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

• Author: Damir STIJEPIC
• DOI: http://doi.org/10.1111/ilr.12162
• Published date: 01 September 2020
• Date: 01 September 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.