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Explaining Financial Literacy in Japan: New Evidence Using Financial
Knowledge, Behavior, and Attitude
Article in SSRN Electronic Journal · January 2017
DOI: 10.2139/ssrn.3067799
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Explaining Financial Literacy in Japan: New Evidence using
Financial Knowledge, Behavior, and Attitude*
Yoshihiko Kadoya †
Mostafa Saidur Rahim Khan‡
Abstract
This study examines the demographic and socio economic factors explaining financial literacy in
Japan by decomposing financial literacy into financial knowledge, attitude, and behavior, which
provides a deeper understanding of the relationships. We used a large dataset from a national
survey conducted by the Bank of Japan in 2016. The GSEM in logit and the OLS regression
coefficients show that age, education, balance of financial assets, and use of financial
information are positively related to overall financial literacy and its three components, while
employment status and experience of financial trouble are negatively associated. Moreover, we
show that males perform better than females do in the overall measure of financial literacy and
financial knowledge, though females outperform males with regard to financial behavior and
financial attitude.
Keywords: financial literacy, financial knowledge, financial behavior, financial attitude,
demographic and socio-economic characteristics
JEL Codes: D14, D19, D10
*
The authors thank Nobuyoshi Yamori and Noriaki Kawashima for their helpful comments. This work
was supported by the JSPS KAKENHI [grant number 15K17075], [grant number 15KK0083], and
RISTEX, JST.
†
‡
Department of Economics, Hiroshima University Email: ykadoya@hiroshima-u.ac.jp
Graduate School of Economics, Nagoya University Email: saidur_rahim@yahoo.com
1
1. Introduction
Financial literacy has gained much interest from academia and policy makers in the last few
decades, which have seen a growing complexity in financial markets and consumer decision
making. The need for financial literacy reflects fact that consumers do not have enough
knowledge and susceptible to making the wrong decision (Knoll and Houts, 2012; OECD, 2006;
De Bondt, 1998). In a modern society, people deal with financial aspects and need to face
contingencies and crises of their own. The extent of government regulations in an open market
economy can only give some protection, but never guarantee success in financial and economic
transactions. Financial literacy enables people to understand the nature and behavior of financial
and economic issues. Previous studies find a relationship between financial literacy and
retirement savings plans, insurance policies, wealth accumulation, consumption decisions, and
stock market investment (Bernheim and Garret, 2003; Van Rooij, Lusardi, and Alessie, 2011,
2012; Lusardi and Mitchell, 2011b; Sekita, 2013). Considering the importance of financial
literacy, the US government created the Financial Literacy and Education Commission after
enacting the Financial Literacy and Education Act in 2003. However, a non-for-profit
organization called the Jump$tart coalition was created in 1995 to encourage financial literacy
among young people. A declaration by the G20 leaders in 2012 prioritized the development of
national strategies for financial education. The “Agenda for Finance and Economics Education in
2005” and “Financial Education program in 2007” shows the Japanese government’s initiative to
propagate financial literacy among its citizens (Furusawa, 2014). The program designed financial
education for Japanese students by age. In response to the G20 declaration, the financial services
agency of Japan (FSA) organized a study group in 2012, which set minimum requirements for
2
financial literacy education in Japan. In addition, the central council for financial services
information (CCFSI) formed a committee in 2013 to promote financial education (Furusawa,
2014). These initiatives demonstrate how governments prioritize financial literacy in national
strategies.
Marcolin and Abraham (2006) emphasize the need to find a standard measure of financial
literacy. Despite the consensus on the importance of financial literacy, its definition and
measurement differ greatly across agencies and research studies. Schmeiser and Seligman (2013)
also find problems measuring financial literacy because respondents do not answer financial
literacy questions consistently. Thus, researchers need an appropriate definition and
measurement of financial literacy to understand its outcomes. Huston (2010) finds several
important facts regarding existing definitions and measurement techniques for financial literacy
in a review of seventy studies. First, most studies did not include a definition and used financial
literacy and financial knowledge interchangeably. Second, most studies with definitions relied on
either ability or knowledge, but the US Financial Literacy and Education Commission and
Jump$tart coalition used both financial knowledge and ability in their definition. The Financial
Literacy and Education Commission (2007) define financial literacy as the ability and awareness
to use knowledge and skills to manage financial resources to achieve maximum financial wellbeing, while Jump$tart (2007) defines it as the ability to use knowledge and skills to manage
one’s financial resources effectively for lifetime financial security. Financial literacy is not a
constant issue, rather it is a continuum of abilities depending on variables such as age, family,
culture, and residence. Financial literacy refers to an evolving state of competency that enables
each individual to respond effectively to ever-changing personal and economic circumstances.
The Organization for Economic Co-operation and Development (OECD) defines financial
3
literacy as the knowledge and understanding of financial concepts and risks, and the skills,
motivation, and confidence to apply this knowledge and understanding to make effective
decisions across a range of financial contexts, to improve the financial well-being of individuals
and society, and to enable participation in economic life (OECD, 2017).
Several studies worldwide find demographic and socio-economic determinants of
financial literacy using conventional definitions of financial literacy that measure peoples’
understanding of financial concepts. Van Rooij et al. (2011), Alessie et al. (2013), Hung, Yoong,
and Brown (2012), Lusardi and Mitchell (2011a), Atkinson and Messy (2012), Brown and Graf
(2013), Kadoya and Khan (2017) and Sekita (2013) provide evidence that men were more
financially literate than women. Others report a significant non-linear age effect on financial
literacy. Middle aged people are more financially literate than younger and older people (Lusardi
and Mitchell, 2011b, 2014; Lusardi, Mitchell, and Curto, 2010). Agarwal et al. (2009) argue that
people become more financially literate through experience, but begin to lose financial literacy at
the old age due to the decrease in cognitive ability. Researchers argue that education enhances
cognitive ability, which in turn increases financial literacy (Gill and Prowse, 2015). Lusardi and
Mitchell (2011b, 2014), Lusardi et al. (2010), and Danes and Haberman (2007) provide
empirical evidence of the positive association between education and financial literacy. Lusardi
and Mitchell (2011a) find that employed people tend to be more financially literate than their
unemployed counterparts are due to the experience they gather from the workplace. Earning
capacity and asset balance could be an important contributor to financial literacy as well.
Atkinson and Messy (2012), Monticone (2010), Lusardi and Tufano (2009), and Guiso and
Jappelli (2008) show that household income and assets contribute positively to financial literacy.
4
This study measures financial literacy from the viewpoint of financial knowledge,
attitude, and behavior, and examines the demographic and socio-economic determinants of
financial literacy and three of its components. Our measure of financial literacy generally follows
the definition of financial literacy provided by the OECD (2017), which focuses on
operationalizing financial knowledge in addition to understanding financial concepts. Given the
problems with measuring financial literacy using traditional questions, we use a new and large
scale survey conducted by the Bank of Japan (BOJ) to provide evidence on the measurement of
financial literacy and its determinants using a new methodology. Our study contributes to the
existing literature in at least three ways. First, to the best of our knowledge, this is the first study
in Japan that examines the factors affecting financial literacy in terms of financial knowledge,
financial attitudes, and financial behavior. Previous studies mostly follow Lusardi and Mitchell’s
(2007, 2008) methodology, which uses questions to measure financial knowledge (Sekita, 2011,
2013; Kadoya and Khan, 2016, 2017). Second, this study provides evidence on the
interrelationships among the components of financial literacy. Finally, this study examines the
demographic and socio-economic determinants of financial literacy and its components to
observe whether the factors affect all components similarly.
The rest of the paper proceeds as follows. Section 2 describes the data and the
methodology, section 3 discusses the empirical findings, section 4 discusses the empirical
findings, and section 5 concludes.
2. Data and Methodology
2.1 Data
5
This study uses data from a large-scale questionnaire survey called the Financial Literacy Survey
2016 by the BOJ that collected information on the financial knowledge and financial decision
making skills of individuals over 18 years of age. The online survey was conducted throughout
Japan between February 2016 and March 2016. The full sample consists of 25,000 individuals
between 18 and 79 years old and covers all prefectures and major cities chosen based on the
proportion of Japan’s demographic features. Samples were selected randomly to satisfy the
sample composition ratio. Participants registered with the survey company were sent an e-mail
requesting participation in the survey. Respondents accessed the designated URL containing the
survey questions and answered them on the website. The questions were a combination of
true/false and multiple choice questions and were designed in accordance with the US Financial
Industry Regulatory Authority (FINRA) and the OECD. Our study uses a sample of 16,345
respondents who have responded to all questions of our interests.
2.2 Variables and measurement issues
Dependent variable
The dependent variable of our study is financial literacy. We obtained the financial literacy score
by summing the average scores on financial knowledge, financial behavior, and financial attitude.
We also used financial knowledge, financial behavior, and financial attitude as dependent
variables in separate models. Given the problems using traditional questions about financial
knowledge to measure financial literacy accurately (Schmeiser and Seligman, 2013), we used
several questions from the survey to measure financial literacy by dividing it into three
components. We argue that this provides a more accurate measure of financial literacy because
6
high scores on financial knowledge, attitude, and behavior reflect that respondents are not only
knowledgeable but can also translate this knowledge into financial decision making. We measure
these three components by putting equal weight on each question and measure financial literacy
by taking the average score of these components. We used several questions from the survey to
measure financial knowledge, financial attitude, and financial behavior.
Financial knowledge: Financial knowledge measures the ability to understand financial
calculations, specifically the implications of interest rates, inflation, and the risk and return on
financial securities. Financial knowledge develops the financial skills necessary to moderate
people’s financial behavior and attitude. We used the questions below to measure financial
knowledge:
1. Suppose you put 1 million yen into a savings account with a guaranteed interest rate of
2% per year. If no further deposits or withdrawals are made, how much would be in the
account after 1 year, once the interest payment is made?
2. Then, how much would be in the account after 5 years?
3. Does high inflation mean that the cost of living is increasing rapidly?
4. Is an investment with a high return likely to be high risk?
5. Does buying a single company's stock usually provide a safer return than a stock mutual
fund?
Financial Behavior: Financial behavior measures how people act in financial transactions. In
other words, it measures whether they skillfully utilize financial knowledge to make better
financial decisions. Generally, financial knowledge and attitude shape people’s financial
behavior. We used the following questions used to measure financial behavior:
7
1. Have you set aside emergency or rainy day funds that would cover your expenses for 3
months in case of sickness, job loss, economic downturn, or other emergencies?
2. Taro and Hanako are the same age. At age 25, Hanako began saving 100,000 yen per
year and continued to save the same amount annually thereafter. Meanwhile, Taro did not
save money at age 25, but began saving 200,000 yen per year at age 50. When they are
aged 75, which of them will have more money saved?
3. Which of the following is an inappropriate action when concluding a contract?
a. Reconsidering whether the contract is truly necessary.
b. Checking whether cancelling the contract is possible and whether a penalty is
charged for doing so.
c. Concluding a contract based on a detailed explanation from the service provider,
and carefully reading the contract document later.
d. Seeking advice from a third party as needed when concluding a contract.
e. Don’t know.
4. How would you rate your overall knowledge about financial matters compared with other
people?
a. Very high. b. Quite high. c. About average. d. Quite low. e. very low. f. Don’t
know.
Financial attitude: Financial attitude measures people’s approach to financial issues. Although
we expect that financially knowledgeable and skillful people will have positive attitude towards
financial transactions, but it is not always warranted. Sometimes, people may fail to translate
8
their knowledge and skills into their attitude. We used the following questions to measure
financial attitude:
1. Which of the following is an inappropriate behavior to avoid financial trouble?
a. Avoiding disclosing your personal information as much as possible.
b. Making an effort to acquire financial and economic knowledge.
c. Trusting and leaving the entire matter to the service provider when it is difficult to
make a decision.
d. Checking user reviews of the product you are planning to purchase.
e. Don’t know.
2. Which of the following is an inappropriate action related to Internet transactions?
a. I updated the security software to the latest version.
b. I received an e-mail, but I did not open it since it was sent from an unknown
address.
c. I made a bank transfer using a computer at an Internet café.
d. I checked many times to make sure that the information I entered had no errors.
e. Don’t know.
Table 1 reports the interrelationship among the measures of financial literacy. The results show a
significantly positive relationship between financial literacy and its components. Moreover,
financial knowledge, financial behavior, and financial attitude have significantly positive
relationships with each other.
[Insert Table 1 around here]
Independent variables
9
To explain financial literacy in Japan, we include a number of variables related to respondents’
demographic and socio-economic characteristics. We include gender because it appears to be an
important feature related to financial literacy. Previous studies find that males are more
financially literate than females are (Van Rooij et al., 2011; Alessie et al., 2013; Hung et al.,
2012; Atkinson and Messy, 2012; Lusardi and Mitchell 2008). Kadoya and Khan (2016) and
Sekita (2013, 2011) find similar evidence for Japan. We also include age because previous
studies find a non-linear relationship with financial literacy, in which financial literacy is higher
for middle aged respondents compared to younger and older respondents (Lusardi and Mitchell,
2011b, 2014; Lusardi et al., 2010). We include respondents’ education because education
enhances money management capacity and cognitive ability, which contribute to attaining
financial literacy (Lusardi and Mitchell, 2014; Lusardi et al., 2010; Gill and Prowse, 2015).
Respondents’ employment status is also an important predictor of financial literacy. Lusardi and
Mitchell (2011a) find that employed respondents were more literate than their unemployed
counterparts are. Financial conditions as reflected by household income and balance of assets can
also explain financial literacy. There is sufficient evidence from empirical studies that household
income and assets are positively linked to financial literacy (Kadoya and Khan, 2016; Lusardi
and Tufano, 2009; Guiso and Jappelli, 2008).
In addition to these traditional demographic and socio-economic variables, we include
two new variables that prior studies do not use to examine their relationship with financial
literacy: respondents’ experience with financial trouble, assuming that such experience in the
recent past is negatively related to financial literacy; and willingness to acquire financial
knowledge from newspapers, magazines, television, and the internet a predictor of financial
literacy since people who acquire financial information are more likely to be financially literate.
10
Table 2 provides the summary statistics of the variables used in this study. Respondents’
average financial literacy score is 0.61 (SD=0.24), indicating a somewhat above average score.
We find a similar result for financial knowledge (mean=0.63 and SD=0.32) and financial
behavior (mean=0.67 and SD=0.31). However, respondents have below average scores on
financial attitude (mean=0.46 and SD=0.41). The demographic and socio-economic background
of the respondents indicate that more than half are male (53%), are 48.69 years old on average
(SD=16.49), earn an average yearly income of 5.15 million yen (SD=3.19 million yen), have a
7.31 million yen balance of financial assets (SD=7.19 million yen), 58.67% are either fully
employed or have some part time jobs, have a more than college level education (mean=14.26
years and SD=2.06 years), only 6.64% faced financial trouble, and 58.12% often acquire
financial and economic information.
[Insert Table 2 around here]
Table 3 shows the distribution of overall financial literacy, financial knowledge, financial
behavior, and financial attitude based on demographic features such as age, gender, and
education. The results show a positive trend between age and financial literacy and its three
components. We divide respondents into three age groups: younger than 40 years, between 40
and 64 years, and older than 64 years. In all measures of financial literacy, older respondents
scored higher than middle aged and younger respondents did. We have interesting results when
dividing the components of financial literacy based on gender. Males scored higher on overall
financial literacy and financial knowledge than females did. However, females scored higher on
financial behavior and financial attitude than males did. We divide respondents into three
education groups: less than 12 years (below college level), between 12 to 16 years
(undergraduate level), more than 16 years (graduate level or above). The distribution of financial
11
literacy components across education groups also shows a positive trend. In all measures of
financial literacy, highly educated respondents performed better than their less educated
counterparts did.
[Insert Table 3 around here]
2.3 Methodology
We use a linear regression model (OLS) to explain how demographic and socio-economic
factors relate to financial literacy. We use four models because we measure financial literacy by
the average scores on financial knowledge, financial behavior, and financial attitude. Model 1
uses overall financial literacy as a dependent variable, while models 2, 3, and 4 use financial
knowledge, financial behavior, and financial attitude, respectively, as dependent variables. All
models include the independent variables of gender, age, education, employment status, income,
financial assets, financial trouble, and financial information. The linear regression is:
Financial Literacy or financial knowledge or financial behavior or financial attitude = α +
β1 gender + β2 age + β3 education + β4 income + β5 financial assets +
β6 employment status + β7 financial trouble + β8 financial information
As a measure to check the robustness of results, we also use a generalized structural
equation model in logit (GSEM in logit), where a financial literacy score of more than 0.5
indicates higher financial literacy, and lower otherwise. The dependent variable of the logit
model takes the value 1 for financially more literate respondents and ‘0’ for financially less
literate respondents. The independent variables remain the same as in the linear regression model.
The GSEM in logit model controls the possible endogeneity bias in the coefficients by including
12
common, unobserved components in the equations for many variables. Like the linear regression
model, we used four GSEM in logit models to explain overall financial literacy and its three
components. The GSEM in logit model is:
Financial Literacy or financial knowledge or financial behavior or financial attitude (1 =
financially more literate and 0 = financially less literate) = α + β1 gender + β2 age +
β3 education + β4 income + β5 financialassets + β6 employment status +
β7 financial trouble + β8 financial information
3. Empirical findings
Table 4 reports the OLS regression coefficients for the demographic and socio-economic factors
explaining financial literacy. Model 1 shows the regression coefficients for overall financial
literacy, while models 2, 3, and 4 shows the coefficients on financial knowledge, financial
behavior, and financial attitude, respectively. The coefficients for model 1 show that gender, age,
education, income, balance of financial assets, and use of financial information are positively
related to financial literacy, while employment status and experience of financial trouble are
negatively related. The coefficients for model 2 show a positive association between gender, age,
education, balance of financial assets, and use of financial information with financial knowledge,
and a negative association with employment status and experience of financial trouble with
financial knowledge. We find no association between respondents’ income with financial
knowledge. While the association of most of the variables is similar for financial literacy and
financial knowledge, interestingly, we find a different association for some demographic
variables with financial behavior and financial attitude. The coefficients for model 3 show that
13
education, balance of financial assets, and use of financial information are positively associated
with financial behavior. However, unlike overall financial literacy and financial knowledge,
gender is negatively associated with financial behavior. Other variables such as employment
status and experience of financial trouble are negatively related to financial literacy. We find no
association between respondents’ income and financial behavior as well. The coefficients for
model 4 show that the age, education, balance of financial assets, and use of financial
information are positively associated with financial attitude. Like financial behavior, we find a
negative association between gender and financial attitude. Employment status and experience
with financial trouble are negatively related, but we find no relation between respondents’
income and financial attitude.
[Insert Table 4 around here]
Table 5 reports the coefficients of the GSEM in logit model to examine what increases
the probability of being more financially literate. Like the OLS regression, we used four models
for overall financial literacy, financial knowledge, financial behavior, and financial attitude. The
coefficients for model 1 show that a change in gender (from female to male), and an increase in
age, education, income, balance of financial assets, and use of financial information tend to
increase financial literacy, while employment status and experience of financial trouble tend to
reduce it. The coefficients for model 2 show that a change in gender (from female to male), and
increase in age, education, income, balance of financial assets, and use of financial information
tend to increase financial knowledge, while experience of financial trouble tends to reduce it. We
find no effect of employment status on financial knowledge. The coefficients for model 3 show
that an increase in education, balance of financial assets, and use of financial information tend to
increase financial behavior, while gender, employment status, and experience of financial trouble
14
tend to decrease it. Finally, the coefficients for model 4 show that increase in age, education, and
balance of financial assets tend to increase financial attitude while gender, employment status,
and experience of financial trouble tend to reduce it. The results of the GSEM in logit models
and the OLS models are similar, implying that our results are robust.
[Insert Table 5 around here]
4. Discussion
Previous studies sought to explain financial literacy worldwide using conventional questions
measuring financial knowledge. However, no study examines the factors that affect the other
important components of financial literacy, such as financial behavior and financial attitude. In
addition to financial knowledge, our study examines the demographic and socio-economic
factors that explain financial behavior and financial attitude in Japan. Measuring financial
literacy by combining these three components provides an opportunity to explain a population’s
understanding and implementation of financial knowledge more rigorously.
Our results show that financial literacy is positively related to gender, age, education,
income, balance of financial assets, and use of financial information, and negatively related to
employment status and experience of financial trouble. The results for the basic demographic
variables such as gender and education support previous findings (Kadoya and Khan, 2017; Van
Rooij et al., 2011; Alessie et al., 2013; Hung et al., 2012; Lusardi and Mitchell, 2011a, 2011b,
2014; Atkinson and Messy, 2012; Brown and Graf, 2013; Sekita, 2013; Lusardi et al. 2010;
Danes and Haberman, 2007). However, our findings of a positive association between age and
financial literacy differ with the non-linear positive effect in existing literature (Lusardi and
15
Mitchell, 2011b, 2014; Lusardi et al., 2010; Agarwal et al., 2009). Our results imply that older
people in Japan are comparative more financially literate than respondents of other age groups.
Although Agarwal et al. (2009) argue that the attainment of financial literacy through experience
begins to diminish at old age, this explanation does not hold true for Japan. The association
between income and balance of financial assets with financial literacy also generally supports
previous findings (Lusardi and Tufano, 2009; Guiso and Jappelli, 2008). We also find a positive
effect from the use of financial information on financial literacy. People who regularly read and
acquire information on financial issues tend to be more financially literate. Our findings on the
negative association of employment status with financial literacy also differ with the previously
findings of a positive association (Lusardi and Mitchell, 2011a). One possible explanation is the
existence of more financially literate older people in the unemployed group. People less than 40
years of age are more likely to be employed, but they also have the lowest score on financial
literacy.
In dividing financial literacy into the three components of financial knowledge, financial
behavior, and financial attitude, we find that the association of the variables with financial
literacy generally holds true for financial knowledge, except for employment status, for which
we find no significant association. However, the association of the variables with financial
behavior and financial attitude differ with the results for financial literacy and financial
knowledge. The most important difference is that gender is negatively related to financial
behavior and financial attitude, meaning that females outperform males, which is an important
issue. We argue that most questions related to financial behavior are on savings practices, where
females traditionally outperform males (Lee and Pocock, 2007; Hungerford, 1999). Moreover,
other studies indicate that females are more risk averse than male are, which could motivate them
16
to save more (Jianakoplos and Bernasek, 1998). Education and balance of financial assets are
positively related, and employment status and experience of financial trouble are negatively
related to both financial behavior and financial attitude. Age has a positive relationship with
financial attitude, but income does not have a significant relationship with either financial
behavior or financial attitude. Our findings on overall financial literacy and its three components
suggest that demographic and socio-economic factors have a generally similar relationship with
all measures of financial literacy, except for gender.
5. Conclusion
Financial literacy is more important as people are now more involved in financial transactions.
However, the lack of a credible measure of financial literacy makes the outcome less certain.
This study examines the demographic and socio economic factors explaining financial literacy in
Japan after dividing financial literacy into three components, financial knowledge, attitude, and
behavior. This division allows us to provide a more rigorous understanding of the relationship
with demographic and socio-economic variables. We used a sample of 16,345 respondents aged
between 18 and 79 from a national survey conducted by the Bank of Japan in 2016. The OLS
and GSEM in logit regression coefficients show that age, education, balance of financial assets,
and use of financial information are positively related to overall financial literacy and its three
components, while employment status and experience of financial trouble are negatively
associated. Moreover, show that males perform better than females in the overall measure of
financial literacy and financial knowledge, though females outperform males with regard to
17
financial behavior and financial attitude. Our results show that a gender difference exists in
financial literacy, but it is not similar for all measures of financial literacy.
18
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22
Table 1: Relationship among the measures of financial literacy
Financial
Literacy
Financial Literacy
Financial
knowledge
1
0.7773
(0.00)
0.7247
Financial behavior
(0.00)
0.6243
Financial attitude
(0.00)
Note: P values within parentheses
Financial
knowledge
Financial
behavior
1
0.2272
(0.00)
0.2151
(0.00)
Financial
attitude
1
0.3979
(0.00)
1
23
Table 2: Descriptive statistics
Variable
Financial literacy
Financial knowledge
Financial behavior
Financial attitude
Gender
Age
Employment status
Education
Financial trouble
Financial information
Income
Financial assets
Obs.
16345
16345
16345
16345
16345
16345
16345
16345
16345
16345
16345
16345
Mean
0.6124
0.6300
0.6655
0.4624
0.5325
48.6849
0.5867
14.2572
0.0664
0.5812
5.1515
7.3100
Std. Dev.
0.2433
0.3239
0.3105
0.4140
0.4990
16.4930
0.4924
2.0589
0.2490
0.4934
3.1850
7.1879
Min
0
0
0
0
0
18
0
9
0
0
0
0
Max
1
1
1
1
1
79
1
18
1
1
15
20
24
Table 3: Distribution of financial literacy by age, gender, and education
Variables
Age
Gender
Education
<40 years
40 to 64 years
>64 years
Male
Female
<12 years
12 to 16 years
>16 years
Financial
literacy
0.5499
0.6452
0.6818
0.6320
0.5901
0.4641
0.6122
0.6986
Financial
knowledge
0.5342
0.6803
0.7227
0.6903
0.5613
0.4164
0.6291
0.7637
Financial
behavior
0.6424
0.6776
0.7069
0.6558
0.6765
0.5710
0.6658
0.7117
Financial
attitude
0.4044
0.4928
0.5295
0.4389
0.4891
0.3697
0.4626
0.5097
25
Table 4: OLS regression coefficients
Model 1
Financial
literacy
Coefficie
nts
Gender
Model 2
Financial
knowledg
e
Gender
Coefficie
nts
Coefficie
nts
Model 4
Financial
attitude
Coefficie
nts
-0.0362 Gender
-0.0602
((7.24)***
8.98)***
Age
Age
Age
Age
-0.0002
0.0010
(-1.3)
(4.77)***
Education
Education
Education
Education
0.0065
0.0064
(5.36)***
(3.89)***
Income
Income
Income
-0.0004 Income
-0.0007
(-0.52)
(-0.65)
Financial
Financial
Financial
0.0073 Financial
0.0103
assets
assets
assets
(18.12)** assets
(18.98)**
*
*
Employm
Employm
Employm
-0.0186 Employm
-0.0184
ent status
ent status
-0.0012 ent status
(- ent status
((-0.23)
3.48)***
2.57)***
Financial
Financial
Financial
-0.0658 Financial
-0.0818
trouble
trouble
-0.0193 trouble
(- trouble
((-2.15)**
6.97)***
6.46)***
Financial
Financial
0.1370 Financial
0.0949 Financial
informati
informati (28.65)** informati (18.87)** informati
0.0652
on
on
* on
* on
(9.67)***
Constant
Constant
-0.0695 Constant
0.5109 Constant
((25.92)**
0.2598
3.71)***
*
(9.83)***
Observati
Observati 16345
Observati 16345
Observati 16345
on
16345 on
on
on
F
554.65** F
610.13** F
163.49** F
141.69**
*
*
*
*
2
2
2
2
Adj. R
.2132 Adj. R
0.2297
Adj. R
0.0737
Adj. R
0.0644
Note: t values in parentheses. *, **, and *** indicate significance at 10%, 5%, and 1%,
respectively.
0.0150
(4.16)***
0.0016
(13.46)**
*
0.0144
(16.31)**
*
0.0021
(3.35)***
0.0077
(26.36)**
*
-0.0107
(2.76)***
-0.0476
(6.97)***
0.1086
(29.93)**
*
0.2014
(14.15)**
*
0.0862
(18.09)**
*
0.0033
(20.88)**
*
0.0238
(20.53)**
*
0.0052
(6.39)***
0.0069
(18.09)**
*
Model 3
Financial
behavior
Gender
26
Table 5: GSEM in logit regression coefficients
Model 1
Financial
literacy
Gender
Coefficie
nts
Model 2
Financial
knowledg
e
Gender
0.1008
(2.59)***
Age
0.0148 Age
(11.79)**
*
Education
0.1168 Education
(12.34)**
*
Income
0.0134 Income
(1.83)*
Assets
0.0740 Financial
(20.33)** assets
*
Employm
-0.1692 Employm
ent status
(- ent status
4.08)***
Financial
-0.4316 Financial
trouble
(- trouble
6.18)***
Financial
0.8494 Financial
informati (22.49)** informati
on
* on
Constant
-2.4371 Constant
(15.91)***
Observati
Observati
on
16345 on
Log
- Log
likelihood 8834.793 likelihood
5
Note: t values in parentheses. *,
respectively.
Coefficie
nts
0.5189
(13.28)**
*
0.0224
(17.51)**
*
0.1573
(16.31)**
*
0.0337
(4.56)***
0.0573
(16.14)**
*
Model 3
Financial
behavior
Coefficie
nts
Model 4
Financial
attitude
Coefficie
nts
Gender
-0.1723 Gender
-0.2252
((4.92)***
6.08)***
Age
-0.0036 Age
(0.0037
3.20)***
(2.97)***
Education
Education
0.0312
0.0314
(3.68)***
(3.44)***
Income
-0.0037 Income
-0.0090
(-0.59)
(-1.45)
Financial
0.0493 Financial
0.0413
assets
(16.92)** assets
(14.32)**
*
*
Employm
-0.1281 Employm
-0.0599 ent status
(- ent status
-0.0180
(-1.44)
3.43)***
(-0.45)
Financial
-0.3279 Financial
-0.4213
-0.1415 trouble
(- trouble
((-1.95)*
5.04)***
5.44)***
0.8443 Financial
0.5610 Financial
(22.33)** informati (16.19)** informati
0.2656
* on
* on
(7.07)***
-3.7000 Constant
-0.3846 Constant
-1.7182
(23.30)**
((*
2.81)***
11.54)***
16345
Observati 16345
Observati 16345
on
on
Log
Log
8716.968 likelihood 10615.82 likelihood 9796.735
9
10
3
**, and *** indicate significance at 10%, 5%, and 1%,
27
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