Discussion Paper No. 960

IS BEING AGREEABLEA KEY TO SUCCESS OR FAILURE
IN THE LABOR MARKET?
Sun Youn Lee
Fumio Ohtake

February 2016

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

Is Being Agreeable a Key to Success or Failure in the Labor Market?†
SunYoun Lee1, Fumio Ohtake2

The aim of this study was to elucidate how individual differences in noncognitive skills, asmeasured by the Big Five personality traits, explain variation in labor market outcomes. Japanese andU.S. survey data were analyzed to examine the associations between personality traits and lateroutcomes in the two countries. We focused on country-specific, noncognitive determinants of annual
income, which were found in agreeableness among male workers. Agreeableness seemed to contributeto annual income in Japanese men, whereas it acted as a penalty in American men. In both countries,
higher agreeableness tended to translate into higher income for those working at large companies(1,000 employees or more) compared with those working at small companies. Although agreeablenesswas rewarded by income, it did not necessarily lead to career advancement. Furthermore, theagreeableness premium was still observed even after controlling for labor-related variables such as
occupational choice and working hours. This suggests that agreeableness might act as part of a skill
set that directly improves job performance and productivity at large companies, rather than acting
indirectly through career advancement or occupational choice.

Keywords: Big Five personality, agreeableness, company size, income, career advancement
JEL Classification Number: J01, D03, J24†

This study was supported by a Grant-in-Aid for Scientific Research A (Grant No. 26245041) from the Japan
Society for the Promotion of Science, and the Joint Usage/Research Center at ISER/Osaka University. We are
grateful to seminar participants at the Research Institute of Economy, Trade and Industry (RIETI), and the 8th
Trans-Pacific Labor Seminar (TPLS) for their constructive comments. This paper is based on preliminary results
published in the RIETI Discussion Papers Series 14-E-023. However, our main hypotheses and ensuingempirical framework were newly set up and tested. The authors are responsible for any errors in this article.

1

Faculty of International Studies, Meiji Gakuin University, E-mail: sylee@k.meijigakuin.ac.jp

2

Institute of Social and Economic Research, Osaka University, E-mail: ohtake@iser.osaka-u.ac.jp

11. Introduction
Dee and West (2008) and Heckman, Moon, Pinto, Savelyev, and Yavitz (2010) have shown theimportance of fostering students’ noncognitive skills through school programs and governmental policies.
Findings of these studies indicate that noncognitive skills have greater long-term effects on life outcome
than do cognitive skills. Chetty, Friedman, Hilger, Saez, Schanzenbach, and Yagan (2011) reported
persistent impacts of Project STAR, a Tennessee class-size reduction demonstration project, on lateroutcomes through the development of students’ noncognitive skills, in contrast to the fade-out effect ofclass quality on test scores after the completion of the project. Thus, early intervention by formulating andfinancing school programs or government policies to foster noncognitive skills is as important as, or evenmore important than, helping children achieve their educational potential. This is particularly relevant tothose raised in low-income families, as such initiatives help prevent a vicious cycle of intergenerational
inequality.
In economics, little attention has been paid to the relation between noncognitive skills andeducational and career success. It is widely recognized, both in practice and in research, that measured
cognitive ability is a strong predictor of educational outcomes and career success, but the role ofnoncognitive skills has received less attention in explaining life outcomes. Heckman (1999) argued that
serious bias can arise when accumulated human capital is evaluated without consideration of bothcognitive skills, as measured by test scores or IQ index, and noncognitive skills, such as motivation andsocial adaptability. Some evidence suggests that approximately 20-30% of individual earnings (in standard
earning equations) can be explained by years of schooling and work experience in addition todemographic variables, including family socioeconomic status (Bowles, Gintis, & Osborne, 2001). Thisimplies that much of the variation in labor market success remains unexplained.
Several studies have recently focused on noncognitive skills as a key predictor of educational
attainment (Borghans, Meijers, & ter Weel, 2006; Heckman, Stixrud, & Urzua, 2006) and earnings(Heineck & Anger, 2010; Carneiro, Crawford, & Goodman, 2007; Muller & Plug, 2006). Heckman et al.
(2006) have found that improvements in personality traits, self-control, and self-esteem in particular, fromthe 25th to the 75th percentile of its distribution, while holding the level of cognitive skills constant,increase the probability of being a four-year college graduate at age 30 by approximately 25 percentage
points. The Big Five personality traits conscientiousness and openness to experiences have been identified
as the best personality predictors of educational performance and years of education, respectively(Borghans et al., 2006). Some studies have examined the importance of noncognitive skills in labormarket outcomes. For example, Heckman, Hsee, and Rubinstein (2001) found that, after controlling formeasured ability, those who obtained a GED (General Educational Development) high school certification2

in the United States tend to earn less than high school dropouts do. The authors explained that a lack ofnoncognitive skills such as discipline, patience, and motivation accounted for the lower earnings among
GED holders compared with dropouts with the same ability.
Noncognitive skills explain variation in schooling and labor market outcomes that is left unexplainedby cognitive skills. Analysis of noncognitive skills is also important in a policy context. Some school
programs and government policies have shown the long-term effects of noncognitive skill development.
Heckman and Kautz (2012) emphasized the significant effect of several public policies that enhance soft
skills on children’s educational outcomes. For example, the Perry Preschool Program for disadvantaged
young children demonstrated the effects of noncognitive skill development on long-term life outcomes.
Chetty et al. (2011) found that noncognitive skills, fostered by changes in school system, have a greater
long-term effect on later outcomes than cognitive skills do. Almlund, Duckworth, Heckman, and Kautz(2011) emphasized that compared with cognitive ability, noncognitive skills are responsive to parental
behaviors, allowing substantial room for parental investments in education and for policy interventions.
As a measure of noncognitive skills, the Five Factor Model (hereinafter, the “Big Five personality
traits”) is a broadly accepted model of personality in the psychology and economics literature. For a brief
measure of Big Five personality traits, many recent studies have utilized a 5- or 10-item inventory
calculated on bipolar scales for five personality facets: extroversion, agreeableness, conscientiousness,emotional stability, and openness to experiences. Gosling, Rentfrow, and Swann (2003) examined theseinventories in terms of (a) their validity, using self-, observer, and peer ratings; (b) the pattern of externalcorrelates, using self-ratings on other measures; and (c) test-retest reliability, using a second assessment of
the same participants. Gosling et al. (2003) concluded that 5- and 10-item inventories were reasonableproxies for lengthier Big Five instruments. Several previous studies have attempted to elucidate how
personality traits act as predictors of educational and labor market outcomes. The stability of personality
traits is a subject of controversy. Although some studies have noted changes in personality traits over anindividual’s life course with changes in environment or gene expression (Roberts & Jackson, 2008), it is
widely accepted that personality traits tend to be stable in adulthood. In a review of the stability of
personality traits and their predictive power, Almlund et al. (2011) noted that personality development
tends to stabilize around the age of 30 years (Caspi, 1997; Soldz & Vaillant, 1999). Cobb-Clark and
Schurer (2012) concluded that personality traits in working-age adults are stable over a 4-year period,
based on their findings of small changes in average personality during the given periods and little relation
between intra-individual personality characteristics and life events (e.g., adverse employment, health, orfamily events).

3

The main motivation for utilizing personality traits is that a single measure cannot predict much of
the variance in educational and labor market outcomes. Also, these soft skills can explain variance inoutcomes that are not attributable to effects of cognitive skills. According to Borghans, Golsteyn,
Heckman, and Humphries (2011), personality traits are incrementally valid in explaining variance ineducational outcomes measured by achievement tests and grades, after deconstructing the outcomes into
IQ and personality traits. Using German data, Almlund et al. (2011) explained that consciousness, longconsidered the best predictor of later-life labor outcomes, has more explanatory power than intelligence.
In this study, we aimed to determine the predictive power of personality traits and to explain themechanisms underlying the relations between personality traits and later outcomes by considering country
differences. Our primary focus was the extent to which noncognitive skills, as measured by the Big Five
personality traits, explain variations in educational and labor market outcomes after controlling forsocioeconomic variables. This study differs from the prior research in this field in several ways. First,
country differences are difficult to examine because previous studies used different measures of
personality traits. Therefore, we utilized survey data from Japan and the United States, which we collatedusing the same questions during the same year. Second, because many studies reported only simple
correlations or simple standardized regression coefficients, such estimated relations could not control forother factors that might influence educational and labor market outcomes. Therefore, we utilized the same
variables and ran multiple regressions while controlling for other factors that might affect outcomes,
including cognitive ability and other socioeconomic variables. Finally, we focused on some interesting
country differences in personality traits affecting men’s income, as found in agreeableness. Because thisparticular personality trait suggests the existence of country-specific noncognitive determinants of lateroutcomes, we analyzed its association with men’s income and career advancement in Japan and America.
We also examined the predictive power of personality traits on educational attainment, income, and careeradvancement in order to determine the channels through which personality traits affect labor market
outcomes. More specifically, we analyzed the mechanisms behind the relations between personality traits
and later outcomes by firm-size and occupation status. Some personality traits might directly affectincome by improving an individual’s job performance and productivity or indirectly affect labor market
outcomes through occupational choice and career advancement.
The remainder of the paper is organized as follows. Section 2 reviews prior studies related to thiswork. Section 3 discusses the dataset and explains how the variables were constructed for subsequent
analyses. Section 4 presents the estimation results. Finally, Section 5 discusses implications of the findings
and concludes the paper.

4

2. Research Background3
2.1 Big Five Personality Traits
The Big Five personality traits are a unifying framework comprising five basic characteristics:
extroversion, agreeableness, conscientiousness, emotional stability, and openness to experiences. Morespecifically, these five characteristics are: extroverted, enthusiastic (sociable, assertive, talkative, active,
unreserved, not shy); agreeable, kind (trusting, generous, sympathetic, cooperative, not aggressive, notcold); dependable, organized (hard-working, responsible, self-disciplined, thorough, not careless, not
impulsive); emotionally stable, calm (relaxed; self-confident; not any of anxious, moody, easily upset, oreasily stressed); open to experience, imaginative (curious, reflective, creative, deep, open-minded,unconventional) (Gosling et al., 2003). Ten questions measuring these five personality traits4 are each
rated on a 7-point scale, ranging from 1 (strongly disagree) to 7 (strongly agree). The average of the two
bipolar items that make up each scale is then calculated and used in subsequent analyses. For example, if a
respondent scores 5 on item 1 (extroverted, enthusiastic) and 2 on item 6 (reserved, quiet), thecomplement of the score for item 6 is found by replacing the 2 with a 6. Then, the average of the score foritem 1 and the (complementary) score for item 6 is calculated.
These single-item scales are typically psychometrically inferior to multiple-item scales, but Burisch(1997) and Gosling et al. (2003) showed that short and simple depression scales can be just as valid aslong and sophisticated ones. In addition, Epstein (1979) emphasized the view that, when averaged overtasks and situations at a point in time, people exhibit a predictable pattern of average behavior (“measured
personality”) with a high degree of reliability across situations. These previous studies support the validityof the Big Five personality traits as a measure of noncognitive skills that affect educational and labormarket outcomes. As explained in the Introduction, stability of personality traits is controversial, thus,
calling into question the legitimacy of adopting this premise when analyzing personality traits in relation
to school and later-life labor outcomes. However, some authors have argued that personality development
tends to stabilize from the age of 30 years onward (Caspi, 1997; Soldz & Vaillant, 1999). Cobb-Clark and
Schurer (2012) also found that personality traits at working age were stable over a 4-year period and did
not vary significantly under any life events. Along these lines, in this paper, we treat personality as
invariant over an individual’s lifetime.

3

Sections 2.1 to 2.3 summarize Lee and Ohtake (2014). Please refer to this paper for more details.

4

In the present study, the Big Five personality traits are measured based on responses to the self-reportquestionnaire.

5

2.2 Personality Traits and Educational Outcomes
Although much of the variation in labor-market success remains unexplained (Bowles et al., 2001),
prior research has observed the role of personality traits in explaining later-life outcomes and investigatedthe mechanisms behind these associations. However, it should be noted that results for the association
between personality traits and later outcomes vary by survey data and analysis method, and that simple
regression or correlation, rather than a causal relation, is still the basis for many findings.
Many studies have investigated the extent to which noncognitive skills explain individual variation in
educational outcomes (e.g., test scores, grade point average [GPA], and total years of schooling). Two of
the Big Five traits—conscientiousness and openness to experiences—were found to be particularly
important indicators of the total years of education that individuals complete in their lifetimes. In addition,
emotional stability, as measured by locus of control and self-esteem, was reported to be an important
indicator of adolescent schooling decisions (Almlund et al., 2011).
Conscientiousness is considered the most predictive Big Five trait across many outcomes (Hampson,
Goldberg, Vogt, & Dubanoski, 2007; Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007; Poropat, 2009),
and is the trait most consistently linked to academic success (O’Connor & Paunonen, 2007). In a
representative sample of Germans aged 21 to 94 years, Almlund et al. (2011) found that variation in yearsof schooling is best explained by the degree of conscientiousness, even after controlling for intelligence.
These authors found it particularly noteworthy that this trait had more explanatory power than intelligence,and that the trait’s predictive power was stronger among men than among women. Given that
conscientiousness is often associated with motivation, the positive correlation between conscientiousness
and educational attainment might suggest that more motivated students perform better than less motivatedcounterparts.
Many previous studies on the role of openness to experiences as a predictor of academic performance
have reported a positive relation between this trait and both GPA and final course grades (Lievens,
Dilchert, & Ones, 2009; Lounsbury, Sundstrom, Loveland, & Gibson, 2003). The mechanisms behind thispositive relation are often explained by the positive correlation between openness to experiences andmeasures of intelligence (Chamorro-Premuzic & Furnham, 2005). Also, Ackerman and Heggestad (1997)
stated that openness to experiences is the only Big Five factor moderately associated with general
intelligence (r = 0.33, as measured in a meta-analysis). Intelligence is a strong predictor of educational
outcomes, so it is easy to appreciate why openness to experiences has a positive effect on educational
attainment.
Emotional stability is also expected to be an important factor for educational attainment. Heckman etal. (2006) found that emotional stability increased the probability of graduating from high school for boys6

in the lowest quantiles of the personality distribution. Emotional stability (low neuroticism), which is
linked to locus of control and self-esteem, seems to play an important role in adolescent educational
decisions. In addition, this trait has been often interpreted in relation to “stress reaction” or “debilitating
anxiety” (Chamorro-Premuzic & Furnham, 2005). Moreover, in studies that used representative samplesof U.S. (Goldberg, Sweeney, Merenda, & Hughes, 1998), Dutch (van Eijck & de Graaf, 2004), andGerman (Almlund et al., 2011) individuals, emotional stability was found to be positively correlated witheducational attainment. Furthermore, several studies have found a significant positive relation between
locus of control (as a measure of emotional stability) and high school graduation (Barón & Cobb-Clark,
2010; Cebi, 2007; Coleman & DeLeire, 2003).
In contrast, extroversion and agreeableness are not consistently associated with academic
performance (O’Connor & Paunonen, 2007). According to some conflicting findings, extroverted children
tend to perform better at school until the age of 12 years (Goff & Ackerman, 1992), whereas introverted
students achieve higher grades (Yates, Yates, & Lippett, 1995). Some recent studies have reported apositive effect of agreeableness on educational outcomes, such as GPA (Farsides & Woodfield, 2003;
Gray & Watson, 2002) and final course grades (Conard, 2006), whereas other studies have found either nosignificant correlation or a significant but negative correlation between agreeableness and educational
attainment (Goldberg et al., 1998; van Eijck & de Graaf, 2004).

2.3. Personality Traits and Labor Market Outcomes
The predictive power of personality traits varies across type of labor market outcome. However, it is
widely accepted that conscientiousness is the best predictor of economic success, whereas emotional
stability (resp., high neuroticism) is often positively (resp., negatively) associated with labor market
outcome.

Conscientiousness

isassociated

with

being

well

organized,

hard-working,andachievement-oriented, and best predicts overall job performance and wages across occupational categories,
whereas the predictive power of intelligence declines as jobs become more complex (Almlund et al.,2011). In particular, men with a high degree of conscientiousness seem to earn higher wages and are more
likely to be promoted than other men (Judge, Higgins, Thoresen, & Barrick, 1999). In addition, because
emotional stability affects job search efforts (Almlund et al., 2011), emotionally stable individuals are
more motivated to find a job that fits their abilities and skills. Semykina and Linz (2007) examined theimportance of emotional stability using Russian data, and found that variation in personality traits, asmeasured by locus of control, accounted for 8% of the gender wage gap.
Some recent studies have observed a relation between the two traits of conscientiousness andemotional stability and labor market outcomes. Using U.S. data, Duckworth and Weir (2010) reported that7

conscientious and emotionally stable adults attained higher lifetime income. More specifically, they foundthat an increase of one standard deviation on conscientiousness and emotional stability was associatedwith, respectively, a 9% and 5% increase in lifetime income. Similarly, Judge et al. (1999) found that,
controlling for childhood IQ, the strongest predictor of a composite measure of self-reported income andoccupational status was childhood conscientiousness, with an effect size higher than that of childhood IQ.
According to Uysal and Pohlmeier (2011), conscientiousness and emotional stability were associated with
unemployment duration, which suggests that personality traits in workers can influence job-searchintensity.
In addition to conscientiousness and emotional stability, Fletcher (2013) highlighted the importanceof extroversion as a predictor of economic success, using a national sample of siblings and twins. He
noted that it is important to consider individual-level heterogeneity in unobserved generic ability for bothcognitive and non-cognitive skills. Previous heritability studies have indicated that measures of
personality traits tend to be about 40-60% heritable, suggesting a significant genetic component to humanbehavior (Bouchard & Loehlin, 2001). The results indicating a strong association between extroversion
and income were obtained after controlling for individual differences related to family background,
occupational sorting, and educational attainment.

2.4. Expected Findings of the Present Study
According to Judge et al. (1999), studies on organizational psychology agree that conscientiousness,
extroversion, and emotional stability are the Big Five factors most strongly correlated with career success.
This consensus is also seen in previous empirical research on noncognitive skills, as discussed in Section
2.3. Although our estimation results were consistent overall with previous studies, we found a differencein agreeableness between Japan and the United States in relation to labor market outcomes, which is thefocus of the present paper. Agreeableness is defined as a “tendency to act in a cooperative and unselfish
manner” (John & Srivastava, 1999). Being more cooperative and likeable could benefit employees withthese characteristics in teamwork settings. However, the negative side of being agreeable is that
“extremely agreeable individuals may sacrifice their success in pleasing others” (Judge et al., 1999, p.
625).
Many empirical studies have found no significant correlation between agreeableness and labormarket outcomes, and even when a correlation was significant, the effect was likely to be negative. We
hypothesized that agreeableness can be rewarded in a teamwork environment (measured by the number of
employees) and that the reward can differ by employment status (between ordinary employees andmanagers). To examine the effect of company size and employment status, we restricted our sample to8

employees working for private companies. The income effect of agreeableness could be either direct orindirect (Heckman et al., 2006; Borghans et al., 2008). This personality trait is part of a skillset, such as
educational attainment and job training, that directly improves productivity. In other words, agreeablenesscould lead directly to higher income by improving an individual’s job performance. In contrast,
agreeableness could indirectly affect labor market outcomes through occupational choice and careeradvancement. To distinguish between these two effects, we formulated empirical models to assess theextent to which coefficients of personality traits change in relation to inclusion of labor-related variables(e.g., occupation, employment status, and working hours). Therefore, finding no significant change inagreeableness, even with occupational choice, career advancement, and working hours held constant,would suggest that a direct effect on productivity leads to higher earnings.

3. Data and Empirical Framework
This study is based on survey data obtained from the "Preference and Life Satisfaction Survey" by
the Center of Excellence project of Osaka University. The data come from two questionnaire surveys
conducted in Japan and the United States. This survey was first conducted in Japan by the drop-off andpick-up method in February 2003, using a random sample drawn from 6,000 individuals selected by adouble-stratified, random-sampling method. It has been conducted annually since then, and new samples
were added in the 2004, 2006, and 2009 surveys by the drop-off method. In the United States, a panel
survey, which began in January and February of 2005 by a mailing method, included 12,338 individuals
and has since been conducted yearly. New samples were added in the 2007, 2008, and 2009 surveys. We
primarily used 2012 survey data for our analyses of both the Japanese and the U.S. data. In this study,
personality traits and labor market outcomes were based on survey year 2012, whereas total years ofschooling and some of the individual characteristics were taken from the 2011 and 2010 surveys
conducted in both countries.
Table 1 shows mean values of each personality trait. The Japanese respondents had a comparatively
high degree of agreeableness, whereas Americans scored higher on conscientiousness (see Figure 2 forcountry comparisons). Similarly, differences in personality traits by gender indicate that women weremore agreeable and extroverted, whereas men were more emotionally stable and open to new experiences(Table 1). Some of these trends are consistent with findings of previous studies of gender differences inpersonality, which have indicated that women typically have a lower degree of emotional stability andopenness to experiences (Feingold, 1994; Costa, Terracciano, & McCrae, 2001).
Using the minimum number of years required to attain each educational level, we obtained the valuesof 13.39 for Japanese and 14.43 for Americans as the mean number of years of schooling. In addition to9using a continuous measure for educational attainment (years of schooling), we also examined thetransition to tertiary education. In our samples, 27% of Japanese respondents and 39% of American
respondents completed college, and 2% of Japanese respondents and 13% of American respondents
continued on to graduate school, across all age groups5. In addition, 17% of the Japanese and American
respondents indicated promotion to a management position at a private company. In the U.S. sample, 14%of women were in a management position, whereas in Japan, female managers accounted for only 4% of
the female labor force6. The percentage of male employees working for private companies with 1,000
employees or more was 21% in Japan and 31% in the United States7.

3.1. Estimation Methods: Schooling
We also investigated personality trait effects on a wide range of later life outcomes. Because
personality stabilizes around the age of 30 years (Caspi, 1997; Soldz & Vaillant, 1999), we restricted oursample to individuals aged 30 to 65 years for all estimations. The base model for examining educational
outcomes is defined as follows:
5
where
and

,

1

represents years of schooling (9-21 years in Japan and 9-23 years in the United States),
5 indicates continuous variables of the Big Five personality traits.

is a vector of individual

characteristics that are assumed to affect later outcomes: age, age squared, gender, and years of schooling(parental educational attainment is controlled for in the analysis of educational attainment). For the U.S.,
because some studies have pointed out differences in later outcomes between races (Fletcher, 2013),
includes race dummies. To investigate effects of personality traits on the probability of attaining a higher
educational level, educational attainment was added to the base model as a binary variable that takes a5According to the data of Ministry of Education, Culture, Sports, Science and Technology, 25% of Japanese people
completedcollege
between
1965
to
2000
(four-year
university)(http://www.mukogawa-u.ac.jp/~kyoken/data/13.pdf ). According to U.S. census data, 31% of Americans have abachelor’s degree or higher, and 11% of college graduates continued to graduate school in 2012(https://www.census.gov/hhes/socdemo/education/data/cps/2012/tables.html).

6

The Japanese government reported that 6.5% of women working in private companies held management positions(section chief or higher) in 2009. (http://www.gender.go.jp/kaigi/renkei/2020_30/pdf/2020_30_all.pdf). In 2013,
women in the United States were 14.6% of executive officers, 8.1% of top earners, 4.6% of Fortune 500 CEOs, andheld 16.9% of Fortune 500 board seats (http://www.catalyst.org/knowledge/statistical-overview-women-workplace).
7

According to data of the Ministry of Health, Labour and Welfare, 22.4% of Japanese employees worked forcompanies with 1,000 employees or more in 2012 (http://www.mhlw.go.jp/toukei/youran/roudou-nenpou/02.html).
In the U.S., the Bureau of Labor Statistics reported that 38.87% of Americans worked for companies with 1,000
employees or more in 2012 (http://www.bls.gov/web/cewbd/table_f.txt).

10value of 1 if the respondent completed college education (orat least a master’s degree program) and 0

otherwise. We carried out all estimations separately for men and women to look for any genderdifferences in addition to country differences.

3.2. Estimation Methods: Labor Market Outcomes
Model 2 is used to examine the effects of personality traits on income:5lnwhere ln,2is the natural logarithm of individual annual income, andcharacteristics, the same as in Model 1.

is a vector of individual

is a vector of labor-related variables that are assumed to affectannual income: type of occupation, type of employment, company size, years of employment at current
workplace, and weekly working hours. In Equation (2), to investigate the mechanism behind the effect of
personality traits on income, we added years of education and labor-related variables separately into themodel (see Table 3). The rest of the estimations were carried out using the sample of only men,considering that women’s decisions on whether to work or not could introduce selection bias.
We examined differences in personality trait effects between employees of large and small
companies by further restricting our sample to those working for private companies. We included aninteraction term for each of the Big Five personality traits in combination with a company size dummythat takes a value of 1 if the company has 1,000 or more employees and 0 otherwise (Table 4). In addition,
we added similar interaction terms between the Big Five personality traits and a management position
dummy (managers = 1) to Equation (2) of the basic model of earnings. See Table 5 (columns 1 and 2) for
estimation results. To investigate differences in the effects of personality traits, in particular agreeableness,in relation to company size and employment status, we included interaction terms of these three variables
into Model 2 (Table 5, columns 3 and 4): agreeableness, a company size dummy and a management
position dummy.
To examine the effects of personality traits on career advancement, model 3 is set up as follows:
5
where

,

represents a binary variable that equals one if the respondent was in a management

position at the time of the survey and zero otherwise8, andin Model 1.

8

3

is a vector of individual characteristics, as

is a vector of labor-related variables that are assumed to affect an individual’s career

The Japanese survey included those in a management position, company executives, or board members.

11

advancement (i.e., company size, type of employment, working hours, and years of employment at current
workplace).

3.3. Estimation Methods: Other Labor Outcomes
To examine the effects of personality traits on other later outcomes aside from economic rewards, we
set up Model 4, the last model, as follows:
5
Here

,

4

represents degree of happiness as measured on an 11-point scale by the following

questions: “Overall, how happy would you say you are currently? Using a scale from 0 to 10 where ‘10’ is‘very happy’ and ‘0’ is ‘very unhappy,’ how would you rate your current level of happiness?”
vector of individual characteristics, as in Model 1, andis arepresents the same variables used in Model 2.

Model 4 is the same as Model 2 except for the dependent variables. To compare the effects of personality
traits and other individual labor-related variables on degree of happiness using results of Model 2, we set
up the same model. Furthermore, we examined how the effects of personality traits (annual income () change when), the dependent variable of Model 2, is held constant, and we investigated thepartial effect of annual income (on degree of happiness by using Model 4.

4. Estimation Results
4.1 Effects of Personality Traits on Educational Attainment
Table 2 presents results of the relation between noncognitive skills and years of schoolingcosmpleted. The two left columns in the upper and bottom panels show estimation results for years ofschooling in Japan and the United States, respectively. Regressions were run with and without adjustment
for years of schooling attained by respondents’ parents. Parents’ completed years of schooling can serve
as a proxy for genetic inheritance of cognitive ability, socioeconomic status, and/or personality traits.
Children of highly educated parents tend to become highly educated partly because of theintergenerational inheritance of unobserved abilities, which positively affect children’s educational
decisions. Our overall results indicate that parental background mitigates the effects of the personality
traits, although the statistical significance of personality traits changed very little even when controllingfor parental effect.
In Japan, among the different facets of personality traits, agreeableness seemed to have a positiveeffect on total years of schooling among men. Agreeableness was also a statistically significant factor bothwith and without control of parental educational background. In contrast, conscientiousness was
statistically significant among only American respondents. As shown by the descriptive statistics in Table
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1, agreeableness (resp., conscientiousness) has the highest mean values among the five personality traits
in Japan (resp., in the United States). Even after controlling for socioeconomic variables, the effect ofthese traits on educational attainment was statistically significant in both countries. In this paper, we
focused on country differences in agreeableness. We found that although agreeableness had a positiveeffect on schooling in Japan, it had a negative effect in the United States, and was a significant negative
factor among women in the United States. Aside from agreeableness and conscientiousness, the degrees
of openness to experiences and emotional stability were important for schooling in Japan and the UnitedStates. Implications of the effects of these two personality traits can be explained by their relation todegree of intelligence, interest in learning, and self-control, all of which significantly affect cognitive
ability and adolescent schooling decisions (see Section 2.2 for details).
Figure 1 displays standardized regression coefficients of personality traits associated with years ofschooling, after controlling for the basic demographic characteristics: age, age-squared, and gender as wellas race dummies for American samples. The two rectangular bars represent estimates of standardized
regression coefficients and the line bars represent robust standard errors, with darker rectangular bars
representing estimates obtained after controlling for parental background. After controlling for parents’
educational attainment, a one standard deviation increase in agreeableness and conscientiousness was
associated with a 0.115 and 0.215 standard deviation increase, respectively, in total years of schoolingcompleted in Japan and the United States. This is approximately equivalent to an increase in schooling by
0.23 and 0.52 years in Japan and the United States, respectively. Compared to the effect of personality
traits, the effect of parental educational background was substantial in both countries, highlighting theimportance of parental socioeconomic status and generic inheritance of cognitive and noncognitive skills.
The inclusion of parental background decreased the size of standardized regression coefficients ofpersonality traits by approximately 0.01. However, agreeableness and conscientiousness were still
significantly correlated with educational attainment even after controlling for parental background.
Figure 1 presents a simple comparison with previous studies that have reported standardized
regression coefficients of personality traits. Results based on American respondents in our study wereconsistent with results reported by Goldberg et al. (1998), which were based on a representative sample ofU.S. working adults, aged 18 to 75 years. Goldberg and colleagues found significant negative correlations
between academic success and agreeableness and extroversion, as well as significant positive correlations
for conscientiousness and openness to experiences.
In addition to total years of schooling completed, Table 2 (columns 3 and 4) shows the effect of
personality traits on the probability of transition to higher levels of education (i.e., college and graduate
school). Japanese males students who were more agreeable and conscientious were also more likely to go

13to college. In contrast, introversion and openness to experiences positively affected the decision ofJapanese men to enter graduate school. In contrast, we found no statistically significant personality effecton female students’ decision to transition from high school to college, whereas extroversion acts as adeterminant for Japanese women’s decision to enter graduate school. Our results suggest that, in Japan,
the effects of personality traits vary at different educational transition points. Interestingly, agreeableness,
which is the best predictor for educational attainment below the college level, became negatively
associated with graduate-level educational attainment, although this effect was not statistically significant.
In the United States, we observed no apparent significant difference in the effects of personality traits on
educational transition when compared with results obtained using the continuous variable of total years ofschooling. More specifically, conscientiousness and emotional stability seemed to play an important rolein the decision to pursue higher levels of education, as well as final educational attainment.

4.2. Effects of Personality Traits on Income
In this section, the relation between annual income and personality factors is investigated (Table 3).
We summarized all estimations by gender and country. Table 3 (upper panel) describes results of Japanesemale and female workers. Differences (see columns 1 through 3) depended on inclusion of variables of
educational attainment (type of occupation, years of schooling, type of employment) and labor (working
hours, company size). As for Japanese male workers, column 3 shows that extroversion, agreeableness,
conscientiousness are seemingly important factors affecting annual income. In Japanese female workers,
extroversion appears to correlate more consistently with income. American male workers were rewarded
by non-agreeableness and conscientiousness, everything else being equal. In American female workers,
extroversion, non-agreeableness, and emotional stability seemed to correlate with annual income. These
results occurred when type of occupation, type of employment, years of schooling, and working hours
were held constant. Even when education attainment and labor market variables were held constant,personality traits were still significantly associated with income, which suggests that they might act as anindividual’s set of productive traits, such as educational attainment. In other words, these noncognitive
skills have a rather direct effect on productivity, which is reflected by income.
Column 4 presents results based on a restricted sample of those working at private companies. For
this estimation, we used the restricted sample of private companies to analyze how the effect ofagreeableness on men’s income differs by company size and employment status. Column 4 presents
observed country differences in agreeableness. In Japan, agreeableness had a statistically significant
positive effect on annual income as well as years of schooling among men, whereas it had a negative14

correlation with income in the United States. This suggests that agreeableness might be a country-specificfactor that affects one’s educational and career success in the opposite direction.

4.3. Personality Traits, Company Size, Employment Status, and Men’s Income

We further investigated how this contradictory personality trait, agreeableness, affects annual income
in Japan and the United States. First, we examined whether personality traits work differently inrespondents as a function of company size (Table 4). Companies with many employees tend to give higher
evaluations to agreeable employees who can cooperate with other colleagues. Rewarding agreeablenessin large-sized companies would have a positive effect on annual income. As shown in Tables 3 and 4,
agreeableness was consistently positive among Japanese male workers and, in particular, those working
for large-sized companies. We observed an interesting contrast in the United States, where agreeablenessseemed to operate as a penalty against raising the annual income of American male workers, except of
those working for large companies (1,000 employees or more), where agreeableness was rewarding forincome as well. In fact, we observed a negative effect of agreeableness on annual income only among
Americans working for small-sized companies. Although employees at large-sized companies wererewarded for being agreeable compared to those working at smaller-sized companies, the total effect wasclose to zero. As for smaller-sized companies, in addition to the effect of agreeableness, being extroverted
and conscientious in Japan and emotionally stable in the United States rewarded the earnings of theirrespective male employees.
We further examined whether personality trait effects differed by employment status (ordinary
employees vs. managers) because a certain personality trait might be essential for those holding
managerial positions. Table 5 (columns 1 and 2) shows interaction terms between each personality trait
and a binary indicator of managers (=1), with the base representing ordinary employees. We found thatextroverted and agreeable ordinary employees in Japan and disagreeable and emotionally stable ordinary
employees in the United States earned more. However, we observed no statistically significant differencein personality trait effects between ordinary employees and managers in both countries.
Thus far, advantageous personality traits differed by company size, but very little by employment
status. More specifically, although the effect of agreeableness did not differ between ordinary employees
and managers, being agreeable seems to be rewarded by higher income in large-sized companies
compared to small-sized companies in both Japan and the United States. These results led us to ask
whether the effect of agreeableness at large-sized companies would differ by employment status. In otherwords, was the positive average effect of agreeableness at large-sized companies more pronounced among
ordinary employees or among managers? To answer this question, Table 5 (columns 3 and 4) also includes

15interaction terms between agreeableness, a binary indicator of managers (=1), and a binary indicator ofcompany size with 1000 employees or more (=1). We found that agreeableness was advantageous for
those working for large companies in both Japan and America, and that this positive effect was significant
even in ordinary employees of large private companies/organizations in both countries. columns 1 and 2of Table 5 show no significant difference between ordinary employees and managers, which suggests thatbeing agreeable is rewarded at large-sized companies, regardless of employment status, more than atsmall-sized companies.
To investigate which personality traits affect the probability of being promoted to a management
position, we conducted probit regressions with a dependent variable equal to one for a respondent working
in a management position at the time of the survey and 0 otherwise (see Table 6). Overall, extroversion inmen was a significant personality trait affecting career advancement in both countries, regardless ofcompany size. In fact, extroversion was more important than any other personality trait for management
positions in Japan and the United States. Therefore, although agreeable employees at large companies are
more likely to earn more, agreeableness does not necessarily improve career advancement. In fact, wemight interpret agreeableness as a trait that directly affects job performance and productivity, whichtranslates into higher earnings, rather than having indirect effects on career advancement or occupational
choice.

4.4. Effects of Personality Traits on HappinessWe further examined the effect of agreeableness on outcomes other than economic rewards, such as
income growth and career advancement. Thus far, our results have revealed that being agreeable is not
rewarding for women and is not rewarding for men in the United States (see Table 3). However, Table 7
shows that being agreeable increased degree of happiness in women of both countries. This positive effectremains significant even when controlling for annual income. Thus, although agreeableness does notaffect income, and may even have a negative relation with income, among women in Japan and the UnitedStates, it might have positive effects on other outcomes, such as subjective well-being. Agreeablenessincreases income for men in Japan and has a significantly positive effect on happiness, with and without
controlling for annual income. Even when labor-related variables, including income, are held equal, thisparticular personality trait was an important factor that increased the subjective feeling of happiness aswell as economic outcomes among Japanese men. In contrast, conscientiousness, which best predicts lateroutcomes, is not correlated with happiness. Thus, conscientiousness might increase years of schooling andincome through hard work, but it does not necessarily directly increase the feeling of happiness.

16

5. Discussion
Studies have given much attention to the predictive power of intelligence measures when evaluating
cumulative human capital. However, it has been argued that no single measure of cognitive ability can
predict much of the variance in educational and labor market outcomes. Because most of the remaining
variance is not explained by measurement error, much room remains for other determinants of success.
This study considered soft skills as possible predictors of the unexplained variance in educational andlabor market outcomes. In this study, soft skills were characterized by scores for the Big Five personality
traits, a widely accepted taxonomy in personality trait research. Our estimated results suggest that
personality traits are significantly correlated with later outcomes. Previous studies using data collected indifferent countries have yielded different results, possibly because the authors controlled for different
covariates, or because some significant country differences exist. In the present study, we evaluated therelation between personality trait and various outcomes using the same covariates. Overall, our results
revealed substantial similarities in the effect of personality traits on both educational and labor market
outcomes across both countries, which is consistent with previous empirical studies, notwithstanding a
few contradictory results between Japan and the United States.
In these countries, conscientiousness, openness to experiences, and/or emotional stability arecorrelated with educational attainment despite differences in the relative importance of each. In previous
literature, conscientiousness was the best predictor of later outcomes. Implications of the effects ofopenness to experiences and emotional stability can be explained in terms of their relation to degree ofintelligence, interest in learning, and self-control, all of which play an important role in cognitive ability
and adolescent schooling decisions. In addition, the effects of personality traits on labor market outcomesare very similar between the two analyzed countries. In both countries, men with a high degree of
conscientiousness seemed to earn more, and extroversion best predicted the probability of promotion to a
management position among men in both countries. These results are consistent with general findings in
extant studies on personality traits and career success. However, no established empirical consensus exists
in the still advancing study of personality traits. Nonetheless, the effects of personality traits that havebeen most commonly identified in previously research as significant for educational and labor market
outcomes were similar to those in the countries analyzed here.
Despite these similarities, Japan and the United States exhibited distinct differences, most notably inthe effect of agreeableness. Japanese respondents scored noticeably higher in agreeableness than
American respondents, and agreeableness was a particularly important predictor for schooling and income
in Japanese men. This finding contrasts with that of a substantial body of literature, in which
agreeableness was a less important predictor of educational attainment. In contrast, agreeableness17

operated in the opposite direction in the United States, which suggests the existence of country-specificdeterminants of success. Woessmann, Luedemann, Schuetz, and West (2009) argued that students’personality traits might depend on characteristics of their educational environment, such as autonomy anddegree of accountability. Rockoff, Jacob, Kane, and Staiger (2008) emphasized the importance of teacher
influence on the development of students’ noncognitive skills. If this holds true, teaching style andeducational philosophy might contribute to the unique variance in personality traits affecting educational
outcomes in Japan.
We focused on how agreeableness, which seems particularly important for schooling in Japan,
affected labor market outcomes, and whether agreeableness would continue its negative correlation in theAmerican labor market. In Japan, being agreeable had a positive effect on years of schooling. Japanese
men who were agreeable were more likely to enter a four-year university. Furthermore, they earned more,even when controlling for occupation, employment type, years of employment, company size, and hours
worked. In contrast, being agreeable in the United States had a negative effect on years of schooling.
Although this negative effect was not statistically significant for American male students, it negatively
affected their income. This penalty continued even when occupation, employment type, years of
employment, company size, and age were held equal. Thus, being agreeable has an income-lowering
effect no matter what kind of job one has or how long one has worked.
To investigate the channels through which agreeableness is associated with labor market outcomes,
we analyzed its effects on annual income by company size and employment status. We observed apremium for being agreeable among those working for large companies in both Japan and the UnitedStates. This result did not change even with type of occupation and other labor-related variables held
constant. Agreeable employees at large companies were likely to earn more than those at small-sizedcompanies, but we found no statistical difference in the effect of agreeableness between ordinary
employees and managers. For promotion to a management position, extroversion was more important thanany other personality trait. These findings suggest that employees of large-sized companies are directly
rewarded for being agreeable through their income, rather than indirectly through occupational choice or
career advancement. Furthermore, agreeableness affects the subjective feeling of happiness as well as
economic outcomes. In particular, Japanese men who are agreeable earn more and feel happier. Even
though women’s income in both countries was negatively associated with agreeableness, it increased thedegree of their subjective well-being. Therefore, although agreeableness did not affect income in Japanesewomen and it had a negative relation with income among American women, it can positively affect otherlater outcomes such as subjective well-being.

18

In summary, we identified the possibility of a premium for being agreeable among employees
working for large companies in Japan and America. The significance of agreeableness still existed evenwhen type of occupation and other labor-related variables were held constant. In contrast, a wage premiumis not necessarily connected with career advancement, which means that a wage premium was not theresult of promotion. Results for income growth and career advancement suggest that agreeableness might
directly affect job performance and increase productivity of employees of large companies, which in turnreflects their annual income. However, some limitations restrict generalizability of the present findings.
Although some extant studies have proven the stability of personality traits at working age and havesuggested that examination of personality traits remain stable under fluctuating economic events, it isdifficult to conclude that a personality trait affects labor outcomes or vice versa, or that they mutually
influence each other. Caution is called for before concluding that the results presented here suggest acomplete causal relation.

19

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23

Table 1. Descriptive Statistics

Dependent variables
Years of schoolingCollege (=1)
Graduate school (=1)
Annual Income (log)Promoted to management position at private companies
Big Five personality
Extroversion
AgreeablenessConscientiousness
Emotional Stability
Openness to Experiences
Socio-economic variables
Age
Age squared
FemaleParental Education
Labor market variables(Type of Occupation)
Office and administrative support
Sales and related occupations
Management, business, and financial operations
Professional and related occupations
Service occupations
Construction, extraction, and maintenanceFarming, fishing, and forestry(Employment Type)
Employee of private company or organization
Government employee
Management position
Self-employed
Family business employee (in self-employed business)(Work Experience and Company Size)
Years of work experience at the current workplace
Size of company (=1 if the number of employees is more than
1000 and 0 otherwise)Japan
Whole Sample
Mean
S.D.
13.39
2.00
0.27
0.44
0.02
0.13
5.63
0.91
0.17
0.38

Males
Mean
S.D.
13.71
2.27
0.40
0.49
0.03
0.17
6.09
0.66
0.28
0.45

Females
Mean
S.D.
13.13
1.71
0.16
0.37
0.01
0.09
5.07
0.86
0.04
0.20

U.S.
Whole Sample
Mean
S.D.
14.43
2.42
0.39
0.49
0.13
0.34
5.95
0.86
0.17
0.37

Males
Mean
S.D.
14.57
2.61
0.42
0.49
0.15
0.36
6.14
0.81
0.20
0.40

Females
Mean
S.D.
14.32
2.24
0.36
0.48
0.12
0.32
5.75
0.87
0.14
0.35

4.09
4.99
3.99
4.01
3.89

1.29
0.93
1.06
1.03
1.07

3.96
4.92
4.00
4.11
4.03

1.29
0.95
1.05
1.01
1.04

4.20
5.04
3.97
3.92
3.78

1.28
0.91
1.07
1.04
1.07

3.96
5.06
5.75
4.84
4.69

1.45
1.22
1.15
1.35
1.16

3.91
4.79
5.61
4.90
4.70

1.47
1.24
1.14
1.37
1.14

4.00
5.28
5.87
4.79
4.67

1.44
1.16
1.14
1.33
1.19

50.34
2625.5
0.55
11.07

9.57
947.4
0.50
1.92

50.85
2673.1
0.00
10.95

9.36
930.7
0.00
1.96

49.92
2586.2
1.00
11.18

9.73
959.5
0.00
1.89

49.75
2564.6
0.54
12.51

9.46
916.2
0.50
2.13

49.68
2557.2
0.00
12.60

9.47
916.2
0.00
2.17

49.81
2570.7
1.00
12.43

9.46
916.6
0.00
2.09

0.22
0.11
0.12
0.21
0.19
0.14
0.02

0.41
0.31
0.33
0.41
0.39
0.34
0.13

0.14
0.09
0.21
0.21
0.16
0.18
0.02

0.34
0.28
0.41
0.41
0.36
0.39
0.14

0.31
0.14
0.02
0.21
0.23
0.08
0.02

0.46
0.35
0.12
0.41
0.42
0.27
0.13

0.14
0.12
0.15
0.29
0.19
0.10
0.01

0.35
0.32
0.36
0.45
0.39
0.30
0.12

0.03
0.11
0.18
0.29
0.19
0.19
0.02

0.17
0.31
0.38
0.45
0.40
0.39
0.13

0.25
0.13
0.13
0.29
0.18
0.01
0.01

0.43
0.34
0.34
0.46
0.38
0.09
0.10

0.69
0.10
0.05
0.10
0.05

0.46
0.30
0.21
0.31
0.22

0.67
0.11
0.07
0.12
0.02

0.47
0.31
0.25
0.33
0.15

0.72
0.09
0.02
0.08
0.09

0.45
0.29
0.14
0.27
0.28

0.60
0.18
0.12
0.09
0.01

0.49
0.38
0.33
0.28
0.11

0.56
0.17
0.16
0.10
0.01

0.50
0.37
0.36
0.31
0.09

0.63
0.19
0.09
0.07
0.02

0.48
0.39
0.29
0.25
0.14

23.97
0.17

3.98
0.38

24.32
0.21

3.30
0.40

23.55
0.13

4.65
0.41

13.07
0.31

9.74
0.46

13.40
0.31

10.14
0.05

12.73
0.32

9.31
0.47

Note. The Big Five personality traits and socioeconomic variables are described with samples used to analyze educational attainment (Table 2, column 2; Japan = 3,199; U.S. = 1,574). Annual income,management position at private companies, and labor market variables are summarized with the sample used to analyze determinants of annual income.

Table 2. Determinants of Educational Attainment in Japan and the United States
Independent Variables
Years of SchoolingYears of SchoolingJapan
w/t Parental eduation
Regression Model: OLS/Probit
Male
FemaleMale
FemaleBig 5 Personality
Extroversion-0.0280
0.0111-0.0555-0.0364(0.051)(0.033)(0.049)(0.032)Agreeableness
0.2033*** 0.0955**
0.1982*** 0.0368(0.066)(0.044)(0.062)(0.042)
Conscientiousness
0.0852-0.0125
0.0865-0.0014(0.062)(0.040)(0.059)(0.037)
Emotional Stability
0.09270.02550.0470-0.0018(0.064)(0.041)(0.062)(0.039)Openness to Experiences
0.1132*0.0753*0.06290.0717*(0.063)(0.039)(0.061)(0.037)
Years of schooling
0.4510*** 0.3668***－－of parents(0.028)(0.020)Observations
1,522
1,844
1,445
1,754
R-squared
0.030
0.054
0.162
0.194
Independent Variables
U.S.
Regression Model: OLS/Probit
Big 5 Personality
Extroversion

Years of Schooling
Male

Female-0.0888(0.069)-0.0924(0.083)0.2721***(0.089)0.2655***(0.078)0.1060(0.087)－0.0224(0.054)-0.1121(0.073)0.2040***(0.075)0.1456**(0.065)0.0765(0.065)－

Years of Schooling
w/t Parental eduation
Male
FemaleCollege Graduates
w/t Parental eduation
Male
FemaleAttainment of grad. level of edu.
w/t Parental eduation
Male
Female-0.0202(0.030)0.1132***(0.040)0.0955***(0.036)0.0443(0.039)-0.0021(0.037)0.2553***(0.020)1,442-0.1451**(0.060)-0.0062(0.079)0.0579(0.071)0.0909(0.074)0.1595**(0.070)0.1332***(0.034)
1,445-0.0286(0.033)-0.0084(0.046)
0.0336(0.039)0.0107(0.039)0.0038(0.038)0.2757***(0.021)
1,760

College Graduates
w/t Parental eduation
Male
Female0.2425**(0.097)-0.1190(0.123)-0.0192(0.105)0.0871(0.107)-0.0363(0.101)0.1556***(0.054)
1,754

Attainment of grad. level of edu.
w/t Parental eduation
Male
Female-0.0998-0.0528-0.0430-0.03850.0099-0.0183(0.067)(0.052)(0.035)(0.034)(0.041)(0.042)Agreeableness-0.1017-0.1537**-0.0537-0.1320***-0.03450.0099(0.082)(0.068)(0.045)(0.048)(0.054)(0.059)Conscientiousness
0.2381*** 0.2078***0.1695*** 0.1347***
0.1130*0.1307**(0.086)(0.069)(0.049)(0.045)(0.061)(0.060)
Emotional Stability
0.2585*** 0.1268**
0.1219*** 0.0729*
0.1242**-0.0230(0.075)(0.061)(0.042)(0.042)(0.052)(0.052)
Openness to Experiences
0.08440.0888-0.0161
0.04620.04970.0464(0.084)(0.060)(0.047)(0.044)(0.057)(0.055)
Years of schooling
0.3970*** 0.4269***
0.1725*** 0.2624***0.1223*** 0.1464***of parents(0.045)(0.033)(0.025)(0.026)(0.028)(0.029)Observations
754
884
717
857
717
857
717
857
R-squared
0.048
0.047
0.155
0.189
Note. Both estimations controlled for socioeconomic variables (age, age-squared, and race dummies [only American samples]). The family socioeconomic variable
signifies parental educational level. Robust standard errors are in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.

Table 3. Effects of (Non)Cognitive Skills on Annual Income
Male Workers (Japan)
Dependent Var. Annual Income (Log)
(1)
(2)
(3)
(4)
Personality Traits
Extroversion
0.0239*0.0284*0.0299** 0.0420***(0.014)(0.015)(0.015)(0.015)
Agreeableness0.0445** 0.0485** 0.0422** 0.0427**(0.019)(0.020)(0.020)(0.018)
Conscientiousness
0.0643*** 0.0592*** 0.0554*** 0.0491***(0.018)(0.019)(0.019)(0.017)
Emotional_Stability-0.0028-0.0020-0.0052-0.0125(0.017)(0.018)(0.018)(0.017)
Openness to Experiences
0.01590.01200.0089-0.0047(0.017)(0.017)(0.017)(0.018)Company Size (1 if # of employees >1000)
0.2452*** 0.2202*** 0.2283***(0.041)(0.041)(0.043)Years of schooling
0.0414*** 0.0441***(0.009)(0.009)Labor market variables
O
O
OO
Company Size×O
OO
Years of schooling××OO
Restricted to private companies
×××O
Observations
1,147
1,067
1,062
838
R-squared
0.305
0.315
0.329
0.417
Male Workers (U.S.)
Dependent Var. Annual Income (Log)
(1)
(2)
(3)
(4)
Personality Traits
Extroversion
0.02390.0356
0.03120.0221(0.023)(0.024)(0.025)(0.031)
Agreeableness-0.0882** -0.0773** -0.0767** -0.0748**(0.036)(0.031)(0.031)(0.032)
Conscientiousness
0.0680** 0.0976*** 0.0917*** 0.0489(0.032)(0.032)(0.034)(0.033)
Emotional Stability
0.04600.04500.03450.0634*(0.029)(0.030)(0.032)(0.036)
Openness to Experiences
0.0038-0.0103-0.0116-0.0055(0.028)(0.030)(0.032)(0.035)Company Size (1 if # of employees >=1000)
0.2012** 0.2000** 0.3013***(0.083)(0.083)(0.086)
Years of schooling
0.0693*** 0.0734***(0.015)(0.018)Labor market variables
O
O
OO
Company Size

×

O

O

O

Female Workers (Japan)
(2)
(3)
(4)
0.0466** 0.0485** 0.0429*(0.022)(0.022)(0.023)-0.0086-0.0069
0.0133(0.026)(0.026)(0.026)0.02800.02880.0158(0.025)(0.025)(0.022)0.02670.02510.0134(0.023)(0.023)(0.022)-0.0084-0.01410.0070(0.024)(0.024)(0.023)0.2549*** 0.2472*** 0.2424***(0.059)(0.059)(0.060)0.02770.0241(0.021)(0.021)
O
O
O
O
×
O
O
O
×
×
O
O
×
×
×
O
933
869
861
657
0.430
0.407
0.405
0.480
Female Workers (U.S.)
(1)
(2)
(3)
(4)
0.0855*** 0.0707** 0.0692*
0.0736(0.033)(0.034)(0.037)(0.046)-0.0840** -0.0964*** -0.0949** -0.0785*(0.035)(0.037)(0.038)(0.047)0.02490.03840.01930.0084(0.049)(0.049)(0.050)(0.062)0.04600.0676*
0.0617*0.0428(0.036)(0.035)(0.036)(0.042)-0.0109-0.0356-0.0305-0.0339(0.037)(0.039)(0.039)(0.048)0.3811*** 0.3967*** 0.4217***(0.077)(0.078)(0.090)0.0610** 0.0602**(0.024)(0.030)OOOO(1)0.0394*(0.021)0.0060(0.025)0.0284(0.024)0.0403*(0.022)-0.0004(0.023)

×

O

O

O

Years of schooling
×
×
O
O
×
×
O
O
Restricted to private companies
×
×
×
O
×
×
×
O
Observations
458
402
369
269
427
372
355
260
R-squared
0.304
0.388
0.424
0.449
0.322
0.424
0.429
0.416
Note. Estimations are additionally controlled for socioeconomic variables (age and its square, type of occupation, employment type, full-time employment, years of
employment at current workplace, working hours, and race dummies [only American samples]). Robust standard errors are in parentheses. ***p < 0.01, **p < 0.05,

Table 4. Effects of (Non)Cognitive Skills on Annual Income by Company Size
Depdent Variables
Annual Income (Log)
Japan
U.S.
(1)
(2)
Personality Traits
Extroversion
0.0516***-0.0187(0.016)(0.043)
Agreeableness0.0225-0.1190**(0.021)(0.048)
Conscientiousness
0.0640***0.0720(0.019)(0.047)
Emotional Stability-0.0135
0.1047**(0.019)(0.048)Openness to Experiences-0.0049-0.0372(0.020)(0.049)Interaction between "1000 Employees and more (=1)" and Personality
1000 Employees and more (=1)×Extroversion
1000 Employees and more (=1)×Agreeableness1000 Employees and more (=1)×Conscientiousness
1000 Employees and more (=1)×Emotional Stability
1000 Employees and more (=1)×Openness to Experiences
Company Size
1000 Employees and more (=1)
Educational Background
Years of Schooling
Labor Market Variables
Working Hours-0.0207(0.039)0.0690*(0.041)-0.0505(0.043)0.0161(0.041)-0.0135(0.041)

0.0956*(0.052)0.1107*(0.063)-0.0707(0.063)-0.1032*(0.057)0.1190(0.073)0.1418(0.277)0.0426***(0.009)-0.2560(0.500)0.0708***(0.018)0.0033*0.0099***(0.002)(0.003)Observations
838
269
R-squared
0.409
0.470
Note. Estimations are additionally controlled for socioeconomic variables (age and its square, type ofoccupation, full-time employment, years of employment at current workplace, and race dummies[only American samples]). Robust standard errors are in parentheses. ***p < 0.01, **p < 0.05, *p <0.1.

Table 5. Effects of (Non)Cognitive Skills on Annual Income by Employment Status and Company Size
Depdent Variables
Annual Income (Log)
Japan
U.S.
(1)
(2)
Personality Traits
Extroversion
0.0460*** -0.0047(0.017)(0.033)
Agreeableness0.0509** -0.0827**(0.022)(0.037)
Conscientiousness
0.03340.0492(0.021)(0.042)
Emotional Stability-0.01430.0641*(0.021)(0.038)Openness to Experiences
0.0057-0.0164(0.022)(0.045)Interaction between "Management Position (=1)" and Personality
Management Position (=1)×Extroversion
Management Position (=1)×AgreeablenessManagement Position (=1)×Conscientiousness
Management Position (=1)×Emotional Stability
Management Position (=1)×Openness to Experiences
Occupation Position
Management Position (=1)
Interaction between "1000 Employees and more (=1)" ×Agreeableness
Ordinary Employees in large-sized companies
Managers in large-sized companies

Educational Background
Years of Schooling
Labor Variable
Working Hours

Annual Income (Log)
Japan
U.S.
(3)
(4)
0.0464***(0.016)
0.0319(0.025)0.0320(0.021)-0.0141(0.021)0.0057(0.022)0.0294(0.032)-0.0962**(0.044)0.0480(0.038)0.0662*(0.039)-0.0362(0.045)-0.0042(0.037)-0.0419(0.038)0.0572(0.036)0.0171(0.036)-0.0381(0.035)-0.1184(0.082)0.0058(0.080)0.0053(0.072)0.0179(0.074)0.1131(0.079)-0.0007(0.037)-0.0333(0.039)0.0592(0.036)0.0166(0.036)-0.0395(0.035)-0.1200(0.088)-0.0077(0.078)0.0028(0.074)0.0210(0.073)0.1196(0.077)0.3566(0.295)-0.0114(0.690)0.3044(0.294)0.0643(0.672)0.0696*(0.042)-0.0122(0.018)0.0967*(0.058)-0.0212(0.038)0.0433*** 0.0726***
0.0439*** 0.0737***(0.010)(0.018)(0.009)(0.018)0.0034*0.0093***0.0034*0.0090***(0.002)(0.003)(0.002)(0.003)Observations
838
269
838
269
0.408
0.455
0.410
0.459
R-squared
Note. Estimations are additionally controlled for socioeconomic variables (age and its square, type of occupation, full-time employment
years of employment at current workplace, and race dummies [only American samples]). Robust standard errors are in parentheses. ***p <0.01, **p < 0.05, *p < 0.1.

Table 6. Effects of (Non)Cognitive Skills on Career Advancement
Dependent variable
Model: Probit
Personality Traits
Extroversion
AgreeablenessConscientiousness
Emotional Stability
Openness to Experiences

Management Position (=1)
Male Workers (Japan)

Male Workers (U.S.)

0.1541***(0.042)0.0653(0.057)0.0271(0.050)0.0333(0.053)-0.0431(0.050)0.1265*(0.066)0.0106(0.075)0.0369(0.090)-0.0087(0.068)-0.0096(0.084)0.1785***(0.048)0.0433(0.068)-0.0141(0.059)0.0534(0.062)-0.0797(0.058)0.1165(0.086)-0.0294(0.094)0.0718(0.119)-0.0016(0.090)0.0973(0.106)

Interaction between "1000 Employees and more (=1)" and Personality
0.0653(0.123)-0.0628(0.099)0.1538(0.114)-0.0742(0.117)0.1262(0.117)1000 Employees and more (=1)×Extraversion
1000 Employees and more (=1)×Agreeableness1000 Employees and more (=1)×Conscientiousness
1000 Employees and more (=1)×Emotional Stability
1000 Employees and more (=1)×Openness to Experiences
Company Size
1000 Employees and more (=1)
Educational Background
Years of Schooling

Labor Market Variable
Working hours

Observations

0.0629(0.152)0.0478(0.133)-0.1252(0.174)0.0294(0.133)-0.3343*(0.175)-0.3775***(0.112)-1.2990(0.842)-0.0768(0.187)1.6237(1.378)0.1376***(0.023)0.1401***(0.023)0.0956***(0.033)

0.0982***(0.033)0.0076*(0.004)0.0076*(0.004)-0.0029(0.006)-0.0032(0.006)

918

918

304

304

Note. Estimations are additionally controlled for socioeconomic variables (age and its square, full-time employment, years of employment at current
workplace, and race dummies [only American samples]). Robust standard errors are in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.

Table 7. Effects of (Non)Cognitive Skills on Happiness
Male (Japan)
Model: OLS(1) Basic Model used for
Dependent Variable: Degree of Happiness
Table 3
(coded on a scale of 0 to 10: 10 is happiest)
Personality Traits
Extroversion(2) Including One's
Own Annual Income

Female (Japan)(1) Basic Model used forTable 3(2) Including One's
Own Annual Income

0.2490***(0.044)0.1841***(0.067)0.0512(0.060)0.2479***(0.062)-0.0501(0.062)

0.2377***(0.044)0.1904***(0.067)0.0461(0.060)0.2221***(0.063)-0.0655(0.063)0.2319***(0.046)0.1685**(0.070)0.0151(0.063)0.2502***(0.064)-0.0616(0.064)0.2271***(0.046)0.1701**(0.070)0.0249(0.063)0.2347***(0.065)-0.0745(0.065)0.0900(0.060)0.2342***(0.083)0.0315(0.071)
0.3418***(0.088)0.0640(0.080)0.1161*(0.065)0.2190**(0.086)0.0228(0.075)0.3420***(0.090)0.0853(0.064)0.2106**(0.087)-0.0101(0.075)0.3818***(0.094)0.0804(0.086)0.1056(0.070)0.1851**(0.092)-0.0056(0.078)0.3856***(0.097)0.0804(0.086)0.0748***(0.024)0.0277(0.026)0.0226(0.026)0.0014***(0.000)-0.0050(0.028)0.0012***(0.000)0.0879**(0.044)0.0586(0.047)0.0476(0.048)0.0009*(0.000)0.0249(0.051)0.0006(0.000)X
5.3315***(1.548)O
6.5070***(1.599)X
6.6485***(1.595)O
7.3290***(1.655)X-0.5477(1.973)

O
0.6764(2.193)X-1.4419(2.241)O-0.6714(2.554)

Observations
R-squared
Model: OLS

1,138
0.115
Male (U.S.)

1,127
0.143

1,021
0.144

1,011
0.163

562
536
0.098
0.112
Female (U.S.)

492
0.110

471
0.124

Dependent Variable: Degree of Happiness(coded on a scale of 0 to 10: 10 is happiest)
Personality Traits
Extroversion(1) Basic Model used forTable 3(2) Including One's
Own Annual Income(1) Basic Model used forTable 3(2) Including One's
Own Annual Income

0.1315*(0.071)0.1089(0.084)0.1678(0.107)0.3602***(0.084)0.1478(0.106)0.1528**(0.070)0.0839(0.087)0.1692(0.111)0.3707***(0.090)0.1438(0.110)0.1025(0.070)0.0943(0.087)
0.0936(0.112)0.4029***(0.086)0.1754*(0.105)0.1228*(0.072)0.0716(0.087)0.1110(0.118)0.4268***(0.093)0.1912*(0.111)

0.2340**(0.094)0.2970**(0.123)0.0070(0.140)0.3426***(0.110)0.1816(0.133)0.2737***(0.103)0.2555*(0.136)
0.0717(0.157)0.4565***(0.120)0.2391*(0.136)0.2306**(0.102)0.2769**(0.130)-0.0067(0.152)0.3524***(0.116)
0.1922(0.153)0.2998***(0.111)0.2592*(0.146)0.0117(0.172)0.4791***(0.128)0.2045(0.152)0.0019(0.040)-0.0371(0.043)-0.0568(0.050)0.0009***(0.000)-0.0530(0.049)0.0005(0.000)0.0139(0.056)-0.0076(0.071)0.0032(0.068)-0.0000(0.001)-0.0083(0.074)-0.0002(0.001)

X
0.7321(2.067)O
1.1549(3.589)X
1.4117(2.153)O
0.4356(3.856)

X
1.8431(3.624)O
1.4173(4.223)

X
1.8669(3.822)

O
1.1921(4.337)

359
0.192

318
0.271

332
0.202

294
0.302

268
0.192

219
0.293

242
0.194

199
0.291

AgreeablenessConscientiousness
Emotional Stability
Openness to Experiences
Education Background and Income
Years of Schooling
One's own Annual Income
Other Control Variables
Occupation/ Employment TypeConstant

AgreeablenessConscientiousness
Emotional Stability
Openness to Experiences
Education Background and Income
Years of Schooling
One's own Annual Income
Other Control Variables
Occupation/ Employment TypeConstant

Observations
R-squared

Note. Estimations are additionally controlled for socioeconomic variables (age and its square, type of occupation, employment type, company size, full-time employment, years of employment atcurrent workplace, and race dummies [only American samples]). Robust standard errors are in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.

Figure 1. Standardized Regression Coefficient Associated with Years of Schooling in Japan and the United States
1-1. Japan
1.2. The U.S.

The Effect of Personality Traits on Years of Schooling(Japan)The Effect of Personality Traits on Years of Schooling (U.S.)
Extraversion

Extraversion
Agreeableness
AgreeablenessConscientiousness

Conscientiousness

Emotional_Stability

Emotional_Stability
Openness_to_Experiences

Openness_to_Experiences

Parents' Educational Attainment

Parents' Educational Attainment

‐0.1

0

0.1

w/o parents' schooling

0.2

0.3

w/t parent's schooling

0.4

0.5

‐0.2

‐0.1

0

0.1

w/o parents' schooling

0.2

0.3

0.4

0.5

w/t parent's schooling

Note. Figure displays standardized regression coefficients from multivariate analysis of years of schooling completed on personality traits and parental education, controlled for age, agesquared, and gender. Darker rectangular bars are estimates with control of parental educational background, and line bars represent robust standard errors.

Figure 2. Distribution of Noncognitive Skills
Extraversion (Males in Japan)

0

0

.1

.1

Density.2

Density
.2

.3

.3

.4

.4

Extraversion (Males in America)

0

2

4extraversion

6

8

0

2

Kernel density estimate
Normal density

4
extraversion

6

8

Kernel density estimate
Normal density

kernel = epanechnikov, bandwidth = 0.5000

kernel = epanechnikov, bandwidth = 0.5000

Agreeableness (Males in Japan)

0

0

.1

.1

Density.2

Density
.2

.3

.3

.4

.4

Agreeableness (Males in America)

02

4
agreeableness

6

8

0

2

Kernel density estimate
Normal density

4
agreeableness

68

Kernel density estimate
Normal density

kernel = epanechnikov, bandwidth = 0.5000

kernel = epanechnikov, bandwidth = 0.5000

Conscientiousness (Males in America)

0

0

.1

.1

Density.2

Density
.2

.3

.3

.4

.4

Conscientiousness (Males in Japan)0

2

4
conscientiousness

6

2

8

4
conscientiousness

68

Kernel density estimate
Normal density

Kernel density estimate
Normal density

kernel = epanechnikov, bandwidth = 0.5000

kernel = epanechnikov, bandwidth = 0.5000

Emotional Stability (Males in Japan)

0

0

.1

.1

Density.2

Density
.2

.3

.3

.4

.4

Emotional Stability (Males in America)

0

2

4
emotional_stability

6

8

0

2

Kernel density estimate
Normal density

4
emotional_stability

68Kernel density estimate
Normal density

kernel = epanechnikov, bandwidth = 0.5000

kernel = epanechnikov, bandwidth = 0.5000

Openness to Experiences (Males in America)

.1
0

0

.1

Density.2

Density
.2

.3

.3

.4

.4

Openness to Experiences (Males in Japan)

02

4
openness_to_experiences
Kernel density estimate
Normal density

kernel = epanechnikov, bandwidth = 0.5000

6

8

2

4
6
openness_to_experiences8

Kernel density estimate
Normal density
kernel = epanechnikov, bandwidth = 0.5000

Note. Distribution of Big Five personality traits are described with samples used to analyze
annual income, using a whole sample (Table 3, column 3).