DEVELOPMENT OF THE REGIONS OF LITHUANIA At the beginning ...
DEVELOPMENT OF THE REGIONS OF LITHUANIA At the beginning of 2008, Lithuania was populated by 3 million 336 thousand persons. A quarter of the population (848 thousand) were living in Vilnius county, 674 thousand – in Kaunas county (which ranked second in Lithuania in terms of the population), 379 thousand – in Klaipėda, 350 thousand – Šiauliai, 284 thousand – Panevėžys counties. The rest of the counties were much smaller: that of Marijampolė – 181 thousand, Alytus – 177 thousand, Telšiai and Utena –173 thousand in each, Tauragė – 127 thousand persons; the total number of residents of these five counties was lower than the population of Vilnius county. Population structure by age groups, beginning of 2008
The number of persons of working age in Vilnius county was the highest in Lithuania, while that of persons of retirement age – the lowest; the number of persons aged 0–15 was relatively low. Thus, it might be concluded that the age structure of the Vilnius county population is determined not only by the natural generational change, but also by a rather massive inflow of young persons arriving to take up residence in the county. The share of persons of retirement age is also relatively low, while that of persons of working age – high in Klaipėda county; in the said county, the share of persons aged 0–15 is somewhat higher than in Vilnius county. In 2008, the “oldest” county was that of Utena, where the share of children was the lowest, that of persons of retirement age – the highest, while that of persons of working age – lower than the national average.
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Children aged 0–15 made up almost one-fifth of the population in Telšiai and Tauragė counties. In Telšiai county, the share of persons of working age was also slightly lower, the share of persons of retirement age – lower than the national average, which made this county one of the demographically “youngest” in Lithuania. In 2001–2007, a negative natural population increase (i.e. the number of deaths per 1000 population was higher than that of live births) in the population was observed. In 2007, due to the negative natural population increase, the population decreased the most in Utena and Panevėžys counties, while the population of Klaipėda, Vilnius and Telšiai counties was influenced by the said factor the least. In 2005–2007, the natural population increase rate in Lithuania stabilised, while in several counties (those of Klaipėda, Telšiai and Tauragė) – even improved. In Vilnius and Kaunas counties, the natural increase rate was more favourable than the national average and remained stable; the rate was stably low in Alytus, Šiauliai and Marijampolė counties. The natural population increase rate was particularly low in Panevėžys and Utena counties, where it has been gradually decreasing. Natural population increase, 2001–2007 Natural increase per 1000 population
Vilnius county
Utena county
Telšiai county
Tauragė county
2003 Šiauliai county
Panevėžys county
Marijampolė county
Klaipėda county
Kaunas county
Alytus county
Lithuania
2001 2005 2007
0 -1 -2 -3 -4 -5 -6 -7 -8 -9 -10
At the beginning of 2008, 66.9 % of the population was living in urban, 33.1 % – in rural areas. In Tauragė and Marijampolė counties, more than half of the population was living in rural areas. In the rest of the counties, a larger share of the population was living in urban areas; however, the share of the urban population exceeded the national average only in the counties of the major cities. In Šiauliai, Panevėžys, Alytus, Telšiai and Utena counties, the shares of the urban and rural population were similar – about 60 and 40 % respectively. Population, beginning of 2008
Klaipėda county
59.0
61.5
41.1
41.0
44.1
59.0
55.9
21.7
Rural areas Urban areas
78.3
Vilnius county
Kaunas county
49.6
58.9
Utena county
72.6
38.5
Telšiai county
71.8
41.0
Tauragė county
59.0
50.4
Šiauliai county
66.9
Alytus county
27.4
Panevėžys county
28.2
33.1
Marijampolė county
41.0
Lithuania
Per cent
3
The structure of the population by sex in all the counties differed from the national indicator just slightly. The share of women was somewhat higher in smaller counties, namely in those where the rural population constituted a larger share (e.g. in Tauragė and Marijampolė counties). In the counties covering the major cities (e.g. in Vilnius, Kaunas or Klaipėda counties) the share of men exceeded the national average. These inconsiderable fluctuations can be explained by the fact that the share of women among persons of retirement age is higher; therefore, the share of women is larger in those counties which have been demographically ageing. An assumption can also be made that the sex distribution is also conditioned by different mobility of men and women – the share of women in those counties whose population is decreasing due to migration should be increasing. Population by sex, beginning of 2008 Per cent 52.5
54.0
53.2
52.5
53.4
53.3
52.5
52.9
52.9
54.0
46.5
47.5
46.0
46.8
47.5
46.6
46.7
47.5
47.1
47.1
46.0
Lithuania
Alytus county
Kaunas county
Klaipėda county
Marijampolė county
Panevėžys county
Šiauliai county
Tauragė county
Telšiai county
Utena county
Vilnius county
Females 53.5
Males
Differences in the indicators of average life expectancy in different counties were inconsiderable – the difference between the highest and the lowest respective indicators (those of Kaunas and Panevėžys, and Utena and Tauragė counties) made 1.7 years. The highest average life expectancy of women was in Alytus (78.1 years), that of men – in Panevėžys (66.2) counties. Meanwhile, the difference between the male and female average life expectancy indicators was much more substantial – about 12–13 years, on average, in all counties, except for Panevėžys county, where this difference was somewhat lower – 11.2 years, and Alytus and Utena counties, where it exceeded 13.5 years. Average life expectancy, 2007 Females Males Males and females
77.4
76.5
65.0
64.1 76.9
70.1
77.7
70.8 64.5
63.7 77.3
77.2
Vilnius county
76.9
64.7
71.3
Utena county
66.2
65.0
70.1
Telšiai county
77.5
70.5
Tauragė county
77.8
65.7
71.8
Šiauliai county
78.1
70.8
Panevėžys county
65.7
64.5
Alytus county
Lithuania
77.2
71.6
Marijampolė county
64.9
71.8
Klaipėda county
70.8
Kaunas county
70.9
4
In 2001, the impact of migration on the population in Lithuania and in separate counties was inconsiderable – although in all counties, except for those of Tauragė and Vilnius, net migration was negative, its impact was about four times as low as that of the negative natural increase. A considerable decrease in the population due to migration was observed in Utena county. Over 2003–2005, migration flows notably increased. In all counties, except for that of Vilnius, international and internal net migration was negative; the most serious problems were faced by Tauragė county (where as late as in 2001 net migration had still been positive), Šiauliai, Telšiai and Alytus counties, where the impact of negative net migration was higher or similar to that of the negative natural population increase. In 2007, the decrease in the population due to migration in Lithuania was not as rapid as in 2005 (however, still more rapid than in 2001); negative net migration turned into positive in Klaipėda county, halved in Kaunas county, notably decreased in Alytus, Marijampolė, Telšiai and Utena counties. The net migration rate changed just inconsiderably in Panevėžys and Tauragė counties, negative net migration increased in Šiauliai county. The largest share of the population due to negative net migration in 2007 was lost by Panevėžys, Tauragė and Šiauliai counties. International and internal net migration per 1000 population, 2001–2007 2001
4 3 2 1 0 -1 -2 -3 -4 -5 -6 -7
2003 2005
Vilnius county
Utena county
Telšiai county
Tauragė county
Šiauliai county
Panevėžys county
Marijampolė county
Klaipėda county
Kaunas county
Alytus county
Lithuania
2007
From 2002 to 2008, due to the negative natural increase and migration, the population of Lithuania decreased by almost 110 thousand. The most notable decrease was observed in Utena, Alytus and Panevėžys counties; the number of residents remained almost unchanged only in Vilnius county. Migration trends from urban and rural areas in different counties are different – e.g. in Panevėžys county the urban population decreased the most, whereas the rural population was increasing much slower. In Alytus county, this difference was not as prominent – both the urban and rural population decreased considerably; a similar trend was observed in Šiauliai county. Meanwhile, in Utena county, the rural population decreased by as much as one-tenth, which to a large extent impacted on the general change in the number of county’s residents. Changes in the population of Klaipėda and partly those in the population of Kaunas county reflect the process of these cities expanding to surrounding rural territories: the rural population in Klaipėda county increased, in Kaunas county – almost did not decrease, although the urban population was decreasing in both counties. Similar processes were observed in Vilnius county, where, however, the urban population was also increasing.
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Population in urban and rural areas, beginning of 2002–2008 2002 Lithuania
2004
2006
2008
3475586
3445857
3403284
3366357
urban areas
2326175
2297400
2268838
2250786
rural areas
1149411
1148457
1134446
1115571
Alytus county
187397
184807
180786
177040
urban areas
110843
108815
106215
104542
rural areas
76554
75992
74571
72498
Kaunas county
699314
691445
680937
673706
urban areas
508924
499058
489561
483560
rural areas
190390
192387
191376
190146
385008
383250
380612
378843
urban areas
282162
279972
277267
274978
rural areas
102846
103278
103345
103865
188298
186736
183870
181219
urban areas
93073
92158
90780
89938
rural areas
95225
94578
93090
91281
298958
295161
289628
284235
urban areas
178440
173902
170412
167723
rural areas
120518
121259
119216
116512
Šiauliai county
369192
364076
357015
349876
urban areas
226559
222489
218479
215021
rural areas
142633
141587
138536
134855
134051
132729
129976
127378
urban areas
54669
54100
53146
52336
rural areas
79382
78629
76830
75042
Telšiai county
179599
178141
175488
173383
urban areas
106350
105016
103034
102258
rural areas
73249
73125
72454
71125
Utena county
184879
181113
176711
172580
urban areas
100338
98573
97045
96461
rural areas
84541
82540
79666
76119
Vilnius county
848890
848399
848261
848097
urban areas
664817
663317
662899
663969
rural areas
184073
185082
185362
184128
Klaipėda county
Marijampolė county
Panevėžys county
Tauragė county
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Population change in urban and rural areas, beginning of 2002–2008 Per cent Urban and rural areas Urban areas Rural areas 1.0
-3.9
Utena county
-10.0
Vilnius county
-6.7
Telšiai county
Tauragė county
-2.9 -3.3 -3.5 -4.3 -3.8 -4.9 -5.2 -5.1 -5.5 -5.0 -5.5 -6.0
Šiauliai county
Kaunas county
Alytus county
-5.0
-3.4 -3.8 -4.1
Panevėžys county
-3.7 -5.5 -5.3 -5.7
Lithuania
-1.6 -2.5
Klaipėda county
-3.1 -2.9 -3.2
-0.1 -0.1 0.0
Marijampolė county
-0.1
The highest educational attainment was in the major counties (those of Vilnius, Kaunas and Klaipėda); in these counties, the share of persons with lower education was the smallest, while that with higher education – the largest. The shares of persons having higher education in Vilnius and Telšiai counties differed as much as 2.5 times. The largest share of the country’s population – 60 % – had secondary education. The major share of such persons was in smaller counties (those of Marijampolė, Telšiai and Alytus). Tauragė and Utena counties stood out among the rest of the counties with a large share of persons having just lower education. Population by educational attainment (by ISCED classification), 2007 Per cent Higher education Secondary education Lower education
68.2
60.6
60.0
67.9
11.1
11.4
8.5
7.9
11.8
12.5
15.2
19.9
15.3
16.3
9.0 Vilnius county
61.6
40.4
Utena county
62.7
23.1
Telšiai county
66.3
16.5
Tauragė county
18.5
Šiauliai county
69.8
22.1
Panevėžys county
65.8
21.3
Marijampolė county
58.0
18.4
Klaipėda county
26.3
Kaunas county
33.5
Alytus county
20.7
Lithuania
28.9
50.6
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In 2007, the unemployment rate in Lithuania made up 4.3 %. The highest unemployment rates were recorded in Panevėžys, Vilnius and Utena counties – 6.5, 4.5 and 4.4 % respectively. As compared with 2001, the unemployment rate in the country decreased 4 times; in Panevėžys county, where it had been the lowest, it decreased 2.25 times, while in Alytus county, where it had been the highest – as much as 6.8 times. In 2005–2007, the average deviation of the unemployment rate in the counties from the national average was growing – from 30.1 % in 2005 to 51.1 % in 2007; however, in 2007, not a single county was faced with a particularly high unemployment rate. Unemployment rate, 2001– 2007 Per cent
The highest employment rate was recorded in Vilnius county, Marijampolė and Kaunas counties (which had ranked first). The highest employment rate in 2007 was recorded in Alytus and Panevėžys counties. The most notable growth in the employment rate was observed in Marijampolė county, which in 2001 had ranked penultimate by the employment rate, while in 2007 – second, being outpaced only by Vilnius county. In Alytus county, the employment rate in 2001 was the lowest in the country, in 2007 it ranked penultimate. The poorest situation – in Panevėžys county, where the employment rate has been growing just insignificantly, which made the county fall from the second position in 2001 to the last one in 2007. The growth in the
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employment rate was slower than the national average in Klaipėda, Šiauliai and Tauragė counties, equalled the national average – in Utena county. Employment rate, 2007 Per cent
The absolute majority of employed persons in 8 out of 10 counties (except for those of Telšiai and Utena) were working in the service sector. In Vilnius county, two-thirds of persons employed were working in the service sector. A higher share of persons working in agriculture was in Marijampolė and Tauragė counties (the share of the value added generated in this sector was lower). The share of persons employed in industry was lower in Vilnius and Tauragė counties, while in the rest of the counties these shares differed inconsiderably. Attention should probably be drawn to the fact that in Telšiai and Utena counties the value added generated in the industrial sector falling within a relatively low number of persons employed in this sector is high. Employment of the population in the country’s regions, their qualification, quality of life, as well as communication and participation in social life regardless of their place of residence are to a large extent related to Internet usage. The share of households having Internet access from 2005 to 2008 grew 2.3 times; each second household had Internet access. The leading counties in terms of the share of households having Internet access were those of Vilnius and Klaipėda; Telšiai county slightly lagged behind Klaipėda county. Although Telšiai county may be
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conditionally classified under the peripheral ones, and despite the fact that quite a number of its residents live in rural areas, this county outpaced those of Kaunas and Šiauliai. The lowest share of households having Internet access – just about one-third – was in Utena and Alytus counties. Although there are still counties lagging behind the rest of the country in terms of Internet usage, territorial disparities have been rapidly decreasing. As late as in 2005, the share of households having Internet access in Vilnius county was almost three times as high as that in Alytus county, while in 2008 this difference was much smaller – 66 %. In less-developed counties, this indicator since 2005 grew about 3.5–4, in the leading ones – 2–3 times. Share of households with Internet access, beginning of 2005 and 2008 Per cent
Alytus county
39.6
10.9
39.8
13.4
43.5
9.1
42.1 12.7
T elšiai county
Vilnius county
51.5
9.2
Šiauliai county
Utena county
44.8
17.0
Panevėžys county
2008
35.0 15.9
Klaipėda county
T auragė county
47.1
6.8
Kaunas county
Marijampolė county
2005
14.4
Lithuania
49.5
7.5
33.6 19.3
58.2
Most social and demographic processes observed in the country’s regions are conditioned by their economic development – economically stronger counties become more attractive for living, migration flows are changing. The economic situation is also related to changes in the birth rate and generational changes. On the other hand, the structure of the population by age, locality of residence or education, social situation and quality of life impact on development conditions of certain branches of economy. One of the key indicators reflecting economic development of the regions is gross domestic product per capita (GDP per capita). The GDP per capita in 2007 made LTL 29.1 thousand, and was exceeded only in Klaipėda (LTL 29.8 thousand) and Vilnius (LTL 45 thousand) counties. The GDP per capita in Vilnius county was 3.3 times higher than that in the poorest – Tauragė – county (LTL 13.7 thousand). Although the GDP per capita growth rate was rather high, its growth rates in different counties were very uneven. Since 2001, the disparity between the per capita GDP in the counties and the national GDP per capita has been growing: in 2001, it made up 20.7 %, in 2005 – 24.2 %, in 2007 – 28.4 %. The unevenness of economic development between Vilnius and other country’s regions is substantial, and no decrease in the disparity has been observed.
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Gross domestic product per capita, 2001–2007 LTL thousand 2001 2003
40
2005
35
2007
30 25 20 15 10 5 Vilnius county
Utena county
Telšiai county
Tauragė county
Šiauliai county
Panevėžys county
Marijampolė county
Klaipėda county
Kaunas county
Alytus county
Lithuania
0
The largest share of the value added in the country was created by the service sector of the economically strongest counties (those of Vilnius, Klaipėda and Kaunas), where the share of the value added generated in the trade, hotels, restaurants, transport and other service sectors was relatively higher than in the regions with a slower economic growth. An exceptionally large share of gross value added in Vilnius county was generated by the financial intermediation sector. Industry dominated in Utena county (with Ignalina Nuclear Power Plant located in it), as well as in Telšiai county (public company Mažeikių nafta – oil refinery). A larger share of agriculture, as compared with other counties, in the gross value added was in the economically weaker Tauragė and Marijampolė counties. Šiauliai, Panevėžys and Alytus counties could be characterised by the share of industry and construction in the gross value added being close to the national indicator, as well as a less-developed service sector (except for public and communal services).
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Gross domestic product per capita compared with the national average and structure of gross value added by economic sector, 2007* Per cent
A low per capita GDP level in less-developed regions is conditioned by the lack of investment in human resources, innovation, technological progress. At the beginning of 2008, foreign direct investment per capita (per capita FDI) in Lithuania made LTL 10 547. The highest per capita FDI was in Telšiai (mostly due to investment in public company Mažeikių nafta) and Vilnius counties, while the lowest – in Tauragė, Marijampolė and Šiauliai counties. The per capita FDI indicators in Tauragė and Marijampolė counties were almost 20 times lower than the national indicator. A low level of foreign investment in some counties could be partially explained by the fact that in those counties, in contradistinction to Vilnius and Telšiai counties, domestic capital enterprises predominated; however, the per capita FDI indicator also reflects the fact that the investment environment in those counties and their major towns is unfavourable.
12
Foreign direct investment per capita, beginning of 2006 and 2008 LTL
The level of entrepreneurship of the population of economically weaker counties is also lower. Although the number of operating economic entities in the country has been gradually increasing, the number of such enterprises per 1000 population in Tauragė, Utena and Marijampolė counties was almost twice as low as in Vilnius county. The number of operating economic entities per 1000 population was close to the national average only in Kaunas and Klaipėda counties. Vilnius county was the obvious leader. The growth rates in the indicator in question differed markedly as well – in Vilnius county from the beginning of 2002 it grew by 43 %, in Panevėžys county – by 21 %, in Kaunas and Klaipėda counties – by 16 % in each, in Alytus county – by 13 %. In the rest of the counties, it grew by just 4–10 %. Territorial disparities of the distribution of operating economic entities have been rapidly increasing.
13
Number of operating economic entities per 1000 population, beginning of 2002–2008
The amount of pollutants emitted into the atmosphere in 2001–2007 was decreasing; it slightly increased only in Tauragė and Šiauliai counties. The lowest amount of pollutants was emitted into the atmosphere in Alytus and Utena county (despite the fact that these counties are characterised by well-developed industry). The highest amount of pollutants was emitted into the atmosphere in Kaunas, Klaipėda and Telšiai (namely in Mažeikiai) counties.
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Emission of pollutants into the atmosphere, 2001–2007 kg/km²
Although the growth of the Lithuanian economy in 2001–2007 was rapid, and its impact on the environment was not high, substantial unevenness in the economic growth, poor level of entrepreneurship of the population in many country’s regions became prominent. However, recently, a decline in unemployment and growth in employment in economically weaker counties have been observed. Presumptively, the improving social situation of the country’s regions will bring about conditions for the improvement of their economic indicators in the future.
The number of persons of working age in Vilnius county was the highest in Lithuania, while that of persons of retirement age – the lowest; the number of persons aged 0–15 was relatively low. Thus, it might be concluded that the age structure of the Vilnius county population is determined not only by the natural generational change, but also by a rather massive inflow of young persons arriving to take up residence in the county. The share of persons of retirement age is also relatively low, while that of persons of working age – high in Klaipėda county; in the said county, the share of persons aged 0–15 is somewhat higher than in Vilnius county. In 2008, the “oldest” county was that of Utena, where the share of children was the lowest, that of persons of retirement age – the highest, while that of persons of working age – lower than the national average.
2
Children aged 0–15 made up almost one-fifth of the population in Telšiai and Tauragė counties. In Telšiai county, the share of persons of working age was also slightly lower, the share of persons of retirement age – lower than the national average, which made this county one of the demographically “youngest” in Lithuania. In 2001–2007, a negative natural population increase (i.e. the number of deaths per 1000 population was higher than that of live births) in the population was observed. In 2007, due to the negative natural population increase, the population decreased the most in Utena and Panevėžys counties, while the population of Klaipėda, Vilnius and Telšiai counties was influenced by the said factor the least. In 2005–2007, the natural population increase rate in Lithuania stabilised, while in several counties (those of Klaipėda, Telšiai and Tauragė) – even improved. In Vilnius and Kaunas counties, the natural increase rate was more favourable than the national average and remained stable; the rate was stably low in Alytus, Šiauliai and Marijampolė counties. The natural population increase rate was particularly low in Panevėžys and Utena counties, where it has been gradually decreasing. Natural population increase, 2001–2007 Natural increase per 1000 population
Vilnius county
Utena county
Telšiai county
Tauragė county
2003 Šiauliai county
Panevėžys county
Marijampolė county
Klaipėda county
Kaunas county
Alytus county
Lithuania
2001 2005 2007
0 -1 -2 -3 -4 -5 -6 -7 -8 -9 -10
At the beginning of 2008, 66.9 % of the population was living in urban, 33.1 % – in rural areas. In Tauragė and Marijampolė counties, more than half of the population was living in rural areas. In the rest of the counties, a larger share of the population was living in urban areas; however, the share of the urban population exceeded the national average only in the counties of the major cities. In Šiauliai, Panevėžys, Alytus, Telšiai and Utena counties, the shares of the urban and rural population were similar – about 60 and 40 % respectively. Population, beginning of 2008
Klaipėda county
59.0
61.5
41.1
41.0
44.1
59.0
55.9
21.7
Rural areas Urban areas
78.3
Vilnius county
Kaunas county
49.6
58.9
Utena county
72.6
38.5
Telšiai county
71.8
41.0
Tauragė county
59.0
50.4
Šiauliai county
66.9
Alytus county
27.4
Panevėžys county
28.2
33.1
Marijampolė county
41.0
Lithuania
Per cent
3
The structure of the population by sex in all the counties differed from the national indicator just slightly. The share of women was somewhat higher in smaller counties, namely in those where the rural population constituted a larger share (e.g. in Tauragė and Marijampolė counties). In the counties covering the major cities (e.g. in Vilnius, Kaunas or Klaipėda counties) the share of men exceeded the national average. These inconsiderable fluctuations can be explained by the fact that the share of women among persons of retirement age is higher; therefore, the share of women is larger in those counties which have been demographically ageing. An assumption can also be made that the sex distribution is also conditioned by different mobility of men and women – the share of women in those counties whose population is decreasing due to migration should be increasing. Population by sex, beginning of 2008 Per cent 52.5
54.0
53.2
52.5
53.4
53.3
52.5
52.9
52.9
54.0
46.5
47.5
46.0
46.8
47.5
46.6
46.7
47.5
47.1
47.1
46.0
Lithuania
Alytus county
Kaunas county
Klaipėda county
Marijampolė county
Panevėžys county
Šiauliai county
Tauragė county
Telšiai county
Utena county
Vilnius county
Females 53.5
Males
Differences in the indicators of average life expectancy in different counties were inconsiderable – the difference between the highest and the lowest respective indicators (those of Kaunas and Panevėžys, and Utena and Tauragė counties) made 1.7 years. The highest average life expectancy of women was in Alytus (78.1 years), that of men – in Panevėžys (66.2) counties. Meanwhile, the difference between the male and female average life expectancy indicators was much more substantial – about 12–13 years, on average, in all counties, except for Panevėžys county, where this difference was somewhat lower – 11.2 years, and Alytus and Utena counties, where it exceeded 13.5 years. Average life expectancy, 2007 Females Males Males and females
77.4
76.5
65.0
64.1 76.9
70.1
77.7
70.8 64.5
63.7 77.3
77.2
Vilnius county
76.9
64.7
71.3
Utena county
66.2
65.0
70.1
Telšiai county
77.5
70.5
Tauragė county
77.8
65.7
71.8
Šiauliai county
78.1
70.8
Panevėžys county
65.7
64.5
Alytus county
Lithuania
77.2
71.6
Marijampolė county
64.9
71.8
Klaipėda county
70.8
Kaunas county
70.9
4
In 2001, the impact of migration on the population in Lithuania and in separate counties was inconsiderable – although in all counties, except for those of Tauragė and Vilnius, net migration was negative, its impact was about four times as low as that of the negative natural increase. A considerable decrease in the population due to migration was observed in Utena county. Over 2003–2005, migration flows notably increased. In all counties, except for that of Vilnius, international and internal net migration was negative; the most serious problems were faced by Tauragė county (where as late as in 2001 net migration had still been positive), Šiauliai, Telšiai and Alytus counties, where the impact of negative net migration was higher or similar to that of the negative natural population increase. In 2007, the decrease in the population due to migration in Lithuania was not as rapid as in 2005 (however, still more rapid than in 2001); negative net migration turned into positive in Klaipėda county, halved in Kaunas county, notably decreased in Alytus, Marijampolė, Telšiai and Utena counties. The net migration rate changed just inconsiderably in Panevėžys and Tauragė counties, negative net migration increased in Šiauliai county. The largest share of the population due to negative net migration in 2007 was lost by Panevėžys, Tauragė and Šiauliai counties. International and internal net migration per 1000 population, 2001–2007 2001
4 3 2 1 0 -1 -2 -3 -4 -5 -6 -7
2003 2005
Vilnius county
Utena county
Telšiai county
Tauragė county
Šiauliai county
Panevėžys county
Marijampolė county
Klaipėda county
Kaunas county
Alytus county
Lithuania
2007
From 2002 to 2008, due to the negative natural increase and migration, the population of Lithuania decreased by almost 110 thousand. The most notable decrease was observed in Utena, Alytus and Panevėžys counties; the number of residents remained almost unchanged only in Vilnius county. Migration trends from urban and rural areas in different counties are different – e.g. in Panevėžys county the urban population decreased the most, whereas the rural population was increasing much slower. In Alytus county, this difference was not as prominent – both the urban and rural population decreased considerably; a similar trend was observed in Šiauliai county. Meanwhile, in Utena county, the rural population decreased by as much as one-tenth, which to a large extent impacted on the general change in the number of county’s residents. Changes in the population of Klaipėda and partly those in the population of Kaunas county reflect the process of these cities expanding to surrounding rural territories: the rural population in Klaipėda county increased, in Kaunas county – almost did not decrease, although the urban population was decreasing in both counties. Similar processes were observed in Vilnius county, where, however, the urban population was also increasing.
5
Population in urban and rural areas, beginning of 2002–2008 2002 Lithuania
2004
2006
2008
3475586
3445857
3403284
3366357
urban areas
2326175
2297400
2268838
2250786
rural areas
1149411
1148457
1134446
1115571
Alytus county
187397
184807
180786
177040
urban areas
110843
108815
106215
104542
rural areas
76554
75992
74571
72498
Kaunas county
699314
691445
680937
673706
urban areas
508924
499058
489561
483560
rural areas
190390
192387
191376
190146
385008
383250
380612
378843
urban areas
282162
279972
277267
274978
rural areas
102846
103278
103345
103865
188298
186736
183870
181219
urban areas
93073
92158
90780
89938
rural areas
95225
94578
93090
91281
298958
295161
289628
284235
urban areas
178440
173902
170412
167723
rural areas
120518
121259
119216
116512
Šiauliai county
369192
364076
357015
349876
urban areas
226559
222489
218479
215021
rural areas
142633
141587
138536
134855
134051
132729
129976
127378
urban areas
54669
54100
53146
52336
rural areas
79382
78629
76830
75042
Telšiai county
179599
178141
175488
173383
urban areas
106350
105016
103034
102258
rural areas
73249
73125
72454
71125
Utena county
184879
181113
176711
172580
urban areas
100338
98573
97045
96461
rural areas
84541
82540
79666
76119
Vilnius county
848890
848399
848261
848097
urban areas
664817
663317
662899
663969
rural areas
184073
185082
185362
184128
Klaipėda county
Marijampolė county
Panevėžys county
Tauragė county
6
Population change in urban and rural areas, beginning of 2002–2008 Per cent Urban and rural areas Urban areas Rural areas 1.0
-3.9
Utena county
-10.0
Vilnius county
-6.7
Telšiai county
Tauragė county
-2.9 -3.3 -3.5 -4.3 -3.8 -4.9 -5.2 -5.1 -5.5 -5.0 -5.5 -6.0
Šiauliai county
Kaunas county
Alytus county
-5.0
-3.4 -3.8 -4.1
Panevėžys county
-3.7 -5.5 -5.3 -5.7
Lithuania
-1.6 -2.5
Klaipėda county
-3.1 -2.9 -3.2
-0.1 -0.1 0.0
Marijampolė county
-0.1
The highest educational attainment was in the major counties (those of Vilnius, Kaunas and Klaipėda); in these counties, the share of persons with lower education was the smallest, while that with higher education – the largest. The shares of persons having higher education in Vilnius and Telšiai counties differed as much as 2.5 times. The largest share of the country’s population – 60 % – had secondary education. The major share of such persons was in smaller counties (those of Marijampolė, Telšiai and Alytus). Tauragė and Utena counties stood out among the rest of the counties with a large share of persons having just lower education. Population by educational attainment (by ISCED classification), 2007 Per cent Higher education Secondary education Lower education
68.2
60.6
60.0
67.9
11.1
11.4
8.5
7.9
11.8
12.5
15.2
19.9
15.3
16.3
9.0 Vilnius county
61.6
40.4
Utena county
62.7
23.1
Telšiai county
66.3
16.5
Tauragė county
18.5
Šiauliai county
69.8
22.1
Panevėžys county
65.8
21.3
Marijampolė county
58.0
18.4
Klaipėda county
26.3
Kaunas county
33.5
Alytus county
20.7
Lithuania
28.9
50.6
7
In 2007, the unemployment rate in Lithuania made up 4.3 %. The highest unemployment rates were recorded in Panevėžys, Vilnius and Utena counties – 6.5, 4.5 and 4.4 % respectively. As compared with 2001, the unemployment rate in the country decreased 4 times; in Panevėžys county, where it had been the lowest, it decreased 2.25 times, while in Alytus county, where it had been the highest – as much as 6.8 times. In 2005–2007, the average deviation of the unemployment rate in the counties from the national average was growing – from 30.1 % in 2005 to 51.1 % in 2007; however, in 2007, not a single county was faced with a particularly high unemployment rate. Unemployment rate, 2001– 2007 Per cent
The highest employment rate was recorded in Vilnius county, Marijampolė and Kaunas counties (which had ranked first). The highest employment rate in 2007 was recorded in Alytus and Panevėžys counties. The most notable growth in the employment rate was observed in Marijampolė county, which in 2001 had ranked penultimate by the employment rate, while in 2007 – second, being outpaced only by Vilnius county. In Alytus county, the employment rate in 2001 was the lowest in the country, in 2007 it ranked penultimate. The poorest situation – in Panevėžys county, where the employment rate has been growing just insignificantly, which made the county fall from the second position in 2001 to the last one in 2007. The growth in the
8
employment rate was slower than the national average in Klaipėda, Šiauliai and Tauragė counties, equalled the national average – in Utena county. Employment rate, 2007 Per cent
The absolute majority of employed persons in 8 out of 10 counties (except for those of Telšiai and Utena) were working in the service sector. In Vilnius county, two-thirds of persons employed were working in the service sector. A higher share of persons working in agriculture was in Marijampolė and Tauragė counties (the share of the value added generated in this sector was lower). The share of persons employed in industry was lower in Vilnius and Tauragė counties, while in the rest of the counties these shares differed inconsiderably. Attention should probably be drawn to the fact that in Telšiai and Utena counties the value added generated in the industrial sector falling within a relatively low number of persons employed in this sector is high. Employment of the population in the country’s regions, their qualification, quality of life, as well as communication and participation in social life regardless of their place of residence are to a large extent related to Internet usage. The share of households having Internet access from 2005 to 2008 grew 2.3 times; each second household had Internet access. The leading counties in terms of the share of households having Internet access were those of Vilnius and Klaipėda; Telšiai county slightly lagged behind Klaipėda county. Although Telšiai county may be
9
conditionally classified under the peripheral ones, and despite the fact that quite a number of its residents live in rural areas, this county outpaced those of Kaunas and Šiauliai. The lowest share of households having Internet access – just about one-third – was in Utena and Alytus counties. Although there are still counties lagging behind the rest of the country in terms of Internet usage, territorial disparities have been rapidly decreasing. As late as in 2005, the share of households having Internet access in Vilnius county was almost three times as high as that in Alytus county, while in 2008 this difference was much smaller – 66 %. In less-developed counties, this indicator since 2005 grew about 3.5–4, in the leading ones – 2–3 times. Share of households with Internet access, beginning of 2005 and 2008 Per cent
Alytus county
39.6
10.9
39.8
13.4
43.5
9.1
42.1 12.7
T elšiai county
Vilnius county
51.5
9.2
Šiauliai county
Utena county
44.8
17.0
Panevėžys county
2008
35.0 15.9
Klaipėda county
T auragė county
47.1
6.8
Kaunas county
Marijampolė county
2005
14.4
Lithuania
49.5
7.5
33.6 19.3
58.2
Most social and demographic processes observed in the country’s regions are conditioned by their economic development – economically stronger counties become more attractive for living, migration flows are changing. The economic situation is also related to changes in the birth rate and generational changes. On the other hand, the structure of the population by age, locality of residence or education, social situation and quality of life impact on development conditions of certain branches of economy. One of the key indicators reflecting economic development of the regions is gross domestic product per capita (GDP per capita). The GDP per capita in 2007 made LTL 29.1 thousand, and was exceeded only in Klaipėda (LTL 29.8 thousand) and Vilnius (LTL 45 thousand) counties. The GDP per capita in Vilnius county was 3.3 times higher than that in the poorest – Tauragė – county (LTL 13.7 thousand). Although the GDP per capita growth rate was rather high, its growth rates in different counties were very uneven. Since 2001, the disparity between the per capita GDP in the counties and the national GDP per capita has been growing: in 2001, it made up 20.7 %, in 2005 – 24.2 %, in 2007 – 28.4 %. The unevenness of economic development between Vilnius and other country’s regions is substantial, and no decrease in the disparity has been observed.
10
Gross domestic product per capita, 2001–2007 LTL thousand 2001 2003
40
2005
35
2007
30 25 20 15 10 5 Vilnius county
Utena county
Telšiai county
Tauragė county
Šiauliai county
Panevėžys county
Marijampolė county
Klaipėda county
Kaunas county
Alytus county
Lithuania
0
The largest share of the value added in the country was created by the service sector of the economically strongest counties (those of Vilnius, Klaipėda and Kaunas), where the share of the value added generated in the trade, hotels, restaurants, transport and other service sectors was relatively higher than in the regions with a slower economic growth. An exceptionally large share of gross value added in Vilnius county was generated by the financial intermediation sector. Industry dominated in Utena county (with Ignalina Nuclear Power Plant located in it), as well as in Telšiai county (public company Mažeikių nafta – oil refinery). A larger share of agriculture, as compared with other counties, in the gross value added was in the economically weaker Tauragė and Marijampolė counties. Šiauliai, Panevėžys and Alytus counties could be characterised by the share of industry and construction in the gross value added being close to the national indicator, as well as a less-developed service sector (except for public and communal services).
11
Gross domestic product per capita compared with the national average and structure of gross value added by economic sector, 2007* Per cent
A low per capita GDP level in less-developed regions is conditioned by the lack of investment in human resources, innovation, technological progress. At the beginning of 2008, foreign direct investment per capita (per capita FDI) in Lithuania made LTL 10 547. The highest per capita FDI was in Telšiai (mostly due to investment in public company Mažeikių nafta) and Vilnius counties, while the lowest – in Tauragė, Marijampolė and Šiauliai counties. The per capita FDI indicators in Tauragė and Marijampolė counties were almost 20 times lower than the national indicator. A low level of foreign investment in some counties could be partially explained by the fact that in those counties, in contradistinction to Vilnius and Telšiai counties, domestic capital enterprises predominated; however, the per capita FDI indicator also reflects the fact that the investment environment in those counties and their major towns is unfavourable.
12
Foreign direct investment per capita, beginning of 2006 and 2008 LTL
The level of entrepreneurship of the population of economically weaker counties is also lower. Although the number of operating economic entities in the country has been gradually increasing, the number of such enterprises per 1000 population in Tauragė, Utena and Marijampolė counties was almost twice as low as in Vilnius county. The number of operating economic entities per 1000 population was close to the national average only in Kaunas and Klaipėda counties. Vilnius county was the obvious leader. The growth rates in the indicator in question differed markedly as well – in Vilnius county from the beginning of 2002 it grew by 43 %, in Panevėžys county – by 21 %, in Kaunas and Klaipėda counties – by 16 % in each, in Alytus county – by 13 %. In the rest of the counties, it grew by just 4–10 %. Territorial disparities of the distribution of operating economic entities have been rapidly increasing.
13
Number of operating economic entities per 1000 population, beginning of 2002–2008
The amount of pollutants emitted into the atmosphere in 2001–2007 was decreasing; it slightly increased only in Tauragė and Šiauliai counties. The lowest amount of pollutants was emitted into the atmosphere in Alytus and Utena county (despite the fact that these counties are characterised by well-developed industry). The highest amount of pollutants was emitted into the atmosphere in Kaunas, Klaipėda and Telšiai (namely in Mažeikiai) counties.
14
Emission of pollutants into the atmosphere, 2001–2007 kg/km²
Although the growth of the Lithuanian economy in 2001–2007 was rapid, and its impact on the environment was not high, substantial unevenness in the economic growth, poor level of entrepreneurship of the population in many country’s regions became prominent. However, recently, a decline in unemployment and growth in employment in economically weaker counties have been observed. Presumptively, the improving social situation of the country’s regions will bring about conditions for the improvement of their economic indicators in the future.
