DISCOUNTING LONG RUN AVERAGE GROWTH IN STOCHASTIC DYNAMIC PROGRAMS

Jorge Durán

Working Papers. Serie AD from Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie)

Abstract: Finding solutions to the Bellman equation often relies on restrictive boundedness assumptions. In this paper we develop a method of proof that allows to dispense with the assumption that returns are bounded from above. In applications our assumptions only imply that long run average (expected) growth is sufficiently discounted, in sharp contrast with classical assumptions either absolutely bounding growth or bounding each period (instead of long run) maximum (instead of average) growth. We discuss our work in relation to the literature and provide several examples.

Keywords: Dynamic Programming; Weighted Norms; Contraction Mappings; Dominated Convergence; Non Additive Recursive Functions. (search for similar items in EconPapers)
Pages: 40 pages
Date: 2002-07
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Published by Ivie

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http://www.ivie.es/downloads/docs/wpasad/wpasad-2002-08.pdf Fisrt version / Primera version, 2002 (application/pdf)

Related works:
Journal Article: Discounting long run average growth in stochastic dynamic programs (2003)
Working Paper: Discounting long run average growth in stochastic dynamic programs (2001)
Working Paper: Discounting Long Run Average Growth in Stochastic Dynamic Programs (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:ivi:wpasad:2002-08

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