A Latent Profile Analysis of Undergraduate Students’ Financial Behavior
Article Sidebar
Main Article Content
Abstract
The purpose of this study was to analyze the latent profile of undergraduate students’ financial behavior. This study employed a survey research design. The sample consisted of 1,464 undergraduate students in 45 public and private institutions. The research instruments comprised a financial behavior level questionnaire with content validity and reliability coefficients of .793 - .819. Data analysis was performed by using descriptive statistics and multivariate analysis technique, which were the mean, standard deviation, Pearson’s correlation, confirmatory factor analysis, and latent profile analysis. The results were as follows:
The undergraduate students’ financial behavior was composed of 3 components: behavior of income and expenses, behavior of saving and being debt free, and financial planning behavior. The measurement model of the undergraduate students’ financial behavior fit the empirical data well (2(1,464, df = 25) = 88.448, p = .000, SRMR = .034, RMSEA = .042). The latent profile analysis of the undergraduate students’ financial behavior identity classified undergraduate students into three classes: class 1 consisted of 407 undergraduate students (27.80%) whose spending was prudential, class 2 consisted of 460 undergraduate students (31.42%) who spent their money wisely, and class 3 consisted of 597 undergraduate students (40.78%) whose level of financial behavior was low. The findings of this study identify the critical class of the undergraduate students’ financial behavior, offer specific entry points for interventions by educators, and provide positive pathways to develop financial behavior of young adults.
Article Details
The content and information contained in the published article in the Journal of Educational Measurement Mahasarakham University represent the opinions and responsibilities of the authors directly. The editorial board of the journal is not necessarily in agreement with or responsible for any of the content.
The articles, data, content, images, etc. that have been published in the Journal of Educational Measurement Mahasarakham University are copyrighted by the journal. If any individual or organization wishes to reproduce or perform any actions involving the entirety or any part of the content, they must obtain written permission from the Journal of Educational Measurement Mahasarakham University.
References
สำนักงานคณะกรรมการการอุดมศึกษา. (2562). รายงานจำนวนนักศึกษาทั้งหมด ปีการศึกษา 2561 ภาคการเรียนที่ 1 จำแนกตามประเภทสถาบัน/ชื่อสถาบัน/ชื่อคณะ/ชื่อหลักสูตร ระดับการศึกษา และเพศ. [ออนไลน์]. ระบบเผยแพร่สารสนเทศอุดมศึกษา. ได้จาก http://www.info.mua.go.th/info/ [สืบค้นเมื่อ วันที่ 27 ตุลาคม 2562].
Agawalla, S. K., Barua, S. K., Jacob, J., & Varma, J. R. (2015). Financial literacy among working young in urban India. World Development, 67, 101-109. doi: 10.1016/j.worlddev.2014.10.004
Antonietti, A., Borsetto, A., & Iannello, P. (2016). A metacognitive approach to financial literacy. In Aprea, C. Wuttke, E. Breuer, K. Koh, N. K. Davies, P. Greimel-Fuhrmann, B. & Lopus, J. S. (Eds.). International handbook of financial literacy (pp. 57-68). Singapore: Springer.
Arceo-Gómez, E. O., & Villagómez, A. (2017). Financial literacy among Mexican high school teenagers. International Review of Economics Education, 24(January 2017), 1-17. doi: 10.1016/j.iree.2016.10.001
Birkenmaier, J., & Fu, Q. (2016). Who uses alternative financial services? A latent class analysis of consumer financial knowledge and behavior. Journal of Social Service Research, 42(3), 412-424. doi: 10.1080/01488376.2016.1147519
Bucher-Koenen, T., Alessie, R., Lusardi, A., & van Rooij, M. (2016). Women, confidence, and financial literacy. [Online] Paper presented at Annual Meeting of the International Association of Applied Econometrics, Milan. Available from https://gflec.org/wp-content/uploads/2017/04/ALESSIE-Paper-Cherry-Blossom-2017.pdf?x70028 [accessed 15 April 2020].
Fabris, N., & Luburić, R. (2016). Financial education of children and youth. Journal of Central Banking Theory and Practice, 2, 65-79. doi: 10.4018/978-1-4666-7484-4.ch005
Garg, N., & Singh, S. (2018). Financial literacy among youth. International Journal of Social Economics, 45(1), 173-186. doi: 10.1108/IJSE-11-2016-0303
Gerhard, P., Gladstone, J. J., & Hoffmann, A. O. I. (2018). Psychological characteristics and household savings behavior: The importance of accounting for latent heterogeneity. Journal of Economic Behavior and Organization, 148(April), 66-82. doi: 10.1016/j.jebo.2018.02.013
Gutman, A., Garon, T., Hogarth, J., & Schneider, R. (2015). Understanding and improving consumer financial health in America. Washington, DC: CFSI Innovation.
Khan, M. N., & Rothwell, D. W. (2015). Perceived financial capability, financial knowledge and financial behaviors of Canadian low-income households. New Orleans, LA: Paper presented at the Society for Social Work Research.
Loerwald, D., & Stemmann, A. (2016). Behavioral finance and financial literacy: Educational implications of biases in financial decision making. In Aprea, C. Wuttke, E. Breuer, K. Koh, N. K. Davies, P. Greimel-Fuhrmann, B. & Lopus, J. S. (Eds.). International handbook of financial literacy (pp. 25-38). Singapore: Springer Science + Business Media Singapore.
Mittal, S., Sondhi, N., & Chawla, D. (2017). Process of impulse buying: A qualitative exploration. Global Business Review, 19(1), 131-146. doi: 10.1177/0972150917713368
Oberski, D. (2016). Mixture models: Latent profile and latent class analysis. In Robertson, J. & Kaptein, M. (Eds.). Modern statistical methods for HCI (pp. 275-287). Switzerland: Springer International Publishing Switzerland. doi: 10.1007/978-3-319-26633-6
OECD. (2016). PISA 2015 Assessment and analytical framework: Science, reading, mathematics and financial literacy. Paris: OECD Publishing. doi: 10.1787/9789264255425-en.
OECD. (2018). G20/OECD INFE policy guidance digitalisation and financial literacy. OECD.
Offringa, R., Tsai, L. C., Aira, T., Riedel, M., & Witte, S. S. (2017). Personal and financial risk typologies among women who engage in sex work in Mongolia: A latent class analysis. Archives of Sexual Behavior, 46(6),1857-1866. doi: 10.1007/s10508-016-0824-1
Shim, S., Barber, B. L., Card, N. A. Xiao, J. J., & Serido, J. (2010). Financial socialization of first-year college students: The roles of parents, work and education. Journal of Youth and Adolescence, 39(12), 1457–1470. doi: 10.1007/s10964-009-9432-x.
Shim, S., Barber, B. L., & Lyons, A. C. (2009). Pathways to life success: A conceptual model of financial well-being for young adults. Journal of Applied Developmental Psychology, 30(6), 708-723. doi: 10.1016/j.appdev.2009.02.003
Sinha, G., Tan, K., & Zhan, M. (2018). Patterns of financial attributes and behaviors of emerging adults in the United States. Children and Youth Services Review, 93(October), 178-185. doi: 10.1016/j.childyouth.2018.07.023
Tein, J. -Y., Coxe, S., & Cham, H. (2013). Statistical power to detect the correct number of classes in latent profile analysis. Structural Equation Modeling, 20(4), 640–657. doi:10.1080/10705511.2013.824781
Xiao, J. J. (2008). Applying behavior theories to financial behaviour. In Xiao, J. J. (Ed.). Handbook of consumer finance research (pp. 69-81). New York: Springer.
Xiao, J. J. (2016). Consumer financial capability and wellbeing. In Xiao, J. J. (Ed.). Handbook of consumer finance research (pp. 3-17). Cham, Switzerland: Springer International Publishing AG.