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REVIEW OF ECONOMIC PERSPECTIVES – NÁRODOHOSPODÁŘSKÝ OBZOR,
VOL. 14, ISSUE 1, 2014, pp. 3–15, DOI: 10.2478/revecp-2014-0001
Soft Skills and their Wage Returns: Overview of
Empirical Literature
1
Jiří Balcar
2
Abstract: Psychological traits, attitudes and soft skills represent factors whose effect on
an individual’s wages has begun to be examined recently. Today, there is an extensive
empirical body on wage returns to the first two factors, but still a relatively small one on
wage returns to soft skills, such as communication, cooperation, leadership etc. The aim
of this paper is to provide an overview of empirical literature on wage returns to soft
skills. It suggests that soft skills are connected with significant wage returns and
contribute to closing the gender wage gap. The end of the paper focuses on a discussion
on methodological approaches to measurement of soft skills and relevancy of their
approximation by job characteristics (incl. suggestion of using tools of competency
modelling for this purpose).
Key words: Soft skills, wage returns, wage gap, skills-job match
JEL classification: J24, J31, J71
Introduction
There is a large number of factors which have been found to be significant determinants
of an individual’s wage (for an overview of the most common supply side wage
determinants see Balcar, 2012). Psychological traits, attitudes and soft skills represent
those whose effect on an individual’s wages has begun to be examined recently. Today,
there is an extensive empirical body on wage returns to the first two factors, but still a
relatively small one on wage returns to soft skills (for instance communication,
cooperation or leadership). The aim of this paper is to provide an overview of empirical
literature focusing exclusively on soft skills in order to evaluate an influence of soft
skills on individual’s wage and discuss approaches employed in soft skills
measurement.
It is worth stressing that “soft skills” represent a term that is generally known and
understood, but yet not precisely defined. This is probably the result of both its usage in
business practice, where specification of particular skills is more important than a
definition of comprehensive term (thus soft skills are usually defined by enumeration of
skills, which can differ among companies), and usage of alternative terms in academic
sphere, such as non-cognitive skills, personal skills or people skills (which do not,
however, represent a synonym for soft skills). An application of the term “soft skills” in
1
This paper has been funded by a grant from the Czech Science Foundation (grant number
P402/11/2464) for a research on the gender wage gap in Czech Republic.
2
VSB - Technical University of Ostrava, Economic faculty, Sokolská třída 33, 701 21 Ostrava;
balcar.er@gmail.com
REVIEW OF ECONOMIC PERSPECTIVES
4
this paper represents an attempt to support applicability of results of academic research
in practice through unification of the terminology.
The first section of the paper provides a general definition of soft skills (incl. some other
relevant terms) and their examples in order to specify the exact focus of this paper. The
second one provides conclusions of empirical studies on wage returns to these skills.
The overview shows that soft skills are statistically significant determinants of an
individual’s wage and contribute to closing the gender wage gap. The last section
discusses methodological approaches to measurement of soft skills and relevancy of
their approximation by job characteristics (incl. suggestion of using tools of competency
modelling for this purpose).
Soft skills
Spreading of a competency approach in human resources management led to focusing
on particular skills of workers / job applicants, instead of their IQ or formal level of
educational attainment, in processes of hiring, evaluation, development and planning of
career growth (Kubeš, Spillerová, Kurnický, 2004). An importance of this trend can be
illustrated by many lists of skills necessary for employability and work performance of
an individual which are defined at national (or international) level and which became a
part of national educational policies (e.g. Basic skills, Core skills, Critical enabling
skills, Employability skills, Essential skills, Generic skills or Key skills; see Table 1.2 in
Balcar, Homolová, Karásek et al., 2011 for their detailed description), or by effort to
identify future skills needs at these levels (e.g. see Balcar, 2011 for information on
future skills needs at EU level).
The bulk of skills supporting individual’s employability can be found among the so
called “soft skills” which can be described as “intangible skills
3
which are hard to
measure and are closely connected with [individual’s] attitudes
4
” (Balcar, Homolová,
Karásek et al., 2011), e.g. communication, cooperation, leadership, independence or
creativity.
5
“Hard skills”, on the other hand, can be described as “skills which are easily
observed and/or measured, easily trained and closely connected with [individual’s]
knowledge
6
” (Balcar, Homolová, Karásek et al., 2011), e.g. ICT skills, surgical skills or
3
Skill is “the capacity for carrying out complex, well-organized patterns of behaviour smoothly
and adaptively so as to achieve some end or goal” (Reber, Reber, 2001).
4
Attitude is „a stable, long-lasting, learned predisposition to respond to certain things in a certain
way” (Statt, 1998).
5
Classification of soft skills used by the National System of Occupations (NSP, 2011) can further
clarify this term (and thus focus of this paper) as it provides definitions of 15 soft skills, including
enumeration of their sub-skills, and behavioural descriptions of their levels. (The classification
comprehends the following skills: communication, cooperation, creativity, flexibility,
consumer orientation, efficiency, independence, problem solving, planning and organizing,
life-long learning, proactive approach, stress resiliency, exploring and orientation in
information, leadership, and influencing others.) It also suggests that terms “people skills” or
“non-cognitive skills”, which are often used in present empirical literature, do not represent
synonym to “soft skills”. It is given by the fact that soft skills are not limited only to skills
necessary for interpersonal interactions and are closely connected to individual’s cognitive skills.
6
Knowledge is “the body of information possessed by a person, by a group of persons or a
culture” (Reber, Reber, 2001).
Volume 14, Issue 1, 2014
5
typing skills. It can be added that hard skills, compared to soft skills, are more closely
related to formal qualification of an individual.
The importance of soft skills has increased significantly in the last few decades. For
example, Borghans, Weel and Weinberg (2006) reported a substantial growth in the
number of people performing job tasks requiring soft skills from 1970 to 2002.
However, Weinberger (2011) found that the growth of employment is concentrated
mainly in jobs requiring a combination of both cognitive and soft skills, whereas
employment in jobs requiring either cognitive or soft skills was relatively stable from
1977 to 2010. It corresponds to the findings of Bacolod and Blum (2008), who found a
statistically significant correlation between requirements on cognitive and soft skills
which showed that they complement each other. An indirect evidence of the growing
importance of soft skills was presented by Bacolod and Blum (2008) who found out that
the wage premium to soft skills doubled during the period 1968 - 1990.
Although there is a wide consensus on the positive role of soft skills on individual’s
employability and other labour market outcomes, there is still a relatively small (but
growing) empirical body on wage returns to this kind of human capital (as was pointed
out also by Borghans, Weel, Weinberg, 2006 and 2008)
7
. Since the aim of this paper is
to provide an overview of empirical literature focused exclusively on soft skills
(according to above stated definition), the rapidly growing literature on wage returns to
various psychological traits and attitudes is not taken into account. (However, it should
be noted that soft skills are significantly influenced by individual’s psychological traits
and attitudes which make their precise distinction difficult.)
Overview of empirical literature on wage returns to soft skills
Wage returns to specific clusters of soft skills, communication skills, leadership skills
and attitudes closely related to particular soft skills are discussed in the following
paragraphs (detailed information on reviewed papers can be found in Table 1).
Borghans, Weel and Weinberg (2006) estimated wage returns to a whole range of soft
skills, presence of which was approximated by importance of “people tasks” for job
performance. They also examined whether or not individual’s sociability (measured
during childhood and early adulthood) is associated with wage premium in jobs where
people tasks are important. Results showed that individuals working in jobs where
people tasks are important face lower wages. The wage penalty connected with a
standard deviation increase in the importance of people tasks was estimated at circa 5%
in the U.S. and 4-9% in UK. The sociability variables, though not all, indicated a very
low wage premium in those jobs (circa 1%).
Bacolod and Blum (2008), who focused on wage returns to people skills, cognitive
skills and motor skills, used a description of job tasks and requirements from Dictionary
of Occupational Titles to define these variables. They found out that wage returns to
7
It can be noted that socioeconomic outcomes of soft skills are not entirely new topic in
economics. It is possible to identify some older empirical papers on this theme, although they are
rare. For instance, Turner and Martinez (1977) discussed effects of individual’s manipulativeness
on family income and occupational prestige among men. They found out that it represents an
important determinant of income and occupational prestige for men with higher education, but not
for less educated men.
REVIEW OF ECONOMIC PERSPECTIVES
6
people skills nearly doubled in the period from 1968 to 1990 (one standard deviation
increase in people skills was associated with 3.2% wage increase in 1968 and 6.0%
increase in 1990), while returns to cognitive skills increased “only” by 60% and returns
to motor skills decreased by 50%. A detailed examination revealed that people skills
have no value themselves, but only as a complement to other skills. The growth of wage
returns to people skills was, in fact, caused by increasing returns to combination of
cognitive (or motor) and people skills in the period from 1968 to 1990. This also
corresponds to the findings of Weinberger (2011) who identified significant growth of
employment only in jobs requiring both cognitive and people (in this case leadership)
skills.
Black and Spitz-Oener (2007) examined gender differences in wage returns to a broad
range of skills approximated by different job tasks. The tasks were identified on the
basis of Qualification and Career Survey, where employees reported their job tasks.
Authors defined five groups of skills: non-routine interactive tasks, non-routine analytic
tasks, routine cognitive tasks, routine manual tasks and non-routine manual tasks, where
the designation “routine tasks” suggests possibility of machine processing. Their
estimation showed that wage premium is connected (in descending order) with non-
routine interactive tasks, non-routine analytic tasks and routine cognitive tasks, whereas
wage penalty is connected with routine manual tasks and non-routine manual tasks.
Borghans, Weel and Weinberg (2008) applied a novel approach to the examination of
wage returns to soft skills by focusing on an interpersonal interaction approximated by a
trade-off between directness, which facilitates accurate communication, and caring,
which establishes a cooperative environment. Results revealed that one standard
deviation increase in directness relative to caring raised wages by 9.6% in 1997 and
10.8% in 2001 in UK, and by 3.8% in 1979 and 10.2% in 1998 in Germany. It means
that a statistically significant increase of returns to directness was identified during the
examined period in both countries. It should be also mentioned that the premium for
directness was higher in occupations, where it is more important.
Another unusual approach was employed by Conti, Galeotti, Mueller and Pudney
(2009), who used popularity (defined as number of classmates who consider a particular
person to be a friend) as a proxy for the ability to make positive personal and social
adjustments (or more precisely ability to understand “the rules of the game", gain
acceptance and social support from colleagues, and distinguish whom to trust and when
to reciprocate). They found out that one additional friendship nomination of the person
in high school is associated with 35% wage premium 35 years later, which corresponds
to 40% of one more year of education.
Kuhn and Weinberger (2005) focused on wage returns to leadership skills in case of
white men. These skills were measured by observable leadership activities of an
individual during his study at high school and by their self-assessment. These leadership
variables were regressed on annual and hourly earnings 9-13 years later (depending on a
dataset used). Estimations showed that men, who were both a captain of an athletic team
and a president of a club or other organization at high school, earn 3.8-22.1% more than
others. The same pattern was identified for self-assessed leadership skills as well.
Authors also proved that individuals who acted in any leadership role (i.e. captain,
president, or both) have a higher probability of occupying a managerial job in the future.
Volume 14, Issue 1, 2014
7
In one of his later papers, Weinberger (2011) brought new evidence on wage returns to
leadership skills. She used behavioural indicator of leadership again and regressed it on
weekly earnings 7 years after graduation. Results confirmed a statistically significant
5.3% wage premium for leadership skills, or more precisely, for leadership in clubs,
performing arts and student publications or sport participation, which more than
doubled between 1979 and 1999. The growth of wage premium differed according to
the complexity of work, i.e. was growing in occupations requiring high levels of both
social and cognitive skill, fairly constant in occupations requiring high levels of either
social or cognitive skill (but not both) and falling in occupations with low skills
requirements.
For an illustration, it is also possible to briefly mention some papers focusing on
psychological traits and preferences closely related to particular soft skills. Fortin
(2008) tried to capture personal motivation and work effort through an importance of
money and work for an individual. He showed that the importance of money/work is a
statistically significant predictor of wage level, and that its effect grows over time.
Dunifon and Duncan (1998) estimated effects of personal efficacy, defined as an ability
to reach long-term goals through individual’s intentional activities, on wages of men.
They found out that one standard deviation increase in personal efficacy measured
during years 1968-1972 is associated with a 14% wage premium in 1988-1992. A need
for challenge (i.e. getting ahead) relative to affiliation (i.e. getting along) measured in
1972 was identified as another significant determinant of wage, because one standard
deviation increase of this ratio led to 7% wage growth in 1988-1992. The wage effect of
the need for challenge relative to affiliation was explored also by Semykina and Linz
(2007), who found 2.9% wage premium for one standard deviation increase of this
variable (but not statistically significant for men). They also examined wage returns to
internal relative to external locus of control as an approximation of individual’s
initiative, which were estimated at the level of 7.9% for one standard deviation change
of this variable. Statistical significance of locus of control on wage was confirmed also
by Andrisani (1977) who found out that e.g. white men of age 16-26 who were „slightly
internal“ have enjoyed a 12% wage premium over men who were „slightly external”
(corresponding wage premium for white men of age 48-62 was 8%).
8
8
It is also possible to mention a study of Machin, McIntosh, Vignoles and Viitanen (2001) who
used wide range of variables describing behaviour and psychological traits of individuals at the
age of 16 to control an influence of these factors on relationship between individual’s verbal and
math abilities and his/her real hourly wage at the age of 33. Unfortunately, an interpretation of the
effect of particular “soft” variables on hourly wage is complicated by duplicities in variables
caused by the fact that the same personal trait is often described by more variables or/and the
same variable is assessed by more than one subject (self-assessment, parents, teacher). Moreover,
the design of variables also affects their statistical significance. However, the estimates showed
that at least being on own, timid and cautious at age 16 lead to lower hourly wage of men at age
33, and having no plans for the future at age 16 decrease hourly wage of women (these results are
valid for estimates controlling for qualification level, verbal and math abilities at age 7 and 16,
type of school, family background, parental occupations, parental interest and region).
REVIEW OF ECONOMIC PERSPECTIVES
8
Table 1: Overview of studies on wage returns to soft skills
Study Borghans, Weel, Weinberg
(2006) Bacolod, Blum
(2008) Black, Spitz-Oener (2007)
Soft skill
variable(s)
Importance of people tasks
I)
(binary variable for the USA
and five-point scale for UK)
Sociability
(self-assessment for the USA
and behavioural description
for UK; sociability during
childhood and early
adulthood)
People skills
index
II)
Non-routine interactive tasks
III)
(number of tasks performed by
worker divided by total number of
tasks in the category in %)
Non-routine analytic tasks
IV)
(number of tasks performed by
worker divided by total number of
tasks in the category in %)
Data
Dictionary of Occupational
Titles 1977 and 1991
(USA), British Skill Survey
1997 and 2001 (UK)
National Longitudinal Study
of Youth 1979 (USA),
British Cohort Study 1970
(UK)
Dictionary of
Occupational
Titles, Current
Population
Survey 1968-
1990; employed
individuals aged
18-64 (USA)
Qualification and Career Survey
1979 and 1999 (self-report of job
tasks), Administrative Social
Security Records; full-time
employees 22-55 years old without
university or technical college
degree only (West Germany)
Dependent
variable Log of wage
at adulthood Log of weekly
earnings Log of daily wage
Results
One standard deviation
increase in the importance of
people tasks was associated
with
c. 5% wage penalty in USA
(coefficients from
-0.018 to -0.021) and 4-9%
wage penalty in UK
(coefficients from -0.010 to -
0.021).
One standard deviation
increase in the sociability
was associated with small
wage premium,
c. 1% (coefficients from
0.002 to 0.005 for both
countries)
One standard
deviation increase
in people skills
was associated
with 3.2% wage
increase in 1968
and 6.0% wage
increase in 1990.
Wage returns to non-routine
interactive tasks and non-routine
analytic tasks were found positive
and statistically significant
(regression coefficients 0.593 and
0.383, respectively). Wage premium
was higher for women in both cases
(coefficient 0.85 for interactive tasks
and 0.838 for analytical tasks).
Other
regressors
Individual dummy variables,
year dummy variables,
education, experience,
experience squared,
occupation random effects
(USA)
Education, gender dummy,
experience, experience
squared, math, reading,
writing, physical strength
and stamina, problem
solving, noticing mistakes,
planning of activities,
knowledge of the
organization, occupation
random effects (UK)
Log of cognitive
skills, log of
motor skills, log
of strength, age,
age squared,
experience,
experience
squared,
experience cubed,
dummy for
female, black,
other non-white
race, SMSA
status, high
school graduate,
college graduate,
region
Routine cognitive tasks, routine
manual tasks, non-routine manual
tasks, education, age, education-
gender interactions, age-gender
interactions, tasks-gender
interactions, industry dummies
Volume 14, Issue 1, 2014
9
Study Borghans, Weel, Weinberg
(2008) Conti, Galeotti, Mueller, Pudney
(2009) Kuhn, Weinberger
(2005)
Soft skill
variable(s) Interpersonal interaction
(directness relative to caring)
V)
Popularity
(number of high school classmates
who consider a particular person
to be a friend)
Leadership
(participation in
leadership activities in
past year and in past 3
years at high school,
self-assessment)
Data
British Skill Survey 1997 and
2001 (self-assessed importance
of job activities and key skills
at five-point scale; UK),
Qualification and Career
Survey 1979, 1985, 1991 and
1998 (self-assessed binary
indicator of presence of
particular tasks) and
Administrative Social Security
Records (Germany)
Wisconsin Longitudinal Study
1957-2005 (senior high school
class) ; full-time male employees
only (USA)
Project TALENT
1960, National
Longitudinal Study of
the High School Class
1972, High School and
Beyond 1982; white
male only (USA)
Dependent
variable Log of wage Log of hourly wage
Log of annual earning
or hourly earnings
(depending on dataset);
9-13 years after high
school graduation
Results
UK: One standard deviation
increase in directness relative
to caring was associated with
wage premium at level 9.6% in
1997 and 10.8% in 2001. (One
standard deviation change in
the relative importance of
directness increased wages by
15.6% in the period 1997-
2001.)
Germany: One standard
deviation increase in directness
relative to caring was
associated with wage premium
at level 3.8% in 1979, 5.2% in
1985, 8.5% in 1991, and 10.2%
in 1998. (One standard
deviation increase in the
relative importance of direct-
ness raised wages by 19.8% in
the period 1979-1998.)
One additional friendship
nomination of the person at high
school was associated with 35%
wage premium 35 years later
Participation in both
captain and president
function was
connected with 3.8-
22.1% wage premium
(depending on dataset).
3 percentiles of people
with highest self-
assessment leadership
score had wages
16.2-32.5% higher
than others (depending
on dataset)
Other
regressors Gender, marital status, level of
education
College-educated father, college-
educated mother, graduating class
size, proportion of students taking
math, proportion of students
taking a language, proportion of
students with college plans,
resident in Wisconsin, IQ, grade
rank, years of schooling, marital
status, social participation, number
of outings with friends, number of
outings with relatives, job found
through network, individual effect
Educational
attainment, math score,
parents’ education
REVIEW OF ECONOMIC PERSPECTIVES
10
Study Weinberger (2011) Fortin (2008) Dunifon, Duncan (1998)
Soft skill
variable(s)
Leadership
(participation in
leadership activities in
past year at
high-school)
Motivation and work
effort
(importance of
money/work)
Personal efficacy
(approximated by ability to reach
long-term goals)
Challenge vs. affiliation
Data
National Longitudinal
Study of the High
School Class 1972,
National Education
Longitudinal Study
1988; white male only
(USA)
National Longitudinal
Study of the High
School Class 1972,
National Educational
Longitudinal Study of
1988/94; employed only
(USA)
Panel Study of Income Dynamics;
men only (USA)
Dependent
variable
Log of weekly earnings;
7 years after high school
graduation Log of wage Log of average hourly earnings
Results
Wage premium at level
of 5.3% in 1979 and
11.5% in 1999 was
estimated for aggregate
leadership variable.
Wage returns were
estimated as statistically
insignificant in 1979 and
9.9% in 1999 for
leadership in clubs,
performing arts, or
student publications, and
4.0% in 1979 and 8.2%
in 1999 for sport
participation
Positive and increasing
impact of perceived
importance of
money/work on wage
(coefficient 0.209 at age
25 and 0.258 at age 32
in NLS dataset and
0.165 at age 24 in NELS
dataset)
One standard deviation increase in
personal efficacy (measured in 1972)
was associated with
14% wage premium in 1988-1992.
One standard deviation increase in
challenge relative to affiliation
(measured during years 1968-1972)
was associated with 7% wage
premium in 1988-1992.
Other
regressors
Math score, interaction
terms
(baseline model)
Importance of
people/family, self-
esteem, locus of control,
gender, high school
math score, education,
experience and tenure,
part-time employment,
black, married, child,
parental experience
Years of education, sentence
completion test score, age, number
of siblings, years of education of
father, dummy variables for black,
father self-employed, father’s
occupation, grew up in a city, grew
up in a town, grew up on a
farm/other area, grew up in the
South, family was poor growing up,
family was well-off, family was of
average income, health limits ability
to work in 1968-1971
Volume 14, Issue 1, 2014
11
Study Semykina, Linz (2007) Andrisani (1977)
Soft skill
variable(s)
Challenge vs. affiliation
Initiative
(approximated by locus
of control)
Initiative
(approximated by locus
of control)
Data Russian Employee Survey 2000, 2002 and
2003 (Russia) National Longitudinal Study; men 16-26
years in 1968 and 48-62 years in 1969 (USA)
Dependent
variable Log of monthly earning Log of hourly
earnings
Results
One standard deviation increase in
challenge relative to affiliation was
associated with 2.9% wage premium
(significant at 10% level). Result was not
statistically significant separately for men
and 3.2% for women.
One standard deviation increase in internal
relative to external locus of control was
associated with 7.9% wage premium. The
same change would increase wages by
4.6% for men (significant at 10% level) and
6.4% for women.
Young (older) white men, who were „slightly
internal“ have enjoyed 12% (8%) wage
premium over comparable men who were
„slightly external”.
Other
regressors
Age, age-squared, years of schooling, job
tenure, job tenure squared, dummy variable
for managers, number of job changes,
dummy for a recent unemployment
experience.
Dummy variables for education, dummy
variable for completion of a formal
occupational training, tenure, potential work
experience, dummy variable for health,
married, residence in the South, degree of
urbanization in the local labour market
Source: Author.
Note:
I) For US data defined as importance of the following job-tasks: adaptability in situations involving
the interpretation of feelings, ideas or facts in terms of personal viewpoint; adaptability in
influencing people in their opinions, attitudes or judgments about ideas or things; adaptability in
dealing with people beyond giving and receiving instructions. For UK data defined as importance of
planning job activities, knowledge about the organization and products, problem solving, noticing
problems and (procedural) faults, and physical skills and work.
II) People skills index comprehends requirements on adaptability in dealing with people beyond
giving and receiving instructions; adaptability in accepting responsibility for direction, control or
planning of an activity; adaptability in influencing people in their opinions, attitudes or judgments
about ideas or things; complexity at which worker performs a job in relation to people: mentoring,
negotiating, instructing, supervising, diverting, persuading, speaking-signalling, serving, taking
instructions.
III) Non-routine interactive consists of negotiating, lobbying, coordinating, organizing; teaching,
training; selling, buying, advising customers, advertising; entertaining, presenting; employ, manage
personnel. IV) Non-routine analytic tasks consist of researching, analysing, evaluating and planning;
making plans, constructions, designing and sketching; working out rules and prescriptions; using
and interpreting rules.
V) Caring is needed to create cooperative environment, directness to communicate accurately. UK:
Directness comprehends instructing, training or teaching people; making speeches or presentations;
persuading or influencing others; and selling a product. Caring comprehends dealing with people;
working in a team of people; counselling, advising or caring for customers; and listening carefully to
colleagues. Germany: Directness comprehends negotiating, lobbying, coordinating and organizing;
teaching or training; selling, buying, or advertising; and entertaining or presenting. Caring
comprehends serving and accommodating; advising customers and clients; and helping out others.
REVIEW OF ECONOMIC PERSPECTIVES
12
This brief overview showing relevancy of soft skills for wage determination can be
supplemented with a note on their relation to recent development of gender wage gap.
The above reviewed papers show that changes in employers’ requirements on soft skills
of employees, accompanied by relevant development of their wage returns, together
with differences in distribution of these skills between genders led to a significant
reduction of the gender wage gap. This conclusion is consistent with results of Bacolod,
Blum (2008), Black, Spitz-Oener (2007) and Borghans, Weel and Weinberg (2006) in
the case of soft skills, and Semykina, Linz (2007) and Fortin (2008) in the case of
attitudes closely related to soft skills.
Discussion on methodology
Two different methodological approaches were used in overviewed papers for
measuring soft skills. The direct one is based on questioning individuals on their
behaviour (e.g. Weinberger, 2011; Kuhn, Weinberger, 2005) or their preferences and
attitudes (e.g. Fortin, 2008; Semykina, Linz, 2007; Dunifon, Duncan, 1998; Andrisani,
1977). The indirect one approximates an individual’s soft skills by job tasks (e.g.
Bacolod, Blum, 2008; Borghans, Weel, Weinberg, 2008 and 2006; Black, Spitz-Oener,
2007), which are identified by trained experts (e.g. in case of Dictionary of
Occupational Titles in USA) or by workers themselves (e.g. in case of British Skill
Survey in UK or Qualification and Career Survey in Germany). It should be noted that
the evidence, referred to by Borghans, Weel and Weinberg (2006), suggests that job
tasks identified by workers and trained experts do not differ significantly.
Does the indirect approach measure soft skills reliably? The approximation of an
individual’s skills by job characteristics (regardless whether job tasks or skills
requirements are taken into account) is based on an assumption that any job is
performed only by workers with relevant skills. Since soft skills are closely related to
attitudes (i.e. relatively stable learned predisposition to respond to certain things in a
certain way) and thus their development is more difficult and slower than in the case of
hard skills, it can be further assumed that only workers who already have relevant soft
skills at required levels are hired (although they may lack some hard skills at the
beginning, since these can be developed relatively easily and quickly). Under the second
assumption, there is no problem with reverse causality in relation between soft skills
and a job performed because the proper set of soft skills represents a condition for
hiring. It should be noted that the mechanism described above does not influence the
role of level and field of individual’s education as the sorting device which is used for
pre-selection of job applicants, because only those who have the education required are
considered for the final selection based on soft skills. (This two-stage selection of
workers based on education and subsequently on soft skills corresponds to the results of
a European survey published in Balcar, Homolová, Karásek et al., 2011).
Relevancy of the assumption that jobs are performed by workers with relevant soft
skills can be confirmed by the results of many empirical studies. The studies found a
statistically significant match of individual’s soft skills with job tasks (e.g. Weinberger,
2011; Borghans, Weel, Weinberg, 2008 and 2006) or at least with type of job (e.g.
Kuhn, Weinberger, 2005, who match leadership skills with employment in managerial
jobs). This evidence suggests that an indirect approach to soft skills measurement
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13
through job characteristics provides relevant data. Moreover, the usage of this approach
can minimize the bias of data caused by subjectivity of individual’s responses, improper
questions or other factors present in case of direct questioning. On the other hand, the
indirect approach is not capable of capturing differences among individuals, but only
groups of individuals, i.e. individuals working in the same job.
The efficiency of indirect measurement of soft skills could be further improved by using
methods of competence modelling, i.e. by using particular skills required for a job
performance instead of widely used job tasks. However, the change of focus from job
tasks to skills is not beneficial by itself. The main improvement consists in clear
specification of levels of each skill by behavioural descriptors, enabling an accurate and
objective description of a person suitable for a job. (The difference between job tasks
and skills approaches can be illustrated by a job where communication on elementary
level is very important, thus the importance of communication as a job task would be
evaluated by high mark, while the required skill level by low mark. The results from
these two approaches would be then significantly different.) Therefore, it is possible to
state that for the purpose of estimating wage returns to particular skills, the approach
based on competency modelling is more suitable.
Conclusions
There is a large number of factors which were found to be significant determinants of an
individual’s wage. Psychological traits, attitudes and soft skills represent factors, whose
effect on individual’s wages has begun to be examined recently. Today, there is an
extensive empirical body on wage returns to the first two factors, but still a relatively
small one on wage returns to soft skills. It can be caused by the fact that soft skills are
hard to measure and so there is a lack of relevant data for its empirical examination.
Empirical papers focusing on soft skills use two different methodological approaches to
measure them. The direct one is based on questioning individuals on their behaviour,
preferences and attitudes, while the indirect one approximates individual’s soft skills by
job tasks identified by trained experts or by workers themselves. It can be noted that
empirical evidences suggest that an indirect approach provides relevant data as well.
An overview of empirical literature on wage returns to soft skills, which can be found in
this paper, shows that soft skills are connected with significant wage returns and
contribute to closing of the gender wage gap. However, heterogeneity of approaches to
specification and quantification of particular soft skills suggests that it is a field of
empirical research with significant potential for further research (e.g. formulation of
generally accepted definition of soft skills, an application of competence modelling
tools for creating more relevant data for an analysis, estimation of returns to particular
soft skills and not to their clusters etc.)
REVIEW OF ECONOMIC PERSPECTIVES
14
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