NC_old2172: Behavioral economics and financial decision-making and information management across the lifespan

(Multistate Research Project)

Status: Inactive/Terminating

NC_old2172: Behavioral economics and financial decision-making and information management across the lifespan

Duration: 10/01/2013 to 09/30/2018

Administrative Advisor(s):

NIFA Reps:

Statement of Issues and Justification

Need: Consumers have been facing a multitude of financial pressures resulting from the 2008 global financial crisis. Home owners struggle with alarming levels of foreclosure while the collective student loan burden of $1 trillion has surpassed total credit card debt for the first time in history. Furthermore, aging baby boomers face the critically important decision of the optimal time to file for Social Security retirement benefits. Financial information is complicated and the majority of consumers feel that they lack the adequate knowledge and skills for obtaining and processing the information. In addition, consumers don't realize the influence that psychological factors have on their financial decisions. All of these factors complicate consumer financial decision-making across the life span. Home ownership has long been considered the American dream as well as a key vehicle to building wealth. Since the housing bubble burst, the home ownership rate has dropped from an historical high due to high foreclosure rates. According to Yellen (2011), only 15% of homeowners expect housing prices to increase over the next year, and barely half expect these prices to increase over the next five years. This is due largely to the fall in house prices and the sustained high rate of unemployment. In fact, approximately 4% of mortgages in the United States are currently in foreclosure. Additionally, in another 3% of mortgages, consumers have missed three or more payments (Yellen, 2011).

However, most Americans continue to believe that home ownership is still an essential part of the American dream. Understanding home ownership decisions and making informed financial choices regarding housing have become more critical than ever before. Buying a home is the single largest consumer financial decision that most households make but many consumers often feel that they do not understand the complex financing and housing choices, especially in the current economic conditions. For struggling home owners, refinancing is another important financial decision. With more opportunities to refinance their mortgage to reduce costs, according to the Agency Financial Report (2011), more education and outreach is needed to help consumers understand the process.

Funding education is another financial decision with life-long consequences. Growing education debt has been a problem for young consumers and their parents. According to the Consumer Financial Protection Bureau, student loan debt has surpassed the $1 trillion mark. While the U.S. Department of Education provides more than $150 million in federal student aid each year in the form of grants, work-study and loans for students seeking postsecondary education, approximately 14 million students currently receive federal student aid with the majority receiving federal student loans (Federal Student Aid, 2011). Many students borrow from private, non-governmental sources, on top of their subsidized federal loans. With the high rate of unemployment, the growing student loan burden can be a huge financial strain for many Americans. This can make it challenging to have sufficient cash flows to purchase a home, or even to purchase a car.

Retirement is another milestone that brings complicated financial decisions when deciding the ideal time to claim Social Security benefits. According to Boehner (2012), Social Security will play a critical role in the lives of 56 million beneficiaries and 159 million covered workers and their families in 2012 (Social Security Administration (2012). When to start Social Security benefits is a crucial financial decision for individual recipients that is far more complicated than most retirees understand. Workers are assigned a full retirement age based on their year of birth, with workers born in 1960 and later having to wait until 67 years old. However, workers can elect to take a reduced benefit at an earlier age, as early as age 62. The benefit is permanently reduced for each month benefits are collected prior to the full retirement age. Another important decision is the election of the spousal benefit. The timing and subsequently the level of the benefit will affect the financial well being of a person or couple for their remaining years. Social Security is the most important retirement income source, and accounted for 90% or more of total income for 36% of all beneficiaries in 2010.

In response to these concerns, this project was developed with a goal to better understand consumer financial decision-making across the lifespan. How consumers process information and make decisions regarding housing (rent vs. buy & mortgage), post-secondard education financing, and Social Security retirement will be examined. This research focus fits within the following Financial Literacy and Education Commissions (FLEC) 2012 Research priorities: Identify optimal combinations of financial information, advice, regulation, disclosure, and delivery mechanisms, including default options, and their impact on starting and maintaining positive financial habits, Identify, evaluate, and build consensus on key metrics for financial education/capability, including measures of knowledge, behaviors, and well-being. FLECs research priorities also include the optimal strategy combinations, including: "What is the most effective mix of financial education, decision framing, and regulation to improve financial well-being? "How does this mix vary across content, delivery channels, target audiences, etc.?" Is it possible to develop an overarching framework for thinking about combining these three approaches or must effective combinations of financial education, decision framing, and regulation be developed on a case by case basis? Importance: Simply providing consumers with information and education are necessary steps, yet not sufficient to address the problem of consumer decision- making in an increasingly complicated financial world. Behavioral economics/psychology research has shown that consumers often make irrational choices (Ariely, 2008; Thaler & Sunstein, 2008;). Consumers are faced with a plethora of information from a variety of sources that may be of questionable reliability. Despite vast sums spent worldwide, we find that interventions to improve financial literacy explain only minimal variance in subsequent financial behavior (Fernandes, Lynch & Netemeyer ,2012, p. 1). Numerous studies reveal that while Americans of all ages are financially illiterate, they overestimate their financial decision-making skills (Lusardi, 2010; 2011; Lusardi & Mitchell, 2008).

There is a pressing need to understand how American households make financial decisions, and to improve the financial decision-making skills of the American family. This research is well suited for a broader land-grant community educational and research priority. Building upon what we have learned about consumer financial socialization and the importance of psychological constructs in the saving decision, this new research fills an important gap in our understanding of the consumer financial decision-making process. The research is informed by the latest in behavioral economic theory and is being applied to improve the overall well-being of the American households.

The renewal of this project is also important for its potential contribution to the field of consumer economics. Our previous research and additional studies over the past two decades clearly show that psychological factors play a powerful role in influencing consumer decisions. While conventional consumer education focuses on providing rational consumers with information (i.e. Consumer Reports) to make optimal decisions, information management (the economics of information) research clearly shows that how consumers acquire and process information may not always be optimal.

There is a solid theoretical foundation upon which to build a long-term research agenda. Shefrin and Thaler (1988) developed the Behavioral Life Cycle (BLC) hypothesis to enrich the life cycle theory of saving by incorporating three psychological components: self-control, mental accounting, and framing. Basically Shefrin and Thaler (1988) modified the life cycle hypothesis (LCH) to make it more reflective of actual consumer behavior. Various studies (Kahneman & Tversky, 1979; Lee & Aaker, 2004; Rothman & Salovey, 1997) demonstrate that how a decision is presented or framed influences consumer decisions. Shefrin and Thalers model recognizes consumers decision-making process is influenced through the psychological principals of self-control, mental accounting, and framing. However, the process of how self-control, framing, and mental accounting work has not been explored sufficiently within the context of consumer decision-making. There is a need for research that recognizes how psychology influences important consumer decisions related to student loan debt, home buying, and when to collect Social Security retirement benefits. This study will examine how psychological factors like self-control, mental accounting, and framing influence decisions linked to housing, saving and when to start social security benefits. Identifying the heuristics specific to each of these three critical consumer decisions will help consumer educators and information providers to enhance the effectiveness of their messages. These interventions may lead to improved financial decision-making by consumers.

Our contribution to the Behavioral Life Cycle hypothesis will focus mainly on the area of information management. We know from previous studies that consumers vary in the extent to which they search for information. Particularly, information search for financial decision-making is associated with a high volume of shopping around due to the complex nature of the exercise (Bi, Montalto & Fox, 2002). Higher levels of income, risk tolerance, regular savings habits and a larger network of financial institutions are factors that have previously been found to be positively correlated with extensive amounts of information search for financial services (Lin & Lee, 2004; Yang & DeVaney, 2006). Age is inversely proportionate to search extent (Yang & DeVaney, 2006). The search for information is just one aspect of information management. Avoiding negative information is a common strategy among consumers across the lifespan and socioeconomic spectrum (Sweeny, Melnyk, Miller & Shepperd, 2010). Financial information avoidance, while arguably a behavior less frequently employed than information search, carries potentially severe financial consequences such as default-related fees and credit score depreciation. Empirical research is yet to be conducted on financial information avoidance. Thus, our contribution to the body of knowledge on this topic will be immediate and significant.

Non-economic psychological factors influence financial decisions. Kahneman (2011) describes some of these psychological factors with the use of two systems. System one reflects the impulsive, heuristic-driven distinctive decision maker; whereas System two describes the rational, logical, deliberative, analytical self. The consumer financial decision-making process seems to follow the law of conservation of mental energy; consumers tend to make decisions using heuristics, thereby using the least amount of mental energy. Further studies and exploration of what these heuristics are and how they are formed will lead to a better understanding of the consumer decision-making process. In particular, understanding how heuristics can be changed or replaced with more effective decision strategies could lead to improved financial well-being.

Technical Feasibility

The researchers will use an experimental design to examine how consumers make financial decisions. Using an experimental design based on scenarios helps to enhance internal and statistical conclusion validity by increasing control over the manipulated variables and reducing random, unmanageable variables (Jin & DeVaney, 2011).

Written scenarios will be developed to simulate the financial decisions. Subjects will be randomly assigned to one of the scenarios. The scenarios will be varied to manipulate factors that are frequently involved in decision making. The researchers will include constructs from information management (such as source of information, use vs. avoidance) and constructs from the BLC theory. For example, in a pilot study by a team member, the participants were assigned to one of two instruments. After ascertaining basic information including financial knowledge, preferences, and experiences with homeownership, participants were presented with two scenarios and asked to select the mortgage (Adjustable Rate Mortgage or Fixed Rate Mortgage) they would choose in that situation. However, in one instrument the participant also received a one-page explanation of the difference between an Adjustable Rate Mortgage and Fixed Rate Mortgage, including when one should choose one over the other. The team will utilize an Internet sampling firm to provide sufficient responses for the study. The firm would facilitate random assignment to the different scenarios.


Findings and implications will be reported to consumer educators including the extensive Cooperative Extension network. We also plan to present this research at appropriate conferences including: Association for Financial Counseling and Planning Education, American Council on Consumer Interests, Family Economics Resource Management Association, as well as others. We also will submit manuscripts to relevant journals including: The Journal of Consumer Affairs, Journal of Financial Counseling and Planning, Family and Consumer Sciences Research Journal, Journal of Family and Economic Issues, International Journal of Consumer Sciences, Journal of Economic Psychology, and other relevant journals in the field of consumer economic behavior.

Potential Impact

This project will assess barriers and motivators that influence the decision-making making process of consumers. Also, this project will continue to examine the effect of economic, psychological, and sociological factors on savings behavior. In summary, this project is an extension of NC 1172 which examined "The Complex Nature of Savings Behavior." However, the focus of this new project is on information management and financial decision-making. This proposal recognizes that consumers are increasingly influenced by the multiple sources of information that they receive on a daily basis.

This project is expected to result in a greater understanding of how consumers make financial decisions. The results should provide a foundation for developing, implementing, and evaluating educational initiatives to increase financial literacy and improve financial decision-making. It may also help to inform regulatory efforts.

Although educational programs delivered through the land-grant systems Cooperative Extension Service (CES) focus on the development of financial decision- making skills, educators have not addressed the underlying psychological factors such as anxiety, distrust, and self-efficacy that influence the decision-making process. Also, we anticipate that the results of this study will help educators include the sociological factors of family, peers, and the influence of social media in educational programs.

This project will result in a better understanding of how consumers use or avoid information and which sources of information are used and/or avoided by different sub-groups of consumers based on demographic and psychological factors. A better understanding of how consumers receive and process information in addition to the awareness of factors that were studied in NC 1172 (e.g., economic, psychological, and sociological factors) should lead to increased effectiveness of CES educational initiatives. Also, the results can be used to recommend public policy initiatives and suggest new or enhanced approaches for reaching consumers beyond traditional audiences.

Related, Current and Previous Work

A search of CRIS indicated that no other research project had specifically examined the issues of personal finance and decision making. There was only one current project related to the proposed study and it was the precursor of this proposed project NC 1172. Results from that project, which help to inform this study, are presented.

The Complex Nature of Savings: The main concepts that were examined in the NC 1172 project, were presented in a series of research papers based on data collected from a sample of almost 1,000 low and moderate income households. The overall goal of incorporating economic, psychological and sociological elements into a savings model were the subject of the paper "Exploring the Relationship of Economic, Sociological, and Psychological Factors to the Savings Behavior of Low- to Moderate-Income Households" (Gutter, Hayhoe, DeVaney, Kim, Bowen, Cheang, Cho, Evans, Gorham, Lown, Mauldin, Solheim, Lokken, & Dorman, 2012). Multinomial logistic regression was utilized to explore the relationship between economic, sociological and psychological variables, and the likelihood of having only a savings account or both savings and investing accounts compared to having no savings or investment accounts. The results indicated that economic factors had a stronger relationship to savings behaviors than sociological or psychological factors.

Specifically, age and a financial behavior score were significantly related to the likelihood of having a savings account. As age of the respondent increased and as the financial behavior score increased, the household was more likely to have a savings account. Psychological factors such as the length of the respondents planning horizon, and number of perceived barriers to saving were also significantly related to the likelihood of having a savings account. Economic factors of net worth, education and income were significantly related to the likelihood of having both savings and investment accounts. One sociological factor, the number of sources of information was significantly related to having both savings and investment accounts. These results are to be used to develop interventions and strategies to increase savings behavior for low and moderate income households.

Methodological Issues: Hayhoe and Gutter (2012) examined the reliability of several psychological scales which were measured during the collection of the data set titled the Complex Nature of Savings: Psychological and Economic Factors. (Note: This is the same data set as described in the preceding paragraph.) The sample considered in this data set is low-to-moderate-income consumers with a respondent (or spouse/partner of the respondents) between the ages of 24 and 66. The data were collected under the sponsorship of the North Central (NC) 1172 multistate research program. Researchers from 12 universities contributed to the development of the instrument for the study. The scales included in the study were as follows: the Rook & Fisher (1995) Impulsivity Scale; the three sub-scales (distrust, anxiety bargain-conscious) from the revised Yamauchi & Templer (1982) Money Attitudes scale by Roberts & Sepulveda (1999); the Richins & Dawson (1992) Materialism Scale; the Sherer et al. (1982) Self-efficacy Scale; and Grable & Joo (2004) Financial Risk-tolerance Scale. In addition, these data were used to develop a Financial Management Behavior Score. The results showed that for people with low-to-moderate incomes and where the respondent or their spouse/partner was between the ages of 24 and 66, the modified scales worked as well as the original scales. Thus, researchers using this data set will be able to employ the scales with confidence.

Socialization and Financial Information Source: Cho, Kim, Mauldin, and Gutter (2012) examined the effect of financial socialization on the financial behaviors of adults aged 24 to 66 from low- to moderate-income households. Data from the NC-1172 Complex Nature of Saving data set were analyzed using ordinary least squares regressions and logistic regressions. The authors used four financial behavior variables - spending less than income, making financial plans, monitoring spending, and having savings goals---as dependent variables. The regression analyses showed that (i) discussions about money with parents as a child and (ii) learning from financial planners significantly influenced adults' financial management behavior. The findings indicated that financial socialization has a significant effect beyond adolescent or college years.

Money Attitudes: Hayhoe, Cho, DeVaney, Worthy, Kim, and Gorham (2012) examined how distrust and anxiety, demographic factors, and financial management behavior were associated with being a regular saver among low- and moderate-income households. The analyses were based on the same data as described in the studies above. The results on the financial management behavior score showed that those with higher levels of distrust and lower levels of anxiety tended to engage in more recommended financial management behaviors. Also, the results showed that anxiety and financial management behaviors were associated with regular savings. In addition, those who practiced more recommended financial management behaviors and those who had lower levels of anxiety were more likely to save regularly. Also, income, net worth, gender (male), and age were associated with saving regularly.

Purchase of Life Insurance: H. Kim, DeVaney, and J. Kim (2012), examined the purchase (e.g. ownership) of term and cash value life insurance by low-to-moderate-income households. The sample for analysis was reduced to 454 households because 354 households in the NC 1172 data set did not answer the survey questions about life insurance. About 37% of the respondents (N = 454) purchased term life insurance and 31% purchased cash value life insurance. Interestingly, 37% had purchased term life insurance on the spouse/partner and 28% held cash value life insurance on the spouse/partner. Factors related to the purchase of term life insurance included household income, higher (self-reported) financial knowledge, and saving regularly. Age and saving regularly were the only two factors significantly related to purchase of cash value life insurance. Although it might be commonly assumed that low to moderate income households cannot afford life insurance, these results show that the purchase of life insurance was feasible for a considerable percentage of low to moderate income households.


  1. Determine motivators that affect economic decision-making in specific decision situations (housing, student loans, and Social Security) across the life-span of households
  2. Determine barriers that affect economic decision-making in specific decision situations across the life-span of households
  3. Determine how motivators and barriers to economic decision-making can be presented in specific decision situations across the life-span of households
  4. Suggest strategies that can be used to improve consumer financial decision-making


This study proposes use of mixed methods to achieving its various objectives. These include: 1.) Determine motivators that affect economic decision-making in specified decision situations across the life-span of households; 2.) Determine barriers that affect economic decision-making in specified decision situations across the life-span of households; 3.) Determine how motivators and barriers to economic decision-making can be manipulated to promote savings across the life-span of households; and 4.) Determine factors that can reduce investment fraud and financial exploitation. Our study uses the Behavioral Life Cycle Hypothesis framework to examine factors influencing the consumer decision-making process. Our initial hypotheses focus on key factors such as the role of, mental accounting, economic socialization, framing, self-control, the role of information, on decisions related to retirement, home ownership, student loan usage. The experimental design for each study will utilize a mixed method approach. We will utilize both online surveys and smaller local convenience samples aimed to explore the decision making by individuals at relevant age ranges. This study is concerned with groups at the household formation stage, wealth building stage, and entering retirement stages of life. These stages are largely consistent with typical age ranges and family composition. Our sample for the only survey should be a total of 1500; with this sample size, the results are expected to lie within two standard deviations of the mean response. Ideally the sample will be split amongst the three different life stages. The Research Committee will contract with an independent data collection agency (such as Survey Sampling International) to sample, collect, and clean the data for the project. An outside data collection agency is preferred to ensure that the instrument is administered uniformly and to increase efficiency in administration and data collection. This agency can randomly assign participants to different versions of the survey. These web surveys will be identical except for the treatment. This treatment could include the introduction of information to the participant, or a difference in choice architecture. The first year of our study will utilize secondary data in order to further refine the model for the remaining stages of the project. The Family in Transition Project, is a longitudinal dataset of rural Iowan families and their response to economic stressors. The research project started in 1989, shortly after the period of extreme economic difficulty for rural farm families of the mid 1980s. During the decade of the 1980s, 20% of Iowa farmers ceased operations, and 75 banks and savings and loans went out of business (Conger & Elder, 1994). Participants were selected for the study met the following criteria: had one child in the 7th grade (target child) in 1989, and another sibling within 4 years of that childs age, and lived on farms or in small towns in an eight county region of North-Central Iowa. Two separate interviews (one survey, one video-taped problem solving) were conducted every one or two years. The first interview was an exhaustive survey of economic, stress, medical, psychological, financial attitudes, decision making process, relationships, employment and demographic survey information. The parent(s), the target child, and the target childs sibling were all interviewed with each wave of data collection. The second interview with the families was videotaped and structured to solicit a range of emotional responses from warmth to problem solving and conflict management as the family discussed common household issues like chores, homework, and family finances. The survey started with 451 families, and in 1991, an additional 107 single mother households were added which included a matched child in the 9th grade cohort. In 1994 the project was renamed the Families in Transition Project and retains that title today. Starting in 1995, the questions were transitioned to focus on the family of the individual who was the 9th grader at the time of the 1991 study. Retention rate for participants in this panel is over 90%. The current research project will analyze the household decision making data to determine what factors are significant in the decision making process. Specifically, researchers will look for motivators and barriers in the household decision making process. With this unique dataset the researchers will be able to investigate the financial socialization process of adolescents as they grow and form their own families. The psychological variable of self-control will be tested to see if associations exist between self-control and wealth creation, educational attainment, and life satisfaction. In addition, qualitative measures of problem solving ability and personality attributes will be included to see what ways these variables are associated with financial outcomes and the decision making process. The study of this panel dataset will help inform future survey and experimental design research in the area of consumer decision making. These experiments of consumer decision making will also be conducted in person with small groups on participating campuses and communities. The goal of these experiments will be to observe the relationships of framing, mental accounting, and other behavioral factors on decision making. The smaller local samples will need to involve 100 participants and will be conducted by select project team on their campuses. In both instances, the participants will be randomly assigned to a treatment group. The treatment in these experiments will be tied to the role of information as a treatment. This will allow for the sharing of the data collection burden but using a coordinated approach for consistency. The protocols were the same across states and information was aggregated and used to further refine the instrument and survey methodology. Participants will be randomly assigned to treatment groups. The online surveys will also include relevant measures suggested by the behavioral life cycle model and results from the NC 1172 studies on the complex nature of savings. This includes factors such as life cycle stage, self control, barriers to behaviors, and economic socialization. The psychological scales have been previously tested in psychological research and work of the NC 1172 Team. Consistent with Dillman (1978, 1991) our survey would be sent initially, with additional follow up emails sent to encourage participation in the study. Other guidelines that will be followed include putting questions in a logical sequence, using the proper format for answering, having an easily read layout with clear and concise statements, and not going beyond what is reasonable to expect for people to respond. If a monetary incentive is used, the incentive would be sent with a thank you and notification of receipt of the completed survey. Several members of the research team would conduct initial data cleaning/coding. The data will be downloadable in raw form from the Survey Monkey Account. In this form, it can be imported into SAS or SPSS easily for purposes of coding and cleaning. The process used in the NC 1172 2011 data collection process (See Hayhoe & Gutter, 2012) will be employed again in this data collection effort. Survey Measures: Development of the survey instrument will be a collaborative effort of members of the research team. Major components of the model are: socialization factors, financial knowledge, information management, resources, psychological scales, demographic and economic factors, and measures of financial behavior and decision outcomes. Socialization includes questions about the influence of parents or guardians, whether parents or guardians borrowed for school, bought a home, decided to retire. It also includes exposure to sources of information, the amount of effort in seeking information, and attitudes toward money from observing others behavior. Financial knowledge measures include understanding education financing, mortgage types and Truth in Lending, and retirement funding. Resources include current job status, job security, spouse or partners job status and job security, and emergency funds. Psychological measures include: measures of self-control, mental accounting, framing effects, and risk tolerance. Demographic factors include age and marital status of respondent, sex, education, race, health, and household size. Data Analysis: Descriptive analysis will be used to examine the socialization factors, decision making outcomes, lifecycle stages, financial knowledge, resources, demographic characteristics, and measures of financial behavior of the sample. Factor analysis will be used to examine the scales of the psychological constructs. Regression analysis and structural equation modeling will be used to examine the relationship among all of the factors in the model of financial decision making. The use of online survey and local smaller groups will help to maintain the cost-effectiveness of this research. Obtaining online samples through use of Survey Sampling International is inexpensive and in person samples should require only modest incentives. Previous data collection efforts were funded with small external grants and pooling Agricultural Experiment Station funding from members of the multistate research team.

Measurement of Progress and Results


  • Analyzed multi-method quantitative and qualitative results; manuscripts, outreach publications
  • Recommendations for developing educational programs or materials to assist consumers in information management and improving the outcomes in decisions regarding student loans, housing, and retirement.
  • Recommendations for regulatory policies related to student loans, housing, and retirement

Outcomes or Projected Impacts

  • Understanding barriers and motivators that influence the consumer decision-making making process
  • Understanding the role of information management in the consumer decision-making process
  • Understanding the role of economic stress on the consumer decision making process
  • Improved educational initiatives that will be expected to increase financial literacy and improve financial decision-making regarding student loans, housing, and retirement.
  • Informed regulatory policy related to student loans, housing, and retirement.


(2013): Analyze Families in Transition Project longitudinal data to inform data collection. Write/publish manuscripts and outreach publications. Submit proposals for presentations.

(2014): Design experiments and other qualitative and quantitative methods of data collection.

(2015): Field student loan experiment and analyze. Write/publish manuscripts and outreach publications. Submit proposals for presentations.

(2016): Field housing and retirement experiments and analyze. Write/publish manuscripts and outreach publications. Submit proposals for presentations.

(2017): Conduct meta-analysis. Write/publish manuscripts and outreach publications. Submit proposals for presentations

Projected Participation

View Appendix E: Participation

Outreach Plan

The results of the study will be made available through articles in appropriate journal and conference proceedings and through refereed and invited presentations at local, state, regional, and national conferences. Along with the answers to the research questions, papers will focus on an explanation of the conceptual model, recommendations for educational curricula, and recommendations for future research. Because several team members hold Cooperative Extension appointments in their respective states, in-service workshops and related lay publications will also be developed and/or modified. This multi-faceted strategy will allow for wide dissemination of research results and subsequent knowledge to diverse audiences across the country.


The results of the study will be made available through articles in appropriate journal and conference proceedings and through refereed and invited presentations at local, state, regional, and national conferences. Along with the answers to the research questions, papers will focus on an explanation of the conceptual model, recommendations for educational curricula, and recommendations for future research. Because several team members hold Cooperative Extension appointments in their respective states, in-service workshops and related lay publications will also be developed and/or modified. This multi-faceted strategy will allow for wide dissemination of research results and subsequent knowledge to diverse audiences across the country.

Literature Cited

Agency Financial Report (2011). The Department of the Treasury. Treasury. Retrieved November 15, 2011, from

Boehner, J. (2012). The Annual Report of the Board of Trustees of the Federal Old-Age and Survivors Insurance and Federal Disability Insurance Trust Funds. Retrieved from April 23, 2012, from

Cho, S. H., Kim, J., Mauldin, T., and Gutter, M. (2012). Effect of socialization and financial information source on financial management behavior among low to moderate income households. Family and Consumer Sciences Research Journal, 40(4), 417-430.

Fast Facts & Figures About Social Security, 2012. SSA Publication No. 13-11785.

Federal Reserve Board (2011). A Consumers Guide to Mortgage Refinancings. Retrieved from March 2, 2011, from

Federal Student Aid (2011). Your Federal Student Loans. U.S. Department of Education. Retrieved from January 1, 2011, from http://

Fernandes, D., Lynch, J., and Netemeyer, R. (2012). A meta-analytic and psychometric investigation of the effect of financial literacy on downstream financial behaviors. Presented at the 2012 Boulder Summer Conference on Consumer Financial Decision Making, Boulder, CO.

Hayhoe, C., Cho, S. H., DeVaney, S., Worthy, S., Kim, J., and Gorham, E. (2012). How do distrust and anxiety affect savings behavior? Family and Consumer Sciences Research Journal, 41(1). 69-85.

Jin, R. & DeVaney, S. A. (2011). Self-Service Technology Users and Their Causal Attributions for Service Outcomes. Family & Consumer Sciences Research Journal, 40(2) December, pp. 171-183.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus, and Giroux.

Lee, A. & Aaker, J. (2004). Brining the frame into focus: The influence of regulatory fit on processing fluency and persuasion. Journal of Personality and Social Psychology, 86(2), 205-218.

Lusardi, A. (2010, February 26). Americans Financial Capability. Report Prepared for the Financial Crisis Inquiry Commission. Retrieved from

Lusardi, A. (2011, January) Americans Financial Capability, PRC WP2011-02 Pension Research Council Working Paper Retrieved from

Lusardi, A., & Mitchell, O. S. (2008). Planning and Financial Literacy: How do Women Fare? American Economic Review: Papers & Proceedings, 98, 413417.

Rothman, A. J., & Salvoey, P. (1997) Shaping perceptions to motivate healthy behavior: The role of message framing. Psychological Bulletin, 121, 3-19.

Shefrin, H. M., & Thaler, R. H. (1988). The behavioral life-cycle hypothesis. Economic Inquiry, 26(4), 609-643.

Sweeny, K., Melnyk, D., Miller, W. & Shepperd, J.A. (2010). Information avoidance: Who, What, When, and Why. Review of General Psychology, 14, 4.

Thaler, R., & Sunstein, C. (2008). Nudge: Improving decisions about health, wealth, and happiness. New York: Penguin Books.

U.S. Department of Education (2011). Ensuring Continued to Student Loans Act (ECASLA). Annual Report to Congress. Retrieved July 1, 2011 from

Yamauchi, K., & Templer, D. I. (1982). The development of a money attitude scale. Journal of Personality Differences, 46, 522528.

Yang, Y. & DeVaney, S. A. (2006). Determinants of the extent of external search for
information about savings and investment. Consumer Interests Annual, 40.
Bi, L., Montalto, C.P. & Fox, J.J. (2002). Household search for and use of financial information. Consumer Interests Annual, 48, 1-9.

Yellen, L. (2011). Housing Market Developments and Their Effects on Low-and Moderate-Income Neighborhoods. Retrieved June 9, 2011, from


Land Grant Participating States/Institutions


Non Land Grant Participating States/Institutions

California State University, Emeritus Collaborator, NORC , North Dakota State University, University of the Incarnate Word
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