Journal of Family and Economic Issues

, Volume 34, Issue 4, pp 369–381

College Students and Credit Card Use: The Role of Parents, Work Experience, Financial Knowledge, and Credit Card Attitudes

Authors

    • Creative Solutions Innovative Strategies, LLC.
  • Bryce L. Jorgensen
    • Department of Child and Family RelationsEast Carolina University
  • Melvin S. Swanson
    • College of NursingEast Carolina University
Original Paper

DOI: 10.1007/s10834-012-9338-8

Cite this article as:
Hancock, A.M., Jorgensen, B.L. & Swanson, M.S. J Fam Econ Iss (2013) 34: 369. doi:10.1007/s10834-012-9338-8

Abstract

This study examined the influence of parental interactions, years of work experience, financial knowledge, credit card attitudes, and personal characteristics on college students’ credit card behaviors (i.e., number of cards and amount of debt). Based on data collected across seven universities (N = 413), we found that students who had parents who argued about finances, were juniors/seniors, and were comfortable making minimum payments were the most likely to have $500 or more in credit card debt and two or more credit cards. In addition, number of credit cards held was the only dependent variable influenced by gender and fear of credit cards. These results highlight the importance of early interventions in the life of college students including involving parents as positive role models.

Keywords

Credit card debtParent–child interactionsWork experienceCollege studentsFinancial attitudes

Introduction

Credit card debt among college students has been a growing concern for researchers and policymakers over the last decade. A credit card debt over $1,000 is considered risky for college students and has been associated with unhealthy behaviors such as abusing drugs and alcohol (Adams and Moore 2007; Berg et al. 2010; Lyons 2004), high stress levels, low financial well-being (Grable and Joo 2006; Nelson et al. 2008; Norvilitis et al. 2006), declined mental and physical health (Berg et al. 2010), and lower academic performance (Pinto et al. 2001). Although having a credit card is one of the few ways available to college students to build a credit history without acquiring debt, having more credit cards (even without accumulating debt) builds a stronger credit history than having fewer credit cards. The majority of college students who obtain credit cards find themselves in debt because they applied for the cards to use them rather than to build credit score (Lyons 2004). Lyons (2004) found the more cards a student had, the greater the risk of accumulating more debt in the future when financial problems arise. In fact, because of financial concerns, 60 % of baccalaureate students are not finishing their education within 6 years, and over half of the students who begin college are not completing their degrees (Horn 2006; Roberts et al. 1999). There is a growing concern among educators that more students are dropping out of school not because of academic failure, but because of financial reasons, especially credit card debt (Gallo 2006; Roberts et al. 1999). This trend is alarming because 84 % of students have a minimum of one credit card, and half of the students hold four or more cards with an average total credit card debt of $3,170 (Sallie Mae 2009). Even more alarming is a pattern which shows that more cards bring more debt, and more debt brings more cards (Norvilitis and MacLean 2010).

Because of the potential negative influence credit cards have on students, it is important to identify which factors contribute to the number of credit cards and the amount of credit card debt students have. Although previous researchers have examined multiple influences on college students’ credit card behaviors, there have been mixed findings. Using family resource management and social learning theories, the current study is among the first to explore how credit card debt and number of credit cards held are influenced by parental interactions, work experience, financial knowledge, students’ credit card attitudes, and personal characteristics.

Theoretical Framework

This research uses family resource management theory and social learning theory as frameworks to address the influence of parental interaction, work experience, financial knowledge, and credit card attitudes on the credit card behaviors (i.e., number of credit cards held and amount of credit card debt) of college students. The authors of family resource management theory (Deacon and Firebaugh 1981) state that behavioral outcomes stem from demands or goals placed on the use of available resources in a given family management system. The theory consists of key elements: inputs, throughputs (information processes), and outputs (outcomes). For the present study, parental interactions, work experience, and personal characteristics were the inputs; financial knowledge and financial attitudes were the throughputs; and credit card debt and number of cards were the outputs (see Fig. 1).
https://static-content.springer.com/image/art%3A10.1007%2Fs10834-012-9338-8/MediaObjects/10834_2012_9338_Fig1_HTML.gif
Fig. 1

Model of study. From “Financial literacy of young adults: The importance of parental socialization,” by Jorgensen and Savla (2010). Adapted with permission

Similar to Jorgensen and Savla’s (2010) conceptual model, we also incorporated Bandura’s social learning theory (Bandura 1977), which states that the interactions within a given environment (i.e., parents, work experience) determine children’s knowledge and attitudes about money. The negative or positive financial attitudes and knowledge young adults have about finances are influenced by parents and work environment, and determine how resources are used. Using these two theories together allows for a better conceptualization of the mechanism by which key socialization processes lead to behavioral outcomes. (Gudmunson and Danes 2011; Hayhoe et al. 2005; Jorgensen and Savla 2010).

Literature Review

Parental Interactions

Parents are the most influential socialization agent regarding credit card knowledge for students (Norvilitis and MacLean 2010; Palmer et al. 2001; Shim et al. 2010). However, many parents may not realize the influence they have on their children’s financial decisions and outcomes (Schuchardt et al. 2009), which last throughout the life course (Gudmunson and Danes 2011). In one recent study, parental influence was determined to have a larger role on their children’s financial behaviors (i.e., credit card use and attitudes) than work experience and previous education combined (Shim et al. 2010). Gudmunson and Beutler (2012) found that young adults who felt that their parents cared for them were less likely to display materialistic behaviors. Furthermore, risky financial behaviors of young adults is significantly increased when parents’ socioeconomic status is low (Xiao et al. 2011). Similarly, Lyons (2004) revealed that college students with higher credit card debt lacked financial help from their parents, while Draut and Silva (2004) established that parents with a household income under $50,000 per year were more likely to have children who made poorer financial decisions. This finding is alarming because parents are the main contributors to their children’s financial attitudes and behaviors (Jorgensen and Savla 2010; Shim et al. 2009). Yet a referral from a parent is the second most common reason that students get credit cards (Nellie Mae 2005). Parents may help students initiate getting credit cards; however, students with four or more credit cards not only had more credit card debt than students with fewer than four cards, but they also had fewer interactions with their parents (Hayhoe et al. 2005).

Types of Parental Interactions

A primary concern of researchers is how and in what ways parents address financial issues with their children (Kim et al. 2011). Parents can help their children learn financial issues through explicitly teaching them by having direct hands-on teaching and discussions (Allen et al. 2007; Norvilitis and MacLean 2010). Explicit teaching is usually associated with positive outcomes, but explicit teaching can result in negative outcomes. For example, in research on students who had a credit card, Norvilitis and MacLean discovered that parental lectures were related to higher levels of student debt, which may be a result of having low levels of parental warmth during such discussions (Kim et al. 2011). Conversely, a parental hands-on approach (e.g., explicit teaching by co-shopping with child) was associated with lower debt (Allen et al. 2007). On the other hand, some researchers noticed that parents taking their children shopping increased materialistic craving (Gudmunson and Danes 2011). Moreover, many have expressed concern that when parents explicitly educate their children, correct information is not communicated to them (Braunsberger et al. 2005).

Parents also implicitly teach their children (Jorgensen and Savla 2010). Researchers have learned the lack of verbal communication about financial matters between parents and their children was associated with increased debt over time (Norvilitis and MacLean 2010). In addition, research has shown that an important reason why financial literacy remains low among college students is that parents are not educating their children about the good and bad use of credit cards (Braunsberger et al. 2005; Gallo 2006).

A third way children learn about finances is by observing their parents’ discussions about finances. Children often see parents arguing about finances (Allen et al. 2007; Shim et al. 2009). Unfortunately, struggling marital and family relationships have negative outcomes financially and impact children to have more materialistic attitudes and unhealthy financial behaviors (Gudmunson and Danes 2011). In one recent study, students whose parents jointly formed financial plans with them for paying off credit card debt (i.e., explicit teaching by having an open discussion about finances) had fewer financial problems (i.e., credit card debt) than students whose parents argued about finances (Allen et al. 2007). Our study is among the first to examine how these three different types of parental interactions influence the amount of credit card debt and number of credit cards college students hold.

Work Experience

Students have reported that a majority of their knowledge, attitudes, and behaviors about finances comes from their parents (Jorgensen and Savla 2010; Shim et al. 2009). Students have also suggested that work experience has influenced their financial literacy (Borden et al. 2008). In the United States, more than 65 % of college students work 10 or more hours (Nellie Mae 2005). Students who work while attending school may experience positive as well as negative outcomes. For example, students who worked more hours per week had better financial knowledge than students who did not work (Chen and Volpe 1998). Conversely, students who worked 10 or more hours a week during the school year had more risky card use and the highest credit card balances (Dale and Bevill 2007; Lyons 2004; Nellie Mae 2005; Norvilitis and MacLean 2010). Chen and Volpe (1998) noticed that college students with more extensive work experience carried higher levels of debt. This increased debt may be from college students who worked while in school and who have less parental financial support (Borden et al. 2008); thus, getting a job while attending school may be a student’s only option. Alternatively, higher debt could be from students’ hope they will be able to pay off debts with their higher earnings once they graduate (Norvilitis et al. 2006). Work experience may play a negative role in educational outcomes, and credit card behaviors as well. The present study is one of the first to examine how years of work experience impacts credit card debt and the number of credit cards held among college students, when measured with the other variables in the study. While working and attending school simultaneously has extended the time needed to graduate, lack of proper credit card management knowledge has not only been shown to contribute to the increase in the length of time needed to graduate, but it has also contributed to dropout rates (Horn 2006; Orozco and Cauthen 2009).

Financial Knowledge

Despite efforts to educate college students about finances, financial knowledge scores remain low across America (Robb 2011), with the average scores falling between 53 and 60 % (Chen and Volpe 1998; Jorgensen and Savla 2010; Norvilitis et al. 2006). According to Norvilitis et al. (2006), a lack of financial knowledge was the strongest predictor of having credit card debt. Furthermore, three research teams (Robb 2011; Shim et al. 2009, 2010) noticed that higher financial knowledge translated to positive behavioral outcomes (e.g., less risky use of credit cards). Although there is some evidence supporting that higher financial knowledge scores have also been associated with avoiding future financial problems (Avard et al. 2005; Braunsberger et al. 2005; Norvilitis et al. 2006; Shim et al. 2010), some researchers have discovered conflicting results. Some researchers have reported greater financial knowledge was associated with more credit card debt (Borden et al. 2008; Norvilitis and MacLean 2010; Robb and Sharpe 2009). Borden et al. (2008) asserted that increasing knowledge of credit cards potentially lowers the fear about using credit cards, and thus, college students would increase their use of credit cards. Some researchers expressed concern that students may prematurely conclude that they have adequate financial knowledge to make good financial decisions because they have used credit cards for an extended period of time (Braunsberger et al. 2005). Despite these conflicting results, many agree that knowledge alone is not enough for effective money management and is not an efficient strategy to lower credit card debt among college students (Borden et al. 2008; Gudmunson and Danes 2011; Norvilitis et al. 2006; Norvilitis and MacLean 2010; Robb 2011; Shim et al. 2009). Building on previous research, Jorgensen and Savla (2010) noticed that the influence of financial knowledge on financial behaviors is mediated by financial attitudes.

Credit Card Attitudes

Although there are conflicting findings on the influence of financial knowledge on financial behaviors, 84 % of undergraduates have positive attitudes about gaining more financial knowledge (Sallie Mae 2009). A positive attitude regarding increased financial knowledge is important because knowledge impacts attitudes and the use of credit cards (Jorgensen and Savla 2010; Shim et al. 2009, 2010). Others noted that a positive attitude toward credit cards leads to an increased number of credit cards and greater use of credit cards; in contrast, a negative or fearful attitude toward credit cards leads to fewer cards and less credit card use (Joo et al. 2003). Risky behaviors will likely be compounded if a positive attitude toward credit card use is based on faulty information (Braunsberger et al. 2005); conversely, healthy attitudes and behaviors will be found to increase as accurate knowledge about credit cards increases (Borden et al. 2008; Jorgensen and Savla 2010; Kidwell et al. 2003; Shim et al. 2009, 2010). In addition, parents heavily influence the formation of credit card attitudes and their usage (Jorgensen and Savla 2010; Gudmunson and Danes 2011; Shim et al. 2009, 2010). Recently, researchers have discerned that a healthy financial well-being exists among students when there is both a positive financial attitude and healthy financial behavior (Gutter and Copur 2011). The current study examined how financial attitudes relate with how many credit cards a student has and the amount of credit card debt he or she has accumulated when measured against the other variables in the study.

Personal Characteristics

A relationship exists between personal characteristics of students and the number of credit cards they hold and personal characteristics and credit card debt. Researchers have included parental income, class rank, and gender because each are significant predictors of financial outcomes (Draut and Silva 2004; Joo and Grable 2004; Shim et al. 2009). Researchers have found that females are more likely to have more credit cards and more debt (Lyons 2004; Robb 2011), while males tend to have more financial knowledge (Borden et al. 2008; Chen and Volpe 1998; Shim et al. 2009). Other researchers have witnessed that class rank plays a significant role as to why students have more risk, more debt, and more credit cards (Hayhoe et al. 2005, 1999; Shim et al. 2009). For these reasons, we include parental income, class rank, and gender in our analysis.

Aims and Purpose

The purpose of this study was to examine the relationships between undergraduate students’ types of interactions with their parents (e.g., explicit, implicit, and arguing), years of work experience, financial knowledge, credit card attitudes, and personal characteristics with the number of credit cards held by the students and the amount of credit card debt held by the students. Because parents play a role in the socialization process of their children, we anticipated that parental interactions would have a more powerful effect than the other independent variables when controlling for all other variables in the model. As a result, we had two hypotheses:
Hypothesis 1

Parental interactions about finances will have a greater influence on the students’ number of credit cards than work experience, financial knowledge, credit card attitudes, or personal characteristics

Hypothesis 2

Parental interactions about finances will have a greater influence on the amount of students’ credit card debt than work experience, financial knowledge, credit card attitudes, or personal characteristics

Method

Research Design

Participants in this cross sectional study were undergraduate students from seven different universities. The current study used data from the Jorgensen and Savla (2010) study which were collected as part of a research project in 2006. The original study created the college student financial literacy survey (CSFLS), which measures the financial knowledge, attitudes, behavior, influences (i.e., parental interactions, work experience), and personal demographics that may affect the financial literacy of college students.

The convenience sample came from six states (Tennessee, Nevada, Oklahoma, South Dakota, Idaho, and Virginia) and seven different undergraduate universities (including private, public, land-grant, research, and liberal arts) with the criteria for inclusion being current status as an undergraduate college student between 18 and 29 years of age. Following the procedures of Pedhazur and Schmelkin (1991), a snowball technique was used to obtain participation from other universities. Professors invited college students in their courses to fill out the online survey. One thousand eighty-four students were invited to complete the surveys; 462 students responded for an overall response rate of 43 %, with 413 students meeting the qualifying parameters for this study. They represented multiple majors: Business 14 %, Agriculture and Life Sciences 16 %, Sciences 11 %, Liberal Arts 10 %, Human Sciences 7 %, Medicine 6 %, Engineering 5 %, Education 3 %, Law 1 %, and 21 % other. The majority of the participants were Caucasian (87 %) with 13 % being Asian, African American, Hispanic, Multiracial, or other.

Measures

The CSFLS contains 44 content questions and 18 personal characteristic items, which took 10–20 min to complete. Following the suggested review process of Crocker and Algina (1986) to increase face and content validity of the CSFLS, the survey was first reviewed by a panel of four experts and edited accordingly. This process was then followed by a review of six diverse undergraduate students who took the online version of the survey, which led to additional revisions before it was used in the study (see Jorgensen and Savla 2010).

Dependent Variables

Credit Card Debt and Number of Credit Cards

Students’ credit card debt was assessed using one multiple-choice question, “What is the combined total balance owed on your credit cards?” Options were $0–99, $100–499, $500–1999, $2000–4999, $5000 or more. In contrast, the number of credit cards was assessed with an open-ended question, “How many credit cards do you have?”

Independent Variables

Parental Interactions

The students’ parental interactions were assessed with one multiple choice answer question as found in the CSFLS (see Jorgensen and Savla 2010), “How would you describe how finances were communicated in your family?” Respondents were asked to “check all that apply” from five options: “1. My parents usually argued about finances; 2. Within the family we openly discussed our finances; 3. My parents explicitly taught me about finances (e.g., credit cards, debt, budgeting, savings); 4. We didn’t talk much about finances, but I learned from their examples; 5. My parents included me in various financial decisions.” For the current study, students were included in the explicitly taught group if they selected options 2, 3, or 5 individually or simultaneously. Students who selected parental interactions number 1 (parents who argued) or 4 (implicit learning) were only included in the analysis if the interaction was the only interaction selected.

Work Experience

Students who had work experience were assessed using the same question developed by Chen and Volpe (1998) as one multiple-choice question, “How many years of work experience do you have? (Include full or part-time experience, internships, co-ops, summer jobs, etc.).” The participants were given five possible responses: “None; Less than 2 years; Two to less than 4 years; Four to less than 6 years; 6 years or more.”

Financial Knowledge

The College Student Financial Knowledge Scale was created for the original study in 2007 and contained 27 questions that assessed financial knowledge of credit cards, loans, insurance, and a variety of other general personal finance issues. Most of the questions were obtained from existing validated surveys, and additional questions were added by Jorgensen based on literature and per suggestions of an expert panel (see Jorgensen and Savla 2010). The internal consistency for the financial knowledge scale (N = 462) was estimated to be 0.75 (Cronbach’s α).

Credit Card Attitudes

Credit card attitudes of the students were assessed with four individual attitude items. We decided to use and treat each attitude statement as an individual item rather than combine them for a scale, because the measure had a weak Cronbach’s α of 0.56. Each attitude item was scored on a 5-point Likert-type scale ranging from 1 (not at all true of me) to 5 (very true of me). The four items were the following: “I feel credit cards are safe and risk free,” “I am afraid of credit and credit cards,” “I feel the cost of using a credit card is too high,” and “I am comfortable with not paying my credit card bills in full each month as long as I make the minimum payment.” This last item did not have a “not applicable” option for those without credit card debt. We therefore interpreted their answer as indicative of how they would answer the question if they did have credit card debt.

Statistical Analyses

Data analysis was conducted using SPSS and included calculating frequencies of variables. Chi square tests were performed along with one-way analysis of variance to find inclusion into the multivariate logistic analysis. For the purpose of this study, only variables that were strongly associated with the outcome (p values ≤ 0.05) were included in the model. Hypotheses were tested in the same order previously addressed, and both regressions were interpreted and presented following the guidelines provided by Pallant (2007, p. 178).

Results

In this sample, 37.8 % (N = 156) of students did not have a credit card and 35 % (N = 144) only had one credit card. The average number of credit cards reported by students was 1.04 (SD = 1.3) with one participant reporting to have 10 credit cards. The sample consisted of 58.4 % women. A majority of the students were either first-years 32.7 % (N = 135) or seniors 32 % (N = 132), followed by sophomores 18.2 % (N = 75) and juniors 17.2 % (N = 71). In estimating their parents’ household income, 13.3 % (N = 55) stated their parents received less than $35,000; 9.7 % (N = 40) received between $35,000 and $49,999; 24.5 % (N = 101) received between $50,000 and $79,999; 39.5 % (N = 163) received more than $80,000; and 13 % (N = 54) did not know their parents’ household income or did not answer.

Although there may be qualitative differences between a student who does not have a card and a student who has one card, we found no statistical differences. Therefore, we divided our participants into two groups: those who reported having one or fewer credit cards and those with two or more credit cards. When asked how much total debt students had on their credit cards, 47.6 % (N = 137) had 0–$99, 23.3 % (N = 67) had between $100 and $499, 17.4 % (N = 50) had between $500 and $1,999, 4.5 % (N = 13) had between $2,000 and $4,999, 2.7 % (N = 11) had over $5,000, and 2.7 % (N = 11) did not know. With the average credit card debt between $100 and $499, participants were divided into two groups: those with under $500 in credit card debt and those with $500 or more in credit card debt.

Participants in the current study had average financial knowledge scores of 60 % with no significant differences between those who had zero or one credit cards. There were significant differences between those who had 0–1 cards and those who had two or more cards, but there were no differences between the amounts of credit card debt held. In addition, because the larger groups of students were primarily first-years or seniors, the students were divided into lower and upper classes (first-year students/sophomores 50.8 % [N = 210] and juniors/seniors 49.2 % [N = 203]). Based on previously established guidelines, parental income was separated into those with $49,999 or less (23 %, N = 95) and those with $50,000 or more 64 % (N = 264; Draut and Silva 2004).

Multivariate Results

Hypothesis 1

Parental interactions about finances will have a greater influence on students’ number of credit cards than work experience, financial knowledge, credit card attitudes, or personal characteristics

To test the first hypothesis, a direct logistic regression was used to analyze what factors impacted whether a student would report ownership of two or more credit cards. Credit card debt was not included in this analysis because it would limit the number of participants included in the analysis (only 278 of the 413 had credit card debt). Nine independent variables met criteria for fit into the model (parents arguing about finances, class rank, years of work experience, attitudes [feel credit cards are safe, afraid of using credit cards, feel credit cards are too costly, comfortable making the minimum credit card payment], financial knowledge, and gender). The full model was statistically significant, χ2 (9, N = 386) = 85.64, p < 0.001, which indicated that the model could discern differences between the students having one or fewer credit cards and those having two or more credit cards. The model was able to explain between 20.0 % (Cox and Snell R square) and 30.0 % (Nagelkerke R square) of the variance in number of credit cards held, and correctly classified 81.1 % of the cases. Five of the independent variables (parents arguing, class rank, afraid of credit cards, comfort with minimum payment, and gender) met statistically significant contributions to the current model (see Table 1).
Table 1

Logistic regression predicting likelihood of having two or more credit cards

 

B

S.E.

Wald

df

p

Odds ratio

95 % CI for

odds ratio

Lower

Upper

Step 1

Parent arguing

0.76

0.34

4.88

1

0.03

2.14

1.09

4.20

Class rank

1.33

0.33

16.37

1

0.00

3.78

1.99

7.21

Yrs work exp

0.21

0.29

0.54

1

0.46

1.24

0.70

2.18

CC safe

0.20

0.14

2.00

1

0.16

1.22

0.93

1.61

CC afraid

−0.29

0.14

3.92

1

0.05

0.75

0.56

1.00

CC High cost

−0.18

0.15

1.55

1

0.21

0.83

0.63

1.11

CC Min pay

0.36

0.12

8.53

1

0.00

1.43

1.13

1.82

Fin Knowledge

0.03

0.04

0.77

1

0.38

1.03

0.96

1.11

Gender

0.88

0.29

8.83

1

0.00

2.41

1.35

4.29

Constant

−3.26

0.97

11.31

1

0.00

0.04

  

CI confidence interval, CC credit card attitude, Min Pay comfortable with minimum payment, Fin Knowledge total financial knowledge

When all other variables in the model were controlled, the strongest predictor for having two or more credit cards was class rank, with an odds ratio of 3.78. This result indicates that juniors and seniors were ~3.8 times more likely to report having two or more credit cards than freshman and sophomores. Females were 2.4 times more likely than males to have two or more credit cards, while students who reported that their parents argued about finances were 2.1 times more likely than those who reported having parents that did not argue. Furthermore, students who had an attitude of being comfortable with making minimum payments were 1.4 times more likely to have two or more credit cards than students who were not comfortable making minimum payments. The lowest odds ratio 0.75 was for having an attitude of being afraid of credit cards, which is <1. This indicates that for every additional unit higher on the attitude scale (being afraid of credit cards), students were 0.75 times less likely to report having two or more credit cards.
Hypothesis 2

Parental interactions about finances will have a greater influence on the amount of students’ credit card debt than work experience, financial knowledge, credit card attitudes, or personal characteristics

For the second hypothesis, another logistical regression measured the likelihood that students would report they had over $500 in credit card debt. Number of credit cards was included in this model because it would not limit the number of students included in the analysis. The model contained five independent variables [parents arguing about finances, class rank, years of work experience, attitude (comfortable with minimum payment), and two or more credit cards]. These variables were statistically significant, χ2 (5, N = 263) = 69.30, p < 0.001, indicating that the model could distinguish between students who reported having $500 or more in credit card debt and those who did not. This model correctly classified the majority (80.6 %) of cases, and explained between 23.2 % (Cox and Snell R square) and 33.9 % (Nagelkerke R square) of the variance in the amount of credit card debt held. Four of the independent variables (parents arguing, class rank, comfort with making minimum payment, and two or more credit cards) met statistically significant contributions to the current model (see Table 2).
Table 2

Logistic regression predicting likelihood of having more than $500 in credit card debt

 

B

S.E.

Wald

df

p

Odds ratio

95 % CI for odds ratio

Lower

Upper

Step 1

Parent arguing

1.04

0.40

6.87

1

0.01

2.82

1.30

6.12

Class rank

0.80

0.37

4.55

1

0.03

2.22

1.07

4.60

Yrs work exp

0.14

0.35

0.17

1

0.68

1.15

0.58

2.28

CC Min pay

0.79

0.14

33.05

1

0.00

2.20

1.68

2.88

2 + Credit cards

1.09

0.34

10.47

1

0.00

2.97

1.54

5.73

Constant

−3.71

0.85

19.29

1

0.00

0.02

  

CI confidence interval, CC credit card attitude, Min Pay comfortable with minimum payment, Yrs Work Exp years work experience

The strongest predictor of having more than $500 in credit card debt was among the students who reported having two or more credit cards, with an odds ratio of 2.97. This indicated that students who had two or more credit cards were approximately three times more likely to report having credit card debt over $500, when all other variables in the model were controlled. The next strongest independent predictor of students having over $500 in credit card debt was parents arguing about finances, with an odds ratio of 2.82. This indicated that students who had parents who argued about finances were over 2.8 times more likely to report having credit card debt over $500. The other variables, class rank and comfort with making minimum payment, had odds ratios of 2.22 and 2.20 respectively.

Discussion

Although others have examined multiple influences on college students and credit cards, the current study is one of the first to examine how parental interactions (Shim et al. 2010), years of work experience (Borden et al. 2008), knowledge (see Norvilitis et al. 2006), and attitudes (Jorgensen and Savla 2010) may together influence the number of credit cards and level of credit card debt of college students. It is clear that the influence of parents cannot be underplayed, especially when parental arguments about finances appears to be associated with a 2.8 times greater chance that students will have more credit card debt and over 2.1 times greater chance of having two or more credit cards. In addition, juniors and seniors were nearly four times more likely to have two or more credit cards and 2.2 times more likely to have $500 or more in credit card debt. Additionally, if students had two or more credit cards, they were three times more likely to have $500 or more of credit card debt than those with no or only one card. This highlights the circular relationship Norvilitis and MacLean (2010) reported, that more credit cards lead to more debt and more debt contributes to more cards. In this study, we were able to locate some of the key variables that influence whether a student will have more than two credit cards and over $500 in credit card debt.

Parental Interactions

Surprisingly, neither explicit nor implicit teaching from parents had any influence on the number of credit cards college students had or the amount of their credit card debt. Previous studies (e.g., Allen et al. 2007) have shown that explicit teaching leads to less debt accumulation. On the other hand, as we expected, parental influence (i.e., parental arguments about finances) was the top independent variable predicting whether a student would have a credit card debt of over $500. Our results confirmed what others have found: parents who argue about finances contribute to increasing card debt in their children (Allen et al. 2007; Shim et al. 2010). Of course, parents arguing over finances may be due to low household income rather than a parental communication pattern, or a combination of both. To inquire whether parental income was influencing argument over finances, we ran a χ2 test between parents’ household income (under $50,000 and over $50,000) and whether or not a student indicated if their parents argued about finances (indicated by a yes or no response). Surprisingly, parents’ income was not a significant factor in this study as to which parents may be more inclined to argue (p = 0.06).

Furthermore, when analyzing parental interactions on the number of credit cards students held, we found that parents who argued about finances had the same predictive value as work experience, knowledge, and credit card attitudes combined. This predictive strength of parents arguing about finances confirms previous research on the powerful influence parents have on financial behaviors (Jorgensen and Savla 2010; Shim et al. 2010) and the powerful socialization that comes from the home (Gudmunson and Danes 2011; Jorgensen and Savla 2010). Because the “arguing about finances” variable was the strongest predictor of both number of credit cards held as well as amount of credit card debt, future studies on parental influence on the financial literacy of their children should include this variable. Research on parents arguing about finances could help us better understand how financial attitudes are formed. If behaviors are directly influenced by attitudes, parents should know the influence their arguing about money have on the attitudes and behaviors of their children. Although these findings did not show that parents’ explicit and implicit teaching styles influenced students’ credit card behaviors, it did show that parents who argued about money negatively influence their children’s credit card behaviors.

Work Experience

Years of work experience was significant in both regression models, yet, when placed into the final logical regression models, it was not statistically significant. One explanation is that students may feel they have a handle on things now because they expect more income in the future (Norvilitis et al. 2006). In other words, in this sample there were direct positive relationships between years of work experience correlating with having a balance over $500 in credit card debt and having two or more credit cards. However, when compared with other factors, such as parents arguing about finances, gender, class rank, and attitudes, it was no longer significant. Thus, work experience influences students’ credit card behaviors outside of the models of this study. It would be interesting to see if this finding would become significant in a more diverse sample (e.g., larger variance in parental income, larger non-white population).

Personal Characteristics

The personal characteristic of class rank had a more powerful predictive value on whether students had two or more cards than gender, parents arguing about finances, and credit card attitudes. Our finding that juniors and seniors were almost four times more likely to have two or more credit cards than first year students and sophomores builds on previous research (Lyons 2004). In addition, juniors and seniors were 2.4 times more likely than first year students and sophomores to have over $500 in debt. These finding indicate that the longer students are enrolled in college, the more likely they are to obtain more credit cards and more debt (Lyons 2004). This finding is possibly because they are becoming less financially dependent on their parents (Shim et al. 2010). It is interesting to note that although in the current study there was not a significant difference between students who paid the balances for their own credit cards and those whose parents paid the credit card balances for them, there were some clear trends (i.e., first-year students, sophomores, and female students were more likely to have parents pay their credit card balances).

Gender played a key role in the number of credit cards college students had. Females were 2.4 times more likely than males to have two or more credit cards when all other factors were held equal in the regression which confirms what others have discovered (Lyons 2004; Robb 2011). However, gender did not meet inclusion criteria for logistic regression when analyzing credit card debt, which is also consistent with past research (Norvilitis et al. 2006; Pinto et al. 2001). It was surprising that parental income was not significant and therefore not included in any of the regression models. This finding may be explained by the fact that over 65 % of the sample had parents with a household income over $50,000. Future research should include a larger percentage of lower-income families than did the current study.

Financial Knowledge

Similar to other studies about financial knowledge of college students (Chen and Volpe 1998; Norvilitis et al. 2006), participants in the current study had average financial knowledge scores of 60 %. Even though financial knowledge was significant in predicting possession of two or more credit cards, so that it met inclusion for the regression model, in the final regression analysis, financial knowledge was not significant. This may indicate that there are variables missing from the model, that financial knowledge is imprecisely measured, or that financial knowledge is not directly associated with financial behavior/outcomes (Borden et al. 2008; Gudmunson and Danes 2011; Peng et al. 2007; Xiao et al. 2011). One possible reason for this complication is that some students may acquire more credit cards over time in order to improve their credit score rather than to increase their level of debt. In sum, complex relationships exist between financial knowledge and financial behaviors among college students (Robb and Sharpe 2009; Xiao et al. 2011), and future research may wish to include financial attitudes as a mediating factor (Gudmunson and Danes 2011; Jorgensen and Savla 2010; Xiao et al. 2011).

Credit Card Attitudes

Comfort with paying minimum balances was the only statistically significant attitude across both direct logistic regression analyses, and the only significant attitude that predicted having $500 or more in credit card debt. Students who were comfortable making minimum payments were 2.2 times more likely to have over $500 in credit card debt, suggesting that financial attitudes influenced whether a student would incur more debt (Shim et al. 2009). Conversely, being afraid of credit cards appears to be associated with students having fewer than two credit cards and using them less (Joo et al. 2003). This is consistent with previous research establishing that financial attitudes influenced financial behaviors (Jorgensen and Savla 2010; Kidwell et al. 2003; Shim et al. 2010). One of the key findings of the current research confirms that credit card attitudes play an important role in students’ credit card behaviors; specifically, being comfortable with minimum payments was one of the largest risk factors for having more debt and a greater number of credit cards.

In order to increase positive credit card behavior through financial education, educators should focus on increasing the financial knowledge of students in ways that also shape their financial attitudes. As Jorgensen and Savla (2010) found, financial attitudes mediated the relationship between financial knowledge and financial behavior. In essence, attitudes shape behavior, so part of increasing financial literacy means increasing financial knowledge as well as addressing financial attitudes. One way to do to this is to have discussions about what money means to them (e.g., we never have enough, money is dirty, money is power), what they think money means to their parents, and if they learned their attitudes from their parents (i.e., are they similar?). Another way is to discuss money in the context of family and personal relationships. Understanding the outcome of good and poor financial behaviors on relationships can influence attitudes towards money. In addition, when analyzing the relationship between class rank and credit card attitudes, the current study revealed that students became more comfortable with minimum payments the longer they were in school. Therefore, early intervention strategies may be important in shaping financial attitudes and behaviors.

Summary

There are clear predictors from this sample as to which students are more likely to have two or more credit cards and have over $500 in credit card debt. Hypothesis 1 was not fully supported: gender and class rank were the top predictors, followed by parents who argued about finances. However, these results highlight the need to address multiple influences and risk factors for having two or more credit cards: junior/senior (3.8 times more likely from regression), female (2.4 times more likely), parents who argue about finances (2.1 times more likely), and comfort making minimum payments (1.4 times more likely). On the other hand, hypothesis two was fully supported, demonstrating that having parents who argue about finances is one of the main influences on whether a student has over $500 in credit card debt. This hypothesis highlights the multiple factors influencing why a student has over $500 in credit card debt. For example, a junior/senior (2.2 times more likely) who has two or more credit cards (three times more likely), has parents that argue about finances (2.8 times more likely), and is comfortable making minimum payments (2.2 times more likely) would have one of the greatest risks to have a credit card balance over $500. Researchers, educators, and policymakers can all help reduce the compounding factors that impact why students have more credit cards and more credit card debt.

Implications

Researchers, educators, and policymakers should work with and include parents in finding effective ways to increase the positive financial behaviors of college students, specifically as those behaviors relate to credit card debt. We need to help students and parents learn financial skills (Norvilitis and Phillip 2002) and establish healthy financial attitudes (Shim et al. 2010) at earlier ages to prevent poor financial habits from taking root (Gutter and Copur 2011). Good places to start might be programs and policies that address targeting key entry points of life (Gudmunson and Danes 2011) in helping promote positive communication about finances for couples/parents, such as financial education before a couple has children or during freshmen orientation.

Future researchers could explore the various ways attitudes mediate the relationship between knowledge and behaviors, as was initiated by Jorgensen and Savla (2010). Our study indicated that financial attitudes were key in both analyses, but financial knowledge was not a significant predictor of why a student would have more credit cards and more debt. Future research on this topic would benefit from incorporating the models created by Gudmunson and Danes (2011), Jorgensen and Savla (2010), and Xiao et al. (2011). Consequently, there is a need for researchers to be aware of the financial attitudes that exist, so that educators can increase healthier credit card attitudes earlier in the lives of the college students. In addition, more should be done to find out effective intervention points and the best ways to address them. Researchers might look at which methods are most effective in helping change unhealthy financial attitudes in order to change unhealthy financial behaviors. Efforts to change financial attitudes should include ways to help parents develop healthier financial communication patterns with each other and their children. Therefore, longitudinal studies will be helpful to address many of these factors so that best practices can be employed. Future researchers should also seek out a more diverse population in terms of income, race, ethnicity, and family type when trying to find good interventions because each population may have unique influences on financial behaviors.

Educational institutions should address student credit card debt by intervening in the early years of school with financial classes or seminars (Borden et al. 2008; Walstad et al. 2010). These classes should focus not only on increasing financial knowledge but on also changing financial attitudes and behaviors. Universities could help all students by involving well-known financial leaders (e.g., Suze Orman, Dave Ramsey) in giving workshops and seminars (Borden et al. 2008), because they will likely draw a bigger crowd and may help more people than academics would. Furthermore, programs aimed at multiple risk factors regarding debt might focus on students who are comfortable with making minimum payments because being comfortable with making minimum payments leads to more credit card debt, which is associated with sensation seeking behaviors (i.e., smoking, drinking, Adams and Moore 2007) and reduced mental and physical health (Berg et al. 2010). These poor coping behaviors can block the needed motivation for students to change their financial behaviors by adding less debt to their cards or making headway in paying them down (Mandell and Klein 2007). In addition, we agree with Maurer and Lee (2011), who stated that programs need to be tailored to the needs of the college students and that more research and educational institutions should look into results of peer financial counseling. Regardless of how it happens, universities should support programs that focus on ways to help increase students’ positive credit card attitudes and behaviors (Borden et al. 2008; Norvilitis et al. 2006; Norvilitis and MacLean 2010; Robb 2011; Shim et al. 2009).

Policymakers could also help create healthier credit card attitudes by requiring students to pass financial management classes in each state (CEE 2011), especially first-year and sophomore college level students, and possibly high school students (Peng et al. 2007; Walstad et al. 2010). However, it may be more realistic to offer financial education modules online or phone applications that are specifically targeted to the individual based on attitude assessments measured before the module begins. It would also be helpful for these modules or courses to incorporate skill building that involves active experimentation approaches (e.g., group activities, practicum). Norvilitis and Phillip (2002) compared contemporary financial learning to the ineffectiveness of the one-dimensional instructional methods of the drug abuse resistance education (DARE) program and past sex education efforts, which established these modalities to be considerably less effective than skill building. Furthermore, Fox and Bartholomae (1999) concluded that doing “hands-on” skill building activities was the preference of over 80 % of participants. Therefore, addressing the “hands-on” learning style may be key to motivating students to do better financially (Fox and Bartholomae 1999; Mandell and Klein 2007), thus giving them experience. This skill building was also recognized by Gutter and Copur (2011), who labeled it “action oriented financial education,” and Xiao et al. (2011), who labeled it “action oriented teaching approaches” with a need to include modern technology. Additionally, policymakers could make these research-based best practices a priority, especially for financially troubled families and students with the higher risk factors discussed in this study. As an extension of this research paper, we see a necessary part of this “action oriented financial education” to include exercises that address credit card attitudes, along with early interventions during the college experience to prevent juniors and seniors from incurring unnecessary debts. Thus, policymakers can help curb the financial problems of college students by funding researchers studying this topic and by working with educational institutions to implement the research findings.

Limitations

This study is not without limitations. A main limitation is that of self-reporting error. We could not interpret whether the students understood whether “your” credit cards meant cards in their own name, or cards they used but were in their parents’ names, or a debit card they thought was a credit card because it had a Visa or Master Card logo. Students’ perceptions may have biased the data, resulting in their reporting fewer numbers of credit cards held and less debt. Whatever the students’ interpretation of “your credit cards,” the amount of debt they held may have been influenced by who made the payments. However, there was one important question that was asked in the survey about who paid for the credit cards, and we found no statistical differences between those who paid the credit cards themselves and those who had parents pay.

Another limitation is that participants come from a convenience sample. Although we gathered data from seven different campuses, a common concern about convenience samples is that they may attract those with better financial practices and discourage those who have more financial problems due to perceived self-embarrassment. Participants may self-report to make themselves appear to have better control of their finances than they actually do. This limitation, as well as the homogeneity of our sample (e.g., 65 % of household incomes were over $50,000, and 87 % were white), could be part of the reason that the amount of debt was considerably lower than the national average.

Finally, we used secondary data and were limited by the constraints of previous established research methods (see Jorgensen and Savla 2010 for additional limitations). For instance, the credit card debt scale had uneven units (i.e., $100–$499 to $500–$1999). This jump in the debt scale made it hard to study the standard credit card debt risk level of $1,000 or more (Lyons 2004). However, this uneven scale may not have affected the results given that the sample had an average credit card debt balance between $100 and $499, which is low compared to the national average of $3,170 (Sallie Mae 2009). Furthermore, 33 % of the sample did not have a credit card compared to the national average of 16 % (Sallie Mae 2009). These limitations may have skewed the data to reflect the trend of having fewer card holders and having fewer number of credit cards (1.5 vs. the national average of 4), as well as having less credit card debt than the rest of the nation.

Conclusion

By understanding the antecedents of those with multiple credit cards (i.e., female, junior or senior, parents who argue about finances, and being comfortable with minimum payments), and with more than $500 in credit card debt (i.e., having two or more cards, parents who argue about finances, junior/senior, and being comfortable with minimum payments), researchers, educators, and policymakers can work together in effective ways to increase students’ positive financial behaviors as it relates to credit card use. Educators and researchers should look into developing national standardized “hands-on” curricula that offer financial services or classes to help create effective interventions, while policymakers should provide the needed financial support to make these curricula a reality. This study highlights the need to find ways to assess credit card attitudes and to assist students through these formative years by addressing harmful financial decisions early on (Schuchardt et al. 2009). Finally, we call on researchers, educators, and policymakers to help educate parents on financial literacy as well as their influence on their children, so those children can have positive financial attitudes and behaviors throughout their lives.

Copyright information

© Springer Science+Business Media New York 2012