Directed Attention and Nonparametric Learning

Ian Dew-Becker and Charles G. Nathanson

No 23917, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C14 D83 E21 (search for similar items in EconPapers)
Date: 2017-10
New Economics Papers: this item is included in nep-cta, nep-mac and nep-upt
Note: AP EFG
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Published as Ian Dew-Becker & Charles G. Nathanson, 2019. "Directed attention and nonparametric learning," Journal of Economic Theory, .

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Journal Article: Directed attention and nonparametric learning (2019)
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