JOURNAL ARTICLE
Financial Self-Efficacy as a Mediator Between Financial Socialization, Early Childhood Consumer Experiences, and Financial Well-Being.
Published In: Journal of Financial Counseling & Planning, 2024, v. 35, n. 1. P. 123 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Ullah, Saif; Tahir, Muhammad S.; Farooq, Muhammad 3 of 3
Abstract
This study used financial socialization theory to examine the direct and indirect association between financial socialization (from parents, peers, and teachers) and financial well-being (FWB) via financial self-efficacy (FSE). Data were collected from Pakistan in early 2020. Our data analysis using the partial least square structural equation modeling approach revealed surprising results. We found that an association between financial socialization from peers and FWB does not exist both directly and indirectly via FSE. Furthermore, the results showed that the association of financial socialization from parents and teachers with FWB is completely mediated by FSE. Other results indicated partial mediation of FSE in the association between early childhood consumer experience and FWB. Our findings imply that learning from others' financial experiences builds young consumers' confidence in dealing with financial matters, which, in turn, helps improve their FWB. We suggest policymakers to consider these findings in designing policies related to the young consumers of developing nations. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Financial Counseling & Planning. 2024/01, Vol. 35, Issue 1, p123
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2024
- ISSN:1052-3073
- DOI:10.1891/JFCP-2022-0087
- Accession Number:176847787
- Copyright Statement:Copyright of Journal of Financial Counseling & Planning is the property of Springer Publishing Company, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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