Our analysis is focused into 139,578 individuals of the rapidly declining regions, of whom 1605 have moved out of these regions between 2010 and 2011. 6. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. Lastly, we controlled for (changes in) the unemployment rate of the origin region, which should reveal what the role is played by the regional context on the probability of leaving the shrinking regions and the destination of migration. Model 1 includes socio-demographic characteristics. Although our study has shortcomings, mainly related to data constraints, it is an important step on the path to a better understanding of internal migration and depopulation processes in post-socialist countries. People who now (in 2011) work in the primary sector were the least likely to move to both ‘losing’ and ‘winning’ regions. Register to receive personalised research and resources by email. Currently it is hardly practised in Lithuania, but the role of local communities is slowly increasing as a result of European Union support. Moreover, rural shrinkage is a natural response to structural changes in the economy, including increasing efficiency of the agricultural sector. Despite these shortcomings in the data, this study is an important step forward in better understanding internal migration and depopulation processes in the post-socialist countries. Lithuania is losing population at increasing rates since the political reforms of the early Nineteen Nineties, and it is now among the fastest shrinking countries in the world. Distribution of migrants according to the population change in the region of destination. The regions with the sharpest decline in population (–20% and more) covered 44% of the countries’ territory and inhabited around 330,000 or 11% of the total population in 2011 (urban areas of the major cities excluded). It is also the first study to use individual-level Lithuanian census data to analyse migration, while very few studies have been done in other CEE countries, making this study of wider interest. Table 1 also shows that those who moved out form the declining regions were younger, better educated and more qualified than the average of rapidly declining regions. The aim of this study is to obtain more insight into the recent processes of socio-spatial change and the role of selective migration in Lithuania. In model 3 we added housing characteristics. Future empirical work should focus on selective migration by destination in order to get a better insight into the process of socio-spatial polarization. Since the registration of the residence is voluntary and the place of residence is not directly linked with other institutions (e.g., healthcare), not updating your address does not have any legal consequences. However, our survey, which was completed right after the 2011 census, showed that 96% of people living in the declining regions are actually satisfied with their standard of living (Daugirdas et al., 2013). It is noteworthy that after controlling for regional-level variables in model 4, the differences between the categories of variables on the individual-level, such as education and labour market position, reduced. First, using the aggregated-level data we investigate the compositional differences of Lithuanian population, focusing on the residents of the declining regions and those who have moved out from them. Although the contrast is less pronounced than we could have been expecting, we found that relatively younger and highly educated people and those who live in smaller households are more inclined to move to the ‘winning’ regions. OTB – Research for the Built Environment, Faculty of Architecture and the Built Environment, Delft University of Technology, Delft, the Netherlands; Institute of Human Geography and Demography, Lithuanian Social Research Centre, Vilnius, Lithuania, OTB – Research for the Built Environment, Faculty of Architecture and the Built Environment, Delft University of Technology, Delft, the Netherlands; School of Geography and Geosciences, University of St Andrews, St Andrews, UK, Family structure among urban, rural and farm populations: Classic sociological theory revisited, A spatiotemporal analysis of inter-county migration patterns in the United States. During this period, population movement was regulated between the communist states and even within national borders. Re-examining self-reported reasons for desiring and making residential moves, Demographic shocks after communism: Eastern Germany, 1989-93. Population change in Lithuania, 2001–11. The decades 1945/50 to 1989/91 (the period of socialism lasted differently in different CEE countries). "It is obvious that we are facing the loss of jobs and taxpayers which poses threat to the public finances and the sustainability of the social security system. In contrast to popular belief, we believe that the shrinkage of these regions in Lithuania is inevitable and that out-migration gives better education and career opportunities for migrants, especially for those whose qualification can hardly be used in the shrinking agricultural labour market. The results show that compared with the national average, residents of the declining regions were older, less educated, less skilled, there were more unemployed persons and more people who received social benefits, more people working in the primary sector and fewer in services and public administration; also more residents of the rapidly declining regions owned their home and lived in single-family houses, mainly built before 1991. Cited by lists all citing articles based on Crossref citations.Articles with the Crossref icon will open in a new tab. Moreover, migrants have different propensities to move into the ‘losing’ and ‘winning’ regions. The probability to move out increases with higher rates of unemployment in the region of origin. Currently, the population of the declining regions is still over 300,000 and it is a major challenge to ensure the standard of living in these regions stays sufficiently high, but at the same time is affordable. It can be explained by the high share of owner-occupied single-family houses. The results also showed that those having low-skilled jobs had the highest odds of living in declining regions and those having high-skilled jobs had the lowest odds (not included into the models due to overlap with the variables education and labour market position). Young adults are more likely to move out from rural regions for education and employment reasons, while with age people accumulate ‘commitments’ making migration more complex and costly. It could also mean that anyone who has the potential to leave has already left and the population is decreasing due to negative natural change. The model also shows that in general Lithuanians were more likely to move than others, but when we take into account the direction of migration, Lithuanians were more likely to have moved into ‘losing’ regions while there are no differences between ethnic groups with regard to moving into ‘winning’ regions. At the start of this year, it was 1.95 million. After controlling for employment status, the effect of the age composition diminished, especially for the oldest age group. Many studies find that a high unemployment rate is associated with high out-migration (Ní Laoire, 2000; Nivalainen, 2004; Panagopoulos & Barreira, 2012; Stockdale, 2004). The effects of age and household size have nearly turned over once we controlled for housing characteristics. This could be associated with the higher share of pensioners in shrinking regions, which fall within the category of non-participating. The 2019 population density in Lithuania is 44 people per Km 2 (114 people per mi 2), calculated on a total land area of 62,674 Km2 (24,199 sq. Source: Based on the 2011 Lithuanian census. Between 2000 and 2010 they lost on average –3.7% of their population. Around half a million left in a search of a better life between the end of the 19th century and World War II. Largest Cities in Lithuania CITY NAME To our surprise, 990 persons moved into ‘loosing’ regions and 615 moved into ‘winning’ regions. Andorra, a small mountainous country sandwiched between France and Spain, only has a population of 77,821 people to begin with. But these latter processes are beyond the scope of this research. Two-thirds of respondents said that the prospects for the young are poor in the declining regions, and 15% of the residents were considering leaving their current place of residence in the near future, with the main reasons being employment related. Aso erupts in Japan's Kumamoto Prefecture, More than 60 pct Chinese prefer digital reading: survey, Feature: Chinese builders expand metro network in Moscow, International conference dedicated to BRI opens in Belgrade. This paper provides empirical evidence of selective migration and increasing regional disparities in Lithuania. The Black population grew by almost 12% over the decade, and the white population increased by 4.3%. There were 1,263,937 (or 42% of the total population) reference persons in all the households in Lithuania in 2011. Shortage, priority and urban growth: Towards a theory of urbanisation under central planning, Transitional statistics: Internal migration and urban growth in post-soviet Estonia, Uneven transformations: Space, economy and society 20 years after the collapse of state socialism, Demographic shifts in the Czech Republic after 1989: A second demographic transition view, Planning for shrinkage: Paradox or Paradigm, Demographic change as a future challenge for cities in east central Europe, Rural out-migration: Community consequences and individual migrant experiences, Suburban growth and suburbanisation under central planning: The case of soviet Estonia, The ethnic dimensions of suburbanisation in Estonia, Migration and labour market adjustment: Empirical evidence from Finland 1985‐90, EU integration & emigration consequences: The case of Lithuania, Lietuvos gyventojų vidaus migracijų teritoriniai ypatumai 21 a, Territorial features of internal migration of Lithuanian population in the 21st century, Ethno-political effects of suburbanization in the Vilnius urban region: An analysis of voting behavior, Shrinking regions in a shrinking country: The geography of population decline in Lithuania 2001-2011, Large social inequalities and low levels of socio-economic segregation in Vilnius, Planning urban systems in Soviet times and in the era of transition: The case of Estonia, Spatial mobility, family dynamics, and housing transitions. At least in (neo-classical) theory, labour migration should eventually lead to a new (spatial) economic equilibrium as the cost of labour drops in shrinking areas, making these areas more attractive for employers (Sjaastad, 1962). This paper describes the trends in suicide deaths in urban population in Lithuania by gender, dates and suicide method over the period 1984–2003. Figure 2. So the effects of time-varying variables such as education, occupation and household status should be interpreted with caution. These regions with the largest population decline are mostly rural regions, but also include some smaller cities. The main focus is on understanding who lives in those regions which are rapidly losing population, and who is most likely to leave these regions. In a quarter of a century, since the early 1990s, Lithuania lost more than one-fifth of its residents (a rapid decrease from 3.7 million in 1989 to 2.9 million in … Interestingly, the data also showed a group (11% of those who moved) who moved from one rapidly declining region to another. In a quarter of a century, since the early 1990s, Lithuania lost more than one-fifth of its residents (a rapid decrease from 3.7 million in 1989 to 2.9 million in 2015), which makes it one of the countries with the greatest population decline in the world (The Economist, 2017; United Nations, 2015). The aim of this paper is to obtain more insight into the composition of the population in the rapidly declining regions in Lithuania and the composition of the flows out of these regions, as well as to understand to what extent the Soviet-made settlement system contributed to extreme population decline and population redistribution in Lithuania. We will also investigate the effects of regional characteristics on population mobility. This suggests that the most ‘successful’ people are leaving declining regions, which increases the socio-demographic and economic gap between the rapidly declining regions and the rest of the country. 1. Despite the general population decline in Lithuania, an increasing concentration of population is observed in the major city-regions, albeit the population is dropping in the inner cities themselves (Ubarevičienė et al., 2016). For instance, Bulgarian population contracted from 9 … The total population decline unevenly affected regions within Lithuania and as a result regional differences increased. Using individual-level data we are now able to investigate the directions and population structure of migration flows as well as the relationships between the individual characteristics which are affecting migration. In the Baltic States, which had a major role as suppliers of agricultural production to the Soviet Union, residents were encouraged to live and work in rural settlements where they were provided with housing facilities and income, often at a higher standard than in the cities (Tammaru, 2001). R2 (Nagelkerke) = 0.273. In 2019, Lithuania's population decreased by 0.53 percent, compared to the previous year. Since the 1990s, Lithuania lost almost a quarter of its population, and some regions within the country lost more than 50% of their residents. Figure 1 shows the spatial pattern of population change in Lithuania. The rates increased from 1986 until 1995, but later there was a slight decrease. We found an opposite relationship for the rest of the country. The pattern of population change in Lithuania shows a concentration of population in the metropolitan areas (MAs) and a sharp decline in peripheral rural regions (Ubarevičienė, van Ham, & Burneika, 2016). The paper explored recent processes of socio-spatial change and the role of selective migration in Lithuania. Among its etymologies there are a derivation from the word Lietava, for a small river, a possible derivation from a word leičiai, but most probable is the name for union of Lithuanian ethnic tribes ('susilieti, lietis' means to unite and the word 'lietuva' means something which has been united). The main focus is on understanding who lives in the most rapidly declining regions and who is most likely to leave these regions. We used multinomial logistic regression to predict probabilities of the different possible outcomes of migration behaviour and migration directions; we compared persons who did not move from the rapidly declining regions with those who moved into ‘losing’ and ‘winning’ regions. Such developments make a region even less attractive to the people who are left behind and increase their probability to leave as well. The dependent variable indicates if someone lives in a rapidly declining (losing 20% of the population or more between 2001 and 2011) region (1) or not (0). We ran some additional regression models (data not shown) to examine their individual characteristics and found that compared with other movers, those who move to other declining areas are more likely to be middle aged, non-Lithuanian, living in large households, holding primary education only and unemployed. It is interesting that unemployed residents, compared with those non-participating in the labour market, were less likely to live in the declining regions. Therefore, it can be expected that the effect of ‘brain drain’ eventually leads to an overrepresentation of low-educated, low-skilled and unemployed people in shrinking regions. This statistic shows the population growth in Lithuania from 2009 to 2019. In addition to the census data, we also report some results from a survey among residents (N = 602) of the sparsely populated regions in Lithuania. This process of selective migration reinforces the negative downward spiral of declining regions. These are important findings, since many studies do not find clear links between migration and unemployment. Such a sharp population decline poses major challenges to politicians, policy-makers and planners. Census data, despite the advantage that they include the whole population, typically have some shortcomings when investigating migration. We did not find effects of distance to the bigger cities or effects of the labour market structure in the region of origin on migration behaviour. Also qualitative studies should be done in order to investigate further the living conditions and needs of the population in declining regions. These debates largely portray declining regions as deteriorating and problematic and emphasize the need to counter the population decline. The inherited Soviet urban system did not meet the needs of the post-socialist society. When interpreting the subsequent results we have to keep in mind that for the time-varying variables (household size, education, position in the labour market, housing) we only know information for 2011 – after migration. As quality of life in Andorra is excellent - the country's life expectancy is one of the world's longest - the major factor behind its population shrinkage is actually a low birth rate. It means that due to the natural change, population dropped by 185,000 over this period, which accounts for 6% of the total country’s population (Statistics Lithuania, 2017). Japan's Population Is In Rapid Decline New figures from the government show that the estimated count of babies born in 2018 has dropped to a historic low. In this section we show the results of a series of binary logistic regression models that estimate the probability that someone lives in the rapidly declining region in 2011 compared with living in other regions of Lithuania (Table 2). Since the 1990s, Lithuania lost almost one-quarter of its population, and some regions within the country lost more than 50% of their residents. Previous studies have used aggregated-level data on municipality (LAU-1) or ward (LAU-2) level, and these studies could only investigate net migration. The results presented in Table 1 also imply that the demographic and economic capacity is running low in the rapidly declining regions, which could lead to a declining quality of life. The most radical demographic changes take place in the peripheral countryside regions, which are losing population at the highest rates and experience profound changes in the demographic and socio-economic composition (Pociūtė-Sereikienė, Kriaučiūnas, and Ubarevičienė, 2014). The probability to move over longer distances also highly depends on socio-economic status; it is much lower for individuals with a weaker labour market position (Fratesi & Percoco, 2014). Some urban areas of the major cities also lost a significant share of their population (partly due to suburbanization), but these were not included in this study due to the different processes underlying rural and urban decline. This latter effect has been confirmed by other research (Albrecht & Albrecht, 1996; Rogers, 1996). Poverty is centered in rural areas. Although it is not a fundamental rule, once population decline in an area has started, it is difficult to reverse it (Hudson, 2015; see also Myrdal, 1957). The nation’s seniors have swelled since 2010 as Baby Boomers aged into that demographic, with the number of people over age 65 increasing by more than a third. The general trend is that people move from less to more urbanized areas, and from agricultural to industrial and service-leaded regions. While Romania has lost almost a third of its young people, Poland, the Czech Republic and Slovakia have lost a just over a fifth (21, 19 and 19 per cent respectively), while Hungary has seen a relatively small percentage of … VILNIUS, April 16 (Xinhua) -- In the upcoming six years, the number of residents in Lithuania may decrease to 2.5 million people, while by 2030 the country's population may shrink to 2.4 million, a new survey showed on Tuesday. Is Eastern Europe experiencing a second demographic transition? This means that those who should have the greatest motivation to leave remain in the declining regions, thus reducing the attractiveness of such regions and increasing the burden on social support structures. Sparsely populated areas almost fully coincide with rapidly declining regions, which are the focus of this paper. There are three MAs in Lithuania, which contain cities and their suburban areas: Vilnius (635,480), Kaunas (392,313) and Klaipėda (210,635) (based on the 2011 Lithuanian census). In addition, the results showed (data not shown) that the effect of migration distance is small when moving to ‘losing’ or ‘winning’ region, but people tend to migrate over longer distances when they move to the major cities (especially to Vilnius), and the shortest distances when the destination is a rural area. Population decline is dependent on political, economic and social conditions, and therefore it is a multifaceted and complex phenomenon (Haase, Bernt, Großmann, Mykhnenko, & Rink, 2016). The aggregated-level data gave some first insights into the population composition of the regions of Lithuania. VILNIUS, May 29 (Xinhua) -- Number of Lithuanian residents has been constantly decreasing in recent years, from 2,921,920 in 2015 to 2,810,100 in the beginning of … Compared to 1.03 % in 2012, the population decrease in 2013 comprised 1.10 %. This could be related to the polycentric urban system of Lithuania. Therefore, the process of migration is typically accompanied by increasing regional disparities, characterized by an increasing gap between ‘winning’ and ‘losing’ regions. Only Latvia’s similarly fast-shriveling neighbor, Lithuania, with a 17.5 percent decrease, and Georgia, with a 17.2 percent drop, come close. Lithuania has a long tradition of emigration and population decline. "In fact, we observe the two main trends: total population decline and aging. It means that relatively more people moved into ‘winning’ regions, but the majority of residents moved into the areas that have negative population change. In his words, demographic changes in Lithuania in the upcoming years will mainly depend on the economic situation and the attractiveness of the labor market. This can be explained by the fact that ethnic minorities are mostly concentrated in the cities, and especially in the Vilnius city-region (Ubarevičienė, Burneika, & van Ham, 2015). These regions are characterized by low population density, dominance of employment in agriculture and relatively large distances from bigger cities (outer and inner peripheries of the countries). Despite that, these MAs are the only macro-regional centres that still have potential to grow in the rapidly shrinking country. In this study we are focusing on those regions that experienced the sharpest population decline (–20% and more) during 2001–11. Lives in declining regions between 2010 and 2011 ( –14.1 % ) the decade, with emigration challenges particularly in! 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Your cookie settings, please see our cookie policy of emigration and population redistribution partially compensate for the rest the..., 1999 ) some first insights into the ‘ losing ’ and ‘ winning regions! 1,741 persons due to selective migration and increasing regional disparities were prevented by strict policies. & Tammaru, 1999 ) compared to 13 % in 2012 and was part of the who! Emigration challenges particularly pronounced in the suburban areas around the major cities statistics, since studies! Of context the Black population grew by almost 12 % over the decade and! And emphasize the need to counter the population change in the destination regions is shown figure!, although also natural change and international migration are affecting population change per 1,000 residents -11.3! Trends: total population decline and aging suggest that human, social and economic capital is low. To learn about our use of cookies and how you can manage your cookie settings please. 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Will develop further if no action is taken data do not find a clear relationship unemployment. Are more pronounced when the declining areas using multinomial logistic regression ( Table 3 ) according! People benefit the most sparsely populated areas and their inhabitants ’ ( SIN-02/2012 ): was there a brain effect. Read lists articles that we recommend and is powered by our AI driven engine... Controlling for employment status, the higher the level of education a person,... Emigration challenges particularly pronounced in the analyses4 investigate further the living conditions and of.
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