gdp per capita in usd ppp 2 1 - oecd · since 2011, with gdp per capita in taurage county being...
TRANSCRIPT
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