Optimal consumption under uncertainty, liquidity constraints, and bounded rationality

Ömer Özak

Journal of Economic Dynamics and Control, 2014, vol. 39, issue C, 237–254

Abstract: 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.

JEL-codes: C6 D8 D9 E21 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Optimal consumption under uncertainty, liquidity constraints, and bounded rationality (2013)
Working Paper: Optimal consumption under uncertainty, liquidity constraints, and bounded rationality (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:39:y:2014:i:c:p:237-254

DOI: 10.1016/j.jedc.2013.12.007

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