Document Type
Article
Publication Date
11-6-2024
Abstract
Personal finance research often utilizes Likert-type items and Likert scales as dependent variables, frequently employing standard probit and ordered probit models. If inappropriately modeled, the "neutral" category of discrete dependent variables can bias estimates of the remaining categories. Through the utilization of hierarchical models, this paper demonstrates a methodology that accounts for the econometric issues of the neutral category. We then analyze the technique through an empirical exercise relevant to personal finance research using data from the National Financial Capability Study. We demonstrate that ignoring the "neutral" category bias can lead to incorrect inferences, hindering the progression of personal finance research. Our findings underscore the importance of refining statistical modeling techniques when dealing with Likert-type data. By accounting for the neutral category, we can enhance the reliability of personal finance research outcomes, fostering improved decision-relevant insights.
This article was published Open Access through the CCU Libraries Open Access Publishing Fund. The article was first published in Econometrics: https://doi.org/10.3390/econometrics12040033
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Pearson, B., Lacombe, D., & Khatun, N. (2024). Likert Scale Variables in Personal Finance Research: The Neutral Category Problem. Econometrics, 12(4), 33. https://doi.org/10.3390/econometrics12040033. Available at https://digitalcommons.coastal.edu/finance-economics/2/