Discounting Long Run Average Growth In Stochastic Dynamic Programs
AbstractFinding 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.
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Bibliographic InfoPaper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2002-08.
Length: 40 pages
Date of creation: Jul 2002
Date of revision:
Publication status: Published by Ivie
Dynamic Programming; Weighted Norms; Contraction Mappings; Dominated Convergence; Non Additive Recursive Functions.;
Other versions of this item:
- Jorge Durán, 2003. "Discounting long run average growth in stochastic dynamic programs," Economic Theory, Springer, vol. 22(2), pages 395-413, 09.
- Duran, Jorge, 2000. "Discounting Long Run Average Growth in Stochastic Dynamic Programs," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2000006, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
- Duran, Jorge, 2001. "Discounting long run average growth in stochastic dynamic programs," CEPREMAP Working Papers (Couverture Orange) 0101, CEPREMAP.
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
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