NBER WORKING PAPER SERIES
FINANCIAL LITERACY AND PLANNING:
IMPLICATIONS FOR RETIREMENT WELLBEING
Annamaria Lusardi
Olivia S. Mitchell
Working Paper 17078
http://www.nber.org/papers/w17078
NATIONAL BUREAU OF ECONOMIC RESEARCH
1050 Massachusetts Avenue
Cambridge, MA 02138
May 2011
The research reported herein was pursuant to a grant from the US Social Security Administration (SSA)
funded as part of the Retirement Research Consortium (RRC) and the Pension Research Council/Boettner
Center at the Wharton School. Without implicating them, we are grateful for comments provided
by Alberto Alesina, Rob Alessie, Maristella Botticini, John Campbell, Andrew Caplin, Sewin Chan,
Gary Engelhardt, Alan Gustman, Mike Hurd, Arie Kapteyn, Mauro Mastrogiacomo, Mary Beth Ofstedal,
William Rodgers, Chris Snyder, Maarten van Rooij, Arthur van Soest, and Steve Utkus. Helpful suggestions
were offered by participants at conference at Dartmouth, Harvard, Rand, the NBER, the Retirement
Research Consortium, the Dutch Central Bank, and the American Economic Association. Mark Christman
and Jason Beeler provided excellent research assistance. Opinions and errors are solely those of the
authors and not of the institutions with whom the authors are affiliated. Findings and conclusions do
not represent the views of the SSA, any agency of the Federal Government, the RRC, or the National
Bureau of Economic Research.
NBER working papers are circulated for discussion and comment purposes. They have not been peer-
reviewed or been subject to the review by the NBER Board of Directors that accompanies official
NBER publications.
© 2011 by Annamaria Lusardi and Olivia S. Mitchell. All rights reserved. Short sections of text, not
to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including
© notice, is given to the source.
Financial Literacy and Planning: Implications for Retirement Wellbeing
Annamaria Lusardi and Olivia S. Mitchell
NBER Working Paper No. 17078
May 2011
JEL No. D91
ABSTRACT
Relatively little is known about why people fail to plan for retirement and whether planning and information
costs might affect retirement saving patterns. This paper reports on a purpose-built survey module
on planning and financial literacy for the Health and Retirement Study which measures how people
make financial plans, collect the information needed to make these plans, and implement the plans.
We show that financial illiteracy is widespread among older Americans, particularly women, minorities,
and the least educated. We also find that the financially savvy are more likely to plan and to succeed
in their planning, and they rely on formal methods such as retirement calculators, retirement seminars,
and financial experts, instead of family/relatives or co-workers. These results have implications for
targeted financial education efforts.
Annamaria Lusardi
George Washington School of Business
2201 G Street, NW
Washington, DC 20052
and NBER
[email protected]
Olivia S. Mitchell
University of Pennsylvania
Wharton School
3620 Locust Walk, St 3000 SH-DH
Philadelphia, PA 19104-6302
and NBER
[email protected]
2
Introduction
Most older Americans are not at all confident about the efficacy of their efforts to
save for retirement, and in fact one-third of adults in their 50s have failed to develop any
kind of retirement saving plan at all (Lusardi 1999, 2003; Yakoboski and Dickemper,
1997). What explains this low level of retirement preparedness? Why do people do such a
poor job when it comes to designing and carrying out retirement saving plans? In this
paper we explore the hypothesis that poor planning may be a primary result of financial
illiteracy. That is, we evaluate whether those who report that they are unable to plan for
retirement and/or who cannot carry out their retirement saving plans are also those who
are’ least aware of fundamental economic concepts driving economic wellbeing over the
life cycle.
While several prior studies offer suggestions about why people fail to plan for
retirement, few examine the roles that planning and information costs might play in
affecting retirement saving decisions. Others have offered evidence on related topics; for
instance Calvert, Campbell, and Sodini (2007) show that more sophisticated households
are more likely to buy equities and invest more efficiently,
1
and Hilgerth, Hogarth, and
Beverly (2003) and Lusardi and Mitchell (2009) demonstrate strong links between
financial knowledge and financial behavior. Our contribution reports on a special module
on planning and financial literacy we designed for the 2004 Health and Retirement Study
(HRS) which allows us to investigate how workers make their saving decisions, how they
collect the information for making these decisions, and whether they possess the financial
literacy needed to make these decisions. Using the responses to this survey, we argue that
3
lack of literacy and financial sophistication are critical because they have important
consequences for lifetime wellbeing.
Methods and Data
The conventional economic framework used to model consumption and saving
decisions posits that rational and foresighted consumers derive utility from consumption
and leisure over the lifetime. In its simplest format, the consumer’s problem is modeled as
in terms of lifetime expected utility or the expected value of the sum of per-period utility
U(c
j
) discounted to the present (with discount factor ), multiplied by the probability of
survival p
j
from the worker’s current age j to the oldest possible lifetime D:
)(
j
D
sj
sj
cUE
.
Per period assets and consumption (a
j
and c
j
) are determined endogenously by
maximizing this function subject to an intertemporal budget constraint; here e
j
is labor
earnings, ra
j
represents the household’s returns on assets a
j
, and SS and PP represent the
household’s Social Security benefits and pensions which depend on the worker’s
retirement (R) age:

)1,...,,
RSjraey
jjj
and
DRjraRPPRSSy
jjjj
,...,,)()(
.
Furthermore consumption depends on income, assets, and benefits so that:

1,...,,
1
RSjayac
jjjj
before retirement (R), and

DRjayac
jjjj
,...,,
1
from retirement to death (D).
2
4
In other words, the economic model posits that the consumer has expectations regarding
prospective survival probabilities, discount rates, investment returns, earnings, pensions
and Social Security benefits, and inflation. Further, the consumer is assumed to use that
information to formulate and execute optimal consumption, work, and saving plans.
This formulation makes it clear that saving for retirement requires substantial
information and financial literacy, as well as the tools to plan and implement retirement
saving plans. But whether “real people” can meet this challenge is a topic of substantial
current interest, and it is particularly important in view of the trend have workers take
responsibility to save, manage their pension investments, and draw down their retirement
assets in a self-managed retirement environment. To further investigate the links between
the sources of information on which households rely, financial literacy, and planning, we
designed a special module on retirement planning to assess levels of financial literacy
along with consumers’ efforts to budget, calculate, and develop retirement saving plans.
We implement this in the context of the Health and Retirement Study (HRS), a nationally
representative longitudinal dataset of Americans over the age of 50. This survey,
conducted every two years since 1992, is designed to address these questions by tracking
health, assets, liabilities, and patterns of wellbeing in older households. The core survey
consists of a 90-minute core questionnaire administered to age-eligible respondents and
their spouses. In addition, our special financial literacy and planning module included
three questions on financial literacy, as follows:
- Suppose you had $100 in a savings account and the interest rate was 2% per
year. After 5 years, how much do you think you would have in the account if
you left the money to grow: more than $102, exactly $102, less than $102?
5
- Imagine that the interest rate on your savings account was 1% per year and
inflation was 2% per year. After 1 year, would you be able to buy more than,
exactly the same as, or less than today with the money in this account?
- Do you think that the following statement is true or false? “Buying a single
company stock usually provides a safer return than a stock mutual fund.”
The first two questions we refer to as the “Compound Interest” and “Inflation” items, and
they indicate whether respondents command the key economic concepts fundamental to
saving. The third question, which we dub “Stock Risk,” evaluates knowledge of risk
diversification, crucial to informed investment decisions.
We also ask respondents to how they calculate retirement saving needs. To do so,
we replicate a question on whether people plan for retirement asked by EBRI in its
Retirement Confidence Survey and in TIAA-CREF surveys (Ameriks, Caplin and Leahy
2003; EBRI 1996, 2001). We also ask whether people ever assessed their retirement
saving needs and what followed from such assessment. The three HRS modular questions
on retirement planning are as follows:
- Have you ever tried to figure out how much your household would need to
save for retirement?
- Did you develop a plan for retirement saving?
- How often were you able to stick to this plan: Would you say always, mostly,
rarely, or never?
Last we assess what tools people use to devise and carry out their retirement saving plans.
Specifically, we inquire whether respondents contact friends, relatives, or experts, and
whether they use retirement calculators. Also we ask whether respondents track their
spending and set spending budgets. The specific planning tools questions are as follows:
- Tell me about the ways you tried to figure out how much your household
would need.
o Did you talk to family and relatives?
6
o Did you talk to co-workers or friends?
o Did you talk to co-workers or friends?
o Did you use calculators or worksheets that are computer or Internet-based?
o Did you consult a financial planner or advisor or an accountant?
- How often do you keep track of your actual spending: would you say always,
mostly, rarely, or never?
- How often do you set budget targets for your spending: would you say always,
mostly, rarely, or never?
Using respondents’ answers to these questions, along with information of their
sociodemographic characteristics, we can assess the prevalence of financial literacy,
retirement calculations, and the planning tools people deploy to devise and execute their
plans. In addition, we determine whether those who lack knowledge of basic economic
concepts also seem to be those who have particular difficulty devising plans and carrying
them out in practice. In what follows, we offer both tabular and multivariate analysis of
the data, so as to evaluate whether those who are more financially literate are also more
likely to plan and be successful planners.
Financial Literacy Results
Our first set of findings on financial literacy among this nationally representative
sample of older Americans is reported in Panel A of Table 1, where we see that only two-
thirds of the respondents understand compound interest. This is a discouraging finding
inasmuch as this generation in its 50’s and 60’s has made many important financial
decisions over its lifetime. More of the respondents, three-quarters, can answer the
inflation question correctly and understand they would be able to buy less after a year if
the interest rate was 1 percent and inflation 2 percent. Yet only half of the respondents
know that holding a single company stock implies a riskier return than a stock mutual
fund. It is also of interest to distinguish between those who can give a correct answer,
7
versus those giving either an incorrect answer or saying they “don’t know” (DK).
Interestingly, the proportion of incorrect/DK responses varies according to the question.
For example, only 9 percent did not know about interest compounding, but more than one-
fifth (22 percent) gave an incorrect answer. On the inflation question, 10 percent did not
know, while 13 percent gave a wrong answer. The question about stock risk elicited the
most DKs: one-third (34 percent) of the sample did not know, while a smaller fraction (13
percent) gave a wrong answer.
Table 1 here
Inasmuch as the first two questions are crucial to financial numeracy, it is
disturbing that only slightly over half (56 percent) of the sample gets both questions right
(see Panel B). Also disturbing is the fact that only one-third (34 percent) of respondents
can correctly answer all three questions. Another interesting finding is that the “DK”
responses are highly correlated: that is, financial illiteracy is systematic across areas
examined. For instance, there is a 70 percent correlation between those who cannot
answer both the interest compounding question and the inflation question. Erroneous
answers are more scattered, with mistakes having a correlation of only 11 percent.
These results reinforce other U.S. findings on older respondents (c.f. Bernheim
1995, 1998; Hogarth and Hilgerth 2002; Moore 2003; and Lusardi and Mitchell 2007b,
2007c). These authors tend to concur that such individuals often fail to understand key
financial concepts particularly relating to bonds, stocks, mutual funds, and the working of
compound interest; they also report that these people often do not understand loans (and in
particular, mortgages).
3
The same is true of younger Americans: the National Council on
Economic Education (NCEE 2005) study of high school students and working-age adults
8
in 2005 revealed a widespread lack of knowledge of fundamental economic concepts.
Similar results for US high school students are reported by Mandell (2004) and young
adults (Lusardi, Mitchell, and Curto 2010).
4
Clearly the news is far from positive:
Americans’ financial literacy levels are low.
Who Is Financially Literate? Next we evaluate the extent of heterogeneity in financial
knowledge across demographic groups. Specifically, we are interested in whether
knowledge patterns differ by race/ethnicity and education, as depicted in Figure1. A first
point to note is the differences in knowledge between Whites, Blacks, and Hispanics.
5
Specifically, fewer than half of the Hispanics can answer correctly the interest
compounding question, and a sizable fraction of the remainder stated they did not know
the answer. This is a potentially important result in view of the fact that many Hispanics
tend to be unbanked and do not hold checking accounts (Hogarth, Anguelov, and Lee
2004). A similar pattern emerges with the question about inflation, where again Hispanics
are least likely to answer correctly. As far as risk diversification is concerned, Hispanics
and Blacks both display difficulty answering this question: only one-third (37 percent) of
the Blacks responded correctly, and over 40 percent did not know the answer to this
question. This may shed further light on why so many Blacks do not hold stocks
(Haliassos and Bertaut 1995).
Figure 1 here
Differences in financial knowledge across education groups are represented in
Figure2, and the patterns confirm expectations that financial literacy is highly and
positively correlated with schooling. Most importantly, financial illiteracy is most acute
for those with less than a high school degree, and fewer than one-third of respondents with
9
only elementary education could correctly answer the question about interest
compounding (another third did not know). The prevalence of correct answers to the
interest compounding question rises with education, while the proportion of both incorrect
answers and DKs falls. A similar pattern characterizes answers to the inflation question,
where those lacking a high school education are much more often incorrect or cannot
answer the question. Turning to the risk diversification question, only those with at least a
college degree display a high proportion of correct answers, though even here, almost a
third of these did not know the answer or answered incorrectly to this question. Among
the less-educated, the proportion of DK was particularly high; over half of those with less
than high school education reported they did not know the answer to these questions.
Figure 2 here
Figure 3 reveals response patterns by sex, where the results confirm that women
are generally less financially knowledgeable than men (c.f. Lusardi and Mitchell 2008).
Concerning risk diversification, women are less likely to respond correctly to the question
compared to men, and are more likely to not know the answer rather than answering
incorrectly. Also fewer women can answer all questions correctly compared to men.
Figure 3 here
For brevity, we merely summarize other financial literacy results for along other
dimensions. Findings worth highlighting including the fact that the leading edge of the
Baby-Boomers (age 51-56 in 2004) was much less knowledgeable about inflation, perhaps
a result of their limited historical exposure to inflation or the fact they were in their 20s in
the high inflation period during the 1970s and early 1980s.
10
Findings for Retirement Planning
Next we turn an assessment of some of the other predictions of the canonic
economic model, including the hypothesis that people look ahead and calculate how much
they need to save for retirement. To this end, our HRS modules asks respondents whether
they ever tried to figure out how much they need to save for retirement and Table 2
reports the results. Somewhat discouragingly, fewer than one-third of the sample
respondents (31 percent) indicated that they actually attempted to do a retirement saving
calculation; these we call the Simple Planners. The small size of this group confirms
summaries of older HRS waves where many people indicated they had given little thought
to retirement even when they were just a few years away from leaving the workforce
(Lusardi 1999, 2002, 2003). Our results also confirm a widespread lack of retirement
planning, even among the educated (Yakobosky and Dickempers 1997; Ameriks, Caplin
and Leahy 2004). It is also consistent with work by Mitchell (1988) and Gustman and
Steinmeier (1999) who found that workers seem to know very little about their Social
Security and pension benefits, two of the most important components of retirement
wealth. In fact, close to half of workers in the HRS analyzed by Gustman and Steinmeier
(2004) could not report their type of pension plan, and an even larger portion was ignorant
of future Social Security benefits.
6
Table 2 here
A key advantage of our module, compared to previous core HRS questions and
other surveys, is that we probe further to inquire about the outcomes associated with
undertaking planning and related calculations. Panel A of Table 2 indicates that only 58
percent of those who tried to develop a plan actually did so, while another handful “more
11
or less” developed a plan (nine percent). Both of these groups we refer to below as the
Serious Planners. The high failure rate, so far as developing a plan is concerned,
underscores the fact that retirement projections are difficult to do. If we consider those
who responded positively to the question, as many as half of simple planners did not
succeed in developing a plan, another disappointing finding. Furthermore, of the subset of
serious planners, only one-third (38 percent) was always able to stick to its plan, while
half were “mostly” able to stick to their plans (below we call these respondents Successful
Planners). In the sample as a whole, this represents a meager 19 percent overall rate of
successful planning. Of course, households may face unexpected shocks making them
deviate from plans, but the fact remains that few respondents do what the economic
models suggest that they should. In other words, planning for retirement is difficult, few
do it, and fewer still think they get it right.
To further evaluate what planning means and what people actually do when
planning for retirement, we also asked respondents to indicate which tools they used in the
process. It is possible that those who used crude or inaccurate tools were also those who
had low planning success. In fact, respondents used a wide variety of tools to calculate
their retirement needs (see Panel A of Table 3; note that these questions were asked only
of those who reported they attempted a retirement saving calculations). Results show that
between one-quarter and one-fifth of respondents talked to family/relatives or co-
workers/friends, while one-third or more used formal means such as retirement
calculators, retirement seminars, or financial experts. Successful Planners were more
likely to use formal means (over 40 percent), whereas Simple Planners – some of whom
tried and failed – tended to rely on less formal approaches. The Table also shows that
12
financial literacy is correlated with planning tools, even though unevenly. The list of tools
does not exhaust what people might do; in fact, as many as one quarter of the self-reported
planners indicated that they did not use any of the listed tools.
Table 3 here
Those who were correct regarding compound interest and inflation were more likely
to have attended a retirement seminar, suggesting that such seminars may provide
information (without further control variables we cannot hold constant other background
variables). Those knowledgeable about risk diversification also tend to use formal rather
than informal tools for planning. Panel B of Table 3 also reveals what the correlations
were between planners’ levels of financial literacy and the tools they used in their
planning efforts. Those who used more sophisticated tools were always more likely to get
the literacy questions right, as compared to those who relied on personal communications;
furthermore, the knowledge gap was relatively the greatest for the compound interest
question. Panel C shows that a very large segment – almost three-quarters (74 percent) of
the respondent pool – indicates that it always or mostly tracks its spending, and over half
(51 percent) always or mostly tries to set spending budget targets. This is impressive given
the low level of planning for retirement. It is unclear whether those undertaking the
spending budget efforts did so simply to get through the month without running out of
money, or whether these efforts indicate a greater sensitivity of retirement saving needs
and plans.
Prior work has established that planning has important implications for wealth
accumulation (Lusardi and Mitchell 2007a, 2007b). To this end, we report the distribution
of total net worth across different planning types in Table 4, and emphasize that, at the
13
median, planners accumulate three times the amount of wealth than non-planners.
Moreover, the amount of planning also matters: Those who are able to develop a plan and
those who can stick to the plan accumulate much more wealth than simple planners.
Table 4 here
Linking Financial Literacy and Planning
One reason people fail to plan for retirement, or do so unsuccessfully, may be
because they are financially illiterate. In this case, they may fail to appreciate the role of
(or may have a hard time solving problems with) compound interest, inflation, and risk.
Table 5 sheds light on the importance of financial literacy and the relationship with
planning in a multivariate Probit analysis of three dependent variables: who was a planner,
who developed a plan, and who was able to stick to a plan.
7
Column I in each case takes
on a value of 1 if the respondent was correct regarding the literacy variables (else, = 0);
Column II adds an indicator equal to 1 if the respondent indicated he did not know the
answer to the question (else, = 0); and Column III has the same dependent variable but
adds controls for demographics and specifically age, race, gender, educational attainment,
and a dummy for being a Baby-Boomer (Probit analysis is appropriate when the outcomes
are qualitative variables; the Table reports marginal effects.)
Table 5 here
The estimates reported are interesting along several dimensions. First, financial
literacy is strongly and positively associated with planning, and the results are statistically
significant at conventional levels. That is, planners of all types are much more likely to
give a correct answer to our basic questions about financial literacy (Column I). Second,
14
knowledge about risk diversification best differentiates between sophisticated and
unsophisticated respondents. Not only does it have a much larger estimated marginal
effect than being able to correctly answer the interest and the inflation questions, but it
also remains statistically significant even after accounting for the demographic
characteristics of the respondent. Third, lack of knowledge also matters. Even with respect
to those answering incorrectly, those who cannot answer the questions are much less
likely to plan and to succeed in their planning effort (Column II). What appears most
crucial is a lack of knowledge about interest compounding, which makes sense since basic
numeracy is crucial for doing calculations about retirement saving. Columns III report
estimates after controlling for demographic characteristics, and some indicators of
financial literacy remain statistically significant even after we account for these factors.
For example, financial literacy clearly is linked to planning above and beyond the effect of
education. Accordingly, the information provided in the financial literacy variables may
prove very useful in explaining the differences we observe among households in their
behavior toward retirement wealth accumulation, to which we now turn.
Wealth Accumulation and Financial Literacy
If financial illiteracy leads to poor or no planning, it may also affect wealth
accumulation. Lusardi (2003) finds that those who plan accumulate more wealth before
retirement and are more likely to invest in stocks. Moreover, planners are more likely to
experience a satisfying retirement, perhaps because they have higher financial resources to
rely on after they stop working. In Table 6 (Panel A), we report estimates from a simple
regression of total net worth on the three dummies measuring financial literacy and a set
15
of demographic characteristics. Here wealth is defined as the sum of checking and savings
accounts, certificate of deposits and other short-terms assets, bonds, stocks, other assets,
housing equity, other real estate, IRAs and Keoghs, business equity, and vehicles minus
all debts.
8
Controls include age, sex, race, education attainment, marital status, place of
birth, and income. Since the direction of causality is unclear, we estimate the model in
both the full sample and also for quartiles of the wealth distribution.
Table 6 here
The results indicate that financial illiteracy is particularly pronounced among those
with low income, low education, and those with low wealth holdings. Further, financial
literacy is positively correlated with wealth at the bottom of the wealth distribution, which
suggests that those who have basic financial knowledge are better able to save. Those
having a command of basic numeracy and who understand risk diversification also have
higher wealth holdings, something of a remarkable result given that we control for several
of the demographic characteristics that elsewhere have been linked to low financial
literacy (race, gender and low income); we also account for educational attainment.
Table 6B reports estimates from a Probit model of stock ownership. The
hypothesis here is that financial literacy will be influential over portfolio choice: if
investors do not understand interest compounding, inflation, or risk diversification, they
are less likely to invest in complex assets such as stocks. We control for both the socio-
demographics listed above and additionally add total net worth. The findings indicate a
strong positive correlation between stock ownership and knowledge of risk diversification,
for both the total sample and across education groups. Basic numeracy also plays a role,
but mostly for those with high education (defined as having more than a high school
16
degree); this is true even after accounting for education and total net worth. These findings
may help explain the “puzzle” of why so few households hold stocks (Haliassos and
Bertaut 1995). Moreover, they may shed light on another puzzling finding in household
surveys such as the Survey of Consumer Finances. When asked how much risk
respondents are willing to take, a large majority (more than 60 percent) state they are
unwilling to take any financial risk. This may be due not only to strong risk aversion, but
also to the fact that many respondents feel they simply do not understand risk
diversification.
Conclusions and Implications
As more individuals approach and cross over the retirement threshold, it is crucial
to ascertain whether they actually know how to plan for retirement and whether they seem
able to execute these plans effectively. Our HRS module is informative in this regard, as
it asks about people’s basic financial literacy in terms of their comprehension of
compound interest rates and inflation, along with the more nuanced concept of risk
diversification. It is disturbing that only half of the respondents can correctly answer
questions regarding interest compounding and inflation, and only one-third can correctly
answer both of those two questions and a question about risk diversification. This
suggests widespread financial illiteracy among older Americans. When we examine
whether people tried to figure out how much they need to save for retirement, whether
they devised a plan, and whether they succeeded at the plan, the news is also not good.
Fewer than one-third of this cohort on the verge of retirement had ever tried to come up
with a retirement plan, and only two-thirds of these succeeded. In the sample as a whole,
17
fewer than one in five of these older Americans engaged in successful retirement
planning.
Furthermore, we show that financial knowledge and planning are clearly
interrelated, and keeping track of spending and budgeting appears conducive to retirement
saving. Finally, we evaluate the planning tools people use. It is interesting that the
respondents who did plan were less likely to talk to family/relatives or co-workers/friends,
and more likely to use formal means such as retirement calculators, retirement seminars,
or financial experts. Inasmuch as planning is an important predictor of saving and
investment success, we may have uncovered an important explanation for why household
wealth holdings differ, and why some people enter retirement with very low wealth (Venti
and Wise 2001; Lusardi 1999; Mitchell and Moore 1998; Moore and Mitchell 2000). The
empirical analysis here suggests that financial literacy can play a key role on both savings
and portfolio choice.
Our work has relevance for policy in several directions. First, there has been a
long-term growth in financial planning products, and service providers (Hung, Clancy,
and Dominitz 2011). Also governments and nonprofits have sponsored programs to spur
financial education, and employers are increasingly offering retirement seminars to their
workers as well (Clark, Morrill, and Allen 2011; Clark and D’Ambrosio 2002; Clark et al.
2003, 2004; Collins 2011). While some researchers suggest that such programs will have
only minimal effects on saving, our work suggests that this may be due to the lack of well-
targeted content. For example, if financial illiteracy is widespread among particular
subsets of employees, a one-time financial education lesson may be insufficient to
influence planning and saving decisions. Conversely, education programs targeted
18
specifically to particular subgroups may be better suited to address substantial differences
in preferences and saving needs.
Acknowledgements
The research reported herein was pursuant to a grant from the US Social Security
Administration (SSA) funded as part of the Retirement Research Consortium (RRC) and
the Pension Research Council/Boettner Center at the Wharton School. Without
implicating them, we are grateful for comments provided by Alberto Alesina, Rob
Alessie, Maristella Botticini, John Campbell, Andrew Caplin, Sewin Chan, Gary
Engelhardt, Alan Gustman, Mike Hurd, Arie Kapteyn, Mauro Mastrogiacomo, Mary Beth
Ofstedal, William Rodgers, Chris Snyder, Maarten van Rooij, Arthur van Soest, and Steve
Utkus. Helpful suggestions were offered by participants at conference at Dartmouth,
Harvard, Rand, the NBER, the Retirement Research Consortium, the Dutch Central Bank,
and the American Economic Association. Mark Christman and Jason Beeler provided
excellent research assistance. Opinions and errors are solely those of the authors and not
of the institutions with whom the authors are affiliated. Findings and conclusions do not
represent the views of the SSA, any agency of the Federal Government, or the RRC.
19
References
Agnew, Julie and Lisa Szykman (2005). “Asset Allocation and Information Overload: The
Influence of Information Display, Asset Choice and Investor Experience.” Journal
of Behavioral Finance 6: 57-70.
Ameriks, John, Andrew Caplin and John Leahy (2003). “Wealth Accumulation and the
Propensity to Plan”. Quarterly Journal of Economics 68: 1007-1047.
Ameriks, John, Andrew Caplin, and John Leahy (2004). “The Absent-Minded Consumer.”
NBER Working Paper 10216.
Bernheim, Douglas (1995). “Do Households Appreciate their Financial Vulnerabilities?
An Analysis of Actions, Perceptions, and Public Policy,” in Tax Policy and
Economic Growth. Washington, DC: American Council for Capital Formation, pp.
1-30
Bernheim, Douglas (1998). “Financial Illiteracy, Education, and Retirement Saving,” in
O.S. Mitchell and S. Schieber, eds., Living with Defined Contribution Pensions.
Philadelphia, PA: University of Pennsylvania Press, pp. 38-68.
Calvert, Laurent, John Campbell and Paolo Sodini (2007). “Down or Out: Assessing the
Welfare Costs of Household Investment Mistakes.” Journal of Political Economy
115: 707-747.
Campbell, John (2006). “Household Finance,” Journal of Finance, 61(4): 1553-1604.
Chan, Sewin and Ann Huff Stevens (2003). “What You Don’t Know Can’t Help You:
Knowledge and Retirement Decision Making.” New York University Working
Paper.
20
Christelis, Dimitris, Tullio Jappelli, and Mario Padula (2005). “Health Risk, Financial
Information and Social Interaction: the Portfolio Choice of European Elderly
Households”. University of Salerno Working Paper.
Clark, Robert, and Madeleine D’Ambrosio (2002). “Saving for Retirement: The Role of
Financial Education.” TIAA-CREF Institute Working paper 4-070102-A.
Clark, Robert, Madeleine D’Ambrosio, Ann McDermed, and Kshama Sawant (2003).
“Financial Education and Retirement Saving.” TIAA-CREF Institute Working
Paper 11-020103.
Clark, Robert, Madeleine D’Ambrosio, Ann McDermed, and Kshama Sawant (2004).
“Sex Differences, Financial Education and Retirement Goals” in O.S. Mitchell and
S. Utkus, eds., Pension Design and Structure: New Lessons from Behavioral
Finance. Oxford: Oxford University Press, pp. 185-206.
Clark, Robert L., Melinda S. Morrill, and Steven G. Allen (2011). ‘Pension Plan
Distributions: The Importance of Financial Literacy,’ in O.S. Mitchell and A.
Lusardi, eds., Financial Literacy: Implications for Retirement Security and the
Financial Marketplace. Oxford: Oxford University Press.
Collins, J. Michael (2011). ‘Improving Financial Literacy: The Role of Nonprofit
Providers,’ in O.S. Mitchell and A. Lusardi, eds., Financial Literacy: Implications
for Retirement Security and the Financial Marketplace. Oxford: Oxford University
Press.
Duflo, Esther and Emmanuel Saez (2003). “The Role of Information and Social
Interactions in Retirement Plan Decisions: Evidence from a Randomized
Experiment”. Quarterly Journal of Economics 118: 815-842.
21
Duflo, Esther and Emmanuel Saez (2004). “Implications of Pension Plan Features,
Information, and Social Interactions for Retirement Saving Decisions,” in O.S.
Mitchell and S. Utkus, eds., Pension Design and Structure: New Lessons from
Behavioral Finance. Oxford: Oxford University Press: pp. 137-153.
Employee Benefits Research Institute (EBRI) (1996). “Participant Education: Actions and
Outcomes”. EBRI Issue Brief 169. January.
Employee Benefits Research Institute (EBRI) (2001). “Retirement Confidence Survey
(RCS), Minority RCS, and Small Employer Retirement Survey”. EBRI Issue Brief
234. June.
Gustman, Alan and Tom Steinmeier (1999). “Effects of Pensions on Savings: Analysis
with Data from the Health and Retirement Study”. Carnegie-Rochester
Conference Series on Public Policy 50: 271-324.
Gustman, Alan and Tom Steinmeier (2004). “What People Don’t Know about their
Pensions and Social Security.” In Private Pensions and Public Policies. Edited by
William Gale, John Shoven and Mark Warshawsky, Washington, DC: Brookings
Institution: 57-125.
Haliassos, Michael and Carol Bertaut (1995). “Why Do So Few Hold Stocks?” Economic
Journal, 105: 1110-1129.
Hilgert, Marianne, Jeanne Hogarth, and Sondra Beverly (2003). "Household Financial
Management: The Connection between Knowledge and Behavior," Federal
Reserve Bulletin, 309-322.
Hogarth, Jeanne, Chris Anguelov, and Jinkook Lee (2004). “Why Don’t Households Have
A Checking Account?” The Journal of Consumer Affairs, 38: 1-34.
22
Hogarth, Jeanne and Marianne Hilgert (2002). "Financial Knowledge, Experience and
Learning Preferences: Preliminary Results from a New Survey on Financial
Literacy," Consumer Interest Annual, 48.
Hung, Angela A., Noreen Clancy, and Jeff Dominitz (2011). ‘Investor Knowledge and
Experience with Investment Advisers and Broker-Dealers,’ in O.S. Mitchell and
A. Lusardi, eds., Financial Literacy: Implications for Retirement Security and the
Financial Marketplace. Oxford: Oxford University Press.
Lusardi, Annamaria (1999). “Information, Expectations, and Savings for Retirement,” in
H. Aaron, ed., Behavioral Dimensions of Retirement Economics. Washington, DC:
Brookings Institution Press and Russell Sage Foundation: pp. 81-116.
Lusardi, Annamaria (2002). “Preparing for Retirement: The Importance of Planning
Costs”. National Tax Association Proceedings 2002: 148-154.
Lusardi, Annamaria (2003). “Planning and Saving for Retirement”. Dartmouth College
Working Paper.
Lusardi, Annamaria and Olivia S. Mitchell (2007a). “Baby Boomer Retirement Security:
The Roles of Planning, Financial Literacy, and Housing Wealth.” Journal of
Monetary Economics. 54(1) January: 205-224.
Lusardi, Annamaria and Olivia S. Mitchell (2007b). “Financial Literacy and Retirement
Planning: New Evidence from the RAND American Life Panel.” NBER Working
Paper.
Lusardi, Annamaria and Olivia S. Mitchell (2007c). “Financial Literacy and Retirement
Preparedness: Evidence and Implications for Financial Education.” Business
Economics 42, 35-44.
23
Lusardi, Annamaria and Olivia S. Mitchell (2008). “Planning and Financial Literacy:
How Do Women Fare?” American Economic Review P&P: 98:2, 413–417
Lusardi, Annamaria and Olivia S. Mitchell (2009). “How Ordinary Consumers Make
Complex Economic Decisions: Financial Literacy and Retirement Readiness.”
NBER Working Paper 15350.
Lusardi, Annamaria, Olivia S. Mitchell, and Vilsa Curto (2010). “Financial Literacy
among the Young: Evidence and Implications for Consumer Policy.” Journal of
Consumer Affairs. (44, 2): 358-380.
Mandell, Lewis (2004). Financial Literacy: Are We Improving? Washington, D.C.:
Jump$tart Coalition for Personal Financial Literacy.
Mastrobuoni, Giovanni (2005). “Do Better-Informed Workers Make Better Retirement
Choice? A Test Based on the Social Security Statement.” Princeton University
Working Paper.
Miles, David (2004). The UK Mortgage Market: Taking a Longer-Term View. London:
UK Treasury.
Mitchell, Olivia (1988). “Worker Knowledge of Pensions Provisions.” Journal of Labor
Economics 6: 28-29.
Mitchell, Olivia S. and James Moore (1998). “Can Americans Afford to Retire? New
Evidence on Retirement Saving Adequacy.” Journal of Risk and Insurance 65:
371-400.
Moore, Danna (2003). “Survey of Financial Literacy in Washington State: Knowledge,
Behavior, Attitudes, and Experiences.” Social and Economic Sciences Research
Center Technical Report 03-39, Washington State University.
24
Moore, James, and Olivia S. Mitchell (2000). “Projected Retirement Wealth and Saving
Adequacy,” in O.S. Mitchell, B. Hammond, and A. Rappaport, eds., Forecasting
Retirement Needs and Retirement Wealth. Philadelphia, PA: University of
Pennsylvania Press, pp. 68-94.
National Council on Economic Education (NCEE) (2005). What American Teens and
Adults Know About Economics. Washington, DC: NCEE.
Venti, Steven and David Wise (2001). “Choice, Chance, and Wealth Dispersion at
Retirement,” in S. Ogura, T. Tachibanaki, and D. Wise, eds., Aging Issues in the
United States and Japan. Chicago, IL: University of Chicago Press, pp. 25-64.
Yakoboski, Paul and Jennifer Dickemper (1997). “Increased Saving but Little Planning.
Results of the 1997 Retirement Confidence Survey”. EBRI Issue Brief 191.
Washington, D.C.: EBRI.
25
Endnotes
1
See Campbell (2006) for an excellent discussion of the myriad problems households face
when making financial decisions.
2
In conventional economic models, assets in the last period of life will not exceed zero
and the consumer does not die in debt.
3
Other surveys also find similar results concerning knowledge regarding properties of
bonds, stocks, and mutual funds (c.f. Agnew and Szykman 2005)
4
Similar findings are found internationally; for instance, Miles (2004) shows that U.K.
borrowers also display poor understanding of mortgages and interest rates, and Christelis,
Jappelli, and Padula (2005) use SHARE surveys from several European countries to show
that these respondents also score low on financial numeracy and literacy scales.
5
For brevity we exclude other minority groups and exclude those who do not answer the
questions (a small group).
6
There is also evidence that knowledge about pensions and Social Security affects
retirement decisions; see Chan and Huff Stevens (2003); Duflo and Saez (2003, 2004);
and Mastrobuoni (2005).
7
It is possible that causality may also go the other way: that is, those who plan may also
become more financially literate and develop the ability to do retirement calculations; for
discussion of endogeneity considerations, see Lusardi and Mitchell (2007a).
8
The analysis herein uses the 2004 wealth data that included imputes for those who did not
report assets or debt.
26
Table 1. Financial Literacy Patterns
(Source: Authors’ calculations based on 2004 Health and Retirement Survey, Planning Module -
unweighted data)
Panel A: Distribution of Responses to Financial Literacy Questions
Responses
Correct Incorrect DK Refuse
Compound Interest
67.1%
22.2%
9.4%
1.3%
Inflation
75.2%
13.4%
9.9%
1.5%
Stock Risk
52.3%
13.2%
33.7%
0.9%
Panel B: Joint Probabilities of Being Correct to Financial Literacy Questions
All 3 responses
correct
Only 2 responses
correct
Only 1 response
correct
No responses
correct
Proportion
34.3%
35.8%
16.3%
9.9%
Note: DK = respondent indicated “don’t know
27
Table 2. Prevalence of Retirement Planning Calculations
(Source: Authors’ calculations based on 2004 Health and Retirement Survey, Planning Module -
unweighted data)
Panel A. Proportion of Planners in Respective Sub-Groups
Did you try to figure out how much to save for retirement?
Yes No Refuse/DK
31.3% 67.8% 0.9%
Did you develop a plan?
Yes More or Less No Refuse/DK
58.4% 9.0% 32.0% 0.6%
Were you able to stick to the plan?
Always Mostly Rarely Never Refuse/DK
37.7% 50.0% 8.0% 2.6% 1.0%
Panel B. Proportion of Planners in the Full Sample
Question
Proportion of Sample
Simple Planners
Yes to “tried to figure out how much to save for retirement”
31.3%
Serious Planners
Replied Yes/More or less to “developed a plan”
21.1%
Successful Planners
Replied Always/Mostly to “able to stick to the plan”
18.5%
28
Table 3. Links between Planning Tools, Planning Success, and Financial Literacy
(Source: Authors’ calculations based on 2004 Health and Retirement Survey, Planning Module -
unweighted data)
Panel A: Tools Planners Report Using
Tools
Simple Planners
n = 397
Successful Planners
n = 235
Talk to family/friends
21.1%
(.409)
17.4%
(.380)
Talk to coworkers/friends
24.7%
(.432)
21.3%
(.410)
Attend retirement seminar
35.3%
(.479)
40.4%
(.492)
Use calculator/worksheet
37.8%
(.485)
43.4%
(.497)
Consult financial planner
39.0%
(.488)
49.4%
(.501)
Panel B: Correlation Between Planning, Tools Used, and Financial Literacy
Simple
Planners
n = 397
Talk to
family/
friends
n = 84
Talk to
coworkers/
friends
n = 98
Attend
retirement
seminar
n = 140
Use
calculator/
worksheet
n = 150
Consult
financial
planner
n = 155
Correct on Compound
Interest
75.3%
65.5%
69.4%
77.9%
83.3%
80.6%
Correct on Inflation
84.4%
82.1%
88.8%
88.6%
89.3%
86.5%
Correct on Stock Risk
52.2%
65.5%
71.4%
80.0%
79.3%
73.5%
Panel C. Budgeting Questions: All Respondents
Always
Mostly
Rarely
Never
Do not
know/Refuse
Track spending
43.2%
30.8%
14.7%
11.0%
0.3%
Set spending budget
23.6%
27.6%
22.4%
26.0%
0.5%
29
Table 4. Planning and Wealth Holdings
(Source: Authors’ calculations based on 2004 Health and Retirement Survey, Planning Module -
unweighted data)
Non-Planners Planners
Simple Planners
Serious Planners Successful Planners
25th percentile 30,400
107,750 171,000 197,500
Median 122,000
307,750 370,000 410,000
75th percentile
334,500 641,000 715,000 781,500
Mean
338,418 742,843 910,382 1,002,975
Note: This table reports the distribution of total net worth across different planning types. Simple Planners are those
who tried to calculate how much they need to save for retirement; Serious Planners are those who were able to
develop a saving plan; Successful Planners are those who were able to stick to their saving plan. The total number of
observations is 1,269.
32
Figure 1a -- Distribution of Responses to Compound Interest Across
Race
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Response
Proportion of Given Response
s
White
72.30% 19.00% 7.50%
Black
53.90% 29.20% 16.30%
His
p
anic
46.70% 35.20% 14.30%
Correct Incorrect DK
Figure 1b -- Distribution of Responses to Inflation Across Race
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
Response
Proportion of Given Respons
e
White
78.50% 12.00% 8.00%
Black
65.20% 18.00% 15.70%
His
p
anic
59.00% 20.00% 18.10%
Correct Incorrect DK
33
(Source: Authors’ calculations based on 2004 Health and Retirement Survey, Planning Module -
unweighted data)
Figure 1c -- Distribution of Responses to Stock Risk Across Race
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
Response
Proportion of Given Respons
e
White
55.20% 12.80% 31.00%
Black
37.10% 21.30% 41.60%
His
p
anic
51.40% 8.60% 39.00%
Correct Incorrect DK
34
Figure 2a -- Distribution of Responses to Compound Interest Across
Education
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
Response
Proportion of Given Respons
e
Elementary
30.20% 35.80% 28.30%
Less than High School
51.40% 28.80% 17.40%
High School
64.80% 24.00% 10.30%
Some College
74.00% 20.30% 4.70%
Colle
g
e and More
81.20% 13.80% 3.30%
Correct Incorrect DK
35
Figure 2b -- Distribution of Responses to Inflation Across Education
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
Response
Proportion of Given Respons
e
Elementary
49.10% 20.70% 26.40%
Less than High School
62.30% 14.60% 20.70%
High School
75.20% 13.10% 10.30%
Some College
79.00% 14.40% 5.30%
Colle
g
e and More
85.10% 10.50% 3.30%
Correct Incorrect DK
Figure 2c -- Distribution of Responses to Stock Risk Across
Education
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Response
Proportion of Given Respons
e
Elementary
43.40% 5.70% 50.90%
Less than High School
30.70% 12.30% 56.10%
High School
50.40% 16.10% 33.50%
Some College
56.70% 12.00% 30.30%
Colle
g
e and More
70.20% 13.40% 14.50%
Correct Incorrect DK
36
(Source: Authors’ calculations based on 2004 Health and Retirement Survey, Planning Module -
unweighted data)
37
(Source: Authors’ calculations based on 2004 Health and Retirement Survey, Planning Module -
unweighted data)
Figure 3 -- Distribution of Responses Across Gender
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
Responses
Proportion of Given Response
s
Male
74.70% 18.60% 6.10% 82.20% 11.50% 5.70% 59.30% 14.80% 24.90%
Female
61.90% 24.70% 11.60% 70.50% 14.70% 12.70% 47.50% 12.30% 39.40%
Correct Incorrect DK Correct Incorrect DK Correct Incorrect DK
Compound Inflation Stock Risk