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Optimal Stabilization Policy in the Presence of Learning by Doing

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  • Martin, Philippe
  • Rogers, Carol Ann

Abstract

This paper analyses the optimal stabilization policy when growth is driven by learning by doing. If benefits of learning by doing are not fully internalized, the optimal policy is to tax labor during expansions and to subsidize it during recessions. The long-term impact of this policy depends critically on initial conditions: If stabilization starts during an expansion, it has a positive effect on long-term production. When stabilization starts during a recession, its long-term effect is negative. The paper makes a methodological contribution in its analytical derivation of the optimal policy along the transition path as well as in the steady state. Copyright 2000 by Blackwell Publishing Inc.

Suggested Citation

  • Martin, Philippe & Rogers, Carol Ann, 2000. "Optimal Stabilization Policy in the Presence of Learning by Doing," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 2(2), pages 213-241.
    • Handle: RePEc:bla:jpbect:v:2:y:2000:i:2:p:213-41
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    Cited by:

    1. Alan Krause, 2008. "Optimal Nonlinear Income Taxation with Learning-by-Doing," Discussion Papers 08/08, Department of Economics, University of York.
    2. Callen, Michael & Imbs, Jean & Mauro, Paolo, 2015. "Pooling risk among countries," Journal of International Economics, Elsevier, vol. 96(1), pages 88-99.
    3. Talukdar, Bidyut, 2017. "Learning-by-doing, organizational capital and optimal markup variations," The Journal of Economic Asymmetries, Elsevier, vol. 15(C), pages 39-47.
    4. Krause, Alan, 2009. "Optimal nonlinear income taxation with learning-by-doing," Journal of Public Economics, Elsevier, vol. 93(9-10), pages 1098-1110, October.

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