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Who Stole the American Dream

Permanent Link: http://ufdc.ufl.edu/UFE0042656/00001

Material Information

Title: Who Stole the American Dream College Students, Social Learning, and Risky Credit Card Behavior
Physical Description: 1 online resource (74 p.)
Language: english
Creator: Jackson, Kristin
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: behavior, card, college, credit, differential, learning, location, norms, oppertunities, perceived, risky, social, students
Family, Youth and Community Sciences -- Dissertations, Academic -- UF
Genre: Family, Youth and Community Sciences thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: College students management or mismanagement of credit today can impact their ability to obtain the lifestyles they desire in the future. This study looks at whether or not receiving need based financial aid is related to students risky credit card behavior. It is anticipated that differences in the frequency of the conversations students have with their parents about money, the frequency with which students have the opportunity to observe their parents managing their money, and the perceptions students have about parents risky credit card behavior will differ based on whether or not they receive need based aid. It was found, that there is a difference between students who receive need based aid and students who do not receive need based aid perceptions about their parents engagement in risky credit card behavior and the difference is significantly related to the student s own risky credit card behavior.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Kristin Jackson.
Thesis: Thesis (M.S.)--University of Florida, 2010.
Local: Adviser: Gutter, Michael S.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042656:00001

Permanent Link: http://ufdc.ufl.edu/UFE0042656/00001

Material Information

Title: Who Stole the American Dream College Students, Social Learning, and Risky Credit Card Behavior
Physical Description: 1 online resource (74 p.)
Language: english
Creator: Jackson, Kristin
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: behavior, card, college, credit, differential, learning, location, norms, oppertunities, perceived, risky, social, students
Family, Youth and Community Sciences -- Dissertations, Academic -- UF
Genre: Family, Youth and Community Sciences thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: College students management or mismanagement of credit today can impact their ability to obtain the lifestyles they desire in the future. This study looks at whether or not receiving need based financial aid is related to students risky credit card behavior. It is anticipated that differences in the frequency of the conversations students have with their parents about money, the frequency with which students have the opportunity to observe their parents managing their money, and the perceptions students have about parents risky credit card behavior will differ based on whether or not they receive need based aid. It was found, that there is a difference between students who receive need based aid and students who do not receive need based aid perceptions about their parents engagement in risky credit card behavior and the difference is significantly related to the student s own risky credit card behavior.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Kristin Jackson.
Thesis: Thesis (M.S.)--University of Florida, 2010.
Local: Adviser: Gutter, Michael S.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042656:00001


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1 WHO STOLE THE AMERICAN DREAM: COLLEGE STUDENTS, SOCIAL LEARNING, AND RISKY CREDIT CARD BEHAVIOR By KRISTIN D. JACKSON A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQ UIREMENTS FOR THE DE GREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2010

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2 2010 Kristin D. Jackson

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3 To my dad and mom

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4 ACKNOWLEDGMENTS I thank God, Elohim, for the strength to endure. All things are through Him. I thank my parents for the ir love and support. I thank my advisors for their guidance and direction.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 LIST OF DEFINITIONS AND ABBREVIATIONS ................................ ............................. 9 ABSTRACT ................................ ................................ ................................ ................... 11 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 12 Introduction ................................ ................................ ................................ ............. 12 Purpose ................................ ................................ ................................ .................. 14 Research Questions ................................ ................................ ............................... 14 Rationale ................................ ................................ ................................ ................. 15 Significance ................................ ................................ ................................ ............ 16 Assumptions ................................ ................................ .............................. 16 Participants ................................ ................................ ................................ ....... 16 Parents ................................ ................................ ................................ ............. 17 Limitations ................................ ................................ ................................ ............... 17 Validity and Reliability ................................ ................................ ...................... 17 Survey Administration ................................ ................................ ...................... 18 2 LITERATURE REVIEW ................................ ................................ .......................... 19 Financial Knowledge and Access ................................ ................................ ........... 19 Theory of Planned Behavior ................................ ................................ ................... 20 History of Learning Theory ................................ ................................ ...................... 23 Social Learning, Perceived Norms, and Financial Behaviors ................................ .. 26 Social Learning Opportunities and Differential Location ................................ ......... 28 Social Learning of Risky Credit Card Behavior ................................ ....................... 29 Summary ................................ ................................ ................................ ................ 31 3 METHODS ................................ ................................ ................................ .............. 36 Sampling and Data Collection ................................ ................................ ................. 36 Independent Variables ................................ ................................ ............................ 37 Descriptive Statistics ................................ ................................ ........................ 37 Differential Location ................................ ................................ .......................... 37 Social Learning Opportu nities (Observed) ................................ ........................ 38 Social Learning Opportunities (Conversations) ................................ ................ 39

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6 Perceived Norms ................................ ................................ .............................. 40 Dependent Variables ................................ ................................ .............................. 41 Risky Credit Card Behavior ................................ ................................ .............. 41 Analysis ................................ ................................ ................................ .................. 42 4 ANALYSIS ................................ ................................ ................................ .............. 49 Analysis ................................ ................................ ................................ .................. 49 Bivariate Analysis ................................ ................................ ................................ ... 49 Independent Variables ................................ ................................ ..................... 49 Descriptive Statistics ................................ ................................ .................. 49 Social Learning Opportunities ................................ ................................ .... 50 Dependent Variable ................................ ................................ .......................... 51 Risky Credit Card Behavior ................................ ................................ ........ 51 Multivariate Analysis: Logistic Regressions ................................ ............................ 51 Reduced Model Logistic Regression ................................ ............................. 51 Demographics ................................ ................................ ............................ 51 Needs ba sed aid equals zero ................................ ................................ ..... 53 Full Model Logistic Regression ................................ ................................ ....... 53 Pell status*Social learning Opportunities ................................ ................... 53 Likelihood Ratio test ................................ ................................ .................. 54 5 CONCLUSION AND IMPLICATIONS ................................ ................................ ..... 59 Conclusion ................................ ................................ ................................ .............. 59 Differential Location and Social Learning Observations ................................ ... 59 Differential Location and Social Learning Conversations ................................ 59 Differential Location and Perceived Norms ................................ ...................... 60 Differential Location and RCB ................................ ................................ .......... 60 Differential L ocation as a moderator between social learning and RCB ........... 60 Discussion and Findings ................................ ................................ ......................... 61 Implications ................................ ................................ ................................ ............. 62 APPENDIX A SURVEY QUESTIONS ................................ ................................ ........................... 64 B VARIABLE CODING ................................ ................................ ............................... 66 C RCB CUMULATIVE MEASURE ................................ ................................ ............. 68 LIST OF REFERENCES ................................ ................................ ............................... 70 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 74

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7 LIST OF TABLES Table page 3 1 Summary of variables in reduced model ................................ ............................ 45 3 2 Summary of variables added to reduced model to form full model ..................... 46 4 1 Sample profile by differential location ................................ ................................ 55 4 2 Reduced model differential location and risky credit card behavior ................... 55 4 3 Full Model differential location moderating risky credit card behavior ................ 56 C 1 Reduced Model OLS regression of RCB ................................ ............................ 68 C 2 Full Model OLS regression RCB ................................ ................................ ....... 68 C 3 Variable Coding of RCB Cumulative ................................ ................................ ... 69

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8 LIST OF FIGURES Figure page 2 2 Model of social learning theory ................................ ................................ ........... 35 3 2 Full social learning model tested with reported betas and odds ......................... 48 4 1 Reduced model tested with betas and odds ratios ................................ ............. 57 4 2 Full model with betas and odds ratios ................................ ................................ 58

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9 LIST OF DEFINITIONS AND ABBREVIAT IONS Attitudes "A person's positive or negative evaluation of a relevant regarding the perceived outcomes of performing a behavior" (Xiao, 2008, p 73). Behavior intentions How likely an individual i s to perform a behavior within their volitional control (xiao, 2008). Behaviors under violation control Require no skills, social cooperation, require short term planning, and assume a chain, additive, or recursive structure, (Liska, 1984) Consumer Soc ialization & Macinnis, 2009, p 397) Differential location Socio economic variables (Durkin, Wolfe, and Clark, 2005, and Lee and Akers, 2004) Expect ancies Self efficacy and outcome expectations (Rotter,1954) Financially at risk (FAR) College students are defined by the following characteristics: they have credit card balances of $1,000 or more, are delinquent on the credit card payments by two month s or more, have reached the limit on their credit cards, and only pay off their credit card balance some of the time or never (Lyons, 2004) Pell grants foundation of federal student financial aid, to which aid from other federal and nonfederal sourc es might be (Federal Student Aid, 2009). Perceived behavioral control behavior, reflecting on both past experience as well as anticipated barriers," (Xia o, 2008, p 73). Risky credit card behaviors Having credit card balances of $1,000 or more, being delinquent on credit card payments by two months or more, having reached the credit limit, not paying off balance is full (Lyons, 2004) Social learning opp ortunities Intentional instruction and reinforcing activities which individuals are exposed (Durkin, Wolfe, and Clark, 2005 and Gutter, Copur, and Garrison, 2009)

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10 Social learning theory (SLT) Looks at how society influences individuals information proce ssing and how having external influences relates to behaviors (Akers, Krohn, Lanza Kaduce, and Radosevich, 1979; Frayne, 1987). Social learning variables Differential association, differential reinforcement, and evaluative definitions (Akers et al, 1979) Social Location Ronald Rousseau, 2002, p 442) Social Norms Learned definitions of behaviors (Akers et al, 1979) Social Structure can impa 258 and Bursik and Grasmick, 1996) Subjective norms 73). Theoretically defined structural varia bles concepts found in various structural theories. These concepts are not usually measured directly but rather are measured indirectly by population, socio demographic, or socio economic measures (Bu rsik ,1988 and Sampson and Groves, 1989) Theory of planned behavior (TPB) The modified model of TRA that incorporated perceived behavioral control is a motivational/behavior theory designed to predict and understand human behavior based on the individual decision making process (Xiao, 2008).

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11 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Thesis of Master of Science WHO STOLE THE AMERICAN DREA M: COLLEGE STUDENTS, SOCIAL LEARNING, AND RISKY CREDIT CARD BEHAVIOR By Kristin D. Jackson December 2010 Chair: Michael Gutter Major: Family, Youth, and Community Sciences their a bility to obtain the lifestyles they desire in the future. This study looks at whether behavior. It is anticipated that differences in the frequency of the conversations s tudents have with their parents about money, the frequency with which students have the opportunity to observe their parents managing their money, and the perceptions edit card behavior will differ based on whether or n ot they receive need based aid. It was found, that there is a difference between students who receive need based aid and students who do not receive need based aid differen ce is significantly

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12 CHAPTER 1 INTRODUCTION Introduction students are the target of aggressive marketing campaigns b y credit card companies because full time students represent over sixty billion dollars in buying power, (Hay hoe, Leach, Turner, Bruin, and Lawrence, 2000). In 2006, the average traditional age undergraduate received between 25 and 50 credit card solicita tions per semester (United College Marketing Services, 2006). In 2009 twenty one percent of undergraduates had balances of between $3,000 and $7,000 (Sallie Study of Usage Rates and Trends 2009 ). Credit allows individuals to trade future con sumption for consumption today. When managed properly it allows individuals to maintain a consistent style of living over and long term consumption by lowering the consu Credit scores are designed to be a measure of risk. Credit scores impact not employment, and the ability to obtain insurance. Payment history and t he amount owed Forty percent of ey to The mismanagement of credit by young adults has lead to the recognition of several alarming statistics and trends. Research has found that young adults who are

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13 able to pay a nd make payments on their outstanding credit obligations spend on average approximately 24% of their income on debt repayment (Draut & Silva, 2004). Further, the dropout rate among college students due to debt and financial pressures is higher than the dro pout rate for academic failure (United College Marketing Services, 2006). Congress considers the potential impacts of credit card misuse by young adults to be so severe that they have passed the Credit Card Accountability, Responsibility, and Disclosure A ct of 2009. The new legislation requires that individuals under 21 have a cosigner or demonstrate the ability to pay. Simply raising the minimum age to obtain a credit card or the implementation of financial restrictions is not enough. The problem is tha t some college students are not knowledgeable about personal financial education topics and responsibilities (Sallie Mae, 2009) Currently only 13 states require students to take a personal finance course or for personal finance to be included in high sch ool economics courses (Counsel for Economic Education, 2009) This means that 69% percent of American students in grades k 12 may not be formally trained within the American School system with regards to matters of personal finance. This creates a complex dynamic between what is learned through formal education and social learning with regards to financial behaviors. In areas where personal financial education is not taught in schools, a large portion of the responsibly is placed on parents. Yet parents ma y not have been formally trained on personal financial topics either. Similar to their children, parents may not understand how to manage their credit, budget, or savings and as a result may deliver inconsistent messages based on their own financial belie fs not facts. Due to the

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14 potential for the inconsistent delivery of positive personal financial messages in the home, additional research on social learning process with regards to financial behaviors is needed. Purpose Current research has demonstrated th at age, gender, race, marital status, income level, dependence on parents, and qualification for needs based financial aid are all related to social learning opportunities (Gutter, Copur, and Garrison, 2009). The purpose of this study will be to at whether or not personal financial social learning opportunities will still differ between groups when a specific behavior, risky credit card behavior, is considered and differential location is the moderator. Differential locat i on is the quantifiable measure of a individual indicators of differential location. This study will use a comprehensive measure looking at the relationship when multiple indicators are weighted and considered all at once. Research Ques tions Q 1 : Is there a difference in observed financial social learning opportunities between groups of college students with differential social location? Q 2 : Is there a difference in opportunities for financial social learning conversations between groups with differential social location? Q 3 : Is there a difference in perceived norms of risky credit card behavior between groups as defined by their differential social location? Q 4 : What is the nature of the relationship between social learning opportuniti es and risky credit card behavior? Q 5 : Does differential location moderate the relationship between social learning opportunities and risky credit card behavior?

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15 Rationale Prior research has established the key circles of influence that surround young peo ple are family, school, and peers (Brendtro, 2006). Parents provide the most information and have the biggest impact on actual behavior (Pinto, Parente, & Mansfield, 2005). Parents influence financial behavior by, guiding the development of consumption pa tterns through verbal and/ or nonverbal communication with their children (Dursun, 1993). Macinn is, 2009). R esearch that has been conducted on the consumer socialization process shows that consumer socialization starts before children have reached four acquire the relevant skills, knowledge, and attitudes necessary to act efficiently in the such as time preference patterns and delay of gratification patterns are firmly established for life (Maital and Maital,1977). Thus lending itself to the idea, many of the financial behaviors, especially with respect to credit card use by college students are learned from their parents even before students would have been exposed to concepts in a fo rmal educational setting. Three key constructs have been identified as affecting consumer socialization in general: individual factors, socializing factors, and learning mechanisms (Hayta, 2008). Individual factors are defined as socioeconomic level, gen der, and age/life period (Hayta, 2008). Socializing factors are defined as family members, friends, school, (2008) model

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16 considers the cognitive development model and social learning model as the primary lea rning mechanisms Hayta (2008) posited that additional research is needed on how individual factors and socializing factors impact consumer socialization. Significance Gutter (2009) and his colleagues are some of the first to attempt to bridge the knowledge gap between what is known about individual differences and how the differences relate to consumer socialization Gutter, Copur, and Garrison (2009) look at the connection between individual factors, financial social learning opportun ities and financial behaviors of college students. Gutter, Copur, and Garrison (2009) reaffirmed that social learning is related to financial socialization. It was also found that age, gender, race, marital status, income level, dependence on parents, an d qualification for needs based financial aid are all related to social learning opportunities (Gutter, Copur, and Garrison, 2009). Due to the long term effects of inadequate consumer socialization it is important that researchers develop a better underst anding of how the socialization process works and how different individual/ socializing factors affect the process. This study will expand on prior research by examining the impact of one individual factor (differential location) and one socializing facto r (parents or primary care givers) on the relationship between social learning opportunities and risky credit card behavior when differential location acts as a moderator. A ssumptions Participants This study uses a 15 campus data set collected by Gutter, Copur, Garrison (2009). The data set was one of the first national data sets to specifically address financial

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17 social learning opportunities. The study use a stratified sampling to first select the states and then large state universities for participat ion. Participants had to be currently enrolled and over 18. There were about 16,876 participants. This study similar to Gutter, Copur, and Garrison eliminated home schooled and international students. Home school students were excluded because of the fac t that in some cases the parents are the teachers. Through participating in the educational process these parents may be exposed to or teach personal finance to their children resulting in these parents being inadvertently more self conscience of the fina ncial messages they send to their children. The responses for international students were excluded because different countries may have different norms about financial behaviors and financial education. Parents This study assumes that parents/guardians all have the same impact on differential association. Differential associations are conceptualized as the time, frequency, and duration of interactions between individuals. The time, frequency, and duration that parents/guardians spend with their children can be influenced by a number of things such as the amount of hours that they work, whether they are the biological parent or the guardian, the nature of the relationship between the parent and the child, or even what age was the child when he/she went to college. Limitations Validity and Reliability Participants for this study were only selected f r om large public universities. There could statistical differences between students that attend smaller colleges, historically black colleges, or private univer sities when compared to those who attend large public

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18 universities. Further, there could be difference between this group, college students, and those that do not attend college at all. Survey Administration Surveys were administered via email. Bias co uld be a problem as certain types of students are more likely to participate in online surveys than others. Additionally there was an incentive offered to participants. Every 1000 th person to complete a survey would receive a $100.00 gift card.

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19 CHAPTE R 2 LITERATURE REVIEW Financial Knowledge and Access For everyone who has will be given more, and he will have abundance King James Version ) This phenomenon is known as t he ffect The parable describes the value of positive consumer socialization and the potential consequence of insufficient consumer socialization The servant with the smallest amount of financial resources did not have the necessary knowledge t o best manage the money which he was entrusted with As a result of his lacking financial ability the master took the money from the least knowledgeable servant and gave it to the servant with the most financial ability. The privilege or disadvantage of financial E ffect still holds true today. Those with financial capabilities and knowledge experience financial gains and those without tend to be plagued by continual financial struggles. Modern day examples of this are ill ustrated through the existence of alternative financial institutions such as payday lenders, pawn shops, rent to own establishments, and high interest credit cards. Consumers who use the services provided by alternative financial institutions are often cha rged higher interest and fees than consumers who use traditional financial institutions; hence certain consumers are at a disadvantage because of their lack of financial knowledge. Financial theorist s use behavior theories such as the theory of planned be havior (TPB) and social learning theory (SLT) to understand the determinants of future financial behaviors such as risky credit card behavior. Financial theorist s who prescribe

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20 to the TPB model argue that consumers engage in risky credit card behavior beca use of personal choices that the y believe are most beneficial to them. Social learning theory incorporates some aspects of TPB, but takes into account the role of the social learning process as it influences planned behavior. ies $3,173 in credit card debt, addition to student loan debt (Sall i e Mae, 2009 ). Without a firm understanding of interest and fees even a small credit card balance can add up quickly, creating a modern day it card allows some students to build credit and to earn greater amounts of interest on the money they have through use of float time (the time from when you make a purchase on a credit card to the time when interest starts accruing). Less knowledgeable s tudents may not have the knowledge or capabilities to use credit as advantageously as their more knowledge/capable counterparts. Using a social lens which incorporates parts of theory of planned behavior and social learning theory allows both the role of i ndividual decision making and social influences to be accounted for as a better understanding of the relationship between college students and risky credit card behavior is sought. Theory of Planned Behavior T he t heory of planned behavior (TPB) is a motiv ational/behavior theory designed to predict and understand human behavior based on the individual decision making process (Xiao, 2008). TPB Reasoned Action (TRA) TPB has been applied in numerous studi es on consumer decision making (Rutherford & DeVaney, 2009; Xiao, 2008). TPB contains five constructs the first five ( attitude, subjective norms, intentions perceived behavior control, and actual behavioral control) which influence the sixth

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21 construct behavior (Figure 1 1) The construct of attitude is used to reference an individual's attitude towards engaging in a behavior or a, "person's positive or negative regarding t he perceived outcomes of performing a behavior" (Xiao, 2 008, p 73). Hence students who engage in risky credit card behavior are evaluating negative behaviors such as: having credit card balances of $1,000 or more, being delinquent on credit card payments b y two months or more, having reached the credit limit, and only paying off credit balances some of the time as maybe not idea, but acceptable behavior Another component of TPB is perception of wheth er significant referents approve or disapprove of a behavior, (Xiao, 2008, p 73). Based on this definition, students who engage in risky credit card behavior would also have parents or other significant referents whom approve of risky credit card behavior or at least do not strongly disapprove of the behavior. It becomes apparent that only looking at risky credit card behavior from the TPB lens may not be the best fit once one begins to examine how the remaining constructs: behavior intentions, actual be havior control, and perceived behavioral control are conceptualized within the TPB framework. Behavior intentions pertain to how likely an individual is to perform a behavior within their volitional control (Xiao, 2008). Behaviors within an individual's v olitiona l c ontrol are those that require little skills, social cooperation, short term planning, and assume a chain, additive, or rec ursive structure (Liska, 1984) I n the broad s ens e risky credit card spending may fall into the category of behavior inte ntions that are with in i tion al control. However, for some individuals, the skills necessary to avoid risky credit card behavior such as :

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22 individual financial planning, loans/financing, net present and net future value, and simple/compou nd inter est are lacking. The number and specificity of skills needed, as well as possible long term planning involved to avoid risky credit card behavior is likely to be beyond the volitional control of college students who are financially at risk (FAR) F AR students may lack the social learning opportunities to obtain necessary skills and, as a result, exercise limited to no volitional control over their risky credit card behaviors. This study will examine whether or not there is a difference between the social learning opportunities of FAR college students and students that are not financially at risk (NFAR). The fifth construct, actual behavior control in TPB is conceptualized similar to social structure in social learning theory (SLT). Social struct ural variables are treated as mediators which have the potential to explain how or why social factors may influence the remainder of the social learning process Both variables take into account factors r her behaviors. The main difference between the two constructs is that actual behavioral control in TPB is often conceptualized as factors that directly influence perceived behavior control or actual control over behaviors. In TPB actual behavior control serves a moderator between perceived behavioral control and behavior. For example, when looking through the TPB lens financial resources could influence risky credit card behaviors through influencing avioral control) or through influencing whether or not students make payments (actual behaviors). Hence the variables associated with actual behavioral control are treated as background variable s in TPB (Liska, 1984) as appose to potential predictor variab les in SLT.

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23 Another addition to the basic TPB is the construct of perceived behavioral control, added by Ajzen (1991). Perceived behavioral control acts as a precursor to behavior, similar to the actions of the constructs of attitude and s ubjective norms Perceived behavior al control describes the perceived difficulty level of performing the behavior, reflecting on both past experience as well as anticipated barriers" (Xiao, 2008, p 73). Perceived behavior al control is also a term used in social learnin g theory (SLT); however, it is conceptualized differently. A key difference is that perceived behavior al in TPB only applies to behaviors with in an individual volitiona l control Perceived behavioral control in SLT attempts to capture one s general belie fs about ability and expectancies toward all behaviors regardless of whether or not the behavior has been carried out. Generally the way perceived behavioral control is conceptualized by Bandura (1997) and applied within the social learning framework is considered to be a better predictor of behavior because it incorporates the key concepts of TPB and considers the potential relationship among them not specified/acknowledge in TPB (Xiao, 2008). When looking specifically at financial behaviors using the social learning framework, the way Bandura (1987) conceptualized perceived behavioral control is useful because it takes in to account behaviors which a person may feel confi dent about performing, but may not currently have the means to accomplish. History of Learning Theory Social learning theory looks at how external or social influences impact in turn behaviors (Akers, Krohn, Lanza Kaduce, & Radosevich, 1979; Frayne, 1987). The ground work for social learning th eory was founded in the field of psychology. Edward Tolman set the frame work for the (1966)

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24 acts tend to be learned or not learned according to the goodness or badness of the consequences (p Social Learning. Millard and Dollard conducted experiments on the learning process of children and also analyzed crowd or group behavior. Their r esearch supported that learning takes place according to certain principles ( Miller & Dollard, 1941 ) Furthermore the learning process is strengthen ed through imitation (Millard & Dollard, 1941). Julian Rotter, also a psychologist, made three important contributions to social learning theory. Rotter : 1) perceived norms and outcome expectations ; 2) developed a scale to measure perceived norms; and 3) r (1954) found s upport for his hypotheses that: 1) people who experienced failure during their first attempt had a high expectancy for punishment or failure and avoided similar situations in the future; and 2) the opposite was true for people who experienced success (Rot ter, 1954). Albert Bandura is considered the founder of modern social learning theory. Through researching aggression in adolescents, Bandura found: Learning would be exceedingly laborious, not to mention hazardous, if people had to rely solely on the ef fects of their own actions to inform them what to do. Fortunately, most human behavior is learned observationally through modeling: from observing others one forms an idea of how new behaviors are performed, and on later occasions this coded informatio n se rves as a guide for action (Bandura, 1977, p. 22).

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25 (1974) concept of differential associations (i.e., learning that occurs through interacting with others) with the prior contribu tions of other theorists, including that of Tolman, Miller and Dollard, and Rotter, into one cohesive theory, to build modern social learning theory. social structure as medi ator in the social learning process. These variables are thought to potentially explain how or why social factors may influence the remainder of the social learning process. This differs from TPB in which social structural variables are incorporated in to the construct actual behavioral control, with other variables thought to directly influence volitional control. Social structural variables include differential location, differential social organization, theoretically defined structural variables, and di fferential social location variables (Akers, R.L, 1998). Differential location is commonly defined as socio economic status which is commonly indicated by income, education, and employment. Differential social organization describes socio demographic vari ables such as age structure or population density. Theoretically defined structural variables are other theoretical approaches to examining the behavior within the model such as TPB. The fourth variable, differential social location is comprised of the in Social structure is thought to influence financial behaviors through differences that exist between groups (Garrison & Gutter, 2008). There is a significant amount of support for the idea that social structure has an influence on social learning

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26 opportunities (SLO): conversations, observations, and perceived norms. SLO are thought to influence behavior intentions and in turn directly influence behavior. The revised model of SLT has three constructs: social structure, social lea rning, and perceived norms. These three constructs are expected to lead to the continuation and expiration of behaviors. Clark, Durkin, and Wolfe tested Akers (1998) revised model of social learning in a study of college students and the risky behavior of binge drinking explaining how social demographic variables are related to binge drinking. However, their sample size was small and the theory has not been tested specifically wi th regards research by looking specifically at the relationship between social learning opportunities and risky credit card behavior of college students with differential l ocation as a moderating variable. Social Learning, Perceived Norms, and Financial Behaviors (Rosenstock, Str echer, & Becker, 1988, p 176). In a study on impulsive purchasing, Luo compared the impact of peer versus parent influence on college students patterns (2005). L u o found that parents were most influential with regards to positive financial deci sion making when it comes to impulsive buying ; ho wever, this finding was dependent on within how attractive a Forsyth, 2000; Turner, Pratka nis, Probasco, & Leve, 1992; Luo, 2005). Hence parental influence may vary based on the natu re of the relationship that parents have with their children. Although parents may

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27 not be the only source of socialization they do provide more financial information than peers, school or the media ( Luo, 2005). Pinto and Mansfield (2006) were able to replicate prior findings with regards to the significance of the role parents have in financial socialization in general but were not able to replicate the significance of parents with re gards to impulsive buying. Thus, demonstrating parents may influence one area of the financial socialization process, but not the behavior. More recent research shows a relationship between financial socialization and financial behaviors, ( Gutter, Copur & Garrison, 200 9 p 83 ; Gutter, Copur, & Garrison, 2010; Garrison & Gutter, 2010 ) Further, this research was able to show that perceived norms impact financial decision making in general as well as influence credit card behaviors (Gut ter & Garrison, 2008) thus demonstrating financial decision making is influenced by others through social learning conversations/social learning others. Perceived norms re flect individual assessments of behaviors as well as and Garrison (2008) combined perceived norms, social learning conversations, and social learning observations into a me asure of social learning opportunities (SLO). Social learning opportunities were shown to be related to financial behaviors (Garrison & Gutter 2010). This study will look at the relationship between social learning opportunities (perceived norms, social l earning conversation, and social learning observations) and risky credit card behavior when differential location is serving as a moderating variable.

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28 By looking at financial behaviors using a broader theoretical approach such as SLT provides a more co mpl ete picture of influence s on financial decision making and financial behaviors SLT combined with similar constructs in TPB, has strong potential for conceptualizing and empirically examining the relationship between social structure, subjective norms, b ehavior intention, and actual behaviors in an attempt to describe how knowledge is transmitted and the factors that encourage or inhibit the transmission pr ocess (Bandura, 1997; Contu & Willmott, 2003). Social Learning Opportunities and Differential Locati on Prior research has looked at the effect of social structure on financial behaviors by examining the variable differential social organization. These studies have found that financial behaviors differ based on educational level gender, and race (Lusard i & Mitchell, 2007 ; Yao, Gutter, & Hanna, 2005; Gutter & Fontes, 2006). Additional research has found that financial differences between these groups may be related to financial soci al learning opportunities (Gutter, Copur, & Garrison, 2010). It is neces sary to conduct research similar to what has been done on gender and race for socio economic status. The variable differential location is the quantifiable cial status (Durkin, Wolfe, & Clark, 2005; Gutter, Copur, & Garrison, 2 009). The receipt of Pell grants is a unique indicator of differential location for college students. Aid, 2009). Pell grants serve as a unique indicator of differential location because they are based on a quantifiable measure of socioeconomic status, expected family contribution (EFC).

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29 EFC is a good indicator of socio economic status and family financial strength because it serves as a standardizing measure of financial resource availability, f unctioning similar to GPA or SAT and academic standing (Free Application for Federal Student Aid, N.D.). EFC takes in account: s tudent status, dependence on/ independence from parents, dependents, receipt of other types of assistance, other debt, income, assets, and other immediate family members in school. Once the cos t of attendance and determine the financial aid award amount (See appendix A). Due to the mathematics behind how EFC is calculated and who qualifies for Pell Grant the receipt or non receipt of the Pell Grant serves as an indicator of a ial resources. Prior research has demonstrated that differences between groups can indicate differences in financial social learning opportunities (Gutter, Copur, & Garrison, 2010). This study will explore whether differential location will moderate the relationship between social learning opportunities and risky credit card behavior. Social Learning of Risky Credit Card Behavior College students represent over sixty billion dollars in buying power (Punch, 1991). Banks are interested in college students because college students are likely to use their available credit and become long time customers (Warwick & Mansfield, 2000, & Sallie Mae, 2009). Due to grants, loans, and other types of educational funding ty of traditional and alternative financial products, but may not be familiar with the rules for advantageous use. While the Credit Card Accountability and Responsibility Disclosure Act of 2009 (CARD) will help to defer the age at which consumers acquire t heir first credit cards, young adults will continue to

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30 Whereas CARD can make it more difficult for students to obtain their first credit card, students can still gain access though the hel p of a cosigner or by demonstrating an ability to pay. This means that there is still the opportunity for some students to misuse credit. The US Public Interest Research Groups (PIRG) reported twenty five percent of the 1,584 college students surveyed pai d a late fee and fifteen percent have Risky credit card behaviors are defined by the following characteristics: having credit card balances of $1,000 or more; being delinquent on credit card payments by two months or more; having reached the credit limit; and/or only paying off credit balances some of the time or never (Lyons, 2004). These same factors are used to determine if a student is financially at risk (FAR). In a study where FAR students are compared to non financially at risk (NFAR) students, FAR students were found to carry higher credit balances and have higher student loan balances (Pinto & Mansfield, 20 06). Factors that are likely to contribute to whether a student is financially at risk include: gender; ethnicity; being a graduate student; being financially independent; receiving financial assistance; owing other debt; and the manner in which credit car ds are acquired (Lyons, 2004). For example, not having the financial knowledge or capabilities necessary to open a bank account cost the average American $86.83 a month and more than $40,000 over there life time on check cashing costs (Pew Charitable Trus t, 2009; President Bill Clinton and California Gov. Arnold Schwarzenegger, 2008) Not understanding credit is even riskier because credit involves fees and compounding interest.

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31 At the collegiate level research continues to show, that parents give out mo re information provided by parents to students is related to lower credit card ba lances credit cards before college are more responsible when it comes to credit usage (Munro & Hirt, 1998). This finding illustrates the relationship between financial so cialization demonstrated that even imagined interactions by the college students with their parents the number of credit the significance of having access to positive financial social learning opportunities such as being able to engage in social learning conversation s or observations. Financial socialization provided by parents early on and the opportunity for students to model negative messages provided by other socialization agent s. Summary Prior research has shown that social learning theory can be used to examine financial behaviors and financial decision making. Further, differences between groups when analyzing social structural variables have been shown to be related to di fferences in financial social learning opportunities and perceived norms (Garrison & Gutter, 2010). Similar research is needed on the social structural variable differential location to answer the following questions:

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32 Q 1 : Is there a difference in observed financial social learning opportunities between groups of college students with differential social location? Q 2 : Is there a difference in opportunities for financial social learning conversations between groups with differential social location? Q 3 : Is there a difference in perceived norms of risky credit card behavior between groups as defined by their differential social location? Q 4 : What is the nature of the relationship between social learning opportunities and risky credit card behavior? Q 5 : Does differential location moderate the relationship between social learning opportunities and risky credit card behavior? This study will expand on prior research by looking at whether or not personal financial social learning opportunities will still differ between groups when a specific behavior, risky credit card behavior, is considered and differential location is the moderator. In order to examine this relationship in detail the following hypothesis will be tested. Ha1: Observed financial social learnin g opportunities will differ between students based on their differential location. Ha 2 : Opportunities to engage in financial social learning conversations will differ between students based on their differential location. Ha 3 : Perceived norms of parent will differ based on differential location. Ha 4 : Differential location will be positively related to risky credit card behavior. Ha 5 : Differential location will serve as a moderator between the social learning opportunities and risk y credit card behavior. Understanding what, if any, differences social structural variables mediate is a step towards understanding differences in social learning opportunities and their relationship to financial behavior. Having a grasp of how these d ifferences vary among groups of individuals has implications for public policy, financial education, and

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33 found to be related to financial behaviors policies may n eed to focus on providing more positive social learning opportunities for individuals or certain groups of individuals, as appose oppose to just restricting the behavior of financial institutions. For now, financial socialization is seen as primarily the responsibility of parents. By separating the components of the social learning opportunities measure (social learning conversations, social learning observations, and perceived norms) it allows for r to be seen. This will allow for future financial education materials and messages to be developed and presented in order to help parents provide the most meaningful financial social learning opportunities for their children.

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34 Figure 2 1 Model of theory of planned behavior

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35 Figure 2 2. Model of social learning theory

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36 CHAPTER 3 METHODS Sampling and Data Collection This study uses a 15 campus, data set of college students that attend lar ge public universities collected by Gutter, Copur, and Garrison (2009). The original data was collected as part of a study that looked at the impact of financial education on financial behaviors. Participants in the original study were selected using stra tified random sampling. First the states were selected for participation and then large state universities from selected states participated. Participants for the study had to be currently enrolled in the selected universities and over 18 years of age. The study was conducted using online sur obtained from participating universities. The student who completed every one thousandth survey received a $100 gift card. There were 16,876 participants which was a 10.22% respo nse rate from college students who were invited to participate in the study (Gutter, Copur, & Garrison, 2009; Garrison & Gutter, 2010). In order to use the data collected by Gutter and Garrison (2009). I filed IRB 02 to request permission to use their dat a. This study uses a cross sectional research design. Groups are based on the independent variable of differential location Differential location is indicated by the stud they receive need based aid /Pell grants or the y do not receive need based aid or Pell grants). While the original sample consisted of 16,876 participants; students that went to high school in other countries were excluded from the final sample, as cultural factors could impact family based social lear ning opportunities. After excluding students from other countries the sample included 12,658 students. Only students who responded to

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37 included in the final sample. This sample consisted of 12,658 student of these student 2,830 receive needs based aid and 9,828 do not. The sample was composed of 34.1% males and 65.9% females. Of the students sampled 82.5% of white (non Hispanics), 4.5% African Americans, 5.8% Hispanics, a nd 7.3% of students from other ethnicities. The average age of the students sampled was 21.31 years. Independent Variables Descriptive Statistics Sex, age, and race were included in the analysis to look at differences that exist between Pell and Non Pe following best describes your race/ethn of the following categories, White, African American, Hispanic, Asian American, Asian, Native American, and other (please specify). Differential Location Differential location is a measure of socioeconomic s tatus (Durkin, Wolfe, and Clark, 2005, and Lee and Akers, 2004) Receiving a Pell grant is used as an indicator of differential location in this study because being a Pell grant recipient is based off of a formula that takes several indicators of socioecon omic status into consideration. To find s seven categories: None Federal Stude nts Loans (i.e. Stafford) Federal work study Need based grants (i.e. Pell) scholarships tuition wavier and other For

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38 based grants status (i.e. Pell status) is used as an indicator of diffe rential location. As Federal aid is awarded based on expected family contribution. Students who check ed needs based grants (i.e., Pell ) are considered Pell students. Students who did not check Pell, but checked any other type of financial aid or none are classified as non Pell students. Pell status served as an indicator of differential location because the Pell Grant is awarded based on expected family contribution (EFC). EFC serves as a standardizing measure of financial resource availability (Free Appl ication for Federal Student Aid, N.D. a ) and is calculated by a formula and chart ed to determine the students Pell grant award amount. The Pell is the bases of all financial aid; hence students that do not qualify for Pell Grants are considered to have fam ilies who can contribute more to the Federal Student Aid, N.D. b ). Social Learning Opportunities (Observed) Social learning opportunities are based on observations, conver sations, and perceived norms of financial opportunities. Students were asked to respo nd to seven items that asked about specifi c positive financial behaviors. These behaviors included: avoiding over spending checking credit report saving/investing banking maintaining health insurance maintain auto insurance and maintain renters insurance Responses ranged fr om 1(never) to Scores on the seven items were coded so that the range of scores was from 7 to 35 Based on the scale used, lower scores

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39 indicate less frequent observed social learning opportunities or the abil ity to recall observed social leaning opportunities less frequently. The observed social learning opportunities measure used in this study is a portion of the scale used in Gutter, Copur, and Garrison, 2009. This measure breaks the components of social learning into separate areas: social learning conversations, social leaning observations, and perceived norms (Akers, 1998 & Veysey & Messner, 1999). In order to test the correlation of measures used in partial scales a reliability analysis should be run. The higher the alpha value the more reliable the scale. The observed social learning opportunities scale used in this study has a cronbach alpha of .811. This indicates that when just measures o f social leaning observations are taken from Gutter, Copur, and is internally consistent Social Learning Opportunities (Conversations) with your parents/caregivers items that asked about specific positive financial behaviors. These behaviors included: avoiding over spending checking credit repor t saving/investing banking maintaining health insurance maintain auto insurance and maintain renters insurance option. Scores on the seven items were added so that the rage of scores was between 7 and 35. Based on the scale used, lower scores indicate less frequent observed social learning opportunities or the ability to recall observed social leaning opportunities less frequently.

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40 The social learning conversation s measure used in this study similar to the social learning observations measure is a portion of the scale used in Gutter, Copur, and Garrison, 2009. The observed social learning opportunities scale has a cronbach alpha of .808. This indicates that when j ust measures of social leaning observations are taken from revised scale is internally consistent. Perceived Norms of the following respond to six items that asked about specific risky credit card behaviors. These behaviors included: using your credit card for everyday expenses, maxing out credit cards, making late payments, going over the credit limit, not paying down balances monthly, and over drafting. Responses ranged from 1(Always) to 5 (Never), and sample. Responses ranged from 1 (Always) to 5 Scores on the six items were coded so that the ranges of scores were from 6 to 30. Higher scores ind icate norms that are less favorable to RCB. The observed perceived norms measure used in this study is also a portion of the scale used in Gutter, Copur, and Garrison, 2009. The perceived norms scale has a cronbach alpha of .812. This indicates that when just measures of perceived norms are combined into a scale the scale is internally consistent.

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41 Dependent Variables Risky Credit Card Behavior For the purpose of this study only the items that pertained specifically to risky credit card behavior were includ ed. These behaviors included: maxing out credit cards, making late payments, not paying your balance in full, and having credit a credit card balance of $1 000.00 or more. many time you did each of the following during if you do not have credit cards in your own name. Students that do not have any credit cards in their name were excluded from the sample. Students we re then asked to respond to three items that asked about specific financial behaviors (maxed out their credit, been delinquent, and do not pay off balance). Responses ranged from 0(never) to 3 (often), corded (0=0, 1 3=1, 4=0, and system missing= system missing). Students were also asked Think about all the credit cards you have. What is the total amount you currently owe on all of your credit cards? RCB. The RCB variable was recorded on an ordinal scale (0=0, 1 3=1, and system missing= system missing) to (0=no, 1=yes, and system missing= system missing ) to a binary variable. Students either engage in risky credit behavior or they do not. Students wh o scored 1 or more are counted as engaging in risky credit card behavior. For the purpose of this study s tudents had to receive a score of 0 to be considered not engaging in risky credit card behavior. The additional credit card balance of $1,000 or mo re behavior was added to the

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42 consistently identified credit misuse and/or mismanagement according to four having credit card balances of $1,000 or more, being delinquent on credit card payments by two or more months, having reached the limit on credit cards, and only paying off their cr edit card credit card behaviors independently. For the purpose of this study the four characterizes were combined into a binary variable where students were looked as engag ing in risky credit card behavior or not because considering each of the behaviors cumulatively was not shown as significant (Appendix C). The cronbach alpha for the Risky Credit Card Behavior (RCB) scale used in this study is .806. A nalysis Initially chi squared analysis will be run to look for significant d ifference s between the Pell and Non Pell groups on the variables sex, age, and race. This will be followed by a p reliminary exploration of the research questions This will include simple bivariate co mparisons employing independent sample t test examine whether or not the financial social learning opportunities and perceived norms of the sample, differed by differential location (Hypotheses 1, 2, 3). Ha1: Observed financial social learning opportuniti es will differ between students based on their differential location. H a 2 : Opportunities to engage in financial social learning conversations will differ between students based on their differential location. Ha 3 : Perceived norms of will d iffer based on differential location.

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43 L ogistic regression will be used to test hypothesis 4. Logistic regression was chosen because the dependent variable is binary (Either students do not engage in RCB= 0 or students engage in RCB= 1). The reduced model will look at the odds of a student not engaging in RCB (RCB=0) and the odds of a student engaging in RCB (RCB=1) based on differential location. Ha 4 : Differential location will be positively related to risky credit card behavior. The foll owing independent variables were included in the reduced model: social learning observations, social learning conversations, perceived norms, and differential location. The demographic variables age, race, and gender were included in the regression model as control variables as prior studies have shown that these variables are related to social learning opportunities (Gutter, Copur, & Garrison, 2009; Gutter Copur & Garrison 2010; Garrison & Gutter, 2010). Due to the dependent variable being binary logisti c regression is the analysis of choice Linear regression works based on two key assumptions: the variance of RCB (y) is constant across all values of the independent variables (x) and the predicted values of RCB are normally distributed; however these as sumptions are impossible when the values for the dependent variable are binary and must take on a value of either 0 or 1. Logistic regression does not require the predicted values of RCB to be normally distributed, instead logistic regression looks at the odds of RCB occurring under the circumstances of the independent variables. Logistic regression will also be used to test hypothesis 5. The full model will look at whether or not differential location serves as a moderator for social lea r ning on risky cr edit card behavior. The full model will take into account all the variables in the

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44 reduced model (age, race, gender, social learning observations, social learning conversations, perceived norms, and differential location) and 3 new variables (Pell status* social learning conversations, Pell status* social learning observations and Pell status* perceived norms his/her social learning opportunities. Ha 5 : Differential location will serve as a mo derator between the social learning opportunities and risky credit card behavior. Once both the reduced and the full models have been tested the likelihood ratio will be calculated to compare the fit of the two models. The reduced model test whether th ere is a relationship between social learning and RCB when the independent variables are taken into account. The full model will test whether there is a relationship between social learning and RCB when differential location is treated as a moderating var iable. The likelihood ratio test will determine if the full model where differential location than the reduced model.

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45 Table 3 1. Summary of variables in reduced model Dependent Variables Independent Variables Risky Credit Card Behavior Differential Location Engages in risky credit card behavior Pell recipient Does no engage in risky credit card Behavior Non Pell recipient Social Learning Conversations Managi ng expenses Checking credit report Paying bills on time Saving and investing money Working with mainstream Financial Institution Buying Health Insurance Buying auto insurance Buying renters insurance Social Learning Observations Managi ng expenses Checking credit report Paying bills on time Saving and investing money Working with mainstream Financial Institution Buying Health Insurance Buying auto insurance Buying renters insurance Perceived Norms Use credit cards for everyday expenses Make late payments on cards Go over credit limit Do not fully pay off their monthly credit card bills Overdraw their checking account Sex Male Female Age Please indicate your a ge Race White (Non Hispanic) African America (Black) Hispanic Other

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46 Table 3 2. Summary of variables added to reduced model to form full model Dependent Variables Independent Variables Pell Status* Social Learning Conversations Managing expenses Checking credit report Paying bills on time Saving and investing money Working with mainstream Financial Institution Buying Health Insurance Buying auto insurance Buying renters insurance Pell Status* Social Learning Observatio ns Managing expenses Checking credit report Paying bills on time Saving and investing money Working with mainstream Financial Institution Buying Health Insurance Buying auto insurance Buying renters insurance Pell Status* Perceived Norm s Use credit cards for everyday expenses Make late payments on cards Go over credit limit Do not fully pay off their monthly credit card bills Overdraw their checking account

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47 Figure 3 1. Reduced social learning model test

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48 Figure 3 2 Full social learning model tested with reported betas and odds

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49 CHAPTER 4 ANALYSIS Analysis This chapter will discuss describe the relationship between the independent variables and dependent variable. The results of the proposed hyp othesis testing in Chapter 3 will be discussed. Descriptive statistics of the sample were run focusing on the variables age, race, and sex. Hypotheses 1, 2, 3 were tested using simple bivariate comparisons employing independent samples t test. Hypothesis 4, what is the relationship between risky credit card behavior, observed social learning opportunities, social learning opportunities differentially reinforce through verbal communication, perceived norms, and differential location are related will be tes ted using a multinomial logistic regression. Bivariate Analysis Independent Variables Descriptive Statistics The Pell versus the Non Pell groups (differential location) were compared based on the variables age, sex, and race. The variable age was compare d by differential location (Pell or Non Pell status) using an independent sample t test. Non Pell students had an average social learning observations score age of 21.27 and Pell students had an average age of 21.46 ( t = 1.964, p =.050).The results of the t test showed significant differences when comparing the frequency of social learning observations by differential location. The variables sex was compared by differential location (Pell or Non Pell status) using chi squared. The chi squared test statistic is 7.089 with a p value of .008. The

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50 results of chi squared test show that need based grants and gender are dependent. A higher percentage of females (65.9%) than males (34.1%) sampled receive Pell grants. The race variables (White, Black, Hispanic, Other ) were compared by differential location (Pell or Non Pell status) using chi squared. The chi squared test statistic is 431.224 with a p value of .000. The results of chi squared test show that need based grants and race are dependent. Further, a larger pr oportion of whites (non Hispanics) (70.6%) sampled receive Pell grants than African Americans (9.7%), Hispanics (10.2%), and of people surveyed from other ethnicities (9.31%). Social Learning Opportunities Non Pell students had an average social learning observations score of 27.510 and Pell students had a mean score of 25.192 ( t = 6.428, p=.000).The results of the t test show a significant difference between the average frequencies that Pell versus Non Pell students have observed their parents engagin g in positive financial behaviors. For Non Pell students the social learning conversations mean score was 22.21. For Pell students the mean score was 21.23 ( t = 5.570, p=.000). The results of the t test show a significant difference between the average frequencies that Pell versus Non Pell students have talked with their parents about engaging in positive financial behaviors. The average perceived norms score for Non Pell students was 10.492. The mean score for Pell students was 11.211 ( t = 6.428, p=.00 0). Pell students think their parents engage in risky credit card behaviors more frequently than Non Pell students.

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51 Dependent Variable Risky Credit Card Behavior Chi squared was use to test whether RCB is independent or dependent of The asymptotic significance is 0.000 which is less than .05 indicating that Pell or Non Pell status and risky credit card behavior are dependent ( =149.847, df =1, p =.000). Risky credit card behavior is not distributed equally between Pell and Non Pell status. Further, the contingency table showed a higher percentage of Pell recipients sampled engage in risky credit card behavior than Non Pell stud ents sampled. Multivariate Analysis: Logistic Regressions Reduced Model Logistic Regression Hypothesis 4: Differential location will be positively related to risky credit card behavior was tested using logistic regression The relationship between age, race, gender, social learning observations, social learning through conversations, and perceived norms on risky credit card behavior is analyzed using logistic regression analysis. Demographics The following demographic variables were entered into the mod el: age, sex, Pell status, race. For the variable age beta ( ) is .157 with a p value of .000. Age is positively related to RCB, so as the student gets older he or she is more likely to participate in risky credit card behavior. For the variable sex is .258 with a p value of .000 indicating that being female is positively related to risky credit card behavior; in other words, females are more likely than males (who served as reference gender in the analyses) to participate in RCB. When compared to W hites (reference group in the analyses) Blacks and Hispanics are more likely to engage in RCB. For the variable of

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52 RCB regressed on Pell status/need based aid, is .569 with a p value of .000. This result indicates that students who have need based fina ncial aid more likely engaged RCB. The variable race used in the initial survey was separated out by ethnicity for analysis in to three groups: African American, Hispanic, and Other (including American Indian, Asian, and any other identified ethnicity). Whites (Non Hispanics) were used as the reference group. For the variable Race African American is .729 with a p value of .000. For the variable Race Hispanic is .617 with a p value of .000. For the variable Race Other is .254 with a p value of .1. Race African American, Race Hispanic, and Race Other are all related to RCB. Social learning opportunities For NRCB to RCB, the Wald test statistic for the predictor social learning observations is 14.341 with a p value of .000. As the frequency of su social learning observations increase, RCB would be expected to decrease by .014. It can be concluded that social learning observations are negatively related to engaging in RCB. For NRCB to RCB, the Wald test statistic for the predic tor social learning conversations is 3.362 with a p value of .067. is .008. As the frequency of survey participants social learning conversations increase, the RCB would be expected to increase by .008. It can be concluded that social learning conversati ons are positively related to engaging in RCB. For RCB to NRCB, the Wald test statistic for the predictor perceived norms of parents is 186.603 with a p

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53 engagement in risky credit card behavior increase t expected to increase by .088. It can be concluded that perceived norms are positively related to RCB. Needs based aid equals zero For NRCB to RCB, the Wald rest statistic for needs based aid equals zero is 79.669 with a p value of .000. decreases) engaging in RCB would be expected to increase by .569. It can be concluded that receiving needs based aid is positively related to RCB. Full Model Logistic Regression Hypothesis 5: Differential location will serve as a moderator between the social learning opportunities and risky credit card behavior was also tested using logistic regression. To test whether family financial strength acts as a moderator the following variables we re added into the regression equation: Pell status*Social learning observations, Pell status*social learning conversations, Pell status*perceived norms. Pell statu s*Social learning Opportunities For RCB to NRCB, the Wald test statistic for the predictor s ocial learning observations is .395 with a p is considered and the frequency of survey participants social learning observations decrease, the log odds of not engaging in RCB over engaging in RCB w ould be expected to decrease by indicated by receipt of needs based aid) is not a significant moderator of social learning observations and RCB.

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54 For NRCB to RCB, the Wald test statistic for th e predictor social learning conversations is .050 with a p aid is considered and the frequency of survey participants social learning conversations increase, the log odds of engaging in RCB over engag ing in RCB would be expected to receipt of needs based aid) status is not significant moderator of social learning conversations and RCB. For RCB to NRCB, the Wald test s tatistic for the predictor perceived norms of parents is 6.153 with a p g odds of engaging in RCB would be expected to decrease by indicated by receipt of needs based aid) is positively related to and is a significant moderator of social learning conversatio ns and RCB. Likelihood Ratio test While not all of the social learning opportunity measures were found to be considered the full model may still be a better fit that the model that does not consider differential location as a moderator. In order to compare the fit of the null (reduced model) and the full (alternative) model a likelihood ratio test was conducted. The likelihood for the null model is 8324.524. The like lihood for the full model is 8317.638. The test statistic is .0016. The test statistic is not significant at .05. Do not reject H 0 The reduce model (where receipt of Pell is not considered a moderator) is a better predictor than the full model.

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55 Tabl e 4 1. Sample profile by differential location Mean/Proportion Variable Non Pell Pell Significance Test Sex Male 34.7% 32.0% = 7.089 Female 65.3% 68.0% 2 = 7.089 Race White 81.4% 18.6% 2 =299.502*** Black 55.2% 44.8% 2 =280.343*** Hispanic 63.7% 36.3% 2 =123.146*** Other 76.1% 23.9% 2 = 6.811** RCB Do not engage in any RCB 60.8% 43.9% 2 =186.648*** Engage in at least 1 RCB 39.2% 56.1% 2 =186.648*** Age 21.27 21.46 1.964* Social Learning Opportunities Social Learning C onversations 22.214 22.232 5.646*** Social Learning Observations 27.510 25.192 11.777*** Perceived Norms 10.492 11.211 6.428*** p <.05,** p <.01,*** p <.001 Table 4 2.Reduced model differential location and risky credit card behavior Variable W ald SE Odds ratio Sex(Female) .258*** 20.394 .057 1.245 Race (whites used as reference group) Black .729*** 25.373 .137 1.758 Hispanic .617*** 30.095 .109 1.819 Other .254** 6.631 .098 1.208 Age .157*** 353.584 .008 1.170 Pell Status .569*** 79. 669 .064 1.767 Social Learning Opportunities Social Learning Conversations .008 3.362 .004 1.012 Social Learning Observations .014*** 14.341 .004 .986 Perceived Norms .008*** 186.603 .006 1.099 p <.05,** p <.01,*** p <.001

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56 Table 4 3.Full Mod el d ifferential location moderating risky credit card behavior Variable Wald SE Odds ratio Sex .256*** 20.064 .057 1.292 Race (whites used as reference group) Black .723*** 24.943 .145 2.060 Hispanic .615*** 29.941 .112 1.850 Other .251 6.4 87 .099 1.285 Age .170*** 356.560 .009 1.186 Social Learning Opportunities Social Learning Conversations .012 181.300 .008 1.106 Social Learning Observations .013*** 8.829 .005 1.008 Perceived Norms .100*** 154.421 .008 .987 Pell Status 1.13 3 18.135 .266 3.104 Social Learning Opportunities Pell Status Social Learning Conversations* Pell status .002 .050 .010 .998 Social Learning Observations* Pell status .006 .395 .009 .994 Perceived Norms .033* 6.153 .013 .967 Likelihood Ratio test for full versus reduced model D= 18.134*** p <.05,** p <.01,*** p <.001

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57 Figure 4 1. Reduced model tested with betas and odds ratios

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58 Figure 4 2.Full m odel with betas and odds ratios

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59 CHAPTER 5 CONCLUSION AND IMPLI CATIONS Conclusion Di fferential Location and Social Learning Observations Hypothesis 1 stated that o bserved financial social learning opportunities will differ between students from families with lower family financial strength and students who have gr eater family financial st rength. The results for the test and the t test indicate that there is a difference between families with lower family financial strength and student who have greater family financial strength. It can be concluded that opportunities to observe positiv e financial behaviors are not the same for students who receive Pell and students that do not receive Pell grants. Students that do not receive Pell grants observe their parents engaging in positive financial behaviors on average more frequently than stude nts who receive Pell grants. Differential Location and Social Learning Conversations Hypothesis 2 stated that opportunities to engage in financial social learning conversations will differ between students from families with lower family financial strength and students who have gr eater family financial strength. The results for the test and the t test indicate that there is a difference between students who receive Pell grants and students who do not receive Pell grants. It can be concluded that the fre quency of opportunities for conversations about positive financial behaviors is not the same for students who receive Pell grants and students who do not. Students that do not receive Pell grants discuss with their parents positive financial behaviors on a verage more frequently than students who receive Pell grants.

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60 Differential Location and Perceived Norms Hypothesis 3 stated p erceived norms of individuals from families with lower family financial strength will differ from students who have greater family financial strength. The results for the test and the t test indicate that there is a difference between families with lower family financial strength and student who have greater family financial strength. It can be concluded that the perceived norms a bout risky credit card behaviors is not the same for students that receive Pell grants and students that do not receive Pell grants. Students who receive Pell grants are on aver more likely to perceive their parents engage in risky credit card behavior. Di fferential Location and RCB Hypothesis 4 stated differential location will be positively related to risky credit card behavior. The results from the test indicate that family financial strength is positively related to risky credit card behavior. It can be concluded that as reliance on needs based assistance increases risky credit card behavior will increase. Differential Location as a moderator between social learning and RCB Hypothesis 5 stated differential location will served as a moderator between the social learning opportunities and risky credit card behavior. In the full model once differential location was taken into account the only soci al learning opportunities measure significantly related to RCB was perceived norms. The likelihood ratio test showed the reduced model was a better fit than the full model. Hence it can be concluded that differential location does not serve as moderator between social learning and RCB. Other facts such as race or gender may in fact play a more significant role in this relationship.

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61 Discussion and Findings The findings of this research are interesting because this study takes a closer look at the social l earning opportunities measure used in prior research. This study looked individually at each of the three components of the social learning measure and their relationship on risky credit card behavior: social learning conversations, social learning observa tions, and perceived norms. Social learning opportunities were found to be significantly different for Non Pell and Pell student. This indicates that additional knowledge and awareness of positive financial practices maybe need by families with lower finan cial strength. Additionally, similar to prior research (Gutter & Garrison, 2008) social learning opportunities specifically perceived norms were found to be related to RCB. By breaking down the traditional social learning opportunities measure into its three components we are able to see how each component affects financial social learning. When differential location was introduced in to the model the social learning opportunities measures did not perform as expected. While social learning observations and conversation were significant before differential location (family financial strength) was introduced they were not significant once differential location was introduced. Perceived norms was the only social learning opportunities measure to still show up as significant once differential location was taken into consideration. This indicates that less frequent social learning observation and conversations about positive behaviors may be related to an increase perceived norms in favor of risky credit ca rd behavior. Further, this study reconfirms the significance of perceived norms with regards to engaging in risky credit card behavior.

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62 Implications Currently financial socialization is seen as primarily the responsibility of parents. Based on the finding of this study, financial socialization by parents alone may not be sufficient. Students from lower income families appear to have been exposed to financial socialization opportunities from parents less frequently than students from families with greater financial strength. One of the main ways that parents can assist their children with financial socialization is by being aware of the importance of talking with their children about money and the frequency with which they talk to their children about money and risky credit card behaviors. If parents realize that they infrequently speak with their children about money they can try to create more opportunities to talk with their children about money. As some parents may not be knowledge about various financia l topics they themselves can seek out additional information and resources and discuss the information they receive with their children. For students that receive needs based grants/aid one of the first steps to avoiding risky credit card behavior knows th at they may be at risk. These students can seek out additional financial social learning opportunities from their parents. If parents are unable to provide financial guidance student can and should consider taking a class on personal finance to increase their capabilities. Practitioners can target more programming towards families with lower financial strength. They can increase marketing of these programs in low to moderate income communities. Additionally they can partner with college campus to deliv er additional financial training to incoming freshman.

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63 Additional research is need on financial socialization and the social learning opportunities components. It would be interesting to see if Pell status would moderate or fail to moderate social learni ng opportunities when other financial behaviors are considered.

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64 APPENDIX A SURVEY QUESTIONS This appendix contains the survey question used in this study. The original questions are from a much large data set on Financial Management Practices of College Students form States with Varying Financial Education Mandates. 2.1 Question: What Is your current age? (open ended) 2.4 Question: Which of the following best describes your race/ethnicity? White African American Asian Native American Other (please spe cify) 2.5 Question: What sex are you? Male Female 3.7 Question: What types of financial aid, if any, are you currently receiving? (Check all that apply.) None Federal student loans (i.e. Stafford) Federal work study Need based grants (i.e. Pell) Scholar ships Tuition Wavier Other (please specify) 8.1 Question: How often did your parents/ caregiver discuss each of the following with you in the past five years? Managing expenses and avoiding overspending Checking credit report Paying bills on time Saving and investing money Working with a mainstream financial institution like a bank or credit union (as opposed to payday lenders) Buying and maintaining health insurance Buying and maintaining auto insurance Buying and maintaining renters insurance

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65 9.1 Quest ion: How often have you observed your parents/caregivers involved in the following during the past five years? Managing expenses and avoiding overspending Checking credit report Paying bills on time Saving and investing money Working with a mainstream fina ncial institution like a bank or credit union (as opposed to payday lenders) Buying and maintaining health insurance Buying and maintaining auto insurance Buying and maintaining renters insurance 13.1 How often do you think your parents do each of the fol lowing (only choose N/A if your parents have no credit cards)? Use credit cards for everyday expenses Make late payments on their credit cards Go over the credit limit on their credit cards Do not fully pay off their monthly cr edit card bills Overdraw their checking account 15.4 Think about all the credit cards you have. What is the total amount you currently owe on all of your credit cards? $0 (I do not owe any money on my credit cards.) $1 $499 $500 $999 $1,000 to $2,999 $ 3,000 $4,999 $5,000 or more Not sure 15.8 Think about your own typical behaviors. Indicate how many times you did each of the following during the last year. Only choose N/A if you do not have credit cards in your own name. Mak e late payments on your credit card Do not pay off your credit card balance fully each month

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66 APPENDIX B VARIABLE CODING Variable Coding Risky Credit Card Behavior Sum of indicators is 0=None, Any 1 0=None, Any=1 Make la te payments on cards 0=None, Any=1 Do not fully pay off their monthly credit card bills 0=None, Any=1 Balance of $1000 or more 0=999.99 or less, 1=$1000 or more Credit Card Balance $999 or less =0, $1000+ = 1 Differential Location 0= Non Pell reci pient ,1= Pell recipient Social Learning Conversations Sum of Scale Scores Managing expenses Scale Score Checking credit report Scale Score Paying bills on time Scale Score Saving and investing money Scale Score Working with mainstream Financial Institution Scale Score Buying Health Insurance Scale Score Buying auto insurance Scale Score Buying renters insurance Scale Score Social Learning Observations Sum of Scale Scores Managing expenses Scale Score Checking credit report Scale Score Pay ing bills on time Scale Score Saving and investing money Scale Score Working with mainstream Financial Institution Scale Score Buying Health Insurance Scale Score Buying auto insurance Scale Score Buying renters insurance Scale Score Perceived Norm s Sum of Scale Scores Use credit cards for everyday expenses Scale Score Scale Score Make late payments on cards Scale Score Go over credit limit Scale Score Do not fully pay off their monthly credit card bills Scale Score Ov erdraw their checking account Scale Score Sex 0=Male, 1= Female Age Scale Score

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67 Variable Coding Race(Reference= White Non Hispanic) African America (Black) 0=all other races, 1= African American(Black) Hispanic 0= all other races, 1= Hispanic Ot her 0=White, African American, Hispanic; 1= Other Pell Status* Social Learning Conversations 0= Non Pell, Scale Score*1=Pell Managing expenses Scale Score Checking credit report Scale Score Paying bills on time Scale Score Saving and investing money Scale Score Working with mainstream Financial Institution Scale Score Buying Health Insurance Scale Score Buying auto insurance Scale Score Buying renters insurance Scale Score Pell Status* Social Learning Observations 0= Non Pell, Scale Score*1=P ell Managing expenses Scale Score Checking credit report Scale Score Paying bills on time Scale Score Saving and investing money Scale Score Working with mainstream Financial Institution Scale Score Buying Health Insurance Scale Score Buying auto insurance Scale Score Buying renters insurance Scale Score Pell Status* Perceived Norms 0= Non Pell, Scale Score*1= Pell Use credit cards for everyday expenses Scale Score Scale Score Make late payments on cards Scale Score Go over credit limit Scale Score Do not fully pay off their monthly credit card bills Scale Score Overdraw their checking account Scale Score

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68 AP P ENDIX C RCB CUMULATIVE MEASU RE Table C 1 Reduced Model OLS regression of RCB Variables Estimate SE Wald Fo ur risky credit card behaviors (0 = Reference) 6.185*** .203 926.717 Three risky credit card behaviors 4.848*** .194 626.752 Two risky credit card behaviors 3.745*** .189 392.166 One risky credit card behaviors 2.701*** .186 209.788 Age .084*** .0 06 228.477 Differential Location .485*** .057 73.325 Sex Female (Male Reference) .192*** .050 14.444 Race African American (White reference) .666*** .124 28.960 Race Hispanic .532*** .101 28.049 Race Other .189* .089 4.491 Perceived Norms .089* ** .006 250.695 Social Learning Conversations .014*** .004 13.923 Social Learning Observations .017*** .003 25.211 p <.05,** p <.01,*** p <.001 Table C 2. Full Model OLS regression RCB Variables Estimate SE Wald Four risky credit card behaviors (0 = Ref erence) 6.294*** .215 854.633 Three risky credit card behaviors 4.957*** .206 577.114 Two risky credit card behaviors 3.854*** .202 363.607 One risky credit card behaviors 2.809*** .200 198.180 Age .084*** .006 228.831 Differential Location .838 *** .229 13.360 Sex Female (Male Reference) .190*** .229 13.360 Race African American (White reference) .657*** .124 28.101 Race Hispanic .532*** .124 28.101 Race Other .186* .089 4.346 Perceived Norms .095 .007 181.815 Social Learning Conversat ions .012** .004 8.575 Social Learning Observations .014*** .004 13.368 Pell status* Perceived Norms .014 .008 2.970 Pell status* Social Learning Conversations .008 .009 .888 Pell status* Social Learning Observations .016 .011 2.043 p <.05,** p <.01,* ** p <.001

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69 Table C 3. Variable Coding of RCB Cumulative Variable Coding Risky Credit Card Behavior Sum of indicators is 0=None, Any 1 0=None, Any=1 Make late payments on cards 0=None, Any=1 Do not fully pay off their monthly cre dit card bills 0=None, Any=1 Balance of $1000 or more 0=999.99 or less, 1=$1000 or more ***All other variables coded the same as in original model (appendix b)

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70 LIST OF REFERENCES Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Beha vior and Human Decision Process, 50, 179 211 Akers, R.L. (1998). Social Learning and Social Structure: A General Theory of Crime and Deviance. Boston: Northeastern University Press. Akers,R., Krohn,M, Lanza Kaduce,L.,& Radosevich, M. (1979). Social Learni ng and Deviant Behavior: A Specific Test of a General Theory. American Sociological Review 44(4) 636 655. Armitage, C., & Conner, M. (2001). Efficacy of the theory of planned behavior: A meta analytic review. British Journal of Social Psychology. 40, 471 499 Bandura, A. (1977). Social Learning Theory. New York: General Learning Press. Bandura, A. (1997). Self efficacy: The Exercise of Control New York: Freeman. Brendtro, L. (2006). The Vision of Urie Bronfenbrenner: Adults Who Are Crazy about Kids. Rec laming Children and Youth: The Journal of Strength based Interventions. 15(3), 162 166 Bobek, D., Hatfield, R., & Wentzel, K. (2007). An Investigation of Why Taxpayers Prefer Refunds: A Theory of Planned Behavior Approach. Journal of the American Taxation Association 29(1), 93 111 Bursik, R. (1988). Social Disorganization and Theories of Crime and Delinquency: Problems and Prospects. Criminology. 26(4) 519 552 Bursik, R. and Grasmick, H. (1996). Use of Contextual Analysis in Models of Criminal Behavior. Ca mbridge University Press: New York. College Board. (2009). What it Cost to Go to College. Retrieved from http://www.collegeboard.com/student/pay/add it up/4494.html Contu, A., & W illmott, H. (2003). Re embedding situatedness: The importance of power relations in learning theory. Organization Science, 14 (3), 283 296. Draut,T. & Silva, J. (2004). Generation Broke: The Growth of Debt Among Young Americans. Retrieved 20 October 2010 fr om http://www.caseyfoundation.net/upload/PublicationFiles/FE3679K542.pdf Durkin,K., Wolfe,T., Clark, G. (2005). College Students and Binge Drinking: An Evaluation of Soc ial Learning Theory. Sociological Spectrum 25(3), 255 272

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71 Dursun, Y. (1993). Kayseri: Erciyes University, The Institute of Social Sciences Doctorate Thesis. ore. Retrieved 20 October 2010 from http://www.myfico.com/CreditEducation/WhatsInYourScore.aspx Federal Student Aid. (2009). The EFC Formula 2008 2009. Retrieved from http://www.ifap.ed.gov/eannouncements/attachments/0809EFCFormulaGuide.pd f Frayne,C. & Latham, G. (1987). Application of Social Learning Theory to Employee Self Management of Atte ndance. Journal of Applied Psychology 72(3):387 392 Free Application for Federal Student Aid. (N.D. a ). Expected Family Contribution. Retrieved from http://www.fafsa.ed.gov/help/fftoc01g.htm Fr ee Application for Federal Student Aid. (N.D. b ). FAQs: Eligibility. Retrieved from Gutter, M, Copur, Z, & Garrison, G. (2009). Which Students are More Likely to Experience Financial Socialization Opportunities? Exploring the Relationship Between Financia l Behaviors and Financial Well Being of College Students. (Working Paper No. 2009 WP 07). Retrieved 20 October 2010 from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1432523 Gutter, M. & Garrison, S. (2008). Perceived Norms, Financial Education, and College Student Credit Card Behavior. Journal of Consumer Education, 24, 73 88 Gutter, M. & Garrison, S. (2010). Gender Differences In Financial Socialization And Willingness To Ta ke Financial Risks. (Accepted for publication in Journal of Financial Counseling and Planning). Gutter, M., Copur, Z., & Garrison, G. (2010). Social Learning Opportunities and the Financial Behaviors of College Students. Family and Consumer Sciences Res earch Journal 38(4), 387 404 Gutter, M.S. & Fontes, A. (2006). Racial Differences in Risky Asset Ownership: A Two stage Model of the Investment Decision Making Process. Financial Counseling and Planning 17(2), 64 78. Hayhoe, C. R., Leach, L. J., Turner P. R., Bruin, M. J., & Lawrence, F. C. (2000). Differences in spending habits and credit use of college students. Journal of Consumer Affairs, 34 (1), 113 133.

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72 Hayta, A. (2009). Socialization of the Child as a Consumer. Family and Consumer Science Resear ch Journal. 37(2), 167 184 Hoyer & Macinnis. (2009). Consumer Behavior. (pp. 397). South Western Cengage learning. HR 627: Credit Card Accountability Responsibility and Disclosure Act of 2009, Pub. L. No. 111 24, §301 305 Jumpstart. (2006). State financi al Education requirement. Retrieved March 10 from http://www.jumpstartcoalition.org/state_legislation/index.cfm?stnm=colorado Lin, H. (2007). Predicting consumer in tentions to shop online: An empirical test of competing theories. Electronic Consumer Research and Application, 6:433 442 Liska, A. (1984). A Critical Examination of the Causal Structure of the Fishbein/Ajzen Attitude Behavior Model. Social Psychology Quarterly 47(1), 61 74 Lusardi, A. & Michell, O. (2007). The Importance of Financial Literacy: Evidence and Implications for Financial Education Programs Retrieved from http://www.dartmouth.edu/~alusardi/Papers/PolicyBrief_lusardi.pdf Lyons, A. (2004). A profile of financially at risk college students. The Journal of Consumer Affairs 38 (1), 56 80 Maital and Maital, 1977 S. Maital and S.L. Maital, Time preference delay and gratification and the intergenerational transmission of econom ic inequality: A behavioral theory of income distribution. In: O. Ashenfelter and W.E. Oates, Editors, Essays in labor market analysis in memory of Yochanan Peter Comay ( pp. 179 199 ). New York (1977) Otte, E. & Rousseau, R. (2002). Social Network Analysis : A Powerful Strategy, also for the Information Sciences. Journal of Information Science 28(6), 441 453 Park, H. & Smith, S. (2007). Distinctiveness and Influence of Subjective Norms, Personal Descriptive and Injunctive Norms and Societal Descriptive and Injunctive Norms on Behavioral Intent: A Case of Two Behaviors Critical to Organ Donation. Human Communication Research 33, 194 218 Pew Charatable Trust (2009) Retrieved 2 April 2010 from http://www.pewtrusts.org/ Pinto, M. and Mansfield, P. (2006). Financially At Risk College Students: An Exploratory Investigation or Student Loan Debt and Prioritization of Debt Repayment. NASFAA Journal of Student Financial Aid 35 (2), 22 32

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73 President Bill Clinton and Califor nia Gov. Arnold Schwarzenegger (2008) Retrieved 2 April 2010 from http://online.wsj.com/article/SB120113610711211855.html Rosenstock, I.M., Strecher, V.J., & Becker, M.H., (1988). Social Learning Theory and the Health Belief Model. Health Education and Beh avior 15, 175 183. Rotter, J. B. (1954). Social Learning and Clinical Psychology Prentice Hall. Rutherford, L. & DeVaney, S. (2009). Utilizing the Theory of Planned Behavior to Understand Convenience Use of Credit Cards. Journal of Financial Counseling and Planning, 20(2), 48 63 Sallie Mae (2009). study of usage rates and trends 2009. Wilkes Barre, PA: Author. Sampson,R. & Groves,W. (1989). Community Structure and Crime: Testing Social D isorganization Theory. The American Journal of Sociology 94(4), 774 802. Schwab, Charles. (2007). Charles Schwab Teens & Money 2007 Survey Findings: Insights into Money, Attitudes, Behaviors, and Concerns of Teens. Retrieved 10 October 2010 from http://www.aboutschwab.com/teensurvey2007.pdf Sutherland, Edwin H, and Johan T. Sellin. (1974 /original published 1931). Prisons of tomorrow. Criminal justice in America New York: Arno Press Uni ted College Marketing Services. (2006). College Credit Card Statistics. Retrieved 20 October 2010 from http://www.ucms.com/college credit card statistics.htm US PRIG Education Fund. Th e Campus Credit Card Trap .Washington: 2008 Veysey, B.M. & Messner, S.F. (1999). Further testing of social disorganization theory: An E Journal of Research in Crime and Delinquency, 36 (2), 1 56 74. Xiao, J. & Wu, J. (2008). Completing Debt Management Plans in Credit Counseling: An Application of the Theory of Planned Behavior. Journal of Financial Counseling and Planning. 19(2), 29 45 Xiao, J. (2008). Applying Behavior Theories to Financial B ehaviors in J. Xiao (Ed.), Handbook of Consumer Finance Research (p 69 81). Kingston: Springer Yao, R., Gutter, M.S., & Hanna, S.D. (2005). The financial risk tolerance of Blacks, Hispanics and whites. Financial Counseling and Planning 16 (1), 51 62

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74 BIOGRAPHICAL SKETCH Kristin Jackson graduated from the University of Florida in fall of 2003 with a Bachelor of Arts in criminology with a minor in sociology. In Fall of 2008, she began the Master of Science in Family, Youth, and Community Science. She ha s an interest in non profit organizations and financial planning.