Optimal Consumption Under Uncertainty, Liquidity Constraints, and Bounded Rationality
68 Pages Posted: 10 Oct 2013
Date Written: October 9, 2013
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.
Keywords: Adaptive learning models, bounded rationality, dynamic programming, consumption function, behavioral economics, saving behavior
JEL Classification: C6, D8, D9, E21
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