Optimal consumption under uncertainty, liquidity constraints, and bounded rationality
AbstractI 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.
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Bibliographic InfoPaper provided by Southern Methodist University, Department of Economics in its series Departmental Working Papers with number 1204.
Date of creation: May 2012
Date of revision:
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
Adaptive learning models; bounded rationality; dynamic programming; consumption function; behavioral economics; liquidity constraint; Markov process;
Find related papers by JEL classification:
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
- D8 - Microeconomics - - Information, Knowledge, and Uncertainty
- D9 - Microeconomics - - Intertemporal Choice and Growth
- E21 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-05-29 (All new papers)
- NEP-DGE-2012-05-29 (Dynamic General Equilibrium)
- NEP-EVO-2012-05-29 (Evolutionary Economics)
- NEP-UPT-2012-05-29 (Utility Models & Prospect Theory)
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