Discussion Papers In Economics
And Business

Male pupils taught by female homeroom teachers show higher
preference for Corporate Social Responsibility in adulthood

Eiji Yamamura, Yoshiro Tsutsui, and Shunsuke Managi

Discussion Paper 18-21

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANMale pupils taught by female homeroom teachers show higher
preference for Corporate Social Responsibility in adulthood

Eiji Yamamura, Yoshiro Tsutsui, and Shunsuke Managi

Discussion Paper 18-21

July 2018

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANMale pupils taught by female homeroom teachers show higher preference for Corporate
Social Responsibility in adulthood
Eiji Yamamura1*, Yoshiro Tsutsui2, and Shunsuke Managi3
1 Department of

Economics, Seinan Gakuin University
6-2-92 Nishijin, Sawara-ku, Fukuoka, 814-8511, Japanyamaei@seinan-gu.ac.jp*corresponding author
2 Faculty of

Economics, Konan University
8-9-1 Okamoto, Higashinada-ku, Kobe, Hyogo, 658-0079, Japan
3 Urban Institute & School ofEngineering, Kyushu University
744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan
managi@doc.kyushu-u.ac.jp

Abstract
On the demand side, we test how early childhood education creates preferences
for Corporate Social Responsibility (CSR) through teacher-student gender randommatching. Using originally collected individual-level data, we examine how female
teachers in elementary school influence students’ CSR stated preferences in theiradulthood. In a quasi-natural experiment setting, our major findings are: (1) female
teachers affect pupils’ preferences for corporate responsibility later in life, (2) the effectof a female teacher is robust if she was a class teacher in first grade, (3) the effect of afemale teacher is observed only for different-gender pupils but not for same-gender ones.
These findings imply that the gender gap in adulthood is reduced by matching female
teachers with male students in earlier years. We examine and support the femalesocialization hypothesis.

JEL classification: G32, G34, J16, M14, I21, H89
Key words: Gender difference, Female socialization, Teacher–Student Gender Matches,
Corporate Social Responsibility, ESG.

1

1. Introduction.

This study tests how learning experience in childhood leads to a sense of values andeconomic outcomes. Early childhood education has received an increasing amount ofattention from social scientists as a key factor to determine students’ life path (e.g.,
Heckman et al., 2010a; 2010b; 2013).1 The influence of education is captured by bothquantity, such as number of schooling years, and by quality. Teaching practices and theeducation system form students’ social capital (Algan et al. 2013), attitude towards risk
(Hryshko et al., 2011), and identity (Aspachs-Bracons et al. 2008).2
Housing economics exert environment influence on students’ outcomes. Outside ofschool, children learn from their parents to form their worldview and social values.
Preferences for trust and cooperation are transmitted in communities through families(Bisin and Verdier, 2001; Bisin et al., 2004). Men with working mothers tend to preferworking women (Kawaguchi and Miyazaki, 2009) and the wives of men whose mothers
worked are significantly more likely to work (Fernandez, et al., 2004). As a consequence,
the gender gap in labor force participation reduces over time. Different-genders matchinghas reverse causality. Men having daughters support women’s views (e.g., Glynn and Sen,
2014; Oswald and Powdthavee, 2010; Washington, 2008). According to this paper,
women influence men’s views and preferences, which is called female socialization

1

Apart from education, the impact of early-life experiences and conditions on managerial decision
are examined (Malmendier et.al, 2011). Differences in individuals' prenatal environments captured bybirth weight cause heterogeneity in financial decisions later in adulthood (Cronqvist et al., 2016).
Early-life disasters influences CEO decision making (Bernile at al, 2017).
2
The quantitative effect of education on citizenship is examined by Milligan et al., (2004) suggestingthat the effect of extra schooling induced through compulsory schooling laws influenced voter turnout.
2

Cronqvist and Yu (2017) examined the female socialization hypothesis in finance byconsidering how corporate social responsibility (CSR) depends on whether a firm’s chief
executive officer (CEO) has his daughter. The daughter’s sense of values is unlikely torelate to the firm’s performance. Investors in socially responsible investment (SRI) funds
are more concerned with ethical or social issues than with fund performance (e.g.,Renneboog et al., 2011; Ho et al., 2016; El Ghoul and Karoui, 2017). That is, investors
will forgo financial performance to invest in accordance with CSR preferences (Riedl andSmeets, 2017). Cronqvist and Yu (2017) explore CSR from the supply side, i.e. the firm’sside. In this paper, we intend to further contribute to the CSR literature by analyzing thegenders’ interactions with respect to the demand for CSR. That is, CSR demand comesfrom people who intend to purchase goods supplied by firms which contribute to CSR
because they value the firm highly. To put it another way, CSR investment provides added
value to the firm’s goods, which increases consumers’ demand for it. This paper
investigates the “different-genders matching effect” on individuals’ CSR preferences byconsidering the propagation mechanism from female teachers into male students.
The Great East Japan earthquake took place in March 2011 and then the Kumamoto
earthquake occurred in April 2016, which invoked citizens to recognize the importanceof firms’ CSR. In June 2016, we collected individual data from the whole of Japan andthe sample size is approximately 7,000. The data includes individuals’ stated CSR
preferences and their detailed educational background. In Japanese elementary schools,
pupils are randomly assigned to classes regardless of the homeroom teacher’s gender.3
Especially in first grade,the assignment is considered as a quasi-natural experiment to3

At elementary school in Japan the homeroom teacher is in charge of one class and teaches most of
the subjects to that class. Therefore, the teacher’s influence on their pupils is much stronger than theteachers in high school.
3

explore teacher-student gender matching effects on students. Schools do not haveinformation about the compatibility between a homeroom teacher and the pupils. Our
dataset has information whether respondents belonged to a female teacher’s class in eachelementary school grade. This data makes it possible to examine how the class teacher’s
gender in the year of entering elementary school form individuals’ CSR preferences inadulthood and compare the effects between male and female respondents.
Using regression analysis, we find the followings. Women tend to prefer firms thatare responsible for the environment, local communities, and governance, compared tomen. However, if the male pupils had a female teacher in the first year, they prefer CSR
in adulthood, while this effect is not observed for female pupils. This implies that thefemale teachers - male pupils matching reduces the gender difference in CSR preferences
since female teachers tend to have stronger interests in CSR compared to male pupils,
whose CSR concerns are low.
The remainder of this article is organized as follows. Section 2 overviews the related
literature. Section 3 describes the setting and the data. Section 4 presents the empiricalmethodology. Estimation results and their interpretation are presented in Section 5. The
final section offers some reflections and conclusions.

2. Literature Review
Economic researchers have paid attention to gender studies. Same-gender teacherstudent matching has been noted to improve students’ educational performance (Dee2007; Lim and Meer 2017). 4 Women’s employment status is transmitted to their

4

The effect of same-gender teachers on students has not been observed in other studies (Holmlund
and Sund 2008; Cho 2012; Winters et al., 2013; Sansone 2017).
4

daughters, suggesting that a mother is a role model for her daughter (Tanaka, 2008).
However, previous research did not emphasize the different gender-matching effects in
education. Individual characteristics and preferences partly differ according to gender(Croson and Gneezy, 2009). Inevitably, the learning effect from the same-gender teacher
and parents becomes smaller. If so, same-gender transmission effects hardly exist anddifferent-gender interaction is possibly influential.5
A number of works examine the female socialization hypothesis where genderdifferences within the family are analyzed. Having a daughter changes a father’s politicalview (Washington, 2008; Oswald and Powdthavee, 2010). Similarly,

having a daughter

leads her father’s preference to be similar to female’s one (Warner 1991; Warner and Steel1999). The reason might be that having a daughter forms a father’s identity (Akerlof andKranton, 2000; Chen and Li, 2009). There are also similar observations for the motherand-son relationship. A son with a full-time working mother is more inclined to have apositive view about working women (Kawaguchi and Miyazaki, 2009), which, in turn,
encourages his wife’s labor force participation (Fernandez, et al., 2004).
Compared to men, women are more benevolent and universally concerned (e.g.,
Beutel and Marini, 1995; Adams and Funk, 2012) and less aggressive in competitiveenvironments (Booth and Yamamura, 2018). In an experimental setting, women behave
more generously than men (Eckel and Grossman, 1998) 6 . It is valuable to examine
whether different-gender interactions through education reduce the gender difference inprosocial preferences, which can be captured by CSR-related preferences.

5

Recently, the influence of gender interactions is explored in credit market (Beck et al. 2018).
In empirical studies, the effect of gender differences of social preferences depends on theexperimental setting (e.g., Andreoni and Vesterlund, 2001; DellaVigna, List, Malmendier, and Rao,2013).
65

A firm’s CSR activities are mainly analyzed from the supply side. A ceaseless firm’s
CSR investment plays an important role in providing information on the firm’s strategy
for investors and consumers in the market (Abdelsalam, 2014). From a valuation
perspective, CSR expenditures potentially create value for the firm (Fatemi et al., 2015).
Empirical works show that a firm’s CSR activities create an ethical and healthy corporate
image, which gives credibility to its R&D projects (Ho et al., 2016). Firms with higher
CSR scores tend to receive more favorable news coverage, and the positive interaction
between CSR and the media coverage improves their performance (Cahan et al., 2015).
Consistently, empirical works report various benefits from CSR; for example, firms withhigher CSR intensity have better stock return performance, profitability, and sales per
employee (Lins et al, 2017), and higher net interest income and non-interest income (Wuand Shen, 2013). The firm’s corporate environmental policies reduce environmental risk
exposure, which increases shareholder value (Fernando et al., 2017). CSR activities
publicized through media coverage increase shareholder value, which, in turn, improves
future operating performance (Byun and Oh, 2018). Better CSR performance results inlower credit risk (Stellner et al., 2015). Socially responsible mutual funds show better
performance than conventional mutual funds during market crises (Nofsinger and Varma,2014).
As far as CSR’ relationship with governance is concerned, CSR investment depends
on the country’s legal origin (Liang and Renneboog, 2017) and local political andreligious factors (Borgers et. al., 2015). Family-controlled firms exhibit lower CSR
performance due to greater agency problems (El Ghoul et al., 2016). These findings
suggest the firm’s governance is crucial in determining the firm’s benefit from CSR. In
line with that, well-governed firms are less likely to suffer from agency concerns and6more likely to engage in CSR (Ferrell et al., 2016). Socially responsible firms which
commit to a high standard of transparency have lower crash risk (Kim et al., 2014). CSR
is thought to increase social capital. This, in turn, reduces the equity cost of firms locatedin areas with high social capital (Gupta et al., 2018). Therefore, a firm’s CSR investment
improves the firm’s performance through the formation of social capital. Therefore, a firmfrom a higher social capital region tends to exhibit higher CSR investment (Jha and Cox,2015).
Gender matters for CSR activities. Confident CEOs are likely to underestimate firmrisks and are unlikely to invest in CSR (McCarthy et al., 2017).7 Men are more inclined
to be over-confident with respect to investing than women, which possibly results insmaller return on investment (Barber and Odean, 2001). Female CEOs invest more in
CSR than male CEOs. When honesty is concerned, men are significantly more inclined
than women to deceive to secure a monetary benefit (Almenberg and Dreber, 2015).8
However, deception results in distrust for those affected by such dishonest behavior,
eventually resulting in lost benefits in the long-run. Naturally, gender-balanced board
meetings lead to improvements in the firm’s efficiency (Schwartz-Ziv, 2017).9
Despite the benefits from female representation, female CEOs are under more severe
credit constraints than male CEOs (Moro et al., 2017). Male Wall Street analysts improvetheir job performance through alumni network better than female analysts (Fang andHuang, 2017). Male executives receive larger profits from insider trading because female
executives have a disadvantage relative to male colleagues in access to insider

7

Female CEOs reduce firm risk compared to male CEOs (Walayet et al., 2013).
It has been observed that men are more dishonest than women (Friesen and Gangadharan, 2012).
9 Having a daughter reduces parents’ dishonest behavior (e.g., Houser et al., 2016).
8

7

information (Inci et al., 2017).10 These findings support the evidence on discrimination
against female executives and the existence of the proverbial glass ceiling.
All the above gender studies about CSR are from the supply-side perspective. We
contribute to the existing literature by studying CSR from the demand-side perspective.
This is the first demand-side gender analysis on CSR. Without gender distinction,
conventional demand analysis points out that individuals were more likely to preferproducts from manufacturing companies with a higher CSR rating and this tendency isstronger for more educated people (Cai and Aguilar, 2013). Similarly, consumers tend toprefer the products of firms who are active in CSR (Arana and Leon, 2009).

3. Empirical methodology
3.1. The data collection process
To investigate the effect of early childhood education on CSR preferences, we
obtained individual-level data through a web-based survey in July 2016. The Nikkei
Research Company was commissioned to conduct the web survey. According to a 2015
survey on information technology, over 90 % of the working-age population in Japan is
web-users. Therefore, selection bias is not expected. 11 The sample’s demographic
composition is equivalent to the 2015 Japan Census composition.
Since we aimed to collect over 10,000 observations, the survey was active until
10,000 observations were collected. Indeed, 12,176 respondents were asked to fill in the10

According to Jensen et al. (2018), female inventors have a disadvantage in the process of obtaining
and maintaining patents. However, patents authored by women who were not easily identified as
women were cited more frequently.
11 Data is available from the official website of the Statistics Bureau, Ministry of Internal Affairs andCommunications http://www.soumu.go.jp/johotsusintokei/statistics/statistics05.html (access on April
5, 2018).
8

questionnaire and 9,997 returned it. However, since some questions were not answered,
the sample size reduced to 6,897. The number of male and female respondents were 3,486
and 3,501, respectively.

3.2. Features of the data
Table 1 provides definitions of the key variables and their descriptive statistics.
CSR is a vague concept and covers various facets in society. We first define our CSR
measure. Environment, Social, and Governance (ESG) have been used in recent studies
to indicate a firm’s social responsibility (Ailman et al., 2017; Hanson et al., 2017).
ESG is a superior measure in that it is a concrete notion. Environment captures the
aspect of the firm’s responsibility for environmental problems, Social captures the firm’s
responsibility for the local community, and Governance reflects the firm’s transparency.
Following existing research, we adopt ESG to analyze the stated preferences for CSR.12
The questions for Environment, Social, and Governance in our survey are presented inTable 1. Participants were asked to provide their responses on a scale ranging from 1(strongly disagree) to 5 (strongly agree). Even though the means and standard deviations
across these composites are not very different from each other, the difference between
men and women varies according to the CSR proxies because different proxies are meant
to capture different CSR aspect. Hence, in order to capture overall CSR, we also use theaverage values of these three variables (ESG), to evaluate how the assignment to a female
teacher class influenced the formation of the pupils’ CSR preferences.
In Japan, education is compulsory for 6 years in elementary school and 3 years in

12

The ESG term is used to examine CSR in the academic literature (Nofsinger and Varma 2014;
Stellner et al., 2015).
9

junior high school. Pupils enter elementary school in April at the age of 6 and graduate
from it in March at the age of 12. Years spent in a female teacher’s class in elementary
school (Female teacher years) range between 0 (i.e., male teachers in all 6 years) and 6(i.e., female teachers in all 6 years). The average value is 3.44, which implies that
respondents were assigned to a class with a female teacher in almost 60 % of theirelementary school years. According to the 2016 School Basic Survey, female teachers
represent 64% of the full-time teachers in elementary school.13 Hence, the sample of thispaper is representative of Japan’s society.
Figure 1 illustrates the difference in CSR scores in adulthood between those who
belonged to a woman’s and a man’s class in each grade in elementary school. Overall, theCSR level of pupils belonging to a woman’s class is higher than that of a man’s class inall cases. The difference in CSR between female and male teachers’ classes is the largest
in first grade and declines as pupils are promoted. The CSR of pupils who belonged tofemale teachers’ classes is not very different from those who belonged to male teachers’classes in the higher grades (from 4th to 6th grade). These findings suggest that female
teachers may influence their students’ CSR preferences only if the respondents belonged
to a female teacher’s class in the lower grades. On the other hand, Figure 2 shows thedifference in CSR values between male and female respondents. In all cases, women’sscores are higher than men’s ones. Considering Figures 1 and 2 together, this study intends
to test the following hypothesis:

13

Data is available from the official website of the Statistics Bureau, Ministry of Internal Affairs andCommunications
https://www.e-stat.go.jp/statsearch/files?page=1&layout=datalist&tstat=000001011528&cycle=0&tclass1=000001110643&tclas
s2=000001110644&tclass3=000001110645&tclass4=000001110649&second2=1 (access on April 5,
2018)
10

Hypothesis:
A female teacher’s CSR preferences form her pupils’ preferences in their adulthood if thepupils belonged to her class in the lower elementary school grades.

4. Empirical specifications
Our baseline model assesses how a female homeroom (class) teacher in elementary
school affects her pupils’ CSR preferences later in life. The estimated function takes thefollowing form:
ESG i = α0 + α1 Female teacher years i + α2 Group learn i + α3 Competition i+ α4 Social capital i + Xi B + u i.

(1)

Apart from the above specification where ESG is the dependent variable, there are threeother specifications where the three factors decomposed from ESG, Environment, Social,and Governance, are dependent variables. Environment, Social, and Governance capture
the respondents’ view on the firm’s responsibility for the environment, transparency, andthe local community. The key independent variable is Female teacher years (the total
number of years with a female homeroom teacher). Its coefficient has a positive sign if
female teachers affected pupils’ CSR preference. In addition to the full-sample estimation,
we use sub-samples divided by the respondents’ gender to examine the teacher–pupil
gender-matching effects. Female teacher years would show a significant positive sign
only for the men’s sample, if a different-gender matching effect exists (e.g., Washington,
2008; Oswald and Powdthavee, 2010; Cronqvist and Yu, 2017). Another possibility isthat Female teacher years shows a significant positive sign only for the women’s sample,
if a same-gender matching effect is observed (e.g., Dee 2007; Lim and Meer, 2017).
11

Teachers have various opportunities to interact with pupils and display their attitudes,
which might reflect their gender identity. This influences pupils’ characters and views.
Early childhood education is expected to develop non-cognitive skills and affectpreferences for policy and firm activity (Yamamura and Tsutsui, 2018). In this study, we
focus on gender difference in the formation of non-cognitive skills. However, someteaching practices such as group study are known to be effective in enhancing noncognitive skills regardless of the teacher’s gender. Based on previous literature (Algan etal., 2013), Group learn and Competition are included as independent variables to control
for these effects.
Further, social capital influences the firm’s CSR investment (Jha and Cox, 2015;
Gupta, et al., 2018) and also the individual’s CSR preference. Accordingly, we also
include Social capital as an independent variable, which captures the individual’s
accumulation of social capital in childhood (see Table 1 for the definitions of thesevariables). These variables are expected to have a positive sign. The reason is individuals
learn diverse values and views from others in their childhood, leading them to havediverse views. This leads them to have critical view about the common view about therole of firm such as pursuing cost minimization in adulthood. This inference is in linewith existing research (e.g., Bisin and Verdier, 2001; Bisin et al., 2004; Algan et al., 2013).
In addition, the control variables vector is denoted by Xi and the vector of theestimated coefficients is denoted by B. The control variables are the individual’s numberof schooling years as a proxy for the quantity of education, age, 17 income dummies, and19 occupation dummies. It is plausible that family conditions also influence the formationof preferences. Parents’ educational attainments are controlled for by including father’sand mother’s educational attainment dummies. Further, family composition is an12

important factor to determine CSR preferences (Cronqvist and Yu, 2017). Therefore, thenumber of siblings is included separately. The effects of life circumstances are controlled
for by dummies for current residential prefecture and residential prefecture when the pupil
was 6 years old. With the exception of number of schooling years, age, and siblings, theestimation results for these control variables are not reported. However, these variables
are included in all estimations. 14 For a more detailed examination of the alternative
specifications, we divide Female teacher years into years spent in low and high grades.
Female teacher years in low grade is the number of years the teacher was a woman during
the first 3 years, that is, first to third grade. Female teacher years in high grade is thenumber of years the teacher was a woman during the last 3 years, that is, forth to sixth
grade.
This specification allows us to compare the effect of a female teacher between theearlier and later development stages. The female teacher’s positive influence is only
observed for Female teacher years in low grade if earlier childhood education has asignificant effect (e.g., Heckman et al., 2010a; 2010b; 2013).. Teachers learn about pupils’
characters and dispositions while teaching them and observing their behavior in school.
When pupils were inappropriately matched with a female teacher in the past, they arelikely to be assigned to a male teacher class. That is, similar to the selection bias ofdaughters’ birth order (Cronqvist and Yu, 2017), the assignment to a female teacher classin higher grades seems to be determined by information about the compatibility between
teacher-pupil genders. Therefore, the assignment to a women’s class in first grade is more
random and exogenous than for other grades. As a result, the first-grade assignment is

14

The results for the control variables are available from the corresponding author upon request.
13

free from selection bias. Therefore, we use dummy variables for a female teacher class ineach grade to identify the effect of a female teacher class in first grade. We note that thereference group is not any grade. The reference group comprises pupils who wereassigned to a male teacher’s class in every grade. Hence, there is a possibility that all the
6 female teacher dummies are equal to 1 when respondents were assigned to a female
teacher’s class from first to sixth grade. Female teacher in 1st year is expected to have asignificant positive sign if the female teacher affects the pupils’ CSR preference. Since
all variables are exogenous with respect to the CSR variables, the models are estimatedwith Ordinary Least Squares (OLS).

5. Results
5.1. Baseline model
Table 2 presents the estimation results of the baseline model. The results based on thefull sample are presented in panel A. The results of the male and female sub-samples arein panels B and C, respectively.
In Panel A, the estimates from the regressions where ESG, Environment, Social, andGovernance are used as the dependent variables are presented in columns 1 to 4,
respectively. The Female teacher years coefficient has a positive sign and is statisticallysignificant in all columns. This is consistent with our Hypothesis provided in section 3.
Therefore, the gender of the elementary school teacher plays a critical role in forming
pupils’ CSR preference. The Women coefficient shows a positive and statisticallysignificant sign except in column 4. These results suggest that, in comparison with male
respondents, female respondents place higher value on firms which are responsible forthe environment and the local community. However, there is no gender difference about
14the firm’s responsibility for transparency (Governance in column 4). According to ourinterpretation of the Female teacher years coefficient, pupils who learned from female
teachers care for CSR. Further, the results of Women show that women are more inclined
to care for CSR. The combined results of the Female teacher years and the Women
variables imply that pupils who learned from female teachers tend to have similar
preferences to their teachers. After controlling for the learning effects (Female teacher
years), the significantly positive sign for the Women coefficient in columns 1-3 indicatesthat the gender-difference in CSR is not only caused by learning from female teachers but
is also natural. On the other hand, as presented in column 4, Women is not statisticallysignificant, implying that the gender-difference of Governance is not determined bynature.
Analyzing education practices in elementary school, panel A shows the signs ofGroup learn and Competition are significant and positive in most cases. This is consistent
with the argument that specific educational features such as teaching practices affectpupils’ preferences and views about society (e.g., Aspachs-Bracons et al., 2008; Hryshko
et al., 2011; Milligan et al., 2004). Regarding extracurricular activities outside school, thecoefficient of Social capital is also positive and statistically significant in all columns.
This implies that social participation extends personal relationships in society and thereby
leads children to have more diverse views about society. In addition to the quality ofeducation, we also investigate the effect of the quantity of education (Schooling years).
In all columns, we observe a significant and positive sign for Schooling years, whichsuggests that CSR preferences depend on the quantity as well as the quality of education.
Even though not reported in the panel, the mother’s and father’s educational attainments
are controlled for, although they do not have any significant effect. Brothers and Sisters
15

have a positive and statistically significant sign in columns 1-3. Hence, learning fromsiblings possibly affects preference formation. The coefficients for Sisters are almost thesame as those for Brothers, suggesting that the effects of siblings do not differ with theirgenders.
We see from panel B that the coefficient estimates for Female teacher years are
similar to those in panel A. On the other hand, in panel C, Female teacher year is notstatistically significant in columns 2 and 3, although it is significantly positive in columns
1 and 4. Comparing panels B and C, we see that the presence of a female teacher
consistently influences male pupils to prefer CSR regardless of the CSR proxies (ESG,
Governance, Environment, and Social), while the female teacher’s influence on female
pupils is observed only for ESG and Governance but not for Environment and Social.
However, the magnitude of the Governance coefficient is the same regardless of thepupils’ gender. Furthermore, in the Governance regression estimation, the Female teacher
years coefficient is 0.03 for both male and female respondents, showing the female
teacher’s effects are the same regardless of the pupils’ gender.

5.2. Closer examination
For closer examination, Female teacher years is divided into lower and higher grades
and its results are presented in Table 3. In this table, all the independent variables otherthan Female teacher years are the same as in Table 2, but not all the results are reported
for the sake of space.
Let us first examine columns 1-3. In Panel A, where the full sample is used, it isinteresting to observe that Female teacher years in low grade shows a significant andpositive sign, while Female teacher years in high grade does not show statistical16

significance. Therefore, the effect of a female teacher’s class on pupils is observed onlyin the lower grades for Environment and Social. On the other hand, the results for Womenare similar to those in Panel A in Table 2, showing there is a gender difference in CSR for
Environment and Social. The full sample and the men’s sub-sample results are consistent
with Figure 1. As for the results based on the female respondents sub-sample, Panel C,neither teacher years in low grade nor teacher years in high grade show statisticalsignificance. Therefore, a female teacher does not influence the same gender pupils’
preferences for Environment and Social at all. We interpret the combined results of Panels
B and C in Table 3 as follows: women assign more importance to y a firm’s responsibility
to the environment and the local community than men, which is a natural trait rather thana result of learning from a teacher. On the other hand, due to the men’s lower level of
CSR preferences for these issues, there is room to positively influence men’s CSR
preferences through the effects of female teachers. The combined results from Panels AC support our hypothesis.
Analyzing column 4 where the dependent variable is Governance in Panels A-C, thefemale teacher’s class has a significant effect on Governance regardless of grades,
although the Female teacher years in high grade coefficient is 0.02 which is smaller than
0.03 (Female teacher years in low grade). However, the Women results do not show
statistical significance; therefore, there is no difference between male and female
respondents. It is interesting to observe that results based on both male and female
respondents’ sub-samples in Panels B and C are almost the same as those of Panel A. Thatis, a female teacher leads pupils to prefer Governance not only for different-gender but
also for same-gender students. In addition, the female teacher’s effects continue to befound in the higher grades although they become weaker. We should carefully consider
17

that, because class assignment is not purely randomly determined. However, the result
suggests that a female teacher influences more mature students and the preference forGovernance is formed not only through infant experience but also through social
experience at the more mature stage.
There is one possible explanation for the fact that female teachers in both low andhigh grades make a significant contribution to forming pupils’ preferences for
Governance regardless of the pupils’ genders. The mechanism of the Governancepreference formation is considered to differ from that of Environment and Social. Pupils
engage in personal interaction by mingling with classmates, which leads them tounderstand the importance of Social. Pupils are also able to directly observe theenvironment around them, which leads them to intuitively recognize its importance. On
the other hand, Governance is a matter of organizational management, which is more
complicated for pupils to understand than Environment and Social. Pupils have tounderstand the notion of organization to have a view about the importance of governance.
That is, experience at the mature stage is also an important factor in determining
Governance. This inevitably causes the results for Governance to differ from
Environment and Social. The reason for statistical significance of the female teacher’sclass not only for the men’s sample but also for the women’s sample will be examined in
the future studies, as further investigation of this topic is beyond the scope of this paper.
Table 4 focuses on the effect of female teacher class in each grade when ESG is thedependent variable. Key variables are the dummies for a female teacher class in each
grade. If pupils are assigned to a female teacher class and match well with the teacher,they might be assigned to a female’s class again in the next grade. Hence, there is apossibility for a selection bias in the subsequent grades. On the other hand, as mentioned
18

earlier, pupils are randomly assigned to a female teacher class in first grade. The classassignment of pupils is determined before they enter elementary school and the possible
compatibility between teachers and pupils is not considered at all. New pupils and theirparents are not allowed to choose a class teacher and they cannot know the gender of theirclass teacher before the entrance ceremony. Therefore, the effect of Female teacher in 1styear is unlikely to suffer from a selection bias. Female teacher in 1st year is considered
to capture the effect of a female teacher’s class in the quasi-natural experiment setting.
Hence, in Table 4, we focus our attention to the result from Female teacher in 1st year.
In Table 4, the results when all 6 grade dummies are included as independent variables
together are reported in column 1 in each panel. However, there seems to be amulticollinearity problem among the dummies. For robustness check, in addition toFemale teacher in 1st year, we include the other grade dummies separately in alternative
specifications. In Panel A, Female teacher in 1st year shows a positive and significant
sign in all columns except for columns 1 and 3. Further, the coefficient of Women has asignificant and positive sign in all columns. In most columns, the coefficient of Women is
0.05 on the-5 point scale, which is equivalent to the value of Female teacher in 1st year.
That is, assignment to a female teacher class in first grade of elementary school is as
important as natural tendencies in explaining gender difference in ESG.
Focusing on the sub-sample results, Panel B of Table 4 shows that only Female
teacher in 1st year shows a statistically significant and positive sign in all columns.
Further, the coefficient is 0.07 and does not change across the different specifications.
Hence, the effect of Female teacher in 1st year can be considered robust. Apart fromcolumn 1, with the exception of Female teacher in 2nd year, a female teacher’s class inlower grades produces a positive and statistical significant sign. Overall, under a natural19

experimental setting, assignment to a female teacher’s class exerts a long-standing
influence on male pupils’ CSR preferences. On the other hand, in Panel C of Table 4,
there is no significant signs at all. Hence, the effects of a female teacher class are only
observed for different-gender pupils and the selection-bias-free effect in first grade issignificant and sizable for the male respondents’ sample.
As is argued earlier, the experimental setting of a random assignment to a female
teacher’s class can be justified only in first grade because the school cannot obtain
information about pupils’ characters before they enter school. The estimation results madeit evident that the random matching of female teachers and male pupils in first grade leads
male pupils to prefer ESG later in life. The female socialization hypothesis holds true forthe formation of CSR preferences not only on the supply side (Cronqvist, and Yu. 2017),
but also on the demand side.

6. Conclusion

An increasing number of studies examine the reason why companies’ boards of directors
emphasize the importance of CSR. It has been shown that women are more likely to
exhibit prosocial preferences (e.g., Beutel and Marini, 1995; Adams and Funk, 2012). In
the CSR literature, women’s gender difference and effect on men have been explored(Cronqvist and Yu, 2017). However, the existing research analyzed the gender effect fromthe supply (firm) side of CSR. The corporate executives make decision in response to thedemand for CSR. To consider the gender effect on CSR, it is necessary to analyze it fromthe demand (i.e., consumers and investors) side. This paper attempts to explore whether
the female socialization hypothesis holds by considering how ordinary people’s CSR
20

preferences form.
We collected individual-level data which contains CSR indices and the elementary
school teacher’s gender. In elementary school, especially in first grade, students are
randomly assigned to teachers, because the school does not know the compatibility
between a teacher and pupils. We conducted a quasi-natural experiment to explore theeffect of teacher–pupil gender matching on stated CSR preferences in adulthood. We
found that assigning pupils to a female teacher class in first grade leads them to prefer
corporate responsibility later in life. The effects of a female teacher on preference
formation are observed for different-gender pupils not but for the same-gender ones.
Based on our findings, we argue that the gender gap in adulthood can be reduced bymatching female teachers with male pupils in earlier years. These findings support thefemale socialization hypothesis. As Dittrich & Leipold (2014) show, men tend to be
impatient and choose to receive an immediate payment rather than a larger sum later. Menseem to put more focus on short-run profit maximization than women. To put it differently,
women have a wider view about the firm’s role in society than men do. However,paradoxically, women’s view possibly results in larger profit in the long-run because CSR
is vital to increase a firm’s value in more developed societies. Interaction between thegenders contributes to realizing not only an efficient but also a sustainable society.
CSR is an ambiguous concept and requires an analysis of its specific factors. We showthat the teacher-pupil gender matching affects CSR preference formation differently
depending on the specific measures. The mechanism of preference formation with respect
to the firm’s responsibility in improving governance is different from that of preference
formation regarding the environment and society. However, it is not known yet how andwhy such differences exist. Furthermore, this paper does not analyze how female teachers21

in elementary school influence the top decision makers such as politicians and corporate
executives regarding CSR issues. Such research should connect financial studies (thesupply side) with educational economics (the demand side) and provide valuable policy
implications. These remaining issues should be addressed in future works.

22

References.
Abdelsalam, O., Duygun, M., Matallín-Sáez, J. C., Tortosa-Ausina, E. 2014. Do ethics
imply persistence? The case of Islamic and socially responsible funds. Journal of
Banking & Finance, 40(C), 182-194.
Adams, R. B., Funk, P., 2012. Beyond the glass ceiling: Does gender matter? Management
Science 58, 219-235.
Ailman, C., Edkins, M., Mitchem, K, Eliopoulos, T., Guillot, J. 2017. The Next Wave of
ESG Integration: Lessons from Institutional Investors. Journal of Applied Corporate
Finance, 29 (2), 32-43.
Akerlof, G. A., Kranton, R. E., 2000. Economics and identity. Quarterly Journal of
Economics 115, 715-753.
Algan, Y., Cahuc, P., Shleifer, A. 2013. Teaching Practices and Social Capital. American
Economic Journal: Applied Economics, 5 (3), 189–210.
Almenberg, J., Dreber, A. 2015. Gender, financial literacy and stock market participation.
Economics Letters 137, 140-142.
Aspachs-Bracons, O., Clots-Figueras, I., Costa-Font, J., Masella, P. 2008. Compulsory
language educational policies and identity formation. Journal of European Economic
Association, 6 (2–3), 434–444.
Andreoni, J., Vesterlund, L., 2001. Which is the fair sex? Gender differences in altruism.
Quarterly Journal of Economics 116, 293-312.
Arana, J. E., Leon, C. J. 2009. The role of environmental management in consumers
preferences for corporate social responsibility. Environmental and Resource
Economics, 44 (4), 495-506.
Barber, B. M., Odean, T. 2001. Boys will be boys: Gender, overconfidence, and common
23stock investment. Quarterly Journal of Economics, 116 (1), 261–292,
Beck, T., Behr, P., Madestam, A. 2018. Do gender interactions matter for credit market
outcomes? Journal of Banking & Finance, 87 (C), 380-396.
Bernile, G., Bhagwat, V., Rau, P. R., 2017. What doesn’t kill you will only make you
more risk loving: Early-life disasters and ceo behavior. The Journal of Finance 72,
167-206.
Beutel, A. M., Marini, M. M., 1995. Gender and values. American Sociological Review
60, 436-448.
Bisin, A., Verdier, T. 2001. The Economics of cultural transmission and the dynamics ofpreferences. Journal of Economic Theory 97 (2): 298–319.
Bisin, A., Topa, G., Verdier, T., 2004. Religious intermarriage and socialization in the
United States. Journal of Political Economy 112, 615-664.
Booth, A., Yamamura, E. 2017. Performance in mixed-sex and single-sex tournaments:
What we can learn from speedboat races in Japan. Forthcoming in Review of
Economics & Statistics.
Borgers, A., Derwall, J., Koedijk, K., ter Horst, J. 2015. Do social factors influence
investment behavior and performance? Evidence from mutual fund holdings.
Journal of Banking & Finance, 60 (C), 112-126.
Byun, S. K., Oh, J.M. 2018. Local corporate social responsibility, media coverage, andshareholder value. Journal of Banking & Finance, 87 (C), 68-86.
Cahan, S. F., Chen, C., Chen, Li., Nguyen, N. H.. 2015. Corporate social responsibility
and media coverage. Journal of Banking & Finance, 59 (C), 409-422.
Cai, Z., Aguilar, F. X. 2013. Consumer stated purchasing preferences and corporate social
responsibility in the wood products industry: A conjoint analysis in the U.S. and24

China. Ecological Economics, 95, 118-27.
Chen, Y., Li, S. X., 2009. Group identity and social preferences. American Economic
Review 99, 431-457.
Cho, Insook, 2012. The effect of teacher–student gender matching: Evidence from OECD
countries. Economics of Education Review, 31 (3), 54-67.
Cronqvist, H., Previtero, A., Siegel, S., White, R E. 2016. The fetal origins hypothesis in
Finance: Prenatal environment, the gender gap, and investor behavior. Review of
Financial Studies, 29 (3), 739-786.
Cronqvist, H., Yu, F. 2017. Shaped by their daughters: Executives, female socialization,and corporate social responsibility, Journal of Financial Economics, 126 (3), 543562.
Croson, R., Gneezy, U., 2009. Gender differences in preferences. Journal of Economic
Literature 47, 448-474.
Dee,T. S. 2007. Teachers and the gender gaps in student achievement," Journal of Human
Resources 42 (3), 528-554.
Della Vigna, S., List, J. A., Malmendier, U., Rao, G., 2013. The importance of being
marginal: Gender differences in generosity. American Economic Review 103, 586590.
Dittrich, M., Leipold, K. 2014. Gender differences in time preferences. Economics Letters,
122 (3), 413–415.
Eckel, C. C., Grossman, P.H. 1998. Are women less selfish than men?: Evidence fromdictator experiments. Economic Journal 108 (448), 726-735.
El Ghoul, S., Guedhami, O., Wang, H., Kwok, C.Y.. 2016. Family control and corporatesocial responsibility. Journal of Banking & Finance, 73 (C), 131-146.
25

El Ghoul, S., Karoui, A. 2017.

Does corporate social responsibility affect mutual fundperformance and flows? Journal of Banking & Finance, 77 (C), 53-63.
Fang, L.Hua., Huang, S. 2017. Gender and connections among Wall Street analysts.
Review of Financial Studies, 30 (9), 3305-3335.
Fatemi, A., Fooladi, I., Tehranian, H. 2015. Valuation effects of corporate social
responsibility. Journal of Banking & Finance, 59 (C), 182-192.
Fernandez, R., Fogli, A., Olivetti, C., 2004. Mothers and sons: Preference formation andfemale labor force dynamics. Quarterly Journal of Economics 119, 1249-1299.
Fernando, C. S., Sharfman, M. P., Uysal, V. B. 2017. Corporate environmental policy andshareholder value: Following the smart money. Journal of Financial and Quantitative
Analysis, 52 (5), 2023-2051.
Ferrell, A., Liang, H., Renneboog, L. 2016. Socially responsible firms. Journal of
Financial Economics, 122 (3), 585-606.
Friesen, L., Gangadharan, L. 2012. Individual level evidence of dishonesty and the gendereffect. Economics Letters, 117 (3), 624-626.
Glynn, A. N., Sen, M., 2014. Identifying judicial empathy: Does having daughters cause
judges to rule for women’s issues? American Journal of Political Science 59, 37-54.
Gupta, A., Raman, K., Shang, C. 2018. Social capital and the cost of equity. Journal of
Banking & Finance, 87 (C), 102-117.
Hanson, D., Lyons, T., Bender, J, Bertocci, B., Lamym, B. 2017. Analysts’ round table on
integrating ESG into investment decision-making. Journal of Applied Corporate
Finance, 29 (2), 44-55.
Heckman, J, Moon, S.H. Pinto, R., Peter Savelyev, P., Yavitz, A. 2010 a. The rate of returnto the high scope Perry Preschool Program. Journal of Public Economics 94 (1262),114-128.
Heckman, J, Moon, S.H., Pinto, R., Peter Savelyev, P,, Yavitz, A. 2010 b. Analyzing social
experiments as implemented: A reexamination of the evidence from the High Scope
Perry Proschool Program. Quantitative Economics 1 (1),1-46.
Heckman, James., Pinto, R., Peter Savelyev, P. 2013. Understanding the mechanisms
through which an influential early childhood program boosted adult outcomes.
American Economic Review 103 (6), 2052-86.
Ho, S. S.M., Li, A. Y., Tam, K., Tong, J. Y.. 2016. Ethical image, corporate social
responsibility, and R&D valuation. Pacific-Basin Finance Journal, Part B, 40, 33548.
Holmlund, H., Sund, K., 2008. Is the gender gap in school performance affected by thesex of the teacher. Labour Economics, 15 (1), 37-53.
Houser, D., List, J. A., Piovesan, M., Samek, A. S., Winter, J., 2016. On the origins of
dishonesty: From parents to children. European Economic Review 82, 242-254.
Hryshko, D., Luengo-Prado, M. J., Sørensen, & Bent E. 2011. Childhood determinants ofrisk aversion: The long shadow of compulsory education. Quantitative Economics,
2 (1), 37-72.
Inci, A. C., Narayanan, M. P., Seyhun, H. N, 2017. Gender differences in executives’access to information. Journal of Financial and Quantitative Analysis, 52 (3), 9911016.
Jha, A., Cox, J. 2015. Corporate social responsibility and social capital. Journal of
Banking & Finance, 60 (C), 252-270.
Jensen, K., Kovács, B., & Sorenson, O. 2018. Gender differences in obtaining andmaintaining patent rights. Nature Biotechnology, 36 (4), 307-309.
27

Kawaguchi, D., Miyazaki, J. 2009. Working mothers and sons’ preferences regarding
female labor supply: Direct evidence from stated preferences. Journal of Population
Economics, 22 (1), 115-130.
Kim, Y., Li, H., Li, S. 2014. Corporate social responsibility and stock price crash risk.
Journal of Banking & Finance, 43 (C), 1-13.
Liang, H., Renneboog, L.. 2017. On the foundations of corporate social responsibility.
Journal of Finance, 72 (2), 853-910.
Lim, J., Meer, J. 2017. The impact of teacher–student gender matches: Random
assignment evidence from South Korea. Journal of Human Resources, 52 (4), 979997.
Lins, K. V., Servaes, H., Tamayo, A. 2017. Social capital, trust, and firm performance:
The value of corporate social responsibility during the financial crisis. Journal of
Finance, 72 (4), 1785-1824.
Malmendier, U., Tate, G., Yan, J., 2011. Overconfidence and early-life experiences: The
effect of managerial traits on corporate financial policies. Journal of Finance, 66,
1687-1733.
McCarthy, S., Oliver, B., Song, S. 2017. Corporate social responsibility and CEO
confidence. Journal of Banking & Finance, 75 (C), 280-291.
Milligan, K., Moretti, E., Oreopoulos, P.. 2004. Does education improve citizenship?
Evidence from the United States and the United Kingdom. Journal of Public
Economics, 88 (9–10), 1667–95.
Moro, A., Wisniewski, T. P., Mantovani, G. M. 2017. Does a manager’s gender matter
when accessing credit? Evidence from European data. Journal of Banking & Finance,
80 (C), 119-134.
28

Nofsinger, J., Varma, A. 2014. Socially responsible funds and market crises. Journal of
Banking & Finance, 48 (C), 180-193.
Oswald, A. J., Powdthavee, N., 2010. Daughters and left-wing voting. Review of
Economics and Statistics, 92, 213-227.
Renneboog, L., Ter Horst, J., Zhang, C.. 2011. Is ethical money financially smart?
Nonfinancial attributes and money flows of socially responsible investment funds.
Journal of Financial Intermediation, 20 (4), 562-588.
Riedl, A.,Smeets, P. 2017. Why do investors hold socially responsible mutual funds?
Journal of Finance, 72 (6), 2505-2550.
Sansone, D. 2017. Why does teacher gender matter? Economics of Education Review 61(C), 9-18.
Schwartz-Ziv, M, 2017. Gender and board activeness: The role of a critical mass. Journalof Financial and Quantitative Analysis, 52 (2), 751-780.
Stellner, C., Klein, C., Zwergel, B. 2015. Corporate social responsibility and Eurozone
corporate bonds: The moderating role of country sustainability. Journal of Banking& Finance, 59 (C), 538-549.
Tanaka, R, 2008. The gender-asymmetric effect of working mothers on children’s
education: Evidence from Japan," Journal of the Japanese and International
Economies, 22 (4), 586-604.
Walayet A. K, Vieito, J.P. 2013. CEO gender and firm performance. Journal of Economics
and Business, 67, 55-66.
Warner, R. L., 1991. Does the sex of your children matter? Support for feminism among
women and men in the United States and Canada. Journal of Marriage and theFamily 53, 1051-1056.
29

Warner, R. L., Steel, B. S., 1999. Child rearing as a mechanism for social change: The
relationship of child gender to parents’ commitment to gender equity. Gender &Society, 13, 503-517.
Washington, E., 2008. Female socialization: How daughters affect their legislator fathers’
voting on women’s issues. American Economic Review, 98, 311-332.
Winters, M. A., Haight, R. C., Swaim, T., Pickering, K. A. 2013. The effect of samegender teacher assignment on student achievement in the elementary and secondary
grades: Evidence from panel data. Economics of Education Review, 34 (C), 69-75.
Wu, M.W., Shen, C.H., 2013. Corporate social responsibility in the banking industry:
Motives and financial performance. Journal of Banking & Finance, 37 (9), 35293547.
Yamamura, E. 2016. Natural disasters and social capital formation: The impact of theGreat Hanshin-Awaji earthquake. Papers in Regional Science, 95 (S1), 143-164.
Yamamura, E., andTsutsui, Y. 2018. Trade policy preference, childhood sporting

experience, and informal school curriculum: An examination of views of the TPP
from the viewpoint of behavioral economics. Forthcoming in Review ofInternational Economics.

30

ESG
3.84

Scores

3.82
3.8
3.78
3.76
3.74
1

2

3

4

5

6

GradesMale teacher

Female teather

Environment
3.82
3.8

Scores

3.78
3.76
3.74
3.72
3.7
3.68
1

2

3

4

5

GradesMale teacher

Female teather

31

6Social
3.76

Scores

3.74
3.72
3.7
3.68
3.66

1

2

3

4

5

6

GradesMale teacher

Female teather

Governance
3.98

3.96

Scores

3.94
3.92
3.9
3.88
3.86
3.84
1

2

3

4

5

6

GradesMale teacher

Female teather

Figure 1. CSR score in adulthood between people who belonged to women’s and men’sclasses in each grade in elementary school

32

4
3.95
3.9
3.85
3.8
3.75
3.7
3.65
3.6
3.55
ESG

Environment
Male repondent

SocialGovernanceFemale respondent

Figure 2. CSR comparison between male and female respondents

33

Variables

Definition

Mean

Min.

Max.

3.76

Standard
deviation
0.78

ESG

(Environment + Social + Governance)/3

1

5Environment

Do you agree that a firm should contribute to society bycoping with environmental problems?
1 (strongly disagree) – 5 (strongly agree)
Do you agree that a firm should contribute to society byparticipating in the local community?
1 (strongly disagree) – 5 (strongly agree)
Do you agree that a firm should be responsible for thetransparency of its corporate governance?
1 (strongly disagree) – 5 (strongly agree)
Number of years in a female teacher class during the 6
years attending elementary school,
Equals 1 if there was a task in which pupils worked
together as a group in elementary school, 0 otherwise
Equals 1 if the teachers ranked the finishing order inrunning races at elementary school, 0 otherwise
Degree of participation in community activities as anelementary school pupil
1 (not at all), 2 (only participated in main community
events), 3 (participated in all community events)
Number of schooling years

3.73

0.86

1

5

3.68

0.85

1

5

3.88

0.87

1

5

3.44

1.50

0

6

0.44

0.49

0

1

0.87

0.32

0

1

2.06

076

1

3

14.7

1.95

6

18

Respondents’ age

43.6

12.7

18

67

Brothers

Number of brothers

0.66

0.72

0

6

Sisters

Number of sisters

0.66

0.72

0

6

Women

Equals 1 if the respondent is a woman, 0 otherwise

0.50

0.50

0

1

SocialGovernanceFemaleteacher years
Group learn
Competition
Social capital

Schooling
years
Age

Table 1. Definitions of key variables and their basic statistics
Note: Apart from the job dummies indicated, 13 other job dummies were included in theestimation model: (1) Chief executive officer, (2) Temporary employee, (3) Public officer,(4) Specialists (lawyers, accountants), (5) self-employment, (6) SOHO (Small OfficeHome Office), (7) Part-time worker, (8) Outside worker, (9) House worker, (10)University student , (11) High-school student, (12) No job or retired, (13) Other worker.

34

Panel A: Full sample(1)

Female teacher
yearsGroup learn
Competition
Social capital
Schooling years
Age
Age square
Brothers
Sisters
Women
R-squared
Observations

(2)

(3)

(4)

ESG

Environment

SocialGovernance

0.02***(3.09)
0.05***(2.85)
0.13***(4.03)
0.08***(6.35)
0.03***(4.78)
0.004(0.73)
0.0001(1.62)
0.03**(2.17)
0.03**(2.01)
0.05**(2.41)
0.09
6,897

0.02**(2.58)
0.04**(2.13)
0.12***(3.32)
0.07***(5.21)
0.03***(4.52)−0.01(−0.94)0.0002***(3.10)
0.02*(1.71)
0.03*(1.79)
0.10***(3.77)
0.08
6,897

0.01*
(1.94)
0.08***(4.02)
0.09**(2.43)
0.10***(7.25)
0.02***(2.77)
0.01(1.45)
0.00004(0.59)
0.04***(2.77)
0.04***(2.74)
0.06**(2.26)
0.08
6,897

0.02***(3.61)
0.03(1.41)
0.18***(5.06)
0.06***(4.43)
0.03***(5.33)
0.01(1.42)
0.00004(0.58)
0.02(1.30)
0.01(0.87)
0.01(0.35)
0.08
6,897

Panel B: Male respondents(1)

Female teacher
yearsGroup learn
Competition
Social capital
Schooling years
Age
Age square
Brothers
Sisters
R-squared
Observations

ESG

0.02**(2.56)
0.05*(2.00)
0.18***(4.07)
0.08***(4.24)
0.02***(2.60)−0.0004(−0.05)0.0002*(1.69)
0.04**(2.42)
0.03(1.41)
0.12
3,486

(2)

Environment
0.02**(2.14)
0.04(1.28)
0.18***(3.60)
0.08***(3.61)
0.02***(1.85)−0.02*(−1.75)0.0004***(3.22)
0.03(1.66)
0.01(0.63)
0.10
3,486

Panel C: Female respondents
35(3)Social0.02*(1.78)
0.09***(2.88)
0.10**(2.09)
0.12***(5.57)
0.01(1.23)
0.01(0.86)
0.0001(0.48)
0.06***(3.18)
0.04**(2.15)
0.10
3,486

(4)

Governance
0.03***(2.75)
0.03(1.06)
0.26***(5.21)
0.04*(1.92)
0.02***(2.76)
0.01(0.71)
0.0001(0.76)
0.03(1.51)
0.02(0.96)
0.10
3,486

(1)

Female teacher
yearsGroup learn
Competition
Social capital
Schooling years
Age
Age square
Brothers
Sisters
R-squared
Observations

ESG

0.02*
(1.82)
0.05*(1.81)
0.08*(1.74)
0.08***(4.54)
0.03***(4.42)
0.008(0.93)
0.0001(0.71)
0.01(0.55)
0.03(1.59)
0.11
3,501

(2)

Environment
0.01(1.34)
0.04(1.57)
0.07(1.36)
0.07***(3.63)
0.04***(4.02)
0.004(0.42)
0.0001(1.12)
0.01(0.60)
0.04**(2.00)
0.10
3,501

(3)

Social

0.01(0.92)
0.07**(2.52)
0.07(1.37)
0.09***(4.50)
0.03***(2.95)
0.01(1.14)
0.0004(0.38)
0.01(0.59)
0.04*(1.79)
0.09
3,501

(4)

Governance
0.03**(2.58)
0.02(0.82)
0.10*(1.95)
0.08***(4.21)
0.05***(5.14)
0.01(0.95)
0.0001(0.40)
0.01(0.31)
0.01(0.56)
0.10
3,501

Table 2. Estimation results of the baseline model (equation 1)
Notes: ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels,
respectively. T-values are calculated based on robust standard errors clustered by
prefectures. In all columns, various control variables such as job dummies, father’s andmother’s educational attainment dummies, current residential prefecture dummies,
residential prefecture dummies when the respondent was 6 years old, and a constant areincluded. However, these estimates are not reported.

Panel A: Full sample(1)

Femaleteacheryears in low grade
Femaleteacheryears in high grade
Women
R-squareObservations

ESG

0.03**(2.57)
0.01(1.57)
0.05**(2.38)
0.10
6,897

(2)

Environment
0.03**(2.36)
0.01(1.09)
0.09***(3.74)
0.09
6,897

(3)

Social0.02*(1.93)
0.01(0.72)
0.06**(2.23)
0.08
6,897

(4)

Governance
0.03**(2.45)
0.02**(2.37)
0.01(0.34)
0.08
6,897

Panel B: Male respondents(1)

Femaleteacheryears in low grade
Femaleteacheryears in high grade
R-squareObservations

ESG

0.03**(2.44)
0.01(0.97)
0.12
3,486

(2)

Environment
0.04**(2.42)
0.01(0.43)
0.10
3,486
36

(3)

Social0.03**(2.04)
0.01(0.36)
0.10
3,486

(4)

Governance0.03*(1.81)
0.02*(1.78)
0.10
3,486Panel C: Female respondents(1)

Femaleteacheryears in low grade
Femaleteacheryears in high grade
R-squareObservations

ESG

0.01
(0.98)
0.02(1.47)
0.11
3,501

(2)

Environment
0.01(0.47)
0.02(1.28)
0.10
3,501

(3)

Social0.001(0.38)
0.01(0.83)
0.09
3,501

(4)

Governance
0.03*(1.76)
0.02*(1.80)
0.10
3,501

Table 3. Estimation results of the model with female teacher years split into low and highgrades
Notes: ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels,
respectively. T-values are calculated based on robust standard errors clustered by
prefectures. In all columns, the same set of independent variables are included as in Table
2. However, these estimates are not reported.

37

Panel A: Full sample
Female teacher
in 1st year.
Female teacher
in 2nd year.
Female teacher
in 3rd year.
Female teacher
in 4th year.
Female teacher
in 5th year.
Female teacher
in 6th year.
Women
R-squareObservations

(1)
0.04
(1.40)
0.02(0.79)
0.01(0.75)
0.04*(1.88)−0.02(−0.91)0.04(1.51)
0.05**(2.35)
0.10
6,897

(2)
0.05**(2.05)(3)
0.03(1.32)
0.02(1.00)(4)
0.04*(1.93)(5)
0.05**(2.08)(6)
0.05**(2.06)(7)
0.05**(2.09)

0.03*(1.75)
0.04**(2.45)
0.005(0.31)
0.05**(2.42)
0.10
6,897

0.05**(2.40)
0.10
6,897

(2)
0.07**(2.10)(3)
0.07*(1.81)
0.002(0.09)

0.05**(2.41)
0.10
6,897

0.05**(2.36)
0.10
6,897

0.05**(2.42)
0.10
6,897

0.02
(1.35)
0.05**(2.44)
0.10
6,897

Panel B: Male respondents

Female teacher
in 1st year.
Female teacher
in 2nd year.
Female teacher
in 3rd year.
Female teacher
in 4th year.
Female teacher
in 5th year.
Female teacher
in 6th year.
R-squareObservations

(1)
0.07*
(1.82)−0.04(−0.11)0.40(1.30)
0.04(1.46)−0.04(−1.34)0.05(1.52)
0.12
3,486

(4)
0.06*
(1.91)(5)
0.07**(2.13)(6)
0.07**(2.10)(7)
0.07**(2.13)

0.06**(2.04)
0.05**(2.15)−0.01(−0.37)
0.10
3,486

0.10
3,486

0.10
3,486

0.08
3,486

0.10
3,486

0.03
(1.01)
0.08
3,486

(2)
0.02
(0.63)(3)−0.002(−0.06)0.04(1.25)(4)
0.02(0.62)(5)
0.02(0.65)(6)
0.02(0.66)(7)
0.02(0.66)

Panel C: Female respondents
Female teacher
in 1st year.
Female teacher
in 2nd year.
Female teacher
in 3rd year.
Female teacher
in 4th year.
Female teacher
in 5th year.
Female teacher
in 6th year.
R-squareObservations

(1)
0.001
(0.04)
0.04(1.15)−0.01(−0.47)0.40(1.49)
0.01(0.18)
0.02(0.46)
0.11
3,501

0.01
(0.33)
0.04(1.57)
0.02(0.89)
0.11
3,501

0.11
3,501

0.11
3,501

0.11
3,501

0.11
3,501

0.02
(0.91)
0.11
3,501

Table 4. Effect of being in a female teacher class in each grade with ESG as the dependent38

variable
Notes: ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.
T-values are calculated based on robust standard errors clustered on prefectures. In all columns,
the same set of independent variables are included as in Table 2. However, these estimates are
not reported.

39