摘要翻译：
本文将离散时间无限时域动态规划的核心结果推广到状态相关贴现的情形。我们得到了折扣因子过程的一个条件，在此条件下所有的标准最优性结果都可以恢复。我们还表明条件不能明显减弱。我们的框架足够通用，可以处理诸如递归偏好和无界奖励之类的复杂问题。讨论了经济和金融应用。
---
英文标题：
《Dynamic Programming with State-Dependent Discounting》
---
作者：
John Stachurski, Junnan Zhang
---
最新提交年份：
2020
---
分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
--
一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
--

---
英文摘要：
  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.
---
PDF链接：
https://arxiv.org/pdf/1908.08800