western balkans labor market trends 2017 - jvi...western balkans labor market trends 2018 report a...

wiiwThe Vienna Institute

for International Economic Studies

Western BalkansLabor Market Trends 2018

Hermine Vidovic, wiiwIsilda Mara, wiiwStefanie Brodmann, World Bank



Motivation

• Provide comparable labor market data for the Western Balkans for national policy makers in the region, national and international institutions/ organisations and the academic community

• produce an annual report on labour market trends in the Western Balkans

• create a repository for high-quality research on labour market issues in the region

Outline

• Western Balkan Labor Market Trends 2018 Report

• SEE Jobs Gateway Database

Western Balkans Labor Market Trends 2018

REPORT

A summary of labor market trends in the Western Balkans and four peer countries (Austria, Bulgaria, Croatia, Hungary) between 2016 Q2 and 2017 Q2

Part I• Population (activity)• Employment • Focus on

- atypical forms of employment- informal sector employment

• Unemployment- NEETs

Part II• Special topic: Improving data on labor mobility in the Western Balkans

Statistical annex

Shrinking working-age population in most Western Balkan countries

Source: SEE Jobs Gateway Database, based on data provided by national statistical offices and Eurostat.

Working-age population (15–64 years), 2016 Q2–2017 Q2, change in %

-6

-5

-4

-3

-2

-1

0

1

2

WB-6 AL BA ME MK RS XK AT BG HR HU

Continued increase in activity rates – but female rates are (very) low compared to peer countries


Activity rates (15–64 years), in %

Total Gender

30

40

50

60

70

80

2010 2011 2012 2013 2014 2015 2016 2017

WB-6 AL BA ME

MK RS XK AT

BG HR HU

0

10

20

30

40

50

60

70

80

90

WB

-6 AL

BA

ME

MK RS

XK

AT

BG

HR

HU

male female

Gender differences in labor market outcomes

• Traditional roles assigned to women, such as care takingresponsibilities (children and older family members)

• Religious and cultural reasons

• Labor taxation and social benefit systems, due to

potential disincentive effects for those seeking

employment (Koettl, 2012)

• Reliance on remittances

ample amount of human potential unused

Inactivity

• Gender: Primarily a phenomenon of women

• Age: Lack of participation is most acute among the youngpeople (2015: total - 71%; women – 78%, men – 64%)

• Education: more likely for the low educated

• Explanations– Lower growth as for example in the EU-CEE– Early retirement– Rising enrolment rates in universities – young people

longer in eduation– Labour taxation, social benefits, remittances

Employment growth highest for females and the highly educated

Note: BA: no employment data by age groups above 24 years.


Employment growth, 2016 Q2–2017 Q2, in %Gender Age Education

Total Male Female 15–24 25–54 55–64 Low Medium High

Albania 3.4 5.6 0.8 13.4 3.0 1.4 2.4 1.2 10.8

Bosnia and Herzegovina 1.9 -0.9 6.8 17.2 . . 5.7 2.5 -4.1

Kosovo 9.2 11.0 2.8 18.2 5.7 18.7 3.5 9.4 13.1

Montenegro 3.5 4.8 1.9 4.9 1.9 9.5 20.1 3.2 -1.0

FYR Macedonia 2.7 1.4 4.7 13.2 3.2 0.1 -6.0 3.9 6.5

Serbia 4.3 2.9 6.2 3.0 2.9 8.9 1.2 4.9 5.4

Western Balkans 3.9 3.3 4.7 9.8 . . 1.8 4.1 5.4

Austria 1.2 1.1 1.3 -1.3 0.8 6.5 -2.2 0.1 4.2

Bulgaria 4.5 4.5 4.5 5.1 3.6 5.7 8.8 4.5 3.0

Croatia 1.7 3.4 -0.2 7.2 1.3 2.4 -18.5 5.2 1.4

Hungary 1.8 2.5 0.9 3.0 1.6 0.6 1.2 1.5 2.6

High share of self-employment signaling large informal sector

Note: Data for 2017 refer to the first two quarters. Data for BA refer to the working-age population 15+.


Self-employment, share in total employment (15–64 years), in %

0

5

10

15

20

25

30

35

40

45

2010 2011 2012 2013 2014 2015 2016 2017

WB-6 AL BA MEMK RS XKAT BG HR HU

0

5

10

15

20

25

30

35

40

45

WB

-6 AL

BA

ME

MK RS

XK

AT

BG

HR

HU

male female

Total Gender

Temporary employment highest among young people

Note: Data for 2017 refer to the first two quarters. Data are not available for Bosnia and Herzegovina.


Temporary employees, share in total employees (15–64 years), in %

0

10

20

30

40

50

60

70

80

90

AL ME MK RS XK AT BG HR HU

total (15-64) young (15-24)

0

10

20

30

40

50

60

70

80

90

2010 2011 2012 2013 2014 2015 2016 2017

AL ME MK

RS XK AT

BG HR HU

15-64 years

Part-time employment less common in the Western Balkans than in EU countries

Note: Data for 2017 refer to the first two quarters. Data for Bosnia and Herzegovina refer to the population aged 15+.


Part-time employment, share in total employment (15–64 years), in %

0

10

20

30

40

50

2010 2011 2012 2013 2014 2015 2016 2017

WB-6 AL BA MEMK RS XKAT BG HR HU

0

10

20

30

40

50

WB

-6 AL

BA

ME

MK RS

XK

AT

BG

HR

HU

male female

Total Gender 2017 Q2

Despite declining, informal sector employment remains at high levels

Source: SEE Jobs Gateway Database, based on data provided by national statistical offices and Eurostat. For BA, ME Krstic and Gashi (2016), for XK Cojocaru (2017).

Share of informal employment in total employment, in %

0

10

20

30

40

50

60

2014Q1 2015Q1 2016Q1 2017Q1

Albania FYR Macedonia Serbia

0

5

10

15

20

25

30

35

40

AL BA ME MK RS XK

20162014 Q1 – 2017 Q2

Self-employed in unregistered businesses now represent the majority of informal sector employment


Structure of informal employment by individual categories, in 1000 persons

Wage workers without contract Unpaid family workers Self-employed

0

25

50

75

100

125

150

2010 2011 2012 2013 2014 2015 2016

FYR Macedonia

0

100

200

300

400

500

600

2010 2011 2012 2013 2014 2015 2016

Serbia

Informal employment – characteristics

• Men are more likely to work in the informal sector than women; the only exception being Serbia

• Young people (young men in particular) account for the highest share of informal employment in Albania, FYR Macedonia and Serbia

• Low-educated constitute the majority of informal workers in Albania and FYR Macedonia, and medium-educated that in Serbia

• About two thirds of informal work is concentrated in agriculture in FYR Macedonia and Serbia (the only countries providing detailed data)

Unemployment decreasing in most countries, but levels remain high


Unemployment rates, in %

Total

Unemployment rates fell faster than average (2016 Q2 -2017 Q2) for- females - young people (15-24 years)- Low- and medium-educated

Unemployment rates in WB-6 in 2017 Q2were - equal for men and women- double the overall rate for the young- highest for the medium-educated

0

5

10

15

20

25

30

35

40

2010 2011 2012 2013 2014 2015 2016 2017

WB-6 AL BA ME

MK RS XK AT

BG HR HU

Despite declining, long-term unemployment remains a major concern for the Western Balkans


Long-term unemployment rate, in %

0

5

10

15

20

25

30

WB

-6 AL

BA

ME

MK RS

XK

AT

HU

Total Low (levels 0-2)

Medium (levels 3-4) High (levels 5-8)

0

5

10

15

20

25

30

201

3 Q

4

20

14 Q

2

20

14 Q

4

20

15 Q

2

201

5 Q

4

20

16 Q

2

20

16 Q

4

20

17 Q

2

AL ME MK RS XK

AT BG HR HU

percentage of labor force (15+ years) Educational attainment, 2016

Probability of young people becoming a NEET (neither in employment nor in education or training) is high

.


NEET rates (15–24 years), in % of the respective population

0

5

10

15

20

25

30

35

40

2010 2011 2012 2013 2014 2015 2016

WB-6 AL BA ME

MK RS XK

AT BG HR HU

0

5

10

15

20

25

30

35

40

AL BA ME MK RS XK AT BG HR HU

male female

Gender (2016)Total

Western Balkan countries EU peer countries

Wage levels differ within the region and in comparison to the peer countries

Note: Wage data refer to register-based survey data for the Western Balkans and peer countries, except Austria and EU-28 which are based on gross wages of National Accounts. Albania: methodological break 2013/2014.Source: SEE Jobs Gateway Database, based on data provided by national statistical offices and Eurostat, own calculations.

Average monthly gross wages, Austria=100 (PPP EUR based)

20

30

40

50

60

70

2010 2011 2012 2013 2014 2015 2016

AL BA ME

MK RS XK

20

30

40

50

60

70

2010 2011 2012 2013 2014 2015 2016

BG HR HU

Main findings

• 231,000 jobs created between 2016 Q2 and 2017 Q2, largest share due to increasing self-employment

• Unemployment decreased by 169,000 (from 18.6 to 16.2 percent of the labor force), reaching historical lows in some countries

• Activity remains low especially among women; long-term unemployment is high and persistent

• Youth unemployment fell faster than overall unemployment, but remained high compared to EU countries; NEETs account for almost one quarter

• Improvements in the labor market were not sufficient to prevent young, educated people from continuing to emigrate

• Emigration from WB-6 in figures

• Main implications

• Data and knowledge gap

• Future direction for research and policy intervention

Special topic: Improving data on labor mobility in the Western Balkans

Emigration from the WB-6 in figures

Emigration share in resident population, 1990-2017

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

1990 2000 2010 2017

Albania Bosnia and Herzegovina

FYR Macedonia Montenegro

Serbia*

Note: * 1990–2000 including Kosovo.Source: UN Statistics (2018).

Note: The stock of migrants as a share of resident population does not include intra-regional migration in the Western Balkans. Source: Stocks of migrants and resident population: UN Statistics (2018).

Stock of emigrants from the Western Balkan region, million persons, 1990–2017

0%

10%

20%

30%

40%

50%

Albania Bosnia andHerzegovina

FYRMacedonia

Montenegro Serbia*

1990 2000

2010 2017

AL BA MK ME RS*

ALMKRS*

BAME

Source: UN Statistics (2017).

Main destination countries for Western Balkan emigrants, share in %, 2015

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Albania Bosnia &Herzegovina

Kosovo FYR Macedonia Montenegro Serbia Total

EU-15 USA Intra-region Canada Asia (Turkey) Australia Other CEE Switzerland

Emigration and demography nexus

0 500 1000 1500 2000

0-45-9

10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+ Population (thousands) 2030

Population (thousands) 2015

Population (thousands) 1990

0 100 200 300

0-4

5 to 9

10 to 14

15 to 19

20 to 24

25 to 29

30 to 34

35 to 39

40 to 44

45 to 49

50 to 54

55 to 59

60 to 64

65 to 69

70 to 74

75 to 79

80 to 84

85+

Source: Eurostat (2017) and United Nations, Department of Economic and Social Affairs, Population Division (2017). World Population Prospects: The 2017 Revision.

Age structure of WB-6 emigrantsto EU-28 & EFTA, 2015, in thousands

Age structure of WB-6 population 1990-2015-2030

Emigration and labor market nexus

Source: DIOC Database 2010-2011.

0%10%20%30%40%50%60%70%80%90%

100%

Me

n

Wo

men

Me

n

Wo

men

Me

n

Wo

men

Me

n

Wo

men

Me

n

Wo

men

Me

n

Wo

men

Me

n

Wo

men

Albania BiHFYR MacedoniaKosovoMontenegroSerbia Total

Employed Unemployed

Inactive NA

0%

20%

40%

60%

80%

100%

Albania Bosnia andHerzegovina

FYR Macedonia Kosovo Montenegro Serbia

NAHigh skill occupation (ISCO: 1-3)Medium skill occupation (ISCO:4-8)Low skill occupation (ISCO:9)

Employed emigrants by occupational skill level, share in %, 2011

Labor force status of emigrants in the OECD countries, share in %, 2011

AL BA MK XK ME RS

AL BA MK XK ME RS Total

Emigration and development nexus

Note: Real GDP per capita in US dollar at 2011 prices.

Source: Maddison Project Database (2018).

GDP per capita, Western Balkan countries versus other countries, 1990–2016, in thousand US dollar

0

5

10

15

20

25

30

35

40

45

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

Albania Bosnia and Herzegovina FYR of MacedoniaMontenegro Serbia EU-CEEEU-15

• Large gap in income levels still a strong pull factor

• Youth unemployment is a strong push factor for migration

• High level of emigration among highly educated – loss of human capital

• Employment of emigrants below their skill level:

– brain waste

– signal of mismatch between skills acquired at home and those in demand

• Brain gain in the form of return migration and transfer of know-how has been less tangible in the region

• High level of remittances, but channeling into investment – with the goal of generating employment – remains of low significance

Main implications

Main data challenges and gaps

• Recording: different rules for registration on arrival and deregistration on departure

• Reaching of target group: from the perspective of origin, emigrants not directly or easily reachable

• Measurement is a complex task due to the many dimensions of labor migration and the target groups involved

• Internationally agreed definition of “migrant worker” is not available

– Duration of stay – intended or actual – is critical in measuring the scale and type of migration, e.g. permanent or temporary

– Motivation for leaving the country of origin is different from the motivation for moving to a particular destination country

– Residence permit registration statistics are too narrow for capturing the variety of migration reasons, different forms of short-term migration, e.g. circular, seasonal.

• There is a lack of consistent statistics on work experience prior to and during the migration, on the recognition of qualifications, and on the acquisition of new skills

• Limitation of resources: infrastructure, financial, and human resources

• Institutional setting surrounding the collection of migration statistics is work in progress

• Adjusting and harmonizing indicators to meet international standards, so that a wider spectrum of push and pull factors can be measured, is of utmost importance for the study of migration

• Increasing the reliability and quality of data in line with international standards on workforce composition at home and on migrants living abroad is necessary for accurate analysis of labor market dynamics

• A special module on labor migration measurement within existing household labor force surveys in the countries of origin could help tackle challenges associated with the comparability of data at a regional and international level

How to address data gaps

• Migration from the region has not lost momentum, potential for leaving is high

• Governments have largely taken a passive approach in the past, but it is time to step in.

• The potential for highly educated migrants to return, knowledge transfer, involvement of the diaspora should be a top priority in the policy agenda

• Maximizing gains but also minimizing losses from massive emigration requires

– a bottom-up approach – building a bridge of communication with migrants

– a top-down approach: e.g. sound empirical data and knowledge on the relationship between emigration and its impact

– explore new venues, initiatives and programs, offer incentives and consultancy for guiding the diaspora/migrants to become more involved in investment and funding activities at home

Policy response and steps forward

Example: direction for future research and policy

Source: World Bank Open Data (2018).

0

5

10

15

20

25

30

Av.

20

05

-20

10

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11

-20

16

Av.

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ALB BIH XKX MKD MNE SRB

Remittances (% of GDP)

FDI, net inflows (% of GDP)

0

5

10

15

20

25

30

Av.

20

05

-20

10

Av.

20

11

-20

16

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20

05

-20

10

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20

11

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16

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05

-20

10

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16

BGR HRV MDA POL ROU WLD

Remittances (% of GDP)

FDI, net inflows (% of GDP)

• Massive emigration generates high inflow of remittances• Remittances inflows are much higher than FDI inflows in most

of the WB-6• High-skilled migration has contributed to a higher inflow of FDI• Channeling remittances, more into sectors that generate

employment, but also high-quality jobs, would be more beneficial than simply smoothing consumption

Remittances vs. FDI, peer countries2005-2010, 2011-2016, average

Remittances vs. FDI, WB-6 2005-2010, 2011-2016, average

AL BA XK MK ME RS BG HR MD PL RO World

SEE Jobs Gateway Database – Content

• Key economic indicators: GDP, CPI

• Labor market

Population, activity, employment, unemployment, inactivity

Informal employment

Non-standard forms of employment (temporary, part-time, self-employment)

Long-term unemployment

Youth not in employment, education, or training (NEET)

• Labor market – sub-national data

Population, activity, employment, unemployment, inactivity

• Earnings and unit labor costs

Average monthly gross wages, monthly gross minimum wages

Unit labor costs

SEE Jobs Gateway Database – Content

• Basis for labor market data: Labor Force surveys

• Countries covered:

6 Western Balkans: Albania, Bosnia and Herzegovina, FYR Macedonia, Kosovo, Montenegro, Serbia

Western Balkans-6: Aggregate 6 countries (only if data are available for countries)

4 EU peer countries: Austria, Bulgaria, Croatia, Hungary

• Availability:

Annual and quarterly data – 2010 to 2017 (Q2)

About 19350 time series

• Excellent support from the Statistical Offices of the region

• Available at https://www.seejobsgateway.net

https://www.seejobsgateway.net/



SEEJobsGateway.worldbank.org

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