Quantitative Economics

Journal Of The Econometric Society

Edited by: Stéphane Bonhomme • Print ISSN: 1759-7323 • Online ISSN: 1759-7331

Quantitative Economics: Jan, 2024, Volume 15, Issue 1

On the Complexity of Forming Mental Models

p. 175-211

Chad Kendall, Ryan Oprea

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.

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Supplemental Material

Supplement to "On the Complexity of Forming Mental Models"

Chad Kendall and Ryan Oprea

This supplemental appendix contains material not found within the manuscript.

Supplement to "On the Complexity of Forming Mental Models"

Chad Kendall and Ryan Oprea

The replication package for this paper is available at https://doi.org/10.5281/zenodo.8335264. The Journal checked the data and codes included in the package for their ability to reproduce the results in the paper and approved online appendices. Given the highly demanding nature of the algorithms, the reproducibility checks were run on a simplified version of the code, which is also available in the replication package.

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