We provide new and robust empirical evidence that procrastinators behave
differently than non‐procrastinators for five important retirement‐related financial behaviors.
Empirically, we define a procrastinator as an individual who waits until the last day of their
health care open enrollment period to make their plan election. Using three separate
administrative data sets, we show that procrastinators are: (i) less likely to participate in a
supplemental savings plan, (ii) take longer to sign up for 401(k) plans, (iii) contribute less, (iv)
are more likely to stick with default portfolio allocations, and (v) are less likely to take the
annuity payout option from their DB plan, especially when the plan is framed so as to make the
investment features more salient. Further evidence shows that these findings are best
explained by procrastination being the outcome of present‐biased preferences, consistent with
the predictions of leading economic models of procrastination.
|9/10/2015||Jeffrey Brown, University of Illinois at Urbana-Champaign and Alessandro Previtero, University of Western Ontario||Social Security Administration||English||Conference Proceedings||Administrative data; Focus groups and/or interviews||Save & Invest||Researcher|
Retirement Savings Plan,
Researchers have become increasingly interested in understanding the sources of heterogeneity in individual financial behaviors. In this paper, we examine how the Big Five personality traits are related to measures of young adults’ financial distress. Using data from the National Longitudinal Study of Adolescent to Adult Health in the United States, we find that conscientiousness is negatively correlated, and neuroticism positively correlated with financial distress. These correlations are robust to controlling for early life background and other demographic and socioeconomic factors. Young adulthood sets the stage for financial security in later life; as such, this study provides insight for lifelong financial wellbeing. Based on the empirical results, we discuss potential behavioral and policy interventions that can be used to improve financial wellbeing
|12/1/2015||Yilan Xu, , Andrea H. Beller, Brent W. Roberts, Jeffrey R. Brown, University of Illinois Urbana-Champaign||Social Security Administration||English||Journal||Survey data||Save & Invest||Researcher||1||Yes|
We propose a model of narrow framing in insurance and test it using data from a new module we designed and fielded in the Health and Retirement Study. We show that respondents subject to narrow framing are substantially less likely to buy long-term care insurance than average. This effect is much larger than the effects of risk aversion or adverse selection, and it offers a new explanation for why people under insure their later-life care needs.
|6/1/2015||Daniel Gottlieb and Olivia S. Mitchell, The Wharton School, University of Pennsylvania||Social Security Administration||English||Working paper||Survey data||Save & Invest||Researcher||1||Yes|
Automatic enrollment has been widely embraced for raising employee participation in 401(k) plans. However, the empirical evidence is based on data with limitations that, up until now, have prevented researchers from extrapolating the effects of automatic enrollment to the broader population of workers. This paper reexamines the determinants of 401(k) participation and contributions in the presence of automatic enrollment using nationally representative data from the Health and Retirement Study (HRS) for 2006 through 2012. The results confirm previous findings that automatic enrollment is associated with a higher proportion of workers included in DC plans; however, automatically enrolled workers are less likely to contribute to their DC plans than voluntarily enrolled workers. Auto enrollment is also associated with lower employee contribution amounts and rates. However, the employers of auto-enrolled workers are more likely to contribute to their employees’ accounts than are the employers of voluntarily enrolled workers. Additionally, employer contribution amounts and rates are higher among workers who are automatically enrolled. Even so, the combined effect is that the retirement accounts of automatically enrolled older workers receive, on average, $900 less in combined annual contributions and have contribution rates that are 1.6 percentage points lower than those of voluntarily enrolled workers.
|7/1/2015||Barbara A. Butrica, Urban Institute, and Nadia S. Karamcheva, Congressional Budget Office||Social Security Administration||English||Working paper||Survey data||Save & Invest||Researcher|
Retirement Savings Plan,
In aggregate, individual retirement savings are reaching unprecedented levels, totaling about $25 trillion. Yet there is considerable variation in retirement wealth across individuals even after taking into account background characteristics, such as age, income, and education. Because changes in the employer-provided pension landscape now require millions of Americans to rely more on their individual savings to finance retirement, understanding what factors contribute to differences in retirement-wealth accumulation and whether individuals are saving inadequately for retirement is a critical policy concern. If psychological biases play a strong role in driving individuals’ decisions, their choices may not be optimal. This study focuses on illuminating the role of two potential biases: “present-biased preferences” and exponential-growth (EG) bias.
|8/1/2015||Gopi Shah Goda, Stanford University and NBER; Colleen Flaherty Manchester, University of Minnesota; Matthew R. Levy, London School of Economics; Aaron J. Sojourner, University of Minnesota and IZA; ||Social Security Administration||English||Conference Proceedings||Survey data||Save & Invest||Researcher|
Retirement Savings Plan, Savings
A report, Opportunities to Improve the Financial Capability and Financial Wellbeing of Postsecondary Students, has been prepared by the Financial Literacy and Education Commission (FLEC) and describes the state of financial education among postsecondary students. The report describes current efforts to enhance financial education in a number of institutions with regards to student understanding of financial aid and financial education topics at two critical junctures:
Choosing Where to Go and How to Finance Postsecondary Education; and
Making Sound Financial Decisions When Enrolled and Beyond.
|Department of the Treasury||FLEC||English||Report||Borrow, Earn, Protect, Save & Invest, Spend||College Savings Plan; Budgeting; Education; Financial Education/Literacy; Planning; Student||Higher Education and Training||FAFSA; Federal Student Loan Programs; Paying for College; Saving for College; Student Loans||Individual, Researcher, Teacher, Youth|
Postsecondary Education, Financial Literacy, Financial Capability
Building Financial Capability: A Planning Guide for Integrated Services is designed for community-based organizations interested in integrating financial capability services into existing programs (e.g. housing, job training, or Head Start). The interactive tools in the guide walk organizations step-by-step through the process of developing an integration plan, beginning with developing a deeper understanding of clients’ financial circumstances and which financial capability services can help them improve their situations. The guide also includes tools to help organizations determine how best to provide financial capability services—whether through referrals, partnerships, or in-house. The final step in the process is the creation of a logic model that serves as a comprehensive roadmap for implementing the integration plan. Building Financial Capability is a practical resource for organizations providing financial capability services for the first time as well as those that want to improve or expand existing efforts.
|Department of Health and Human Services||English||Guide||Borrow, Earn, Protect, Save & Invest, Spend||Employment; Home Ownership; Business Ownership; Planning for Retirement; Unplanned Events||Individual|
Financial Capability, Integration, Financial Education, Credit, Financial Coaching, Asset Building
PISA 2012 is the first large-scale international study to assess the financial literacy, learned in and outside of school, of 15-year-olds nearing the end of compulsory education. It assesses the extent to which students in 18 participating countries and economies have the knowledge and skills that are essential to make financial decisions and plans for their future. The assessment highlights the importance of financial literacy, defines financial education and financial literacy, and discusses how the assessment was organized. It also offers an overview of the limited and uneven provision of financial education in schools in participating countries and economies, and describes the steps taken in some countries to improve financial literacy among students.
|7/22/2014||Department of Education||English||Dataset; Report||Researcher|
PISA, Financial Literacy, Programme for International Student Assessment, data
Economic studies on households’ financial asset ownership and allocation have discussed the relationship between asset holdings and socioeconomic variables. The current research on asset ownership has been conducted with data from the country of China utilizing a random sample of 2080 Chinese households collected in 2009. Greater asset levels increased holding of mutual funds, stocks, bonds, certificates of deposit, gold, life insurance, housing savings, and pensions. Greater levels of debt decreased holdings of gold, certificates of deposit, and cash. Age was negatively related to the holding of cash, and positively correlated with holdings of certificates of deposit, mutual funds, bonds, gold, housing savings, pensions, and other assets; with the effect falling for those over the age of 60. Self employed were less likely to own stocks, bonds, housing savings, and pensions; when compared to salary earners. Those not working were less likely to own life insurance, housing savings, and pensions; the latter two being contingent upon employment. Educational level was positively related to the ownership of mutual funds, government bonds, life insurance, housing savings, and pensions, indicating the presence of human capital to reinforce diversification, as well as understanding risk management. In sum, the results fit most models of asset ownership with income, education, employment status, and financial goals having relatively robust results. The continued introduction of financial markets and financial planning to the Chinese population, as markets mature, future analyses are expected to be asymptotic to those found in mature financial markets.
|Robert O. Weagley, Li Liao, Rui Yao, Jing Xiao, and Feifei Wang||Department of Agriculture||English||Working paper||Survey data||Borrow||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/yao_domarketreturns.pdf||1/1/2011||Rui Yao and Angela L. Curl||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Save & Invest||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/yao_anexploratorystudy.pdf||1/1/2011||Rui Yao, Deanna L. Sharpe, and Elizabeth E. Gorham||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Borrow||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/yao_decomposing.pdf||1/1/2011||Rui Yao, Deanna L. Sharpe, and Feifei Wang||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Save & Invest||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/weagley_householdsaving.pdf||1/1/2011||Rui Yao, Feifei Wang, Robert O. Weagley, and Li Liao||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Save & Invest||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/yao_familyfinances.pdf||1/1/2010||Li Liao, Nuonan Huang, and Rui Yao||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Borrow, Earn, Save & Invest, Spend||Researcher||1||Yes|
|1/1/2010||Tansel Tilmazer and Angela C. Lyons||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Save & Invest||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/yilmazer_theuseofownerresources.pdf||1/1/2010||Tansel Yilmazer and Holly Schrank||Department of Agriculture||English||Article; Journal; Peer-reviewed||Literature review||Earn, Save & Invest||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/yao_selfperceivedage.pdf||1/1/2010||Bin Ying and Rui Yao||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Spend||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/sharpe_effectofpersonal.pdf||1/1/2009||Cliff A. Robb and Deanna L. Sharpe||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Borrow||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/sharpe_economicstatus.pdf||1/1/2008||Deanna L. Sharpe||Department of Agriculture||English||Article; Journal; Peer-reviewed||Census data||Earn||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/sharpe_istimerunningout.pdf||1/1/2007||Russell N. James and Deanna L. Sharpe||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Save & Invest||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/sharpe_thesecteffect.pdf||1/1/2007||Russell N. James and Deanna L. Sharpe||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Spend||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/sharpe_thenature.pdf||1/1/2007||Russell N. James and Deanna L. Sharpe||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Spend||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/sharpe_predictors.pdf||1/1/2007||Yoon G. Lee, Jean M. Lown, and Deanna L. Sharpe||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Borrow||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/sharpe_financialissues.pdf||1/1/2007||Deanna L. Sharpe and Dana Lee Baker||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Protect, Spend||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/sharpe_specificelements.pdf||1/1/2007||Deanna L. Sharpe, Carol Anderson, Andrea White, Susan Galvin, and Martin Siesta||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Save & Invest||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/yao_factorsrelated.pdf||1/1/2002||Rui Yao, Sherman D. Hanna, and Catherine P. Montalto||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Save & Invest||Researcher||1||Yes|
|1/1/2006||Michael S. Finke, Sandra J. Huston, and Deanna L. Sharpe||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Save & Invest||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/weagley_collegestudents.pdf||1/1/2006||Pamela S. Norum and Robert O. Weagley||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Protect||Researcher||1||Yes|
|1/1/2006||Deanna L. Sharpe and Mohamed Abdel-Ghany||Department of Agriculture||English||Article; Journal; Peer-reviewed||Census data||Earn||Researcher||1||Yes|
|http://pfp.missouri.edu/documents/research/yao_consumptionpatterns.pdf||1/1/2006||Bin Ying and Rui Yao||Department of Agriculture||English||Article; Journal; Peer-reviewed||Survey data||Spend||Researcher||1||Yes|