Scrap Value Functions in Dynamic Decision Problems

M. Ikefuji, R.J.A. Laeven, J.R. Magnus, C.H.M. Muris

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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.
Original languageEnglish
Place of PublicationTilburg
Number of pages18
Publication statusPublished - 2010

Publication series

NameCentER Discussion Paper


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


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