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Dynamic Programming with State-Dependent Discounting

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  • John Stachurski
  • Junnan Zhang

Abstract

This paper extends the core results of discrete time infinite horizon dynamic programming to the case of state-dependent discounting. We obtain a condition on the discount factor process under which all of the standard optimality results can be recovered. We also show that the condition cannot be significantly weakened. Our framework is general enough to handle complications such as recursive preferences and unbounded rewards. Economic and financial applications are discussed.

Suggested Citation

  • John Stachurski & Junnan Zhang, 2019. "Dynamic Programming with State-Dependent Discounting," Papers 1908.08800, arXiv.org, revised Oct 2020.
    • Handle: RePEc:arx:papers:1908.08800
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    1. Dynamic Programming with State-Dependent Discounting
      by Christian Zimmermann in NEP-DGE blog on 2019-09-25 22:14:42

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