Employment effects of skills around the world: Evidence from the PIAAC

AuthorDamir STIJEPIC
DOIhttp://doi.org/10.1111/ilr.12162
Publication Date01 Sep 2020
Copyright © The author 2020
Journal compilation © International Labour Organization 2020
International Labour Review, Vol. 159 (2020), No. 3
Employment effects
of skills around the world:
Evidence from the PIAAC
Damir STIJEPIC*
Abstract. Using an international survey that directly assesses the cognitive skills
of participants, the author studies the eect of skills on employment in 32 coun-
tries. On average, a 1 standard deviation increase in numeracy is associated with
an 8.4 percentage point increase in the probability of being employed, reducing the
probability of being out of the labour force and unemployed by 6.4 and 2.1 per-
centage points, respectively. After controlling for numeracy, the estimated employ-
ment eect of years in education falls by one third, from 2.7 to 1.8 percentage
points. Notably, the employment eect of skills is more pronounced in countries
with higher unemployment.
Keywords: cognitive skills, education, labour force status, employment,
international comparisons, Survey of Adult Skills, PIAAC.
1. Introduction
Individuals with lower (measured) cognitive skills face disadvantages in the la-
bour market. In particular, they are less likely to be employed (McIntosh and
Vignoles, 2001; Heckman, Stixrud and Urzua, 2006). The employment eects
of skills are of interest beyond their direct labour income eects. A large and
inuential body of literature documents the impact of displacement and em-
ployment breaks on various life outcomes including divorce, criminality and
mental and physical health (Eliason, 2012; Fougère, Pouget and Kramarz, 2009 ;
Kuhn, Lalive and Zweimüller, 2009; Sullivan and von Wachter, 200 9). However,
large international comparisons of the eects of skills on adult populations typ-
ically focus on wage premia (e.g. Hanushek et al., 2015 and 20 17; Leuven, Oost-
erbeek and van Ophem, 200 4).1 Non-employment, that is, unemployment and
*Johannes Gutenberg University, Mainz, email: mail@damir.stijepic.com. The author wishes
to thank Denis Stijepic, Tzehainesh Teklè, Klaus Wälde, Peter Winker and two anonymous referees
for their helpful comments. He gratefully acknowledges the nancial support provided by the Fritz
Thyssen Foundation under the grant No. 40.16.0.028WW and by the German Research Foundation
(DFG) under the grant No. 433336278.
Responsibility for opinions expressed in signed articles rests solely with their authors, and
publication does not constitute an endorsement by the ILO.
1 Hanushek and Woessmann (2011) discuss the advantages and challenges of the cross-country
comparative approach that makes use of international achievement tests in order to analyse the
determinants and eects of cognitive skills.
International Labour Review
308
inactivity, is only taken into account in so far as it induces a selection bias in
the wage regressions.2
A notable exception in this regard is Abrassart (2 013), who examines the
sources of the employment disadvantage among individuals with low levels of
formal education in 14 countries over the period 1994 –98. He argues that dif-
ferences in cognitive skills, rather than dierences in labour market regulation,
explain the cross-country variation in the employment opportunities of indi-
viduals with low educational attainment. The gap in the probability of being
employed between individuals with intermediate and low levels of educational
attainment is particularly wide in countries in which the skill gap between the
two groups is also wide. However, his estimates reect the situation in the 1990s.
The employment eects of cognitive skills from two decades ago may no longer
be good indicators of the situation in today’s economies. In particular, recent
contributions document a reversal in the demand for cognitive tasks and skills
(Beaudry, Green and Sand, 2016).
Making use of the Survey of Adult Skills of the Programme for the Inter-
national Assessment of Adult Competencies (PIAAC), I study the relationship
between cognitive skills and the probability of being employed in 32 countries
over the period 2011–15. In addition to a standard socio-economic background
questionnaire, the PIAAC directly assesses the cognitive skills of the survey par-
ticipants, providing internationally comparable data on key skills in the adult
population. On average across the 32 countries in the sample, I estimate that a
1 standard deviation increase in numeracy skills is associated with an 8.4 per-
centage point increase in the probability of being employed among individuals
aged 25 –54. The estimated employment eect of skills is substantial compared
to the 2.7 percentage point employment eect of years spent in education.
There are various further notable results. First, the 8.4 percentage point
employment eect of numeracy skills is associated with a reduction in the probabil-
ity of being out of the labour force and of being unemployed of 6.4 and 2.1 per-
centage points, respectively. Second, the employment eect of years spent in
education falls by one third, from 2.7 to 1.8 percentage points, after controlling
for numeracy skills. Third, a rst investigation suggests that the employment
eect of numeracy skills reects a causal relationship rather than a mere cor-
relation. Fourth, there is substantial heterogeneity across subpopulations and
countries. Notably, the employment eect of skills tends to be more pronounced
in countries with higher unemployment. Accordingly, a twofold increase in un-
employment relative to employment is associated with a 1.9–2.3 percentage
point increase in the employment eect of standardized numeracy skills.
The remainder of this article is structured as follows. The second section
provides an overview of the PIAAC data and presents descriptive statistics. The
employment eects of skills are analysed in the third section, considering dier-
ent subpopulations, the question of causality and the eects of regional condi-
2 For instance, Hanushek et al. (2015) address the employment eects of cognitive skills in
two sentences before continuing their study of the wage returns to skills: “The rst row of Table
6 reports the impact of numeracy on employment in a linear probability model. Consistently across
countries, better skills are indeed signicantly related to higher employment probabilities.” (p. 117).
Employment eects of skills 309
tions. The fourth estimates the employment eects of years spent in education,
also taking into account the role of skills. Some conclusions are presented in
the fth section, while further details on the data used and auxiliary results are
found in the Appendix.
2. The PIAAC data
The following empirical analysis is based on the Survey of Adult Skills of the
PIAAC. The PIAAC is a large-scale initiative of the Organisation for Economic Co-
operation and Development (OECD), providing internationally comparable data
on the key skills of the adult populations in the countries surveyed.3 During the
rst round in 2011–12, 2 4 countries participated in the data collection; of these,
the following 2 3 are covered in this article: Austria, Belgium (specically Flan-
ders), Canada, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany,
Ireland, Italy, Japan, Republic of Korea, the Netherlands, Norway, Poland, Rus-
sian Federation (excluding the Moscow municipal area), Slovakia, Spain, Sweden,
the United Kingdom (specically England and Northern Ireland) and the United
States.4 Another nine countries participated in the second round in 20 14 –15:
Chile, Greece, Indonesia (specically Jakarta), Israel, Lithuania, New Zealand,
Singapore, Slovenia and Turkey.5
The Survey of Adult Skills is designed to measure key cognitive skills that
are essential for participation in the labour market and in society. In contrast
with IQ tests, the PIAAC achievement tests measure general knowledge that can
be acquired in schools and through life experiences. The cognitive assessment is
supplemented with a questionnaire that collects a wide variety of background
information, including demographic, social, educational and economic variables.
In each country, a representative sample of adults aged 16–65 is interviewed at
home. The standard survey mode is to answer questions on a computer, but a
pencil-and-paper interview option also exists for respondents who are not com-
puter-literate.6 The countries use dierent sampling schemes in selecting their
samples, but the samples are all aligned to known population counts with post-
sampling weightings. I employ these weights in all calculations, giving the same
weight to each country in the pooled international sample.
The PIAAC measures the cognitive skills of the survey participants in three
domains: numeracy, literacy and problem-solving in technology-rich environ-
ments. However, the assessment of problem-solving skills is not carried out in
all countries and among all survey participants in a country. The PIAAC denes
literacy as “understanding, evaluating, using and engaging with written texts to
3 See Perry and Rammstedt (2016) and the OECD (2016) technical report for further informa-
tion on the PIAAC.
4 Australia is not included as its public-use le is not directly accessible over the OECD
website.
5 Other studies (e.g. Hanushek et al., 2015) do not use the data for the Russian Federation
given that, among other things, any statistics are potentially biased by the omission of the capital
region.
6 In Indonesia, the assessment was carried out exclusively using the pencil-and-paper option
due to low computer literacy among the target population.

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