Dynamic Programming with State-Dependent Discounting

John Stachurski and Junnan Zhang

Papers from arXiv.org

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.

Date: 2019-08, Revised 2020-10
New Economics Papers: this item is included in nep-dge
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1908.08800

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