Discussion Paper No. 982

WHAT DETERMINESFINANCIAL LITERACY
IN JAPAN?

Yoshihiko Kadoya
Mostafa Saidur Rahim Khan

October 2016

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

What Determines Financial Literacy in Japan?*
Yoshihiko Kadoya†

Mostafa Saidur Rahim Khan‡

Abstract
This study aims to determine the factors that affect financial literacy in Japan using data from
Osaka University’s Preference Parameter Study in Japan. We examined fourteen variables
covering respondents’ demographic, socio-economic, and psychological backgrounds drawn
from social learning, consumer socialization, and psychology theories of learning. The results
indicate that the demographic factors of gender, age, and education; the socio-economic factorsof income and occupation; and the psychological factor of perceptions about future significantly
affect the level of financial literacy. We checked the robustness of results using a different
measure of financial literacy, which also confirmed our findings. The results emphasize the needfor a formal financial education and social contact to boost financial literacy levels in Japan.
Keywords: financial literacy, household, financeJEL codes: D14, G02
This research used micro data from the Preference Parameters Study of Osaka University’s 21st Century
COE Program ‘Behavioral Macrodynamics Based on Surveys and Experiments’ and its Global COE
project ‘Human Behavior and Socioeconomic Dynamics’. We acknowledge the program/project’s
contributors: Yoshiro Tsutsui, Fumio Ohtake, and Shinsuke Ikeda. We thank Nobuyoshi Yamori,
Noriyoshi Yanase, and the other seminar participants at Japan Institute of Life Insurance. This work was
supported by JSPS KAKENHI Grant Number 15K17075, 15KK0083, and RISTEX, JST..

*†

School of Economics, Hiroshima University, 1-2-1 Kagamiyama, Higashi Hiroshima, Hiroshima 7398525 JAPAN Email: ykadoya@hiroshima-u.ac.jp‡

Graduate School of Economics, Nagoya University, Furo-cho, Chikusa, Nagoya 4648601, Japan. Email:saidur_rahim@yahoo.com
1INTRODUCTION
Households now need more financial knowledge in their decision making because thecurrent marketplace is more risky and globalized (Lusardi and Mitchell 2011a). Although social
security and public health provisions are developing, people need financial literacy to determine
retirement savings and costs for healthcare and long-term care (Banks 2010) and to improve thepracticality and utility of savings, investment, retirement planning, wealth accumulation, andstock market participation decisions (Bernheim and Garret 2003; Van Rooij, Lusardi, andAlessie 2011, 2012; Lusardi and Mitchell 2011b; Sekita 2013). Financial literacy improves
retirement planning (Lusardi and Mitchell 2011b), the ability to save and invest in complex
financial assets (Van Rooij, Lusardi, and Alessie 2011), and wealth accumulation through better
retirement planning, savings plans, and stock market investments (Van Rooij, Lusardi, andAlessie 2012). While most evidence comes from the American context, some research exists for
the Netherlands (Alessie, van Rooij, and Lusardi 2011), Japan (Sekita 2011, 2013), Canada(Boisclair, Lusardi, and Michaud 2014), Switzerland (Brown and Graf 2013), and Australia(Agnew, Bateman, and Thorp 2013). Although many previous studies focused on the link
between financial literacy and savings and investment decisions, relatively few examine thefactors that affect financial literacy.
Financial literacy means understanding the value of money and how to maximize thebenefits of money utilization. Many institutions and authors provided different definitions offinancial literacy, but their inherent meanings are similar. The US Financial Literacy and
Education Commission of 2007 and the Organization for Economic Co-operation andDevelopment (OECD) summarized the previous definitions as the ability and awareness to use
knowledge and skills to manage financial resources to achieve maximum financial well-being2

(OECD 2013; Financial Literacy and Education Commission 2007). Our study defines financial
literacy as the ability to understand the implications of interest, inflation, risks, anddiversification. This definition provides the benefit of measurability, which enables researchers
to relate financial literacy with a country’s demographic and socio-economic environment.
Although financial literacy is an important issue that affects household decisions on savings andinvestment, there is still no nationwide comprehensive study on the determinants of financial
literacy in Japan.
There are several existing theories related to financial literacy. Social learning theory andthe theory of consumer socialization grew from theories about learning processes in a society.
Social learning theory argues that as social entities, people learn from observing the behavior andactions of others (Bandura and Walters 1977). Several studies used social learning theory toinvestigate financial behavior (Hira 1997; Martin and Bush 2000). The theory of consumer
socialization argues that children learn the consumption-related knowledge and skills required tolive capably in society from parents, schools, mass media, and peers (Ward 1974; Moschis andChurchill 1978). Some empirical evidence showed an important relationship between financial
knowledge and behavior and social learning opportunities (Gutter, Garrison, and Copur 2010).
Both theories emphasize that people learn financial skills from society, and directly imply thatknowledge and attributes of the people with whom subjects live significantly affects financial
literacy.

LachanceandChoquette-Bernier(2004)

found

that

observation,

parentalcommunication, and learning through error contributed to students’ acquisition of financial
knowledge. Koonce et al. (2008) showed that society, family, peers, and media, contributed
people’s financial literacy. Economic and financial theories based on psychology and behavior
emphasize that behavioural patterns affect financial decisions (Kahneman and Tversky 1979). In3

a recent study, Gill and Prowse (2015) argued that learning is positively related to cognitive
ability, agreeability, and emotional stability. Several studies investigated the role of psychology
in determining financial literacy and showed that confidence, trust, financial satisfaction,orientation for future, anxiety about life in the future, and other factors shape the acquisition offinancial knowledge (Kadoya and Khan 2016; Arellano, Cámara, and Tuesta 2014; Murphy2013).
The study of financial literacy in Japan is important for several reasons. Althoughfinancial literacy is associated with financial wellbeing, the level of financial literacy worldwide,
including Japan, is not so high (Lusardi and Mitchell 2011a; Sekita 2011; Hussein and Kalli
2009; Jappelli 2009; Boisclair, Lusardi, and Michaud 2014). Therefore, it is important toexamine the factors responsible for financial literacy to determine why financial literacy in Japanis at its low level. Moreover, several studies found that Japan is culturally distinct from othercountries and that Japanese people have different of savings and investment behaviors (Chui,
Titman, and Wei 2010). Japanese people tend toward risk aversion, passivity, collectivism, andlow individualism, which research into their effect on financial literacy in Japan.
Our study examines the factors affecting the level of financial literacy among Japanesepeople using several demographic, socio-economic, and psychological factors to investigate theireffect on financial literacy. Our study offers at least two contributions to the existing literature.
First, to the best of our knowledge, this is the first study that explores the demographic,
economic, and psychological factors in financial literacy in Japan, and second, this study seeks to
explain why financial literacy is historically low among Japanese people.
Rest of the paper is organized as follows. Sections 2 and 3 describe the data and define
the variables, respectively. Section 4 describes the methodology and section 5 reports the4empirical results. Section 6 shows robustness of results. Section 7 discusses the results in thecontext of existing research and section 8 concludes the paper.

METHODOLGOY
Variables and Measurements
Dependent Variable
The most important aspect of a study examining the determinants of financial literacy is anappropriate measure of financial literacy. Lusardi and Mitchell (2007, 2008) measured financial
literacy using three questions; Van Rooij, Lusardi, and Alessie (2011) used five questions; andStango and Zinman (2009) used only one question. While the number of questions in each ofthese studies differs, most recent studies (Sekita 2013) followed Lusardi and Mitchell’s (2007,2008) methodology. We do the same, but use four questions to measure the dependent variable,financial literacy, as respondents’ ability to understand basic financial calculations, inflation,risks, and the pricing behavior of financial securities. Respondents answered the following
questions with a set of options
1. Suppose you had ¥10,000 in a savings account, with an interest rate of 2% per year, and you
never withdraw money or interest payments. After 5 years, how much would you have in thisaccount?
□ More than ¥10,200 □ Exactly ¥10,200 □ Less than ¥10,200 □ Do not know □ Refuse to answer
2. Imagine that the interest rate on your savings account is 1% per year and inflation is 2% per
year. After 1 year, how much would you be able to buy with the money in this account?
□ More than today □ Exactly the same □ Less than today □ Do not know □ Refuse to answer

5

3. Please indicate whether the following statement is True or False: “Buying a company stock
usually provides a safer return than a stock mutual fund.”□ True □ False □ Do not know □ Refuse to answer
4. If the interest rate falls, what should happen to bond prices?
□ Rise □ Fall □ Stay the same □ None of the above □ Do not know □ Refuse to answer
The first two questions measure respondents’ ability to understand basic financial
calculations, and the last two questions are more related to financial instruments to measure
respondents’ ability to understand the basic nature and movement of financial securities’ prices.
We assigned one point to each correct answer and did not deduct points for a wrong answer.
We then use the number of correct answers as the respondent’s level of financial literacy. This
process of measuring financial literacy is unweighted and thus does not put more weight ondifficult questions. Our alternative measure of financial literacy assigns one point for eachcorrect answer and deduct points for each wrong answer; it also puts more weight on the last twoquestions. Sekita (2013) also used both weighted and unweighted methods to examine therelationship between financial literacy and wealth accumulation, and found that both measures
produced similar results. While measurement issues do not seem to affect the implications of theresults, we used both measures of financial literacy to check the robustness of our results.
Table 2 reports the distribution of the financial literacy scores by age, gender, and education.
Financial literacy increases with age up to a certain level, after which it begins to fall: middleaged respondents had the highest financial literacy, though older respondents had more financial
literacy than the younger respondents. Male respondents were more financially literate thanfemale respondents. The level of financial literacy differed significantly depending on the levelof education. More educated respondents had high financial literacy scores. We grouped6education into three levels: up to college level (12 years of education), graduate level (16 yearsof education), and post graduate level (more than 16 years of education). Financial literacy
among respondents with more than 16 years of education was much higher than for the othergroups.
[Insert Table 2 about here]
Independent variables
To explain the determinants of financial literacy we include variables related todemographics, socio-economics, and psychological background, in line with the theories
discussed in the introduction. Table 3 reports the variables used in this study.
[Insert Table 3 about here]
Several studies found that financial literacy varies by gender (Kadoya and Khan 2016; Van
Rooij, Lusardi, and Alessie 2011; Alessie et al. 2013; Hung, Yoong, and Brown 2012; Atkinson
and Messy 2012; Sekita 2011; Lusardi and Mitchell 2008). Kadoya and Khan (2016) and Sekita(2011) report that women in Japan score lower financial literacy. While women had nearly
equivalent scores for the basic financial literacy questions, they scored significantly lower forcomplex questions related to risk and diversification. However, it is difficult to explain thesegender differences. The social learning process could partially explain women’s lower financial
literacy. Women, particularly married women, have less scope than men to learn socially andfrom experience, which could lead to difficulty in understanding financial issues. Nevertheless,this theory cannot explain why single, educated women, who more opportunities for social
learning have lower scores (Mahdavi 2012). We thus include the gender variable in this study.
Age is an important determinant because people learn from previous mistakes (Lachance
and Choquette-Bernier 2004; Martin and Oliva 2001) and eventually become more
7

knowledgeable over time. However, Lusardi and Mitchell (2014) outlined a theoreticalframework in which they argued that a hump-shaped lifecycle of financial literacy exits. Other
studies also showed a non-linear relationship between age and financial literacy, as evident bylower financial literacy among younger people and older people (Lusardi and Mitchell 2011b;
Lusardi, Mitchell, and Curto 2010). The initial increase in financial literacy could come fromexperience, while the subsequent decline could be due to a decrease in cognitive abilities(Agarwal et al. 2009). We include the age variable to explore the relationship between age andfinancial literacy in Japan.
Respondents’ and their spouses’ level of education has a direct impact on financial literacy.
Because more educated people have more opportunities to take courses related to money
management, we expect that they will be more financially literate (Lusardi and Mitchell 2011b,
2014). Psychological theories emphasizing cognitive ability could explain the empiricallyevident relationship between education and financial literacy (Gill and Prowse 2015; Lusardi,
Mitchell and Curto 2010). Danes and Haberman (2007) provided evidence that taking a financial
planning curriculum contributed positively to students’ financial literacy. Social learning theories,
on the other hand, could explain why the education level of a spouse and parents affects
respondents’ financial literacy. Empirical research shows that people learn from theirsurroundings, particularly from parents (Pinto, Parente, and Mansfield 2005). People witheducated parents and spouses could learn from their knowledge and experience (Mahdavi 2012).
To accommodate these dimensions of education, we included respondents’ education, spouse’s
education, and parents’ education.

8

Social learning process implies that having a spouse provides more opportunities to shareand gather experiences, which could improve financial literacy. Therefore, we include thevariable “spouse.”
Social learning and consumer socialization theories imply that employment status
significantly affects knowledge acquisition. People who are employed and have more
opportunities to learn about financial issues from the workplace should be more financiallyliterate. Lusardi and Mitchell (2011a) found that employed people had higher financial literacy
worldwide. Occupations could also significantly affect financial literacy. An occupation that
requires an understanding economic and financial aspects provides more scope for people toachieve financial literacy. Our study used “finance and insurance” as the occupation that could
positively affect financial literacy.
Previous studies also provide evidence that household income and balance of financial
assets are related to financial literacy (Lusardi and Tufano 2009; Guiso and Jappelli 2008).
Economic factors create a link between income and assets and financial assets. People who earnmore income and hold more assets need to understand how to use money to maximize their
future benefits. Thus, we included income and asset variables and assume that respondents withmore income and assets will be more financially literate.
We include three behavioral variables in our study: future orientation, current state offinancial satisfaction, and anxiety about life in old age. A psychological orientation toward thefuture could affect the acquisition of financial literacy (Howlett, Kees, and Kemp 2008). People
who emphasize the present have low incentives to acquire financial literacy to maximize futurefinancial benefits. This study used the question, “Since the future is uncertain, it is a waste tothink about it” to measure respondents’ orientation for future. Our second behavioral variable,

9current state of financial satisfaction, also affects financial literacy (Murphy 2013). We measurefinancial satisfaction according to subjective responses to the question, “How satisfied you arewith the current financial situation of your family?” Finally, our third behavioral variable,
anxiety about life in old age could also motivate people to acquire more financial knowledge
about savings and retirement planning to make life during old age more secure.

Data
We used micro data from the Preference Parameters Study of Osaka University’s 21stCentury Center of Excellence (COE) Program, “Behavioral Macrodynamics Based on Surveys
and Experiments” and its Global COE project, “Human Behavior and Socioeconomic Dynamics.”
The data were collected with a nation-wide survey between December 2011 and May 2012 using
visits and placement surveys. The study applied two-stage stratified random sampling of thisdata: first, we divided Japan’s prefectures into 10 regional blocks: Hokkaido, Tohoku, Kanto,
Koshinetsu, Hokuriku, Tokai, Kinki, Chugoku, Shikoku, and Kyusyu; and we then subdivided
each region into four strata: government-designated major cities, cities with populations of morethan 100,000, cities with populations of less than 100,000, and towns and villages. The response
rate was 93.9 percent. The fact that the project was a panel survey explains the high response rate.
The data of respondents’ financial literacy and education were from the wave 2010 and 2011
respectively, because these questions weren’t asked in the 2012 wave. We selected the subjects
with no missing variables and the current study uses a sample of 1,948 respondents.
Table 1 summarizes the descriptive statistics of the variables used in the study. The meanvalue of financial literacy is 0.48, indicating that respondents had a low ability to respondcorrectly to the financial literacy questions. On average, respondents could answer two questions

10

correctly out of four. In terms of demographics, male respondents were somewhat higher innumeracy than the female respondents. The respondents were on average 49.31 years old, with aminimum age of 24 and a maximum age of 69. Most respondents were married. We measured
respondents’ socio-economic features using their level of education and that of their spouses andparents. Japan traditionally has a high level of education, which is reflected in our study.
Respondents on average had more than 13 years of education, meaning that they attained an
above college-level education. Respondents’ spouses also attained similar levels of education.
Respondents’ parents attained an average of 10.84 years of education, with fathers’ educationlevels slightly higher than that of mothers. Although high, household income and asset holdings
showed some degree of disparity among respondents. Respondents’ average income was JPY
6,662,640, with a minimum income of JPY 1,000,000 and a maximum income of JPY
20,000,000. Average asset holdings were JPY 20,920,000, ranging from a minimum of JPY
2,500,000 and a maximum of JPY 100,000,000. In terms of psychological features, respondents
were moderately fatalist, believing that the future is uncertain and thinking about it is a waste oftime. Respondents were also moderately satisfied with their current financial condition. Finally,
their mean anxiety was 3.47, which is moderately high on a five-point scale.
[Insert Table 1 about here]
Model
This study used a linear regression model to investigate the determinants of financial literacy
in Japan. In the regression, financial literacy is the dependent variable, and there are fourteen
independent variables for respondents’ demographic, socio-economic, and psychological features.
The regression equation is as follows:11

Financial Literacy fliteracy(1)
Since distribution of financial literacy by age in Table 2 indicates a nonlinear relationshipbetween financial literacy and age, we examined the relationship more closely by adding an age2
variable in model 2. A positive coefficient on age would indicate a positive relationship between
age and financial literacy, and negative coefficient on age would indicate a nonlinear relationship.
Financial Literacy fliteracy

2(2)

EMPIRICAL RESULTS
Table 4 summarizes the findings on the determinants of financial literacy in Japan. The F
statistic demonstrates the overall validity of the model. We show that demographic features suchas gender, age, and education affect financial literacy considerably. Among the demographic
variables, gender appears to be the most significant, indicating that male respondents are
significantly more financially literate than female respondents, which is in line with the12descriptive statistics in Table 1. Age and education were also significant determinants offinancial literacy in Japan. Both are positively related to financial literacy, indicating thatyounger and less educated respondents are less financially literate. However, age does not have alinear relationship to financial literacy, meaning that age is positively related to financial literacy
up to a certain point, after which the relationship does not hold true. Although marital status did
not affect financial literacy significantly, the spouse’s education is positively related to financial
literacy, suggesting that more educated spouses help their counterparts attain a higher level offinancial literacy. The education of respondents’ parents did not affect financial literacy, contrary
to our hypothesis. We used several economic variables to examine the link between economic
condition and financial literacy. As we expected, both income and assets are positively related tofinancial literacy. Although respondents’ employment status does not contribute to financial
literacy, occupation was significantly positive. This means that respondents who have exposure
to a financial environment in the workplace tend to be more financially literate. We used threepsychological variables in our model, of which orientation toward the future was negatively
related to financial literacy. The coefficient indicates that respondents who consider thinking
about future a waste of time tend to be less financially literate. However, we did not find any
evidence that respondents’ satisfaction with their present financial situation or anxiety about life
in old age influenced financial literacy.
[Insert Table 4 about here]
Robustness checks
We checked the robustness of the results using an alternative measure of financial literacy
that puts more weight on the questions of risks diversification and pricing behavior. The term
weighted financial literacy (fliteracy_w) denotes financial literacy measured by the alternative13

method with the same linear regression model. The results in Table 5 show that as in theunweighted measure of financial literacy, the weighted measure is also affected by factors suchas gender, age, respondents’ and spouses’ education, income, assets, occupation, and orientation
toward the future. Since the effect and statistical significance of the variables are similar for both
the weighted and unweighted measures of financial literacy, we conclude that issues related tomeasuring financial literacy do not create biases in the estimation.
[Insert Table 5 about here]
Endogeneity could affect the OLS regression coefficients reported in Table 4, likely due tothe asset variable. It is possible that asset holdings can increase financial literacy, or that
financial literacy can increase asset holding. To control this reverse causality between assets andfinancial literacy, we used asset inheritance from parents as an instrument for assets. Assetinheritance is a dummy variable equal to 1 if respondents received at least five million yen fromtheir parents and 0 otherwise. Table 6 reports the regression coefficients for Models 1 and 2,
which shows that the positive effect of assets on financial literacy no longer exists using this
instrument. However, effect of other variables remains almost the same.
[Insert Table 6 about here]
DISCUSSION
Previous studies investigated the need for financial literacy to improve household decisions
such as savings, retirement planning, and investment (Bernheim and Garret 2003; Van Rooij,
Lusardi, and Alessie 2011, 2012, Lusardi and Mitchell, 2011; Sekita 2013; Boisclair, Lusardi,
Michaud 2014). However, few studies examine the reverse association. Our study provides
evidence of the determinants of financial literacy in Japan. We based the study on three theories
related to the learning process: social learning theory, consumer socialization theory, and14

psychological theory. We identified fourteen variables that could affect financial literacy andgrouped them into demographic, socio-economic, and psychological factors. Among thedemographic factors, we found that gender, age, and education significantly affect financial
literacy in Japan. Our finding that male respondents are more financially literate than female
respondents is also supported by previous studies (Kadoya and Khan 2016; Lusardi, Alessie, and
Van Rooij 2012; Hung, Yoong, and Brown 2012; Atkinson and Messy 2012; Sekita 2011;
Lusardi and Mitchell 2008). Fonseca et al. (2010) argued that the gender gap in financial literacy
cannot be explained by the characteristics of men and women but rather by how literacy is
produced. Apart from gender, age was also positively related to financial literacy. However, wefound that the relationship is not monotonous; rather, financial literacy peaked in middle age andbegan to decline thereafter. Although previous studies argue that people that learn throughmistakes and over time become more knowledgeable (Lachance and Choquette-Bernier 2004;
Martin and Oliva 2001), Lusardi and Mitchell (2014) argued that the relationship is not so linear.
Lusardi and Mitchell (2011b) and Lusardi, Mitchell, and Curto (2010) also found a non-linear
relationship between age and financial literacy. Education is an important variable with the mostdirect influence on financial literacy, which is supported by psychological theory thatemphasizes cognitive ability (Gill and Prowse 2015; Lusardi, Mitchell and Curto 2010), while
the influence of spouses’ and parents’ education is supported by social learning theory (Pinto
Parente, and Mansfield 2005; Mahdavi 2012). We found that respondents’ and spouses’
education have a positive impact on financial literacy, while parents’ education does not.
Although our findings related to respondents and their spouse’s education are supported bytheory and empirical evidence, the insignificant impact of parents’ education was contrary to ourhypothesis. We argue that the age structure of respondents and their parents could explain this15

finding. Since average age of the respondents in this sample was more than 49 years, they could
have less interaction with their parents. Moreover, parents from the older generations arethemselves less financially educated, which gave their children fewer opportunities to learn
through socialization. Among the demographic variables, marital status did not influencefinancial literacy, though spouse’s education did, which implies that social learning theory works
only when respondents’ have capable spouses.
In terms of socio-economic background, both income and assets have significantly
positive effects on financial literacy, in line with previous studies (Lusardi and Tufano 2009;
Guiso and Jappelli 2008). We also examined employment status and type of occupation tounderstand whether work experience is related to financial literacy. Although employment status
did not have an effect, occupation did have a significant impact. Respondents with working
experience in the finance area were more financially literate than others. However, Lusardi and
Mitchell (2011b) reported that financial literacy was higher among employed respondents intheir sample, our findings suggest that employment status itself did not enhance financial
knowledge; rather, work experience in a relevant field improves financial knowledge.
We also looked at psychological factors to investigate whether respondents’ behavior
influenced financial literacy. A focus on the future strongly influenced respondents’ acquisitionof financial knowledge. Those who consider thinking about the future as a waste of time wereless financially literate. Perceptions about the future is also related to time discount factors andfinancial literacy (Howlett, Kees, and Kemp 2008). The other two factors, level of financial
satisfaction and anxiety about life in old age, did not have a significant influence on financial
literacy.

16

The results did not change after checking the robustness using a weighted financial
literacy score instead of the original unweighted score. We also checked for endogeneity
problems from the potential reverse causality of the asset variable. Using an IV regression model,
we found that the positive effect of assets on financial literacy disappears, while the effect of theother variables remain the same.
Our study has some limitations that affect the interpretations of our results and open avenues
for future research. First, although we checked the robustness of our findings using a weighted
measure of financial literacy, there is no consensus on how to measure financial literacy.
Previous studies report that financial literacy scores vary depending on the questions in thequestionnaire (Hung, Parker, and Yoong 2009; Moore 2003; Mandell 2007). Second, although
we used fourteen variables representing demographic, social-economic, and psychologicalfactors, we did not have the data available to examine respondents’ area of education. Third, selfreported subjective anxiety and financial satisfaction levels might be somewhat misleading.
Some people tend to make extreme choices (i.e., choosing 1 or 5 on a five-point scale), whileothers prefer to make moderate choices (i.e., 3), which affect our results.
Overall, the results of our study suggest that socialization and family orientation have a

profound impact on the acquisition of financial literacy in Japan, which could improve theirsavings, retirement planning, and investment decisions.

17

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Table 1: Descriptive Statistics
Variablefliteracy
genderage
spouse
educ
seduc
feduc
meduc
incomeasset
emplstatus
occupation
futurefinsatisfaction
anxiety

Obs
1948
1948
1948
1948
1948
1948
1948
1948
1948
1948
1948
1948
1948
1948
1948

Mean
0.481
0.569
49.3050.994
13.34813.10910.98610.702
6.662
20.918
0.914
0.030
2.697
2.891
3.474

Std. Dev.
0.280
0.495
9.879
0.078
2.092
1.991
2.350
1.734
3.861
23.565
0.280
0.171
0.850
1.019
1.070

Min
0
0
24
0
9
9
9
9
1
2.5
0
0
1
1
1

Max
1
1
69
1
21
21
21
17
20
100
1
1
5
5
5

24

Table 2: 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
0.381
0.498
0.474
0.532
0.413
0.373
0.466
0.661

25

Table 3: Variables and definitions
Variable
Dependant variable
Financial literacy

Independent Variables
gender
age
educ
Sedu
Fedu
medu
spouseemplstatus
occupation
Asset
Incomefuturefinsatisfaction
anxiety

Definition
Financial literacy is measured by four questions related to basic
financial calculation skills and financial instruments. The first question
measures the understanding of compound interest, the second question
measures the understanding of the effect of inflation, the third question
measures the understanding of risk, and the fourth question measuresthe understanding of bond pricing behavior.
1= male, 0 = female
Respondents’ age
Years of education
Years of education of the spouseYears of education of respondents’ father
Years of education of respondents’ mother
1= married, 0= otherwise
1= currently employed 0 = otherwise
1= working in finance and insurance 0 = all other occupations
Balance of financial assets (savings, stocks, bonds, insurance, etc.) of
the entire household
Household income
1=respondents who consider the future uncertain, 0 = otherwise
Level of current satisfaction with the family’s financial situation.
(minimum=1; maximum=5).
Level of anxiety about life during old age on a five-point scale(minimum=1; maximum=5).

26

Table 4: Regression coefficients

fliteracy
genderage
spouse
educ
seduc
feduc
meduc
incomeasset
emplstatus
occupation
Futurefinsatisfaction
anxietycons

Model 1
Coef.
0.093
0.003
0.017
0.023
0.009
0.001
0.002
0.009
0.001
0.010
0.189
-0.0180.007
0.003-0.305F
Adj. R2
Obs.

30.06***
17.28
1948

t
7.69***
5.17***
0.23
6.73***
2.72***
0.28
0.37
5.83***
4.29***
0.45
5.57***-2.60***
1.03
0.57-2.74***

fliteracy
genderage
age2
spouse
educ
seduc
feduc
meduc
incomeasset
emplstatus
occupation
futurefinsatisfaction
anxietycons
F
Adj. R2
Obs.

Model 2
Coef.
0.094
0.013
0.000
0.016
0.023
0.009
0.001
0.002
0.009
0.001
0.005
0.187
-0.017
0.008
0.002
0.530
28.31***
17.39
1948

t
7.81***
2.45**-1.83*
0.22
6.58***
2.60***
0.32
0.52
5.35***
4.35***
0.26
5.53***-2.57***
1.23
0.39-3.19***

27

Table 5: Robustness check regression coefficients
fliteracy_w
genderage
spouse
educ
seduc
feduc
meduc
incomeasset
emplstatus
occupation
futurefinsatisfaction
anxietycons

Model 1
Coef.
0.373
0.014
0.068
0.093
0.037
0.004
0.006
0.038
0.005
0.038
0.756
-0.0720.027
0.014-3.879F
Adj. R2
Obs.

30.06***
0.172
1948

t
7.69***
5.17***
0.23
6.73***
2.72***
0.28
0.37
5.83***
4.29***
0.45
5.57***-2.60***
1.03
0.57-8.71***

fliteracy_w
genderage
Age2
spouse
educ
seduc
feduc
meduc
incomeasset
emplstatus
occupation
futurefinsatisfaction
anxietycons
F
Adj. R2
Obs.

Model 2
Coef.
0.379
0.054
0.000
0.066
0.091
0.036
0.004
0.009
0.038
0.005
0.022
0.749
-0.071
0.032
0.009-4.78128.31***
0.17391948t
7.81***
2.45***-1.83*
0.22
6.58***
2.60***
0.32
0.52
5.35***
4.35***
0.22
0.553-2.57***
1.23
0.39-7.20***

28

Table 6: Regression coefficients using instrument variablefliteracy
genderage
spouse
educ
seduc
feduc
meduc
incomeasset
emplstatus
occupation
Futurefinsatisfaction
anxietycons

Model 1
Coef.
0.09410.00460.02550.02440.00960.00060.00310.0100-0.00030.00970.1944-0.01960.00890.0022-0.3785

Wald Chi2
R2
Obs.

399.55***
1664
1948

t
7.64***
1.79*
0.33
5.47***
2.75***
0.19
0.56
3.75***-0.09
0.46
5.40***-2.50**
1.10
0.33-1.94*

fliteracy
genderage
age2
spouse
educ
seduc
feduc
meduc
incomeasset
emplstatus
occupation
futurefinsatisfaction
anxietycons
Wald Chi2
R2
Obs.

Model 2
Coef.
0.09560.0137-0.0001
0.02510.02401
0.00930.00070.00370.0100-0.0003
0.00620.1929-0.01940.01020.0012-0.5823403.09***0.16791948t
7.77***
2.47**-1.54
0.33
5.30***
2.64***
0.22
0.69
3.40***-0.09
0.29
5.35***-2.47**
1.27
0.19-2.89***

29