Sticky Models

Paul Grass, Philipp Schirmer () and Malin Siemers ()

CRC TR 224 Discussion Paper Series from University of Bonn and University of Mannheim, Germany

Keywords: mental models; learning dynamics; attention; mental representation; bounded rationality People often form mental models based on incomplete information; revising them as new relevant data becomes available. In this paper; we experimentally investigate how individuals update their models when data on predictive variables are gradually revealed. We find that people’s models tend to be ‘sticky; ’ as their final models remain strongly influenced by earlier models formed using a subset of variables. Guided by a simple framework highlighting the role of attention in shaping model revisions; we document that only participants who exert lower cognitive effort during the revising stage; relative to the initial model formation stage – as proxied by time spent – exhibit significant model stickiness. Additionally; subjects’ final models are strongly predicted by their reasoning type – their self-described approach to extracting models from multidimensional data. While model stickiness varies across reasoning types; effort allocation across stages remains a strong predictor of stickiness even when accounting for reasoning. (search for similar items in EconPapers)
JEL-codes: D83 D91 (search for similar items in EconPapers)
Pages: 63
Date: 2025-02
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Working Paper: Sticky Models (2025)
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