Sticky Models

Paul Grass, Philipp Schirmer () and Malin Siemers ()
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Philipp Schirmer: University of Bonn
Malin Siemers: University of Bonn

No 355, ECONtribute Discussion Papers Series from University of Bonn and University of Cologne, Germany

Abstract: 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.

Keywords: Mental models; learning dynamics; attention; mental representation; bounded rationality (search for similar items in EconPapers)
JEL-codes: D83 D91 (search for similar items in EconPapers)
Pages: 63
Date: 2025-02
New Economics Papers: this item is included in nep-cbe
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https://www.econtribute.de/RePEc/ajk/ajkdps/ECONtribute_355_2025.pdf First version, 2025 (application/pdf)

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Working Paper: Sticky Models (2025)
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Persistent link: https://EconPapers.repec.org/RePEc:ajk:ajkdps:355

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