Discounting Long Run Average Growth in Stochastic Dynamic Programs
AbstractFinding solutions to the Bellman equation relies on restrictive boundedness assumptions. The literature on endogenous growth or business cycle models with unbounded random shocks provide with numerous examples of recursive programs in which returns are not bounded along feasible paths. In this paper we develop a method of proof that allows to account for models of this type. 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 Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES) in its series Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) with number 2000006.
Date of creation: 01 Feb 2000
Date of revision:
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.
- Jorge Durán, 2002. "Discounting Long Run Average Growth In Stochastic Dynamic Programs," Working Papers. Serie AD 2002-08, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-02-10 (All new papers)
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