Learning with limited memory: Bayesianism vs heuristics

Kalyan Chatterjee and Tai-Wei Hu

Journal of Economic Theory, 2023, vol. 209, issue C

Abstract: Bayesian analysis is considered the optimal way of processing information. However, it often leads to problems for decision-makers with constrained cognitive capacity. Modeling such constrained capacity by finite automata, we answer two questions in the context of Wald's (1947) sequential analysis, namely in what environments is optimal Bayesian analysis possible even with constraints; also, when it is not possible what simplifications in the analysis enable us to obtain a satisfactory outcome. We identify two features of the simplified analysis: information stickiness (ignoring information) and rule stickiness (ignoring small differences in the environment).

Keywords: Imperfect recall; Bounded rationality; Bounded memory; Heuristics; Behavioral biases (search for similar items in EconPapers)
JEL-codes: D81 D83 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0022053123000388
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:209:y:2023:i:c:s0022053123000388

DOI: 10.1016/j.jet.2023.105642

Access Statistics for this article

Journal of Economic Theory is currently edited by A. Lizzeri and K. Shell

More articles in Journal of Economic Theory from Elsevier
Bibliographic data for series maintained by Catherine Liu ().