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Scrap Value Functions in Dynamic Decision Problems

Author

Listed:
  • Ikefuji, M.
  • Laeven, R.J.A.

    (Tilburg University, Center For Economic Research)

  • Magnus, J.R.

    (Tilburg University, Center For Economic Research)

  • Muris, C.H.M.

    (Tilburg University, Center For Economic Research)

Abstract

We introduce an accurate, easily implementable, and fast algorithm to compute optimal decisions in discrete-time long-horizon welfaremaximizing problems. The algorithm is useful when interest is only in the decisions up to period T, where T is small. It relies on a flexible parametrization of the relationship between state variables and optimal total time-discounted welfare through scrap value functions. We demonstrate that this relationship depends on the boundedness, half-boundedness, or unboundedness of the utility function, and on whether a state variable increases or decreases welfare. We propose functional forms for this relationship for large classes of utility functions and explain how to identify the parameters.

Suggested Citation

  • Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Scrap Value Functions in Dynamic Decision Problems," Discussion Paper 2010-77, Tilburg University, Center for Economic Research.
  • Handle: RePEc:tiu:tiucen:94a6f785-0395-4b35-9c57-744ad3cafa92
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    File URL: https://pure.uvt.nl/portal/files/1251065/2010-77.pdf
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    References listed on IDEAS

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    Cited by:

    1. Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model," Discussion Paper 2010-122, Tilburg University, Center for Economic Research.

    More about this item

    Keywords

    Scrap value function; Dynamic optimization; Computation; Short horizon.;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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