Equality and cohesion

• Author: Lukas Borunsky
• Pages: 199-254

CHAPTER 4

INNOVATION,

THE FUTURE

OF WORK AND

INEQUALITY

KEY FIGURES

11.1 %

adult participation

in learning

73 %

of platform workers

are men

133 million

new work roles may

emerge worldwide

until 2022

1 in 5

jobs created in 2017

were part-time

200

What can we learn?

 Digitalisation, automation, and robotisation

risk creating job displacement and further

shrinking the labour share of income,

which could have consequences for inequality,

particularly income inequality and inequality

in opportunities.

 Changing skills demand may lead to high

job polarisation in the labour market and is

hollowing out the middle-skilled jobs.

 Even if technologies and business models

may produce a suf‌f‌icient number of new

jobs to keep unemployment low, they may

contribute to a decline in overall job

quality and employment standards.

 While there is a lack of evidence on massive

disruption across sectors, technological

transformation will not be friction free and

individuals or whole sectors need to capitalise

on the benef‌its of new technologies in the

workplace.

 The emergence of digital technologies does

not help to close the gender gap, as

observed by the lower participation of women

in ICT-related f‌ields and platform work.

What does it mean for policy?

 With very limited growth in the share

of adults participating in education and

training, it is important to increase adult

participation in learning, in particular for

those in most need of access to learning.

 Improved skills intelligence, labour-

market relevant skills provision,

transparency and recognition of all

types of skills remain a challenge. Increased

synergies among programmes such as

Horizon Europe, the European Social Fund

(ESF) and Erasmus+ could address these

challenges at dif‌ferent stages. Furthermore,

policymakers need better intelligence to

act (shorter forecasts, scenario planning

and simulations in forecasting models) and

policy design that allows for a quick

response.

 Uptake of new technologies and industries

has not helped reduce gender gaps; policies

to support the participation of women

in specialised ICT-related positions

should be maintained and where possible

reinforced to make further progress.

201

CHAPTER 4

1. Rise in inequality and its perception related to

technological developments

1 Globalisation, demographic developments and household composition rank among other factors.

Inequality has been growing in most advanced

economies in recent years, as indicated by the

Gini coef‌f‌icient of market income inequality

(Figure 4.1-1). The index shows that inequality in

market income has grown with the EU currently

facing similar levels of market income inequality as

in the United States. Nevertheless, Europe remains

a more equal place to live compared to other

countries because the national tax and welfare

systems reduce the relatively high market income

inequality. Although a substantial mitigation of

a general rise in income inequality can be observed

in Europe, there are certain age groups or places

of residence that face increased income inequality

(OECD, 2019). Furthermore, phenomena such as

youth unemployment and inequality of opportunity

can have long-lasting ef‌fects on young people in

many European regions.

While f‌iscal policy has a direct impact

on disposable income (i.e. aer taxes and

social benef‌its), other policies enhancing

productivity and real wages, or upgrading

skills and providing equal opportunities can

be equally important. Technological change

ranks among the most important factors1

af‌fecting income distribution as an increase

in the demand for high-skilled employees

leads to increases in their wage premiums and

amplif‌ies wage dispersion (EC, 2017).

Figure 4.1-1 Gini index of inequality - household market income

(pre-tax, pre-transfer), 1995-2016

Gini index of inequality

Japan

South Korea

United States

EU(1)

China

30

35

40

45

50

55

1

995

1

996

1

997

1

998

1

999

2

000

2

001

2

002

2

003

2

004

2

005

2

006

2

007

2

008

2

009

2

010

2

011

2

012

2

013

2

014

2

015

2

016

Science, research and innovation performance of the EU 2020

Source: DG Research and Innovation, Chief Economist - R&I Strategy & Foresight Unit based on Eurostat data

Note: (1)EU is the weighted average of the values for the EU Member States.

Stat. link: https://ec.europa.eu/info/sites/info/f‌iles/srip/2020/parti/chapter41/f‌igure-41-1.xlsx