Predicting savings adequacy using machine learning: A behavioural economics approach

作者：

Highlights：

• Savings adequacy is best predicted by the decision tree model with 96.1% accuracy.

• Mental accounting categories have predictive power on savings adequacy.

• Luxury items and current asset amount were most important to savings adequacy.

摘要

•Savings adequacy is best predicted by the decision tree model with 96.1% accuracy.•Mental accounting categories have predictive power on savings adequacy.•Luxury items and current asset amount were most important to savings adequacy.

论文关键词：Behavioural finance,Economics,Human decision-making,Psychology

论文评审过程：Received 13 February 2022, Revised 29 April 2022, Accepted 1 May 2022, Available online 6 May 2022, Version of Record 12 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117502