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The Trade-off between Innovation and Defence Industrial Policy: A Simulation Model Analysis of the Norwegian Defence Industry


  • Blom, Martin
  • Castellacci, Fulvio
  • Fevolden, Arne


The paper investigates the trade-off between innovation and defence industrial policy. It presents an agent-based simulation model calibrated for the Norwegian defence industry that compares different policy scenarios and examines the effects of a pending EU market liberalization process. The paper points to two main results. (1) It finds that a pure scenario where national authorities focus on, and provide support exclusively for, either a) international competitiveness or b) national defence and security objectives, is more Pareto efficient than a corresponding mixed strategy where policy makers simultaneously pursue both international competitiveness and defence and security objectives. (2) Under the conditions of the new EU liberalization regime, a stronger and more visible trade-off will emerge between international competitiveness and national defence and security objectives. Policy makers will have to choose which to prioritise, and set a clear agenda focusing on one of the two objectives.

Suggested Citation

  • Blom, Martin & Castellacci, Fulvio & Fevolden, Arne, 2014. "The Trade-off between Innovation and Defence Industrial Policy: A Simulation Model Analysis of the Norwegian Defence Industry," MPRA Paper 55326, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:55326

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    References listed on IDEAS

    1. Elhanan Helpman & Marc J. Melitz & Stephen R. Yeaple, 2004. "Export Versus FDI with Heterogeneous Firms," American Economic Review, American Economic Association, vol. 94(1), pages 300-316, March.
    2. Pavitt, Keith, 1984. "Sectoral patterns of technical change: Towards a taxonomy and a theory," Research Policy, Elsevier, vol. 13(6), pages 343-373, December.
    3. Gilbert, Nigel & Ahrweiler, Petra & Pyka, Andreas, 2007. "Learning in innovation networks: Some simulation experiments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 100-109.
    4. Tesfatsion, Leigh S., 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Staff General Research Papers Archive 5075, Iowa State University, Department of Economics.
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    Cited by:

    1. repec:seb:journl:v:15:y:2017:i:2:p:103-125 is not listed on IDEAS
    2. Bojnec, Štefan, 2016. "Dual-use products export multipliers with the indirect effects," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 287-296.

    More about this item


    Innovation policy; industrial policy; defense industry; EU liberalization; agent-based simulation model;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • H0 - Public Economics - - General
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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