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Directed Attention and Nonparametric Learning

Ian Dew-Becker, Charles G. Nathanson

NBER Working Paper No. 23917
Issued in October 2017
NBER Program(s):The Asset Pricing Program, The Economic Fluctuations and Growth Program

We study an ambiguity-averse agent with uncertainty about income dynamics who chooses what aspects of the income process to learn about. The agent chooses to learn most about income dynamics at the very lowest frequencies, which have the greatest effect on utility. Deviations of consumption from the full-information benchmark are then largest at high frequencies, so consumption responds strongly to predictable changes in income in the short-run but is closer to a random walk in the long-run. Whereas ambiguity aversion typically leads agents to act as though shocks are more persistent than the truth, endogenous learning here eliminates that effect.

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Document Object Identifier (DOI): 10.3386/w23917

Published: Ian Dew-Becker & Charles G. Nathanson, 2019. "Directed attention and nonparametric learning," Journal of Economic Theory, .

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