Optimal consumption under uncertainty, liquidity constraints, and bounded rationality
I study how boundedly rational agents can learn the solution to an infinite horizon optimal consumption problem under uncertainty and liquidity constraints. I present conditions for the existence of an optimal linear consumption rule and characterize it. Additionally, I use an empirically plausible theory of learning to generate a class of adaptive learning algorithms that converges to the optimal rule. This provides an adaptive and boundedly rational foundation to neoclassical consumption theory.
|Date of creation:||May 2012|
|Contact details of provider:|| Postal: Department of Economics, P.O. Box 750496, Southern Methodist University, Dallas, TX 75275-0496|
Web page: http://www.smu.edu/economics
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