Financial literacy and financial behavior:
Assessing knowledge and confidence

Colleen Tokar Asaada,*
aSchool of Business, Baldwin Wallace University, Berea, OH 44017, USA

Abstract

This article explores how financial literacy, comprised of both actual financial knowledge and
perceived financial confidence, affect financial decisions. Using national survey data from the United
States, results indicate that financial confidence is a critical component of financial literacy and is
important across all knowledge levels. However, overconfident individuals, or those with high
confidence (or self-assessed) knowledge but low actual knowledge, have a higher propensity to engage
in risky (costly) financial behaviors. Together, results suggest that financial literacy initiatives should
focus not only on factual knowledge, but on helping individuals achieve a healthy dose of confidence.
© 2015 Academy of Financial Services. All rights reserved.

Jel classification: D03; D14; D80

Keywords: Financial literacy; Confidence; Overconfidence; Financial behaviors; Risk

1. Introduction

Financial literacy is a measure of the degree to which one understands key financial concepts
and possesses the ability and confidence to manage personal finances through appropriate
short-term decision making and sound, long-range financial planning, while mindful of life
events and changing economic conditions. (Remund, 2010, p. 284)

Financial decision making is an essential component of day-to-day life, from minor
decisions such as deciding whether or not to purchase a latte to major decisions such as
taking on a home mortgage. Several definitions of financial literacy highlight that to make
sound financial decisions, individuals must not only possess the necessary knowledge, but

* Corresponding author. Tel.: �1-440-826-2392; fax: �1-440-826-3868.
E-mail address: colleen.tokar@gmail.com

Financial Services Review 24 (2015) 101–117

1057-0810/15/$ – see front matter © 2015 Academy of Financial Services. All rights reserved.



must also have “the ability and confidence” to apply their knowledge. This article
explores how financial literacy influences financial behaviors. By examining two com-
ponents of financial literacy, financial knowledge, and financial confidence (or perceived
knowledge), this article demonstrates that both components are critically important to
sound decision-making.

Using survey data from FINRAs 2012 National Financial Capability Study (NFCS),
financial knowledge is measured by the number of correct answers to multiple-choice and
true or false questions. Financial confidence reflects a self-assessed level of financial
knowledge, which may or may not coincide with measured financial knowledge. This article
demonstrates that both knowledge and confidence influence financial behaviors, and surpris-
ingly, the effect of financial confidence on behaviors is just as important as the effect of
financial knowledge. Furthermore, confidence is an important predictor of financial behavior
across all actual financial knowledge level groups.

Additionally, by examining the interaction of financial knowledge and confidence, this
study expands on the literature related to overconfidence, or the tendency to overestimate
one’s accuracy and to underestimate risk. In instances where confidence exceeds actual
knowledge (i.e., overconfidence), an individual has a greater likelihood of engaging in risky
(costly) financial behaviors, such as taking out a title-loan. A key contribution, therefore, is
a better understanding of how confidence influences financial behaviors: confidence is good,
but not if it greatly exceeds actual knowledge. Prior research associating perceived knowl-
edge with individual financial behaviors has failed to reconcile instances in which inaccurate
self-assessments can be harmful. This article shows that, overall, positive illusions are good.
However, this article also illuminates the particular risky situations in which overconfidence
is self-injurious. These findings are relevant across a multitude of disciplines and are
pertinent to individuals, practitioners, and institutions alike. There are clear implications for
financial literacy initiatives, initiatives that are of utmost importance given the pervasiveness
of financial decisions in every individual’s daily life.

The article is organized as follows. Section 2 provides an overview of the literature,
touching on financial literacy, perceived knowledge, and overconfidence. Section 3 details
the hypotheses, as well as an overview of the data, measures, and methods. Section 4
presents the results and Section 5 concludes.

2. Literature review

2.1. Financial literacy

Mandell (2008, p. 257) describes financial literacy as “the ability of consumers to make
financial decisions in their own best short- and long-term interests.” At its most basic level,
“financial literacy relates to a person’s competency for managing money” and “is typically
measured at the individual level and then aggregated by groups” (Remund, 2010, p. 279).
Because of the changing economic environment (e.g., see Organisation for Economic
C-operation and Development [OECD], 2005), financial literacy initiatives have received
much attention.

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Research suggests that financial education has a positive effect on financial behaviors:
education programs and seminars affect savings and total financial wealth (Lusardi, 2004),
and individuals who studied economics or business in high school are less likely to be
unbanked (Bernheim, Garrett, and Maki, 2001; Grimes, Rogers, and Smith, 2010). However,
other research questions the effectiveness of financial literacy initiatives: educating employ-
ees about the risks of employer stock does not significantly affect 401k holdings (Choi,
Laibson, Madrian, and Metrick, 2005) and high school students who complete a semester of
a financial literacy course are no more financially literate than high school students who have
not completed the course (Mandell and Klein, 2009). U.S. households with higher levels of
knowledge engage in more financial planning, although this positive relationship is weak
(Alhenawi and Elkhal, 2013).

If financial knowledge is not enough, what other factors influence the financial-decision
making process? This article explores how a specific cognitive element, perceived knowl-
edge (or financial confidence), shapes financial behaviors.

2.2. Perceived knowledge (confidence)

Researchers often emphasize what people actually know at a given time, yet understand-
ing perceptions is also important. Park, Gardner, and Thukral (1988) emphasize that per-
ceived knowledge is related to cognitive functioning, including recognition (Schachter,
1983), identification (Nelson, Gerler, and Narens, 1984), and problem solving (Metcalfe,
1986). Both an individual’s actual financial knowledge and perceived financial knowledge
influence investments (Kyrychenko and Shumb, 2009), retirement planning (Parker, Bruin,
Yoong, and Willis, 2011), and credit card behaviors (Allgood and Walstad, 2013). Further-
more, Carpena, Cole, Shapiro, and Zia (2011) emphasize that aside from numeracy based
knowledge, financial literacy may also affect decisions through an individual’s increased
awareness and initiative. Thus, financial confidence is a critical component of financial
decision making.

Often there is a discrepancy between an individual’s actual knowledge and an individual’s
self-perception, or confidence. Correlations between actual and perceived financial knowl-
edge vary considerably on an individual basis (Agnew and Szykman, 2005). It is interesting
to look at the interactions and differences between these two measures of knowledge,
specifically in situations where confidence exceeds actual knowledge.

2.2.1. Overconfidence
Overconfidence refers to an individual’s propensity to overestimate the accuracy of his or

her estimates, meaning that there is “a positive difference between assessed confidence and
observed achievement” (Campbell, Goodie, and Foster, 2004, p. 299). Such overestimation,
is more likely to occur “after unexpectedly difficult tasks” (Healy and Moore, 2007, p. 4). For
example, less skilled financial planners are more confident than the more skilled (Cordell,
Smith, and Terry, 2011). Individuals who are overconfident have narrow confidence intervals
and, therefore, tend to overestimate precision and underestimate risk (Goel and Thakor,
2008). Often, those who take more risk are not necessarily risk-seeking, but are less aware

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of the risk (Simon, Houghton, and Aquino, 2000). Even when given high incentives for
accuracy, individuals still exhibit overconfidence (Williams and Gilovich, 2008).

In a theoretical model, Goel and Thakor (2008) posit that CEO overconfidence effects firm
value nonmonotonically, meaning that overconfidence is good up to a point (to overcome
initial risk aversion) but then is harmful (leading to excessive risk-taking). Likely, these
findings will hold for the individual financial decisions considered in this analysis: that
overconfidence is “good” for most financial decisions, but overconfidence is harmful for
risky financial decisions. As Johnson and Fowler (2011, p. 320) warn, “it seems that we are
likely to become overconfident in precisely the most dangerous of situations.”

3. Method

3.1. Hypotheses and research approach

Hypothesis 1 (H1): Financial confidence predicts financial behavior.

Because cognitive functioning is a critical component of the decision making process (see
Section 2.2.), financial confidence likely influences all types of financial decisions. In fact,
Carpena et al., (2011) find that financial education initiatives do not equip individuals with
the numeracy knowledge needed to make complex financial decisions; however, the initia-
tives greatly affect awareness and familiarity with financial services and products. Thus,
confidence is likely an important component of financial decision making. Logistic regres-
sions explore whether financial confidence affects financial behaviors above and beyond the
influence of actual (measured) financial knowledge.

Hypothesis 2 (H2): Overconfident individuals (high confidence, low knowledge) are
most likely to engage in risky financial behaviors.

Overconfidence, or “that upward gap between what we know and what we think we know”
(Cordell, Smith, and Terry, 2011, p. 255), results in an overestimation of accuracy and
underestimation of risk (see Section 2.2.1.). Based on Goel and Thakor’s (2008) theoretical
model, overconfidence may be beneficial to overcome initial risk aversion, but also leads to
excessive risk-taking. Those individuals who self-assess their financial knowledge as higher
than their actual knowledge may improperly assess risk levels, resulting in risky financial
behaviors. It is hypothesized, then, that in most circumstances higher levels of confidence
leads to “better” financial behaviors. However, too much confidence may be harmful in
riskier circumstances because the risk level is not properly assessed. Logistic regressions
explore whether overconfidence leads to an increased propensity to engage in risky (or
costly) financial behaviors.

3.2. Data

Data are obtained from the 2012 National Financial Capability Study (NFCS) commis-
sioned by the Financial Regulatory Authority’s (FINRA) Investor Education Foundation.
The study, with support from the U.S. Department of the Treasury and the President’s

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Advisory Council on Financial Literacy, aims to measure American’s money skills. The
state-by-state survey collected data from 25,509 respondents via an online survey. All
analyses are weighted based on national distributions within age/gender, ethnicity, education,
and Census division. Table 1 provides descriptive statistics for the survey sample. The
sample is �51% female, 67% White, 53% married, and over 62% has an education beyond
high school.

3.3. Measuring financial literacy

3.3.1. Financial knowledge
Five survey questions are used to measure basic financial knowledge. Table 2 documents

the five questions and the survey results. The dummy variables Interest, Inflation, Bond,
Mortgage, and Risk are created whereby a 1 represents a correct response and a 0 represents
an incorrect response, a “Don’t Know,” or a refusal to answer.1

Approximately 14% of the respondents answered all five financial literacy questions
correctly. Consistent with previous findings the results point to differences in knowledge
across gender and race (Fisher, 2010; Lusardi, 2008; Mandell, 2006).2 These gender differ-

Table 1 Characteristics of the sample

N %

Total sample 25,509 100.0
Gender/sex

Male 12,392 48.6
Female 13,117 51.4

Age
18–24 3,139 12.3
25–34 4,669 18.3
35–44 4,171 16.3
45–54 5,005 19.6
55–64 4,569 17.9
65� 3,956 15.5

Ethnicity/race
White 16,956 66.5
Non-White 8,553 33.5

Marital status
Married 13,782 53.4
Single 7,469 28.2
Separated or divorced 10,899 14.0
Widowed 985 4.4

Education
Not complete high school 2,210 8.7
High school graduate 5,695 22.3
GED 1,818 7.1
Some college 9,160 35.9
College graduate 4,105 16.1
Post-graduate education 2,519 9.9

Data was obtained from 2012 FINRAs National Financial Capability Study and is weighted based on national
distributions within age/gender, ethnicity, education, and Census division.

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ences hold across age groups (Lusardi and Mitchell, 2007; Lusardi, Mitchell, and Curto,
2010) and cross-nationally (Lusardi and Mitchell, 2011). Also consistent with the literature,
there is an inverted U-shape relation between age and financial literacy and a positive relation
between education levels and literacy levels (Lusardi and Mitchell, 2011).

3.3.2. Financial confidence (or perceived knowledge)
In the NFCS survey, participants rated their own financial knowledge on a 7-point Likert

item scale whereby a “1” reflects low self-assessed levels of financial knowledge and a “7”
reflects high self-assessed levels of financial knowledge. The question, as presented in the
survey, reads, “On a scale from 1 to 7, where 1 means very low and 7 means very high, how

Table 2 Financial knowledge

Question Responses (N) Percentage

Interest: 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 19,112 74.9
Exactly $102 1,906 7.5
Less than $102 1,407 5.5
Don’t know 2,818 11.0
Prefer not to say 266 1.0

Inflation: Imagine that the interest rate on your savings account was 1% per year and inflation was 2% per
year. After 1 year, how much would you be able to buy with the money in this account?

More than today 2,201 8.6
Exactly the same 2,176 8.5
Less than today 15,630 61.3
Don’t know 5,164 20.2
Prefer not to say 334 1.3

Bond: If interest rates rise, what will typically happen to bond prices?
They will rise 5,014 19.7
They will fall 7,168 28.1
They will stay the same 1,290 5.1
There is no relationship� 2,186 8.6
Don’t know 9,545 37.4
Prefer not to say 306 38.6

Mortgage: A 15-year mortgage typically requires higher monthly payments than a 30-year mortgage, but the
total interest paid over the life of the loan will be less.

True 19,142 75.0
False 2,303 9.0
Don’t know 3,882 15.2
Prefer not to say 182 0.7

Risk: Buying a single company’s stock usually provides a safer return than a stock mutual fund.
True 2,209 8.7
False 12,366 48.5
Don’t know 10,715 42.0
Prefer not to say 219 0.9

The five financial literacy questions as they appear in FINRAs 2012 National Financial Capability Study.
Correct answers are italicized. Binary variables were created for each of the five literacy topics (Interest,
Inflation, Bond, Mortgage, and Risk) whereby a correct response is coded as 1. If the respondent incorrectly
answered the question, responded “Don’t know” or “Prefer not to say” the answer was coded as not correct
(or 0).

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would you assess your overall financial knowledge?” On average, individuals rated their
financial knowledge (Overall) as 5.15 on a 7-point scale. Table 3 shows that only 9.4% of
individuals self-assessed their knowledge level as below average, whereas 15.3% of indi-
viduals rated their knowledge as average and 75.2% rated their knowledge as above average.

Two additional questions, measured on a 7-point scale, assess confidence levels:

How strongly do you agree or disagree with the following statements?

Y I am good at dealing with day-to-day financial matters, such as checking accounts,
credit and debit cards, and tracking expenses.

Y I am pretty good at math.

As seen in Table 3, the majority of individuals rate themselves as better than average: the
mean and median responses are all above four. Robb, Babiarz, and Woodyard (2012)
measure financial confidence as an average of the confidence responses. Following their
method, an “average” financial confidence measure is created (Average) as the mean of the
three responses (Overall, Day-to-Day, Math).3

3.3.3. Knowledge and confidence
Allgood and Walstad (2013) develop a measure that accounts for both an individual’s

actual financial knowledge and perceived financial knowledge, arguing that the combination
provides “more robust and nuanced insights” about how financial literacy affects financial

Table 3 Financial confidence

Overall Day-to-Day Math

N % N % N %

1–Very low/strongly disagree 500 2.0 947 3.8 1,177 4.7
2 506 2.0 574 2.3 704 2.8
3 1,329 5.4 865 3.4 991 3.9
4–Average/neither agree or disagree 3,792 15.3 3,207 12.8 2,924 11.6
5 8,461 34.2 3,287 13.1 3,403 13.5
6 6,652 26.9 5,698 22.7 5,896 23.4
7–Very high/strongly agree 3,479 14.1 10,518 41.9 10,099 40.1
Mean 5.15 5.65 5.57
Median 5.00 6.00 6.00
Standard Deviation 1.30 1.60 1.70

Three questions in the NFCS survey touch on financial confidence: (1) “On a scale from 1 to 7, where 1 means
very low and 7 means very high, how would you assess your overall financial knowledge?” (Overall); “How
strongly do you agree or disagree with the following statements?” (2) “I am good at dealing with day-to-day
financial matters, such as checking accounts, credit and debit cards, and tracking expenses.” (Day-to-Day); (3) “I
am pretty good at math.” (Math) Respondent’s answering “Don’t Know” for overall financial knowledge (528,
or 2.1%); day-to-day matters (204, or 0.8%); and math (136, or 0.5%). Respondent’s that “prefer not to say” for
overall financial knowledge (790, or 3.1%); day-to-day matters (210, or 0.8%); and math (179, or 0.7%).
Correlations between the confidence measures of 58.2% (Day-to-Day and Math), 41.8% (Day-to-Day and
Overall), and 36.0% (Overall and Math). All correlations significant at the 1% level. An average financial
confidence measure (Average) is also created and represents the average of responses to the three confidence
questions (Overall, Day-to-Day, and Math).

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behavior. Following their methodology, a composite knowledge measure is created. First,
“high” and “low” groups are established for both financial knowledge and confidence, where
those individuals with above average scores are categorized as “high” and those individuals
with below average scores are categorized as “low.”4 Then four additional variables are
created to represent the four types of combined (knowledge-confidence) financial literacy
(High-High, High-Low, Low-High, and Low-Low). About 28% and 20% of the sample are
classified as High-High and Low-Low literacy, respectively. Approximately one-third of the
sample has High-Low literacy and about 10% of the sample is overconfident (Low-High
knowledge).

3.4. Measuring financial behaviors

The NFCS surveys numerous financial topics. The behaviors considered in this analysis
are detailed in the Appendix. Although it is not appropriate to label financial behaviors with
normative values (e.g., “good” and “bad” behaviors ultimately depend on individual pref-
erences and circumstances), it is possible to discern whether or not an individual is engaging
in a “good” or “recommended” financial practice. For example, checking your credit rating
is a “good” financial practice while being involved in a foreclosure process is a “bad”
financial practice. Applying Goel and Thakor’s (2008) theory, higher levels confidence will
lead to “better” financial decisions, except in the riskiest of circumstances.

Financial behaviors classified as “risky” are costly behaviors that are riskier and pricier
than other short-term loan alternatives, including: taking out an auto title loan; taking out a
short-term payday loan; receiving a tax advance on a refund; using a pawn shop; and using
a rent-to-own facility. If overconfident individuals underestimate risk, they will be more
likely than other groups to engage in these costly behaviors that jeopardize their resources.

4. Results

Logistic regressions explore how the two components of financial literacy influence
financial behaviors. In logistic regressions, the dependent variable is a binary variable and the
models attempt to predict whether or not an individual engages in a specific type of financial
behavior. The � coefficients are difficult to interpret; therefore, the odds ratio, a more useful
measure of effect size, is reported. The measure is the ratio of the likelihood of an event
occurring in one group to the likelihood of the same event occurring in another group.

In addition to the four financial knowledge groups, several other demographic factors are
considered (almost all of which are dummy variables), including: gender (female � 1); age
(18–24, 24–34, 35–44, 45–54, 55–64, or 65�); race (non-White � 1); education (�high
school, GED, high school graduate only, some college, college graduate only, or postgrad-
uate); employment status (self-employed, full-time, part-time, homemaker, student, unable,
unemployed, or retired); marital status (single, married, divorced or separated, or widowed
or widower); dependent children (no children or dependent children, one child, two children,
or three or more children); annual income (less than $15K, $15–25, $25–35, $35–50,
$50–75, $75–100, $100–150, or $150K or more); income-drop (� 1 if “experienced a large

108 C.T. Asaad / Financial Services Review 24 (2015) 101–117



drop in income which you did not expect” in the past 12 months); and risk tolerance (scale
from 1 to 10 whereby 1 means “not at all willing” to take risks with financial investments
and 10 means “very willing”). The use of these demographic controls is established in the
literature (e.g., see Allgood and Walstad, 2013 or Lusardi and Mitchell, 2011). Unless
otherwise noted, the omitted variables are: the Low-Low group, 18–24 age group, college
graduate, full-time employment, married, no dependent children, and annual income of at
least $50,000 but less than $75,000. All variables are interpreted in reference to these groups.

4.1. Predicting financial behaviors

In Table 4, financial knowledge and confidence are both statistically significant predictors
of financial behavior. Because the omitted variable is the Low-Low group, interpreting the
odds ratio of the low knowledge and high confidence group reflects a difference in confi-
dence, and interpreting the odds ratio of the high knowledge and low confidence group
reflects a difference in actual knowledge. For example, those with high confidence (holding
actual knowledge constant at a low level) are 1.131 times more likely to have obtained a
credit report whereas those with high actual knowledge (holding confidence constant at a low
level) are 1.294 times more likely to have obtained a credit report.

As a robustness check to ensure that confidence affects financial behaviors regardless of
the level of actual financial knowledge, Table 5 reconsiders the regressions in Table 4.
Instead of using the four knowledge groups as predictors, continuous variables are used to
measure Knowledge (ranging from 0 of 5 questions correct to 5 of 5 correct) and Confidence

Table 4 Financial literacy and financial behavior

High knowledge,
high confidence

High knowledge,
low confidence

Low knowledge,
high confidence

Savings and borrowing behaviors
Calculate 1.459*** 1.350*** 1.609***
Compare credit cards 1.205*** 1.456*** 1.650***
Credit report 1.329*** 1.131** 1.294***
Credit score 1.247*** 1.218*** 1.380***
Health insurance 1.055* 1.116* 1.133**
Life insurance 1.102*** 1.051 1.215***
Investments 1.429*** 1.569*** 1.170***
Loan from retirement account 0.801*** 0.724** 1.017
Home equity loan 0.943 1.176 1.393***
Foreclosure 0.892** 0.846 1.471***

Logistic regressions predicting financial behavior whereby the predictor variables control for gender, age,
education, employment status, marital status, income, income-drop, and risk tolerance. The dependent
variables are listed vertically and represent the financial behaviors (0 � did not engage in behavior; 1 �
engaged in behavior), which are detailed in the Appendix. The odds ratio for three financial knowledge
groups is reported, a ratio of the likelihood of an event occurring in one group to the likelihood of the same
event occurring in another group. The omitted variable is the low actual knowledge and low confidence
group. The odd ratios of the three reported knowledge groups are interpreted in reference to this omitted
group. The results for the control variables are not reported. ***, **, and * represent statistical significance
at the 1%, 5%, and 10% levels, respectively.

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(self-assessed rating from 1 to 7). Confidence is measured using overall financial confidence
(Overall) and an average financial confidence (Average). For interpretation purposes, stan-
dardized variables are used in the regression so that the odds ratio reflects how a one standard
deviation above or below the average affects financial behaviors. Echoing the results of Table
4, Table 5 also demonstrates that both knowledge and confidence are important components
of financial behaviors. For example, with a one standard deviation increase above the mean
in knowledge and confidence an individual is 1.236 and 1.372 times more likely, respec-
tively, to have calculated how much he or she needs to save for retirement.

Higher levels of financial literacy lead to “better” financial decision making. However,
learning from the consequences of past financial decisions, particularly learning from
mistakes, may also lead to higher levels of financial literacy. For example, financial knowl-
edge is positively related to seeking financial advice (Collins, 2012; Robb, Babiarz, and
Woodyard, 2012). Herein lies a potential endogeneity problem: financial literacy levels
predict financial behaviors and financial behaviors (experience) may predict financial literacy
levels.

To address the potential simultaneity issue, correlations examine the inter-relation be-
tween different financial behaviors. Then, two-stage least squares regressions use high school
financial education to instrument for financial literacy. Similarly, van Rooij, Lusardi, and
Alessie (2011) use economic education in high school as an instrumental variable, arguing
that it is correlated with financial literacy (the independent variable) but not correlated with
stock market participation (the dependent variable). First, there is not a clear statistical

Table 5 Robustness checks for confidence measure

Overall Average

Knowledge Confidence Knowledge Confidence

Savings and borrowing behaviors
Calculate 1.236*** 1.372*** 1.227*** 1.226***
Compare credit cards 1.115*** 1.276*** 1.102*** 1.206***
Credit report 1.118*** 1.297*** 1.111*** 1.201***
Credit score 1.099*** 1.241*** 1.088*** 1.190***
Health insurance 1.089*** 1.033* 1.082*** 1.021
Life insurance 0.990 1.157*** 0.981 1.129***
Investments 1.324*** 1.298*** 1.320*** 1.169***
Loan from retirement account 0.776*** 1.060 0.706*** 0.857***
Home equity loan 0.925*** 1.120*** 0.935** 0.991
Foreclosure 0.703*** 1.161*** 0.725*** 0.920**

The logistic regressions from Table 4 are reconsidered. Instead of using the four knowledge groups, continuous
variables are used for financial knowledge and financial confidence. The financial knowledge measure reflects the
number of correctly answered questions, and thus ranges from 0 to 5. Several confidence measures are considered:
Overall, Day-to-Day, Math, and Average. In all regressions, both the financial knowledge variable and the
respective financial confidence variable are standardized for ease of interpretation of the odds ratios. The control
variables gender, age, education, employment status, marital status, income, income-drop, and risk tolerance are
not reported. The financial behaviors (0�did not engage in behavior; 1�engaged in behavior) are listed vertically
along the left panel and are detailed in the Appendix. The odds ratio represents reflects how a one standard
deviation above or below the average affects financial behaviors. ***, **, and * represent statistical significance
at the 1%, 5%, and 10% levels, respectively.

110 C.T. Asaad / Financial Services Review 24 (2015) 101–117



relationship across financial behaviors, suggesting that financial behaviors are not distinct
predictors of financial literacy (see also Allgood and Walstad, 2013). Second, in all speci-
fications, the financial confidence variable is still statistically and economically significant.
Moreover, previous research has also not found reverse causality to be an issue (Allgood and
Walstad, 2013; van Rooij, Lusardi, and Alessie, 2011).

The results in Tables 4 and 5 provide support for H1, that financial confidence predicts
financial behavior. In addition, these findings support Remund’s (2010, p. 284) definition of
financial literacy as “a measure of the degree to which one understands key financial
concepts and possesses the ability and confidence to manage personal finances” and the work
of Courchane, Gailey, and Zorn (2008, p. 137) who find that “optimistic self-assessments,
not accurate ones, lead to better financial outcomes.”

4.2. Risky behaviors

H2 proposes that overconfident individuals are most likely to engage in risky financial
behaviors. Table 4 hints that this may be the case: the High-High knowledge group is less
likely than the Low-Low knowledge group to have experienced a foreclosure process while
the Low-High (overconfident) knowledge group is more likely than the Low-Low group.
Because of an underestimation of risk, overconfident individuals likely have an increased
propensity to engage in risky behaviors.

The omitted knowledge group in this next series of regressions is the overconfident group,
or those with low knowledge and high confidence (Low-High). If the overconfident are more
likely to engage in risky behaviors, then the odds ratios of the other knowledge groups should
be below one, indicating that these groups are less likely to engage in risky behaviors than
the Low-High group. After controlling for many other factors, including risk tolerance, Table
6 shows that “overconfident” individuals are more likely than other knowledge groups to take
these financial risks. Compared with “overconfident” individuals, those with low perceived

Table 6 Financial literacy and risky behavior

High knowledge,
high confidence

High knowledge,
low confidence

Low knowledge,
low confidence

Risky, high-cost behaviors
Title-loan 0.484*** 0.656*** 0.575***
Pay-day loan 0.595*** 0.719*** 0.745***
Tax advance 0.496*** 0.602*** 0.588***
Pawn shop 0.656*** 0.804*** 0.780***
Rent-to-own 0.630*** 0.586*** 0.769***

Logistic regressions predicting financial behavior whereby the predictor variables control for gender, age,
education, employment status, marital status, income, income-drop, and risk tolerance. The dependent variables
are listed vertically and represent the financial behaviors (0 � did not engage in behavior; 1 � engaged in
behavior), which are detailed in the Appendix. The odds ratio for three financial knowledge groups is reported,
a ratio of the likelihood of an event occurring in one group to the likelihood of the same event occurring in another
group. The omitted variable is the low actual knowledge and high confidence group. The odd ratios of the three
reported knowledge groups are interpreted in reference to this omitted group. The results for the control variables
are not reported. ***, **, and * represent statistical significance at the 1%, 5%, and 10% levels, respectively.

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and low actual knowledge are about 25% less likely to have obtained a payday loan and 22%
less likely to have taken a tax advance. Because actual knowledge is low across these two
groups, the increased propensity to engage in these risky behaviors is because of the
high-perceived knowledge (confidence), that is, overconfidence.

As a robustness check, Table 7 reconsiders the regressions in Table 6, but instead of using
the four knowledge groups as predictor variables, standardized continuous variables are used
to measure Knowledge and Confidence. An interaction term, Knowledge*Confidence, con-
siders the relation between the two financial literacy components. The statistically significant
interaction terms in Table 7 indicate that confidence influences the relationship between
knowledge and financial behavior, affecting the strength and/or direction of the relationship.

Fig. 1 illustrates one of the interactions from Table 7, how confidence affects the use of
payday loans. The slope of the high confidence line is steeper than the low confidence line
indicating that the affect of knowledge on payday loan behavior is different for different
confidence levels. When knowledge is low, those with high confidence are more likely to
engage in the risky behavior and when knowledge is high, those with high confidence are less
likely to engage in the risky behavior. This illustrates that confidence is good, but too much
confidence is harmful.

This link between overconfidence and risky behaviors helps elucidate the discrepancy that
Parker, Bruin, Yoong, and Willis (2012) could not explain: They found that confidence is
positively associated with “good” financial decisions, yet prior research demonstrates a
negative association between overconfidence and trading behaviors (e.g., Barber and Odean,
2000; Grinblatt and Keloharju, 2009). People tend to have unrealistic self-perceptions, but
these positive-illusions can be advantageous (Sedikides, 1993). This self-efficacy gives
individuals the confidence to act (Bandura, 1997). Thus, as Parker, Bruin, Yoong, and Willis
(2012, p. 387) suggest, “confidence may play a role in reducing hesitation and increasing risk
taking.” However, in some financial circumstances, inaccurately assessing the level of risk

Table 7 Robustness checks overconfidence measure

Knowledge Confidence Knowledge*Confidence

Risky, high-cost behaviors
Title-loan 0.673*** 1.060** 0.897***
Pay-day loan 0.713*** 0.966 0.923***
Tax advance 0.652*** 1.066** 0.886***
Pawn shop 0.770*** 0.949** 0.926***
Rent-to-own 0.667*** 1.074*** 0.884***

The logistic regressions from Table 6 are reconsidered. Instead of using the four knowledge groups, continuous
variables are used for financial knowledge and financial confidence. The financial knowledge measure reflects the
number of correctly answered questions, and thus ranges from 0 to 5. The Overall confidence measure (1–7) is
considered. In all regressions, both the financial knowledge variable and the financial confidence variable are
standardized. An interaction term, Knowledge*Confidence, considers the relation between the two financial
literacy components, knowledge, and confidence. The control variables gender, age, education, employment
status, marital status, income, income-drop, and risk tolerance are not reported. The financial behaviors (0 � did
not engage in behavior; 1 � engaged in behavior) are listed vertically along the left panel and are detailed in the
Appendix. The odds ratio represents reflects how a one standard deviation above or below the average affects
financial behaviors. ***, **, and * represent statistical significance at the 1%, 5%, and 10% levels, respectively.

112 C.T. Asaad / Financial Services Review 24 (2015) 101–117



can lead to risky decisions. The results in Table 6, Table 7, and Fig. 1 support H2, that
overconfident individuals are most likely to engage in risky financial behaviors. Together,
these findings align with Goel and Thakor’s (2008) theoretical model: some overconfidence
is good, but too much is bad.

5. Conclusion

This analysis examines two components of financial literacy, knowledge, and confidence.
Not surprisingly, individuals with both high knowledge and confidence are more likely to
make “good” financial decisions than individuals with both low knowledge and confidence.
Somewhat surprising, however, is how influential perceived knowledge is on financial
behavior. Additionally, when confidence is high and actual knowledge is low, individuals are
more likely to take financial risks by engaging in costly behaviors. These findings are robust
to measurement changes for the four knowledge groups, confidence, and overconfidence.

This article makes two noteworthy contributions. First, confidence, or self-perceived
knowledge, is an important component of financial literacy. Prior studies found a positive
association between an individual’s self-assessed level of confidence with investing, retire-
ment planning, and credit card behaviors. This analysis extends these findings by demon-
strating, with a large nationally representative sample, that confidence affects additional
savings and borrowing behaviors. In most financial circumstances, higher confidence is
beneficial. However, the second contribution of this article is the clarification of when
confidence can be detrimental. Overconfident individuals tend to overestimate the precision
of their knowledge and underestimate risk; thus, perhaps even unbeknownst to them,
overconfident individuals are more likely to engage in risky and costly financial behaviors.

Fig. 1. Confidence and the probability of obtaining a payday loan by knowledge level. This figure illustrates the
interaction between knowledge and confidence and the effect on the probability of obtaining a payday loan.
Graph created using the regression coefficients, including control variables, from Table 7 and the website:
http://www.jeremydawson.co.uk/slopes.htm.

113C.T. Asaad / Financial Services Review 24 (2015) 101–117



These findings are based on survey data. As such, the results are only as good as the survey
design and participant veracity. Survey responses are “vulnerable to social desirability,”
meaning that if financial behaviors are viewed as having “a normative valence” then
respondents are apt to overstate “good” financial behaviors and understate ‘bad’ financial
behaviors (Willis, 2008). Additionally, financial decisions are not strictly about money but
involve balancing life’s tradeoffs, and it is possible that some of these omitted factors, such
as personality characteristics, may play a role in shaping financial behaviors. As predicted,
confidence is an important part of financial decision making. The strength of the findings
may relate to survey design issues: the confidence measure may pick up on a more “general”
financial knowledge (or perhaps financial resourcefulness or experience) that the actual
knowledge measure misses or may also reflect other confidence issues such as trust or
general life outlook. Future experimental research may help explicate these measures and
their respective affects on financial behaviors.

What is clear from the analysis, however, is that financial literacy encapsulates more than
just numeracy knowledge. Understanding that confidence is just as important as knowledge
is of paramount value to educators and policy makers, helping to structure more effective
financial literacy initiatives and improve individuals’ everyday financial decision making.
The risky financial behaviors addressed in this article are complex and require numeracy
knowledge; however, based on Carpena et al.’s (2011) findings, more exposure to these
financial topics will increase awareness and hopefully positively affect decision making.
Although numeracy and math-based skills are necessary for specific, concrete calculations,
exposing individuals to financial topics and products may help individuals make more
informed financial decisions. The challenge then is to create education initiatives that help
individuals find a healthy dose of confidence.

Notes

1 The three questions (Risk, Interest, and Inflation), developed by Annamaria Lusardi
and Olivia Mitchell, first appear in the 2004 cross-section of the Health and Retirement
Study. Lusardi and Mitchell (2011) describe their rationale for using these three
questions as a measure of financial literacy, emphasizing that the measures were
chosen keeping four principles in mind: (1) Simplicity, that is, basic financial concepts;
(2) Relevance, that is, pertinent to daily financial decision-making; (3) Brevity, that is,
small number of questions for widespread adoption; and (4) Capacity to differentiate,
that is, distinguish different levels of knowledge.

2 Lusardi and Mitchell (2011) also report that not only are women less likely than men
to correctly answer the financial literacy questions, but women are also less likely to
respond, that is, women are more likely to answer that they “do not know.” Similarly,
Beierlein and Neverett (2013) find that women are less likely to enroll in an elective
personal finance course.

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3 Using FINRAs 2009 survey, Robb, Babiarz, and Woodyard’s (2012) average financial
confidence measure is computed as an average of four confidence variables. “I
regularly keep up with economic and financial news” is not included in the 2012
survey, and thus the average confidence variable is computed as an average of three
confidence variables.

4 Individuals are classified as having high confidence if they self-assessed their Overall
financial knowledge as a 6 or 7 on a 7-point scale and classified as having low
confidence if they self-assessed their financial knowledge as 5 or lower on a 7-point
scale (mean � 5.15; median � 5.00). Individual are classified as having high actual
financial knowledge if they answered 3, 4, or 5 of 5 questions correctly and as low
actual financial knowledge if they answered 2 questions or less correctly (mean �
2.88; median � 3.00).

Appendix: FINRAs 2012 National Financial Capability Study: Selected Survey
Topics and Questions

Savings and loan behaviors
Calculate Have you ever tried to figure out how much you need to save for retirement?
Compare CCs Thinking about when you obtained your most recent credit card, did you collect in

formation about different cards from more than one company in order to compare
them?

Credit report In the past 12 months, have you obtained a copy of your credit report?
Credit score In the past 12 months, have you checked your credit score?
Health insurance Are you covered by health insurance?
Life insurance Do you have a life insurance policy?
Investments Not including retirement accounts, do you have any investments in stocks, bonds,

mutual funds, or other securities?
Retirement loan In the last 12 months, have you or your spouse/partner taken a loan from your

retirement account(s)?
Home equity loan Do you have any home equity loans?
Foreclosure Have you been involved in a foreclosure process on your home in the last 2 years?

Risky, high-cost behaviors
Auto title loan In the last two years, have you taken out an auto title loan?
Payday loan In the last two years, have you taken out a short term “payday” loan?
Tax advance In the last two years, have you gotten an advance on your tax refund?
Used pawn shop In the last two years, have you used a pawn shop?
Used rent-to-own In the last two years, have you used a rent-to-own store?

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