Financial Literacy and Credit Card Behaviors - USF Scholar Commons

Numeracy Advancing Education in Quantitative Literacy Volume 6 | Issue 2 2013

Financial Literacy and Credit Card Behaviors: A Cross-Sectional Analysis by Age Sam Allgood University of Nebraska, Lincoln, [email protected]

William Walstad University of Nebraska, Lincoln, [email protected]

Follow this and additional works at: http://scholarcommons.usf.edu/numeracy Part of the Social and Behavioral Sciences Commons Recommended Citation Allgood, Sam and Walstad, William (2013) "Financial Literacy and Credit Card Behaviors: A Cross-Sectional Analysis by Age," Numeracy: Vol. 6 : Iss. 2 , Article 3. DOI: http://dx.doi.org/10.5038/1936-4660.6.2.3 Available at: http://scholarcommons.usf.edu/numeracy/vol6/iss2/art3

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Article 3

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

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. Keywords

financial literacy, credit cards, financial behavior, consumers Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License Cover Page Footnote

Sam Allgood is the Edwin J. Faulkner Professor of Economics in the Department of Economics at the University of Nebraska-Lincoln, Associate Editor of the Journal of Economic Education, and the Chair of the Committee on Economic Education for the American Economic Association. William B. Walstad is the John T. and Mable M. Hay Professor of Economics in the Department of Economics at the University of Nebraska-Lincoln, Editor of the Journal of Economic Education, and former Chair of the Committee on Economic Education of the American Economic Association.

This theme collection: financial literacy is available in Numeracy: http://scholarcommons.usf.edu/numeracy/vol6/iss2/art3

Allgood and Walstad: Financial Literacy and Credit Card Behaviors

Introduction Over the past thirty years interest in financial literacy has grown significantly. One reason for this heightened interest is substantial changes in the workplace that have placed more responsibility on workers for financial decisions over such matters as retirement savings and investments. The growing complexity of the economy over the past few decades also has required households to make more integrated personal financial decisions regarding shorter-term financial objectives, such as managing household budgets, using credit cards for purchases, and paying annual Federal and state taxes, and regarding longer-term financial goals, such as saving for a child’s college education and planning for retirement. Questions have arisen about whether the American public is sufficiently knowledgeable and prepared to handle the difficult and complex financial choices they face on a regular basis and over a lifetime. This interest in financial literacy has spawned extensive research on how financial literacy influences decision making and improves the financial capability of adults (e.g., Braunstein and Welch 2002; Hilgert et al. 2003; Lusardi and Mitchell 2007; Gale and Levine 2011; Hastings et al. 2012). For this study we incorporated an alternative measure of financial literacy to what is typically used in studies of financial literacy. We added a subjective dimension that captures what individuals believe they know about financial matters to the usual objective multiple-choice and true-false test questions used for assessing financial literacy. We found in a previous study of financial behaviors (Allgood and Walstad 2012) that the combination of actual financial literacy, as measured by correct responses to cognitive test questions, and perceived financial literacy, as measured by respondents’ self-assessment, provides more robust and nuanced insights about how financial literacy affects financial behavior. For example, individuals with a low level of actual financial literacy but a high level of perceived financial literacy were significantly less likely to adopt costly or potentially problematic financial behaviors. Our continuing thesis for this study is that this subjective assessment of financial literacy should be combined with an objective assessment of financial literacy because the composite measure provides more insights and shows a greater effect of financial literacy on financial behavior than does the use of objective assessments alone. Another important dimension of this study is the cross-sectional analysis by age based on the recognition that financial decisions and behaviors are likely to change over the life cycle (Agarwal et al. 2009). The data contain survey responses from adults ages 18 to 65 (and older) on their demographic characteristics, financial literacy, and financial behaviors. Instead of analyzing the

Published by Scholar Commons, 2013

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Numeracy, Vol. 6 [2013], Iss. 2, Art. 3

full data set using all ages as we did in our prior study and as is done in many studies with national samples of adults, we split the full sample into five agebased samples that roughly approximate the five major adult decades of the life cycle: 18–29; 30–39; 40–49; 50–59; and 60–69 (and older). This cross-sectional analysis is an effective way to test how perceived financial literacy affects each age group and is valuable for investigating how actual and perceived financial literacy interact. To demonstrate the value of this cross-sectional analysis by age, we focused on consumer behavior related to credit cards, which are frequently used by consumers and can be costly if consumers incur fees and regularly pay interest charges (Stango and Zinman 2009). The five behaviors that we studied related to credit card use were whether a consumer: (1) always pays a credit card bill in full; (2) carries over a credit card balance and is charged interest; (3) makes only a minimum payment on a credit card balance; (4) is assessed a late fee for a late credit card payment; and (5) is charged an over-the-limit fee for exceeding a credit card limit. The results from the analysis supply a decade-by-decade picture that offers subtle insights about what adults know about financial literacy, how they perceive financial literacy, and other factors that affect financial literacy at different ages.

Background: Data and Literature The survey data used for this study came from the 2009 National Financial Capability Study (NFCS), which was commissioned by the Financial Industry Regulatory Authority (FINRA) Investor Education Foundation and conducted in consultation with the US Treasury Department and the US President’s Advisory Council on Financial Literacy. The goal of the study was to “assess and establish a baseline measure of the financial capability of US adults” through the administration of an online questionnaire about their financial behaviors and practices. The national sample is based on interviews that were conducted from June through October 2009 with 500 to 550 adults, 18 years of age and older, in each state and the District of Columbia. We combined state and DC data using NFCS-supplied weights that accounted for sampling unit differences based on age, gender, race and ethnicity, education levels, state, and region. This aggregation produced a representative national sample of 28,146 adults. 1 The extensive NFCS questionnaire asked about many different financial topics, such as credit cards, checking and banking, saving and investing, 1

The FINRA Foundation website provides a copy of the questionnaire, a report on survey methods and basic survey findings, and an SPSS data file for the sample. The data were collected from May to July 2009. See: www.finrafoundation.org/programs/capability/index.htm and www.usfinancialcapability.org.

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homeownership and mortgages, insurance and risk taking, retirement accounts and pensions, and auto and consumer loans. We limited our investigation to the effect of financial literacy on credit card behavior. We selected this topic because there is widespread consumer use of credit cards and their use provides key insights into financial behavior as consumers make frequent or regular purchases of goods and services (Gerdes 2008; Stango and Zinman 2009). Credit cards also are widely used across all age segments of the adult population, but likely for different purposes depending on age, thus making this financial topic a worthy one for a cross-sectional analysis by age grouping with the NFCS data. The other NFCS survey topics covered financial decisions that focused more on a product for specific conditions (types of insurance), involved large and discrete purchases (home mortgages or auto loans), or had unique financial characteristics often related to income (banking and investments). These topics were considered to be less suitable for our cross-sectional analysis by age because, unlike credit card use, which has fairly standard measures, the other financial products or services vary considerably and their use may be concentrated at particular ages (e.g., applying for and obtaining a mortgage for a home purchase). A challenge of conducting research on financial literacy is how to define financial literacy because there is no standard definition in the literature (Remund 2010). This lack of consensus on the concept makes it difficult to construct measures of financial literacy that are broadly accepted and widely used. As a result, there have been significant differences in the methods used to assess financial literacy in research and evaluation studies. Most of the measurement of financial literacy to date has focused on the objective aspects of the concept and what people know or understand about financial matters because “to be financially literate, individuals must demonstrate literacy and skills needed to make choices within a financial marketplace” (Huston 2010, 309–10). This measurement is most often conducted using a set of multiple-choice and/or truefalse test questions that are part of a larger survey instrument that asks about general or specific financial matters and behaviors (e.g., Hung et al. 2009). The NFCS survey included five knowledge questions testing understanding of five financial concepts—compound interest, inflation effects on money, the relationship between bond prices and interest rates, interest payment differences on shorter- and longer-term mortgages, and stock diversification and risk. Three questions are multiple-choice and two are true-false, with the correct answers noted by an asterisk. Question 1: Suppose you had $100 in a savings account and the interest rate was 2% per year. After 5 years how much do you think you would have in the account if you left the money to grow: (a) more than $102*; (b) Exactly $102; (c) less than $102.


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Question 2: Imagine that the interest rate on your savings account was 1% per year and inflation was 2% per year. After 1 year, how much would you be able to buy with the money in the account? (a) more than today; (b) exactly the same; (c) less than today*. Question 3: If interest rates rise, what will typically happen to bond prices? (a) they will rise; (b) they will fall*; (c) they will remain the same; (d) there is no relationship between bond prices and the interest rate. Question 4: A 15-year mortgage typically requires higher monthly payments than a 30-year mortgage, but the total interest paid over the life of the loan will be less. (a) true*; (b) false. Question 5: Buying a single company’s stock usually provides a safer return than a stock mutual fund. (a) true; (b) false*. These questions have been placed in several national surveys, with results used as measures of financial literacy either via a question-by-question analysis or combined as an aggregate test score based on the percentage correct across items. Questions 1, 2, and 5 were used in the 2004 Health and Retirement Survey and in Wave 11 of the 2007–2008 National Longitudinal Survey of Youth (e.g., Lusardi and Mitchell 2008; Lusardi et al. 2010). Questions 1, 2, 4, and 5 have been used in the RAND American Life Panel (e.g., Lusardi and Mitchell 2009). A version of question 5 was used in a Survey of Consumers conducted by the University of Michigan in 2001 (Hilgert et al. 2003). Although the NFCS test questions focus on basic financial concepts in a simple format, they have been found to be challenging for adults and have served as valuable indictors of financial literacy in the above cited studies and several others (e.g., Lusardi 2011; Hastings et al. 2012). A unique feature of the NFCS survey is the inclusion of two types of questions to assess respondents’ level of financial literacy. In addition to the five objective test questions there is a subjective question asking respondents for a self-assessment of financial literacy: “On a scale from 1 to 7, where 1 means very low and 7 means very high, how would you assess your overall financial literacy?” Perceived financial literacy is recognized as an important dimension in a conceptual model of financial literacy (Hung et al. 2009), but empirical studies of this dimension are few and largely focus on cross-tabulations of self-ratings of financial (or economic) literacy with percentage correct scores on items testing financial literacy (Lusardi and Mitchell 2009; Lusardi and Tufano 2009; Lusardi 2010; Van Rooij et al. 2011). Further study of perceived financial literacy, in particular its interaction with objective assessments, would be beneficial because it can expand our understanding of how a more comprehensive measure affects financial behavior. It is likely to be the case that people’s perceptions of their

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overall financial literacy serve as influential and valid indicators of their financial behavior, even when controlling for their knowledge on specific financial topics.

Variables: Age, Literacy, and Others Table 1 reports the proportions, or means, for all the variables used in the study by age group and the sample size for each group.2 The data on age were collected using ten age groups: 18–24, 25–29, 30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64, and 65 and older. To simplify the analysis, we combined two adjacent age groups so that the total number of categories was reduced to five: 18–29, 30–39, 40–49, 50–59, and 60–69 and older. These categories either exactly represent or approximate the five main decades of the adult life cycle, from the 20s through the 60s. The sample size of the categories ranged from a low of 3,457 for 18- to 29-year-olds to a high of 4,958 for adults 60 years of age and older. Age was transformed into a continuous variable for the five categories by setting age at the midpoint of the two age ranges within a category (e.g., 18–24 and 25–29 for the 18–29 range) and calculating a weighted average. The oldest category (60–69 and up) was constructed by combining the 60- to 64-year-olds with those 65 years of age and older. Although the midpoint of the age range was used as the mean for the 60–64 group, the mean age for the 65 and older group was set at 70 for calculating the 60–69 and older mean age. The result of this transformation shows that the mean age is about at the middle of each age “decade” with the exception of the 20s, for which it is slightly lower at 23.27 years. The standard deviation is given in parenthesis below the mean for each age category. For the full sample the mean age was 45.24 years old. Table 1 Variable Means by Age Group Variables Age 18–24 Age 25–29 Age 30–34 Age 35–39 Age 40–44 Age 45–49 Age 50–54 Age 55–59 Age 60–64 Age 65+ Age

(1) 18–29 0.622 0.378

(2) 30–39

(3) 40–49

(4) 50–59

0.506 0.494 0.514 0.486 0.528 0.472

23.27 (2.91)

35.97 (3.00)

44.94 (2.00)

54.89 (2.00)

(5) 60–69+

(6) 18–69+ 0.135 0.082 0.087 0.087 0.096 0.091 0.105 0.094 0.313 0.069 0.687 0.152 65.75 45.24 (1.85) (15.41) (continued on next page)

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Appendix A provides a detailed explanation of how each variable in Table 1 was obtained or constructed from the FINRA Financial Capability data set.


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Q1 (interest) Q2 (inflation) Q3 (bonds) Q4 (mortgage) Q5 (stocks) Actual literacy

0.739 0.784 0.781 0.791 0.794 0.777 0.456 0.589 0.682 0.739 0.760 0.645 0.214 0.264 0.294 0.308 0.304 0.276 0.666 0.752 0.784 0.797 0.787 0.756 0.414 0.523 0.545 0.567 0.621 0.534 2.489 2.912 3.086 3.201 3.267 2.989 (1.41) (1.44) (1.43) (1.40) (1.40) (1.44) Perceived literacy 4.701 4.863 4.869 5.037 5.240 4.947 (1.33) (1.33) (1.34) (1.28) (1.19) (1.31) Perceived-Hi 0.267 0.309 0.314 0.367 0.439 0.341 Perceived-Lo 0.733 0.691 0.686 0.633 0.561 0.659 Actual-Hi 0.270 0.394 0.450 0.483 0.514 0.422 Actual-Lo 0.730 0.606 0.550 0.517 0.486 0.578 Perc-Hi+Actual-Hi 0.092 0.149 0.177 0.215 0.268 0.182 Perc-Hi+Actual-Lo 0.175 0.160 0.136 0.153 0.171 0.160 Perc-Lo+Actual-Hi 0.184 0.252 0.283 0.275 0.256 0.249 Perc-Lo+Actual-Lo 0.549 0.439 0.404 0.358 0.305 0.410 Paidfull 0.441 0.338 0.356 0.368 0.542 0.418 Carrybalance 0.546 0.649 0.635 0.619 0.468 0.575 Minpayment 0.499 0.514 0.457 0.391 0.228 0.402 Latefee 0.324 0.353 0.293 0.256 0.146 0.264 Exceedcredit 0.223 0.217 0.167 0.144 0.074 0.157 Male 0.506 0.505 0.498 0.482 0.449 0.487 White 0.496 0.597 0.697 0.756 0.867 0.685 Nonwhite 0.504 0.403 0.303 0.244 0.133 0.315 mean; (b) Actual-Lo = test score < mean. 16. Financial literacy groups: (a) Perc-Hi+Actual-Hi = self-rating > mean and test score > mean; (b) PercHi+Actual-Lo = self-rating > mean and test score < mean; (c) Perc-Lo+Actual-Hi = self-rating < mean and test score > mean; (d) Perc-Lo+Actual-Lo: = self-rating < mean and test score < mean. C. Credit Card (CC) Behaviors 17. Paidfull = I always paid my credit cards in full. Yes. [F2_1] 18. Carrybalance = In some months, I carried over a balance and was charged interest. Yes. [F2_2] 19. Minpayment = In some months, I paid the minimum payment only. Yes. [F2_3] 20. Latefee = In some months, I was charged a late fee for a late payment. Yes. [F2_4] 21. Exceedcredit = In some months, I was charged an over the limit fee for exceeding my credit line. Yes. [F2_5] Note: Variables are based on the National Financial Capability Study (NFCS) data set. The bracket item at the end of a variable or set of variables is the NFCS item survey code. All variables constructed from this data set for this study are (0,1) dummy variables except five (Age, Children, Income, Actual literacy, and Perceived literacy).

Appendix B: Probit Results (all variables) (continued on next page)


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Table B1 Always Paid Credit Card Bill in Full by Age Variables Perc-Hi+Actual-Hi (1) Perc-Hi+Actual-Lo (2) Perc-Lo+Actual-Hi (3) Male White