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Variational Bayes and non-Bayesian Updating

Tomasz Strzalecki

arXiv 14 May 2024 · Theoretical Economics

arXiv:2405.08796 · PDF · DOI · OpenAlex · Extracted main text

Abstract

I show how variational Bayes can be used as a microfoundation for a popular model of non-Bayesian updating.

Citation extraction

34
references
35
in-text mentions
34
distinct cited
0
self-citations
1,948
main-text words

appendix boundary found by appendix_command · 89% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Hansen and Sargent (2001) Robust control and model uncertainty0.5112250%
2Augenblick and Rabin (2021) Belief movement, uncertainty reduction, and rational updating0.40511100%
3Bénabou and Tirole (2016) Mindful economics: The production, consumption, and value of beliefs0.40511100%
4Benjamin (2019) Errors in probabilistic reasoning and judgment biases0.40511100%
5Bhattacharya, Pati, and Yang (2019) Bayesian fractional posteriors0.40511100%
6Bissiri, Holmes, and Walker (2016) A general framework for updating belief distributions0.40511100%
7Blei, Kucukelbir, and McAuliffe (2017) Variational inference: A review for statisticians0.40511100%
8Brunnermeier and Parker (2005) Optimal expectations0.40511100%
9Cover and Thomas (1991) Information theory and statistics0.40511100%
10Dominiak, Kovach, and Tserenjigmid (2023) Inertial Updating0.40511100%

Showing the top 10 of 34 scored citations.