Updated the 5th of March 2019

Regional gap in GDP per capita, 2000-16 Index of regional disparity in GDP per capita, 2016

The gap in GDP per capita between the richest (Vilnius) and the poorest (Taurage) Lithuanian regions has been slightly increasing since 2011, with GDP per capita in Taurage county being equivalent to 39% GDP per capita in Vilnius in 2015. Lithuania remains close to the OECD median country in terms of regional economic disparities.

With a productivity growth of 2.5% per year between 2000 and 2015, Utena has fallen further behind Vilnius, with the latter region experiencing a productivity growth of 4.3% per year over the same period.

Unemployment rates are above the OECD average in all Lithuanian regions, except Vilnius and Kaunas with rates of 4.8% and 5.6% in 2017, respectively. Unemployment varies widely across Lithuanian regions. Utena is the region with the highest unemployment rate in Lithuania, ten percentage points higher than in Vilnius.

Productivity trends, most and least dynamic regions, 2000-16 Unemployment rate, 15 years old or more, 2007-17

Source: OECD Regional Database. Notes: (1) Figure on regional gap in GDP per capita: OECD regions refer to the administrative tier of subnational government; Lithuania is composed of nine small regions. (2) Figure on index of regional disparity: top (bottom) 20% regions are defined as those with the highest (lowest) GDP per capita until the equivalent of 20% of national population is reached, this indicator provides a harmonised measure to rank OECD countries, using data for small regions (Territorial Level 3) when available. (3) Productivity is measured as GDP per employee at place of work in constant prices, constant Purchasing Power Parities (reference year 2010).

0

5 000

10 000

15 000

20 000

25 000

30 000

35 000

40 000

2000 2005 2010 2015

GDP per capita in USD PPP

Low est region

Taurage

Highest region

Vilnius

14 437 USD

37 422 USD

25 184 USD

Lithuania

1

2

3

4

Top 20 % richest over bottom 20% poorest regionsRatio

Country (number of regions considered)

Small regions(TL3)

Large regions (TL2)

2016 2000

Lithuania

20 000

30 000

40 000

50 000

60 000

70 000

80 000

2000 2005 2010 2015

GDP per worker in USD PPP

Utena: low est

productiv ity grow th

(+2.5% annually )

Vilnius: highest

productiv ity in 2016

(+4.3% av erage annual

grow th ov er 2000-16)

OECD

0

5

10

15

20

25

2007 2012 2017

rate (% )

Lowest rateVilnius

Highest rateUtena

4.8%

14.9%

7.1%

Lithuania

Regions and Cities at a Glance 2018 – LITHUANIA http://www.oecd.org/regional

Economic trends in regions

Updated the 5th of March 2019

Relative ranking of the regions with the best and worst outcomes in the 11 well-being dimensions, with respect to all 402 OECD regions. The eleven dimensions are ordered by decreasing regional disparities in the country. Each well-being dimension is measured by the indicators in the table below.

All regions of Lithuania are among the top 30% of OECD regions in terms of education (labour force with at least upper secondary education), although all regions are in the bottom 10% in terms of health (life expectancy and mortality rate). Large disparities are found in outcomes related to jobs (employment and unemployment rates) with Klaipeda in the top 30% of OECD regions and Alytus in the bottom 20%.

The high performing Lithuanian regions fare better than the OECD median region in employment rate as well as in labour force education.

Source: OECD Regional Database. Visualisation: https://www.oecdregionalwellbeing.org. Notes: (1) OECD regions refer to the first administrative tier of subnational government; Lithuania is composed of nine small regions. (2) Household income per capita data are based on USD constant PPP, constant prices (year 2010).

Klaipeda

Kaunas

Utena

Alytus

Kaunas

Vilnius

KlaipedaAlytus

Taurage

Alytus

TelšiaiUtena

Marijampole Utena

Jobs Education Environment Civic Engagement

Access to services

Safety Health

Ran

kin

g o

f OE

CD

re

gio

ns

(1 to

40

2)

top

20

%b

otto

m 2

0%

mid

dle

60

%

Vilnius CountyTop region Bottom region

Top 20% Bottom 20%

Jobs

Employment rate 15 to 64 years old (%), 2017 70.2 67.7 72.1 61.0

Unemployment rate 15 to 64 years old (%), 2017 7.3 5.5 6.7 14.2

Education

Labour force with at least upper secondary education (%), 2017 95.7 81.7 96.8 90.9

Environment

Level of air pollution in PM 2.5 (µg/m³), 2015 13.3 12.4 12.7 15.8

Civic engagement

Voters in last national election (%), 2017 or lastest year 47.9 70.9 52.2 41.0

Access to services

Households with broadband access (%), 2017 75.0 78.0 75.0 61.5

Safety

Homicide Rate (per 100 000 people), 2016 5.2 1.4 4.3 7.8

Health

Life Expectancy at birth (years), 2016 74.9 80.4 75.3 73.6

Age adjusted mortality rate (per 1 000 people), 2016 11.3 8.1 11.1 11.9

Income

Disposable income per capita (in USD PPP), 2016 13 889 17 695 .. ..

Housing

Rooms per person, 2016 .. 1.8 .. ..

Community

Perceived social network support (%), 2013 .. 91.4 .. ..

Life Satisfaction

Life satisfaction (scale from 0 to 10), 2013 .. 6.8 .. ..

Lithuanian regionsCountry

Average

OECD median

region

Differences in well-being across regions

Updated the 5th of March 2019

OECD population is concentrated in cities* Percentage of population in cities, 2016

Source: OECD Metropolitan Database. Number of cities: 6 in Lithuania compared to 1 138 within the OECD.

In Lithuania, 51% of the population lives in cities of more than 50 000 inhabitants. The share of population in cities with more than 500 000 people is 23% compared to 55% in the OECD area.

Importance of metropolitan areas Cities above 500 000 people, 2016

Contribution of metropolitan areas to GDP growth Cities above 500 000 people, 2000-16

The Metropolitan area of Vilnius (city above 500 000 inhabitants) accounts for 35% of national GDP and 26% of employment. Between 2000 and 2016 it generated for 39% of the national GDP growth.

In terms of GDP per capita, Vilnius is close to the median of the 327 OECD metropolitan areas. Air pollution in Vilnius is among the third of the metropolitan areas most polluted across the OECD.

OECD Metropolitan areas ranking Cities above 500 000 people

GDP per capita, 2016

Air pollution (PM2.5), 2017

Source: OECD Metropolitan Database. Number of metropolitan areas with a population of over 500 000: 1 in Lithuania compared to 327 in the OECD.

* Note: Cities are defined here as functional urban areas, which are composed by high-density urban centres of at least 50,000 people and their areas of influence (commuting zone). For more information, see: http://www.oecd.org/cfe/regional-policy/functionalurbanareasbycountry.htm.

23%

13%

15%

49%

United States

people in citieswith population above 500 000

peopleoutside cities

United States

people in cities withpopulation between50 000 and 250 000

2.9 million people - 51% live in cities

United StatesLithuania

people in cities with population between 250 000 and 500 000

OECD average

1.2 billion people - 70%live in cities

people in citieswith population

above 500 000

people in cities withpopulation between

50 000 and 250 000

peopleoutside cities

55%

9%

30%

people in cities with populationbetween 250 000 and 500 000

6%

35%26% 23%

63%58% 55%

0

10

20

30

40

50

60

70

80

90

% of nationalGDP

% of nationalemployment

% of nationalpopulation

Lithuania OECD average%

39%

68%V

ilniu

s

0

10

20

30

40

50

60

70

80

90

1 2

%

All metropolitan areas Largest contributor

Lithuania OECD average

32

7 m

etr

op

olit

an

are

as

0

20 000

40 000

60 000

80 000

100 000USD PPP

Top 20% richest metropolitan areas

Bottom 20% poorest metropolitan areas

0

10

20

30

Lev el of air pollution in PM 2.5 (µg/m³)

Top 20% least polluted metropolitan areas

Bottom 20% most polluted metropolitan areas

Metropolitan areas in the national economy