Financial Literacy and Credit Card Behaviors: A Cross-Sectional Analysis by Age

By Sam Allgood, W. Walstad. 2013

138 citations recorded by the source corpus.

In this study, we use a measure of financial literacy that includes both a test score of actual financial literacy and a self-rating of perceived financial literacy to investigate how financial literacy affects five credit card behaviors: (1) always paying a credit card balance in full; (2) carrying over a credit card balance and being charged interest; (3) making only a minimum payment on a credit card balance; (4) being charged a fee for a late payment; and (5) being charged a fee for exceeding a credit limit. Probit analysis was used to assess each behavior with a large nationally representative sample of U.S. adults (N = 28,146) divided into groups to reflect the five major decades in the adult life cycle (18–29; 30–39; 40–49; 50–59; and 60–69 and older). Perceived financial literacy was found to be a stronger predictor of less costly practices in credit card use than actual financial literacy for the five credit card behaviors and across each of the five age groups. The study also shows that the combination of the subjective assessment with the objective assessment of financial literacy provides a more comprehensive analysis of how financial literacy affects each credit card behavior. This combined approach to assessment produced the largest estimates of the effects of financial literacy on credit card behavior. The findings hold across the five credit card behaviors and the five age groups.

Subfields: Accounting, Demography, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/d6e594584fb73e10430dabef2d653ccc7775f9ae

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In Accounting

1. Jing Jian Xiao
2. Satish Kumar
3. Kirtika Goyal
4. Cheng Chen
5. Jingfei Xiao
6. Lei Sun
7. Oscar Stolper
8. A. Walter

In Demography

1. Jing Jian Xiao
2. Oscar Stolper
3. A. Walter
4. Jingfei Xiao
5. Satish Kumar
6. Lei Sun
7. Kirtika Goyal
8. Cheng Chen

In Economics and Econometrics

1. Jing Jian Xiao
2. Cheng Chen
3. Satish Kumar
4. Kirtika Goyal
5. Jingfei Xiao
6. Lei Sun
7. Oscar Stolper
8. A. Walter

Citations in the corpus

• Antecedents and consequences of Personal Financial Management Behavior: a systematic literature review and future research agenda (2021, background): “There are significant other factors that connect to individual financial behavior such as demographics (Allgood and Walstad, 2013), socio-economic factors (Gorniak, 1999; Grable et al., 2009), social factors (shim et al., 2009), FL (Lusardi and Mitchell, 2007) and technological factors (Panos and…”
• Financial literacy among youth (2018, background): “…has evidenced lower level of financial literacy particularly among youth (van Rooij et al., 2009; Lusardi et al., 2010; Lusardi and Mitchell, 2011; Allgood and Walstad, 2013; Agarwalla et al., 2013) which raises serious issue about the individual’s capability to secure his financial well-being.”
• Financial literacy and financial behavior (2015, unknown): “The use of these demographic controls is established in the literature (e.g., see Allgood and Walstad, 2013 or Lusardi and Mitchell, 2011).”
• The Economic Importance of Financial Literacy: Theory and Evidence (2014, unknown): “Moreover, both self-assessed and actual literacy is found to have an effect on credit card behavior over the life cycle (Allgood and Walstad, 2013).”
• Financial literacy, financial advice, and financial behavior (2017, background): “Other recent studies document that individuals with low levels of financial literacy are significantly less likely to use their credit cards efficiently (e.g., Lusardi and Tufano 2015; Mottola 2013; Allgood and Walstad 2013).”
• Age differences in consumer financial capability (2015, methodology): “Both objective and subjective financial literacy factors were used to predict financial behavior (Robb and Woodyard, 2011; Xiao et al., 2011; Allgood and Walstad, 2013).”