GrowingUnitedUpgrading Europe’s Convergence Machine

#EUGrowingUnited

Europe: the ConvergenceMachine

2

The EU: A globally unrivalled convergence machine

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35% to 58%:

Change in Romania’s GDP per capita relative to the EU average between 2005 and 2016BG

CZ

EE

HR

HU

LT

LV

PL

RO

SI

SK

30

40

50

60

70

80

90

100

30 40 50 60 70 80 90 100

GD

P p

er

ca

pita

re

lativ

e t

o t

he

EU

av

era

ge

(10

0),

Ce

ntr

al a

nd

So

uth

ea

st E

uro

pe

, 2

01

6

GDP per capita relative to the EU average (100), Central

and Southeast Europe, 2005

Productivity growth has stalled in Southern Europe

Low-income Europeans are being left behind

4

3 signs of growing divides

0 growth in GDP per capita

among lagging regions in

Southern Europe, 2000-15

28% increase in regional

inequality in GDP per capita

within Central and Southern

Europe

Growing regional divides

-7%

15%

25%

66%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

Poorest

10%

Poorest

40%

Middle

50-90%

Richest

10%

Growth of earnings, 1980s-2010s

-5%

0%

5%

10%

15%

20%

25%

Northern and

Continental

Europe

Southern

Europe

Central and

Southeast

Europe

Total Factor Productivity Growth,

2000-16

Accelerating technological change is generating growing divergence

5

Technological change is making jobs more intensive in non-routine cognitive tasks

6

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.21998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

EU 15

Non-routine cognitive analitycal Non-routine cognitive personal Routine Cognitive

Non-routine manual personal Routine manual

So

urc

e: G

ork

ae

t al. (2

01

7), c

om

missio

ne

d fo

r this re

po

rt.

Occupation-specific task intensities, aggregated for each country and standardized over time, regional averages, 1998-2014

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Romania

High-skill workers are gaining, low-skill workers are losing

7

Source: Gorka et al. (2017), commissioned for this report. Note: Jobs are classified by their most intensive task into non-routine cognitive, routine cognitive, and manual.

-10

-8

-6

-4

-2

0

2

4

6

8

Southern

Europe

Continental

Europe

Northern

Europe

CEE South CEE

Continental

CEE North

Percentage point changes in share of workers in each job type,

1998-2014

Non-routine cognitive Routine cognitive Manual

Boosting opportunities for people and firms to make tech change work for all

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Technological change: good where opportunities for people and firm are high, disruptive where they are low

9

60

65

70

75

80

85

90

35 40 45 50 55 60 65 70 75

Op

po

rtu

nitie

s fo

r firm

s

Opportunities for people

high growth potentiallow inclusion potential

high inclusive growth potential

low growth potentiallow inclusion potential

low growth potentialhigh inclusion potential

Technological change: good where opportunities for people and firm are high, disruptive where they are low

10

AT

BEBG

CZ

DE

DK

EE

EL

ES

FI

FR

HU

IE

IT

LT

LU

LV

MT

NL

PLPT

RO

SE

SISK

UK

HR

60

65

70

75

80

85

90

35 40 45 50 55 60 65 70 75

Op

po

rtu

nitie

s fo

r firm

s

Opportunities for people

high growth potentiallow inclusion potential

high inclusive growth potential

low growth potentiallow inclusion potential

low growth potentialhigh inclusion potential

EU average

EU average

High

opportunity

places: High

share of high-

skill workers and

frontier firms

Low opportunity

places: High

share of low-skill

workers and

lagging firms

Source: Own

calculations based on PISA and Doing Business data. Note: Cross-lines are EU average. OP is measured by share of

15 year-olds above proficiency in PISA reading in 2015, corrected for inequality of opportunities (variation in PISA scores

explain by socio-economic status of students) and the proportion of young people that leave school with at most lower secondary. OF is measures by the 2017 Doing Business distance to frontier index.

Opportunities also vary between regions: e.g. Spain

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Andalucia

Aragon

Asturias

Baleares

Canarias CantabriaCastilla la

Mancha Castilla y Leon

CatalunyaValencia

Extremadura

Galicia

La RiojaMadrid

Murcia

Pais Vasco

60

65

70

75

45 50 55 60 65 70 75

Op

po

rtu

nitie

s fo

r firm

s

Opportunities for people

high growth potentiallow inclusion potential

high inclusive growth potential

low growth potentiallow inclusion potential

low growth potentialhigh inclusion potential

Source: Own calculations based on PISA and Doing Business subnational data.Note: Cross-lines are Spain average

Top 25% global

performer on

construction permits: La Rioja (Galicia among the bottom 25%)

90% of students in

Castilla y Leon have basic competency in math (69% in Extremadura)

Opportunities for people and firms vary across EU countries and regions

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Europe’s significant foundational skills gap…

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Source: World Bank staff calculations based on PISA 2015

0

10

20

30

40

50

60

70

80

EE DK FI IE SI NL PL DE SE BE LV CZ UK AT ES IT EU FR PT LT LU SK HU MT HR EL RO BG

Share of low performers by socio-economic status, PISA 2015

mathematics

All students

…is largely an equity story for individuals…

14

Source: World Bank staff calculations based on PISA 2015

0

10

20

30

40

50

60

70

80

EE DK FI IE SI NL PL DE SE BE LV CZ UK AT ES IT EU FR PT LT LU SK HU MT HR EL RO BG

Share of low performers by socio-economic status, PISA 2015

mathematics

All students Students in bottom ESCS quintile

…and regions (eg Italy)

15

400

420

440

460

480

500

520

540

Ca

lab

ria

Bu

lga

ria

Sic

ilia

Sa

rde

gn

a

Ca

mp

an

ia

Ba

silic

ata

Mo

lise

Ab

ruzz

o

Lazi

o

Tosc

an

a

Ita

ly

Lig

uria

Um

bria

Pu

glia

OEC

D

Ma

rch

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Bo

lza

no

Em

ilia

Ro

ma

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a

Va

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Ao

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Fiu

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en

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iulia

Lom

ba

rdia

Tre

nto

Ve

ne

to

Fin

lan

d

PISA 2012 reading scores by Italian regions and select other countries

Labor market policy very limited and mostly passive

16

0

0.5

1

1.5

2

2.5

3

3.5

DK FR FI NL ES BE AT IE SE IT PT DE LU HU CY HR SI EL PL EE CZ BG LV LT SK RO

Sh

are

of

GD

P

LMP expenditure (2015)

Active Passive Total

Source: World Bank staff calculations based on Eurostat. Note: Active includes training, employment incentives, supported employment and rehabilitation, direct job creation and start-up incentives. Passive includes income support and early retirement. Total also includes labor market services.

Romania can improve its business environment…

18.05.2018 Sample footer text 17

60

65

70

75

80

85

90

DK FI IE SE UK AT BE DE FR LU NL CY EL ES IT MT PT EE LT LV CZ HU PL SI SK BG RO

EU17 North EU17 Continental EU17 South CEE North CEE Continental CEE

South

Doing Business Distance to Frontier (2017)

Source: Doing Business and World Economic Forum. Note: Doing Business Indicators measure distance to best performer in Doing

Business (best performer = 100).

…which varies significantly between regions

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Starting a Business

Dealing with construction

permits

Getting electricity

Registering property

Enforcing contracts

City DTF Rank DTF Rank DTF Rank DTF Rank DTF Rank

Brasov 88.8 9 56.3 17 49.6 19 74.7 9 65.5 22 Bucharest 89.5 5 58.1 15 53.2 15 74.7 9 66.4 18 Cluj Napoca 88.8 9 54.3 20 50.4 18 73.8 16 64.1 14 Constanta 87.5 17 49.3 21 49.0 20 74.7 9 62.0 8 Craiova 86.3 22 61.3 14 53.0 16 74.7 9 68.0 13 Iasi 88.3 12 56.0 18 57.8 11 74.7 9 65.3 16 Oradea 89.5 5 57.8 16 50.8 17 75.5 8 66.7 19 Ploiesti 89.5 5 54.4 19 47.2 21 74.6 15 64.5 21 Timisoara 89.5 5 48.9 22 43.6 22 74.7 9 61.8 5

Source: World Bank (2017), drawing on the Doing Business database. Note: The distance to frontier (DTF) score shows how far a location is from the best performance achieved by any economy on each Doing Business indicator. The score is normalized to range from 0 to 100, with 100 representing the frontier of best practices (the higher the score, the better). Rank represents the rank of Romanian cities across a sample of Bulgarian, Hungarian and Romanian cities.

Subnational Doing Business scores for Romania 2017

Romania can also enhance its innovation environment

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Source: Eurostat and 2014 Community Innovation Survey. Notes: Percentage of innovating firms is measured on the right axis. A firm is innovating if it has implemented a new/significantly improved product, process, new marketing method, new organizational method in business practices, workplace organization or external relations.

0

10

20

30

40

50

60

70

80

0.0

0.5

1.0

1.5

2.0

2.5

DK IE FI SE UK BE DE FR LU NL AT EL ES IT CYMT PT EE LV LT CZ HR HU PL SI SK BGRO

Northern

Europe

Continental

Europe

Southern Europe CEE

North

CEE Continental CEE

South

Inn

ov

atin

g f

irm

s (%

)

Bu

sin

ess

R&

D (

% o

f G

DP

)

Business R&D (% GDP) Innovating firms (%)

Convergence machine 2.0: Toward convergence of opportunities

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Equalizing opportunities for people & firms goes together

• People• Universal foundational cognitive skills?

• Education equity (households and regions): a rethink?

• Enhancing social protection for those left behind?

• Firms• Business environment: regulations and implementation?

• Connective infrastructure in lagging regions?

• Boosting firm innovation and technology adoption?

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Convergence machine 2.0 is a shared responsibility

• Upgrade of policy at regional, national and EU level: Most policy levers are national and regional.

• Convergence Machine 2.0 need not mean new centralization of powers to the EU level, but fully exploiting its key instruments and the benefits of being a union of many countries.

• Global Europe: look out for ideas and solutions around the world.

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Download the report from

www.worldbank.org/eca/growingunited

#EUGrowingUnited