Learning by Convex Combination,

Clicks: 3
ID: 320393
2026
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Abstract
Abstract We study how an agent evaluates an action when she observes a sample of its outcomes rather than its outcome-generating distribution. We propose a model where the agent’s estimated value for the action is a convex combination of her average utility over the sample outcomes and an ex ante utility reflecting her prior information. The weight put on the average utility increases with sample size, reflecting the inferential advantages of larger samples. The model nests certain forms of Bayesian behaviour and, more generally, identifies parameters quantifying departures from Bayesian updating, such as conservatism and the Law of Small Numbers.
Reference Key
openalex_W7167976779 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Karol Flores-Szwagrzak
Journal the economic journal
Year 2026
DOI
10.1093/ej/ueag090
URL
Keywords Keywords not found

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