced by optimal fifrm behaviour and the socially optimal dynamics. We show that the structure of cross-technology interactions is highly important. It shapes the dynamics of technological change in the decentralised and the socially optimal solution, including the prospects of continued productivity growth. It determines whether the decentralised and the socially optimal solution have similar or qualitatively difffferent dynamics. Finally, it is highly important for the question whether simple r&d policies can induce effifficient technological change.

Suggested Citation

  • Bondarev, Anton & Krysiak, Frank C., 2017. "Dynamic heterogeneous R&D with cross-technologies interactions," Working papers 2017/13, Faculty of Business and Economics - University of Basel.
  • Handle: RePEc:bsl:wpaper:2017/13
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    References listed on IDEAS

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    1. Pietro Peretto & Sjak Smulders, 2002. "Technological Distance, Growth And Scale Effects," Economic Journal, Royal Economic Society, vol. 112(481), pages 603-624, July.
    2. Fischer, Carolyn & Parry, Ian W. H. & Pizer, William A., 2003. "Instrument choice for environmental protection when technological innovation is endogenous," Journal of Environmental Economics and Management, Elsevier, vol. 45(3), pages 523-545, May.
    3. Anton Bondarev, 2012. "The long-run dynamics of product and process innovations for a multi-product monopolist," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 21(8), pages 775-799, November.
    4. Chu, Angus C. & Cozzi, Guido & Galli, Silvia, 2012. "Does intellectual monopoly stimulate or stifle innovation?," European Economic Review, Elsevier, vol. 56(4), pages 727-746.
    5. Sjak Smulders, 1995. "Entropy, environment, and endogenous economic growth," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 2(2), pages 319-340, August.
    6. Acemoglu, Daron & Cao, Dan, 2015. "Innovation by entrants and incumbents," Journal of Economic Theory, Elsevier, vol. 157(C), pages 255-294.
    7. Pietro Peretto & Michelle Connolly, 2007. "The Manhattan Metaphor," Journal of Economic Growth, Springer, vol. 12(4), pages 329-350, December.
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    Cited by:

    1. Bondarev, Anton, 2018. "Heterogeneous R&D spillovers and sustainable growth: Limits to efficient regulation," Working papers 2018/04, Faculty of Business and Economics - University of Basel.

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    More about this item

    Keywords

    technological spillovers; social optimality; market inefficiency; optimal control; heterogeneous innovations;
    All these keywords.

    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
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D62 - Microeconomics - - Welfare Economics - - - Externalities

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