On the complexity of forming mental models

• 成果类型: Article
• 署名作者: Kendall, Chad; Oprea, Ryan
• 署名单位: University of Southern California; University of California System; University of California Los Angeles
• 刊物名称: QUANTITATIVE ECONOMICS
• ISSN/ISSBN: 1759-7323
• DOI: 10.3982/QE2264
• 发表日期: 2024
• 页码: 175-211
• 关键词: Complexity; mental models; inference; bounded rationality; behavioral economics; economics experiments; C0; C91; D91

摘要

We experimentally study how people form predictive models of simple data generating processes (DGPs), by showing subjects data sets and asking them to predict future outputs. We find that subjects: (i) often fail to predict in this task, indicating a failure to form a model, (ii) often cannot explicitly describe the model they have formed even when successful, and (iii) tend to be attracted to the same, simple models when multiple models fit the data. Examining a number of formal complexity metrics, we find that all three patterns are well organized by metrics suggested by Lipman (1995) and Gabaix (2014) that describe the information processing required to deploy models in prediction.