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Optimal consumption under uncertainty, liquidity constraints, and bounded rationality

  • Ömer Özak

    ()

    (Southern Methodist University)

I study how boundedly rational agents can learn a “good” solution to an infinite horizon optimal consumption problem under uncertainty and liquidity constraints. Using an empirically plausible theory of learning I propose a class of adaptive learning algorithms that agents might use to choose a consumption rule. I show that the algorithm always has a globally asymptotically stable consumption rule, which is optimal. Additionally, I present extensions of the model to finite horizon settings, where agents have finite lives and life-cycle income patterns. This provides a simple and parsimonious model of consumption for large agent based models.

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File URL: ftp://ftp1.economics.smu.edu/WorkingPapers/2013/OZAK/OZAK-2013-07.pdf
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Paper provided by Southern Methodist University, Department of Economics in its series Departmental Working Papers with number 1307.

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Date of creation: Sep 2013
Date of revision:
Handle: RePEc:smu:ecowpa:1307
Contact details of provider: Postal: Department of Economics, P.O. Box 750496, Southern Methodist University, Dallas, TX 75275-0496
Phone: 214-768-2715
Fax: 214-768-1821
Web page: http://www.smu.edu/economics

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  1. Loomes, Graham & Sugden, Robert, 1982. "Regret Theory: An Alternative Theory of Rational Choice under Uncertainty," Economic Journal, Royal Economic Society, vol. 92(368), pages 805-24, December.
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