The relative importance of type of education and subject area: empirical evidence for educational decisions

Pages30-58
Date03 April 2017
Published date03 April 2017
DOIhttps://doi.org/10.1108/EBHRM-05-2015-0019
AuthorCurdin Pfister,Simone N. Tuor Sartore,Uschi Backes-Gellner
Subject MatterHR & organizational behaviour,Global HRM
The relative importance of type
of education and subject area:
empirical evidence for
educational decisions
Curdin Pfister, Simone N. Tuor Sartore and Uschi Backes-Gellner
Department of Business Administration, University of Zurich, Zurich, Switzerland
Abstract
Purpose The purpose of this paper is to provide empirical evidence for individual educational investment
decisions and to investigate the relative importance of two factors, the type of education (vocational vs
academic) and subject area (e.g. commercial or health), in determining variance in earnings.
Design/methodology/approach Using a sample of 1,200 individuals based on the 2011 Swiss Adult
Education Survey, Mincer-type earnings equations are estimated. The variance in earnings is decomposed
with respect to the two factors mentioned above, which allows to quantify the relative contributions of type of
education and subject area to variance in earnings.
Findings The results of the variance decomposition show that subject area explains nearly twice the
variance in earnings compared with that explained by type of education.
Social implications As results show that earnings variance and thereby risk relate more to subject
area than to type of education, this study suggests that for individuals caring about the risk of their
educational decision the selection of a specific subject area is more relevant than the choice between
vocational and academic tracks; in addition, educational policies as part of HRM policies should devote as
much attention to the choice of subject areas as to vocational or academic education. This is especially
important for companies or countries planning to introduce or to extend vocational education as part of their
human resources strategies.
Originality/value This study is the first to show whether earnings vary more by type of education
or by subject area.
Keywords Vocational education, Academic education, Subject area, Variance decomposition
Paper type Research paper
1. Introduction
This paper provides evidence-based support for educational investments and focuses on the
variance of returns rather than the average returns, which have been analyzed extensively
in the past. Returns and variance reflect two important aspects of educational investments:
profitability and riskiness. In determining variance in earnings, this paper investigates for
the first time the relative importance of two factors, the type of education (vocational vs
academic) and the subject area (e.g. commercial or health).
Returns as well as variance differ with respect to two factors. The first factor refers to the
type of education and distinguishes between vocational and academic education.
The second factor refers to the subject area and distinguishes among fields of education,
e.g., commercial, health, science, technology, engineering and math (STEM), and social and
service. Studies investigating returns to education show mixed results with respect to type
of education. On the one hand, previous research finds that academic education leads to
higher earnings returns than vocational education (Conlon, 2005; Dearden et al., 2002; Heijke
and Koeslag, 1999). On the other hand, results from countries with stronger vocational
educational systems show reasonable and in some cases even higher earnings returns to
vocational education (Tuor and Backes-Gellner, 2010; Wolter and Weber, 1999). Regarding
subject area, results on returns to education are consistent across studies and indicate that
the most profitable fields are engineering, health, and business and that the least profitable
Evidence-based HRM: a Global
Forum for Empirical Scholarship
Vol. 5 No. 1, 2017
pp. 30-58
© Emerald PublishingLimited
2049-3983
DOI 10.1108/EBHRM-05-2015-0019
Received 29 May 2015
Revised 16 September 2015
Accepted 7 October 2015
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2049-3983.htm
30
EBHRM
5,1
are education, social sciences, and humanities (Altonji et al., 2012; Finnie and Frenette, 2003;
Rumberger and Thomas, 1993; Thomas, 2000; Thomas and Zhang, 2005). Only one study,
Glocker and Storck (2014) focuses on both factors (type of education and subject area) and
finds that university education is not always the most profitable path[1]. Thus, regarding
returns to educational investments, previous research shows that both type of education
and subject area are related to earnings.
In comparison to returns to education, much less empirical evidence is available
regarding the risk associated with human capital investments (Dickson and Harmon, 2011).
However, the risk, or more precisely the variance in earnings has recently received
considerable attention and is now the focus of an increasing number of studies (e.g. Hartog
and Vijverberg, 2007; Bonin et al., 2007). Regarding the type of education, Koerselman and
Uusitalo (2014) find that, after accounting for returns and risk, university graduates are in a
much better position than are vocational high school graduates. Regarding subject area,
Christiansen et al. (2007) focus on the risk-return properties of human capital investments
and find strong heterogeneity in returns and returns per unit of risk across fields. Thus far,
no study reveals the extent to which these two factors contribute to the variance in earnings.
In this paper, we focus on both factors simultaneously and examine the relative
importance of type of education and subject area for the variance in earnings. To do so,
we decompose the variance in earnings to quantify the separate contribution of each of the
two factors to the variance in earnings. Hence, we show the importance of these two factors
in determining subsequent earnings.
To quantify the effect of each factor, we proceed in two steps. In the first step, we
estimate ordinary least squares (OLS) regressions in the form of Mincer-type earnings
equations. Instead of a continuous variable years of schooling,we create dummy variables
for type of education and subject area. For type of education, we distinguish among purely
vocational, purely academic, and mixed education, i.e., individuals who combine vocational
and academic educations. For subject area, we form the following five categories:
commercial, health, STEM, social and service, and combined subject areas, i.e., individuals
who combine different subject areas. In the second step, to analyze the importance of these
two educational factors in determining the variance in earnings, we focus on the variance of
these returns to type of education and to subject areas and compute the variance
decomposition. This variance decomposition allows us to quantify the separate contribution
of each educational choice variable to variance in earnings.
To estimate the relative effect of the two educational factors, we use the 2011
Swiss Adult Education Survey (CH-AES 2011) and construct a sample of approximately
1,200 individuals, all of whom have a tertiary educational degree. These individuals are all
highly educated and therefore consist a rather homogenous group. The results of the
Mincer-type earnings equations show that both type of education and subject area have
statistically significant impacts on returns to education. Regarding the type of education,
academic and mixed educations yield higher returns than vocational education. Regarding
subject area, commercial is the most profitable field, whereas the returns to social and
service fields constitute the other side of the spectrum. The results of the variance
decomposition show that 9 percent of the explained variance in earnings is attributable to
the type of education, whereas nearly 17 percent is attributable to the subject area, that is,
subject area explains nearly double the variance in earnings.
Our findings show that earnings relate more to subject area than to type of education.
Hence, as the decision between vocational and academic education is less relevant than the
choice of a specific field, policy discussions on the educational system should devote at least
as much attention to the choice of subject area as to the type of education. In addition, given
the favorable returns observed for mixed educational careers, the permeability of
educational systems should also be discussed.
31
Empirical
evidence for
educational
decisions

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