Asset Allocation and Information Overload: The Influence of Information Display, Asset Choice, and Investor Experience
Open accessAbstract
This paper investigates three common differences among DC plans that may lead to varying degrees of information overload. We hypothesize that information overload is one reason DC participants often choose the default options. In two experiments, we manipulate the display of the investment information, the number of choices offered, and the similarity of these choices. In addition, we measure the financial knowledge of the participants. We test how these factors influence the participant's feelings of information overload, decision satisfaction and choice of the default. The main contribution of this analysis is that it explores the interaction between the individual's tested financial knowledge and the manipulated plan features. In our study, women with relatively lower salaries and less education tend to fall into our low knowledge category. Our findings do show that changes to plan design can help some individuals. We find individuals with above average financial knowledge do report significantly less overload when given fewer investment choices. This confirms previous research that plan design is important. Our results also show that financial knowledge plays a large role in who opts for the default. We find that low knowledge individuals opt for the default allocation more often than high knowledge individuals (experiment one: 20% vs. 2%). Our findings suggest individuals with below average knowledge are simply overwhelmed by the investment decision in general. Altering the plan by offering investment information in a more easily comparable format or by reducing the choices offered does not attenuate the low knowledge individuals' feelings of overload. The findings suggest that the success of certain plan features depends strongly on the financial background of the participant. The results emphasize the importance of plan design, especially the careful selection of plan default options, and the need to improve the financial literacy of participants.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Individuals tend to be overly confident about how much they really know.
“Comparing test-based and self-assessed financial literacy, the literature reveals that individuals tend to be overly confident about how much they really know (e.g., Agnew and Szykman 2005).”
From Financial literacy, financial advice, and financial behavior (2017) · cites this paper as Agnew and Szykman 2005
There is a median correlation of 0.49 between actual and self-assessed financial literacy scores.
“Agnew and Szykman (2005), for instance, document a median correlation of 0.49 between actual and self-assessed financial literacy scores”
From Financial literacy, financial advice, and financial behavior (2017) · cites this paper as Agnew and Szykman (2005)
Cites
When choice is demotivating: can one desire too much of a good thing?
Iyengar, S. S., & Lepper, M. R. (2000) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.79.6.995 · Cited by 2,878 · see citing works
Adaptive strategy selection in decision making.
Payne, J. W., Bettman, J. R., & Johnson, E. J. (1988) · Journal of Experimental Psychology: Learning, Memory, and Cognition · doi:10.1037/0278-7393.14.3.534 · Cited by 1,955 · see citing works
Bettman, J. R., & Park, C. W. (1980) · Journal of Consumer Research · doi:10.1086/208812 · Cited by 1,344 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Financial literacy and stock market participation
van Rooij, M., Lusardi, A., & Alessie, R. (2011) · Journal of Financial Economics · doi:10.1016/j.jfineco.2011.03.006 · Cited by 3,554 · see citing works
Financial Literacy, Financial Education, and Downstream Financial Behaviors
Fernandes, D., Lynch, J. G., & Netemeyer, R. G. (2014) · Management Science · doi:10.1287/mnsc.2013.1849 · Cited by 2,152 · see citing works
Financial Literacy among the Young
LUSARDI, A., MITCHELL, O. S., & CURTO, V. (2010) · Journal of Consumer Affairs · doi:10.1111/j.1745-6606.2010.01173.x · Cited by 1,804 · see citing works
Planning and Financial Literacy: How Do Women Fare?
Lusardi, A., & Mitchell, O. S. (2008) · American Economic Review · doi:10.1257/aer.98.2.413 · Cited by 1,512 · see citing works
Financial Literacy, Financial Education, and Economic Outcomes
Hastings, J. S., Madrian, B. C., & Skimmyhorn, W. L. (2013) · Annual Review of Economics · doi:10.1146/annurev-economics-082312-125807 · Cited by 1,041 · see citing works
THE EFFECTS OF PERCEIVED AND ACTUAL FINANCIAL LITERACY ON FINANCIAL BEHAVIORS
Allgood, S., & Walstad, W. B. (2016) · Economic Inquiry · doi:10.1111/ecin.12255 · Cited by 620 · see citing works
How Ordinary Consumers Make Complex Economic Decisions: Financial Literacy and Retirement Readiness
Lusardi, A., & Mitchell, O. (2009) · doi:10.3386/w15350 · Cited by 587 · see citing works
Chattaraman, V., Kwon, W.-S., Gilbert, J. E., & Ross, K. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.08.048 · Cited by 510 · see citing works
Financial literacy, financial advice, and financial behavior
Stolper, O. A., & Walter, A. (2017) · Journal of Business Economics · doi:10.1007/s11573-017-0853-9 · Cited by 471 · see citing works
“Agnew and Szykman (2005), for instance, document a median correlation of 0.49 between actual and self-assessed financial literacy scores, a finding which is qualitatively corroborated in Lusardi and Mitchell (2009) and Parker et al. (2012). Moreover, both types of measures have been shown to be individually associated…”
BackgroundResultInfluentialFinancial Literacy Among the Young
Lusardi, A., Mitchell, O. S., & Curto, V. (2009) · SSRN Electronic Journal · doi:10.2139/ssrn.1476982 · Cited by 1,804 · see citing works
Lee, T., Lee, B.-K., & Lee-Geiller, S. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102098 · Cited by 122 · see citing works
- Authors
- Agnew, J. R., & Szykman, L. R.
- Affiliations
- William & Mary (US)
- ORCID
- Agnew, Julie R.
- Venue
- Journal of Behavioral Finance
- Publisher
- Informa UK Limited
- Published
- 2005-06
- Volume
- 6
- Issue
- 2
- Pages
- 57-70
- ISSN
- 1520-8834 (ISSN-L)
- 1542-7560
- 1542-7579
- OpenAlex
- W1976943697
- Cited by
- 561
- References
- 3
- Citations by year
- 2026: 19 · 2025: 24 · 2024: 19 · 2023: 30 · 2022: 30 · 2021: 51 · 2020: 42 · 2019: 47 · 2018: 37 · 2017: 27 · 2016: 29 · 2015: 29 · 2014: 26 · 2013: 19 · 2012: 20
- FWCI
- 46.47
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Behavioral Finance (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- U.S. Social Security Administration
- Boston College
- Center for Retirement Research, Boston College
- Strong
- Australian Government
- Topics
- Social Sciences › Business, Management and Accounting › Accounting › Financial Literacy, Pension, Retirement Analysis
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Business, Management and Accounting › Accounting › Financial Literacy and Behavior
- Keywords
- information overload, defined contribution pensions, asset allocation, default options, path of least resistance, investment decision-making, information visualization, financial literacy, investor experience, plan design, retirement savings
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review