### Abstract

Original language | English |
---|---|

Place of Publication | Tilburg |

Publisher | Econometrics |

Number of pages | 18 |

Volume | 2010-77 |

Publication status | Published - 2010 |

### Publication series

Name | CentER Discussion Paper |
---|---|

Volume | 2010-77 |

### Fingerprint

### Keywords

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

### Cite this

*Scrap Value Functions in Dynamic Decision Problems*. (CentER Discussion Paper; Vol. 2010-77). Tilburg: Econometrics.

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**Scrap Value Functions in Dynamic Decision Problems.** / Ikefuji, M.; Laeven, R.J.A.; Magnus, J.R.; Muris, C.H.M.

Research output: Working paper › Discussion paper › Other research output

TY - UNPB

T1 - Scrap Value Functions in Dynamic Decision Problems

AU - Ikefuji, M.

AU - Laeven, R.J.A.

AU - Magnus, J.R.

AU - Muris, C.H.M.

N1 - Pagination: 18

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - Scrap value function

KW - Dynamic optimization

KW - Computation

KW - Short horizon.

M3 - Discussion paper

VL - 2010-77

T3 - CentER Discussion Paper

BT - Scrap Value Functions in Dynamic Decision Problems

PB - Econometrics

CY - Tilburg

ER -