Dynamic programming for non-additive stochastic objectives

Hiroyuki Ozaki, Peter A. Streufert

研究成果: Article

15 引用 (Scopus)

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We derive the existence of an optimum and the techniques of dynamic programming for non-additive stochastic objectives. Our key assumption for non-negative objectives is that asymptotic impatience exceeds asymptotic 'mean' growth, where 'mean' growth is derived not only from intertemporal inelasticity and the random return on investment but also from the curvature of the non-additive stochastic aggregator (i.e. the 'certainty equivalent'). We provide broad families of new, interesting, and tractable examples. They illustrate that 'mean' growth can exist even when the distribution of returns has unbounded support, that power discounting often implies infinite asymptotic impatience, and that non-positive objectives are easily handled with few restrictions on growth.

元の言語English
ページ(範囲)391-442
ページ数52
ジャーナルJournal of Mathematical Economics
25
発行部数4
DOI
出版物ステータスPublished - 1996
外部発表Yes

ASJC Scopus subject areas

  • Economics and Econometrics
  • Applied Mathematics

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