Four Lithuanian Emigration Waves: Comparison Analysis of the Main Host Countries

Abstract

Lithuania gained its Independent from the Soviet Union after a 50 year occupation in 1990. The country went through an economic, political, social and cultural transformation, which affected the lives of its citizens. All these changes influenced emigration from Lithuania. This chapter reviews four emigration waves of Lithuania from 1990 to 2016. In addition, the chapter presents the results of an empirical study provided with Lithuanian diasporas in the four main destination countries, including the UK, Norway, Germany and Ireland during four emigration waves. The results revealed the main push and pull factors, which influenced people to depart to those countries. Low wages in Lithuania was highlighted as a primary factor in all host countries and its significance grows during all migration waves of modern Lithuania.

1 Introduction

The number of international migrants reached 244 million in 2015 for the world as a whole (United Nations 2015). This number, according to the same source, increased by 41% compared to 2000. This demonstrates the growing relevance of studies a diaspora can have on both the home and host countries even as of 2003, Meyer (2003) wrote that such population movements have become more fluid, with greater opportunities to maintaining links and increased interaction between home and host country. According to Minto-Coy (2011), the past two decades have seen significant growth in the body of work on population movements generally referred to as diasporas.

This chapter focuses on the case of Lithuania. It is counted that one in six citizens has emigrated from Lithuania in the last decade.

Lithuania restored its Independence from the Soviet Union after 50 years in 1990. Independence brought the collapse of existing political, social and economic systems. The change from command to market economy caused many companies’ bankruptcy and rapid growth of unemployment (Stankunas et al. 2006). At the same time, the transition from a communist to democratic system influenced growing inequality among citizens which increased, corresponding with findings of Pridemore et al. (2007) and Cao and Zhao (2010). In addition, the failure of the economy influences the alienation and consequent emigration of citizens (Kaminski 2014), and this situation was seen in Lithuania. Emigration became one of surviving strategies for citizens after such big changes (Kumpikaitė-Valiūnienė and Žičkutė 2017). Lithuanians started to migrate to the United States, which historically was always very attractive for Lithuanian emigrants (Kumpikaitė-Valiūnienė and Žičkutė 2016). Moreover, Lithuania has taken a leading position for emigration among all European Union countries since it joined the EU in 2004. Looking at the Lithuanian migration picture from 1990, four waves of emigration can be identified. Moreover, changes of host countries are fixed during that period.

Therefore, this chapter aims to present a comparison analysis of push and pull factors in the main Lithuanian host countries (the United Kingdom, Ireland, Norway and Germany) according to four Lithuanian emigration waves in period of 1990–2016.

The chapter is organized as follows: the first section gives a brief introduction of four migration situations and their waves in Lithuania during 1990–2016. It continues with Lithuania in the migration picture of the EU. The second section reviews Lithuanian diasporas in the main host countries. It consists of introduction of the main destination countries and an overview of the main economic factors in those countries. The third section presents an empirical study of emigrants in the main host countries the UK, Ireland, Norway and Germany. Comparison analysis according to four emigration waves is developed. Moreover, some “Brexit” issues are reviewed in the third section also. This is followed by conclusions highlighted from the conducted study.

2 Migration Situation in Lithuania

2.1 Four Migration Waves in Modern Lithuania

Officially, almost 150,000 citizens emigrated over the past 10 years and about 670,000 people left from Lithuania during 1990–2011. However, there is no very clear official statistics about emigration numbers. According to Rakauskienė and Ranceva (2013) just 55% of emigrants declared their migration after 1990.

This period could be divided into 4 waves (see Fig. 1):

• 1. Migration after Independence, 1990–2003;

• 2. Migration after joining the EU, 2004 (May)–2008;

• 3. Migration connected with economic crisis and joining Schengen zone, from 2009;

• 4. Migration after joining Euro zone, 2015– now.

Fig. 1

International emigration ratios in Lithuania 1990–2015. Note: Designed by the author in accordance with Source: Statistical office of Lithuania 2016, www.stat.gov.lt

The first migrants from Lithuanian after gaining Independence were members of the Soviet army and their family members repatriating to Russia. In addition, the Jewish community left to Israel as they gained the possibility for free movement. The migration of Lithuanians started in 1992 and 1993, when the country from planned economy started to change to free economy. Many companies closed, the unemployment rate rose from 0% in 1990 and grew to 14% in 1994 and 17.1% in 1995 (official calculation of this indicator started just in 1994). Kaminski (2014) noted that citizens’ lives are influenced when society has political, economic, social and cultural transformations. In addition, during such rapid changes, the inequality among citizens grows (Cao and Zhao 2010). Having such big changes in economic, social and political life, people started seeing migration as a means of survival in Lithuania. Moreover, migration was as a part of a business strategy. Citizens started to go abroad to buy goods and to sell them after returning to Lithuania. The USA was the most attractive destination country for migration in that period. Many students applying for visas and going to the USA with the “Work & Travel USA” program went there and stayed for longer. Other countries with high wages, such as Germany and the UK, were attractive destinations as well. Spain, with its geography and possibility to work in gardens, became attractive for emigrants as well and became a number four destination country for Lithuanians. The majority of migrants were illegal and did not declare during this first phase of migration of Modern Lithuania.

The period when Lithuania joined the EU in May of 2004, was the beginning of the second big wave of migration from Lithuania as the EU labour market opened its borders for Lithuanians. During that period, the United Kingdom became the number one destination for emigrants, leading against the USA. Ireland became number three, Germany fell to number four and Spain to number five. It should be mentioned that unqualified, qualified employees and criminals left Lithuanian during that period. This period’s strategy from “surviving” (in the majority of cases) changed to a strategy of “ensuring the livelihood of retirement”, “better education” strategy and “career” strategy. The biggest flow of migrants was counted in 2005. It was 57,885 declared citizens, in comparison with 26,283 in 2003 and 32,390 in 2006. Emigration flows from Lithuania started to decrease from 2006 to 2009. This decrease was connected with the “gold time” of Lithuania, when the unemployment level decreased to 4.2% in 2007, and wages grew. Economic development was seen very well and stability in Lithuania finally arrived. During the period from 2004 and 2009, on average 16,000 people emigrated from Lithuania annually.

However, this continued just for a few years, before the economic crisis came to Lithuania at the end of 2008. Economic crises as well as imbalances in the wage system created by migration influenced the third wave of migration in Modern Lithuania. According to Kaminski (2014), the failure of the economy influences the alienation and consequent emigration of citizens. The unemployment level jumped 2% and people started seeing emigration again as a “survival strategy”. This period had the highest levels of emigration. However, it should be mentioned that it started to be more declared at that time. Eight three thousand declared their departure in 2010 and 54,000 in 2011. This huge growth of declared migration was connected with new laws for all permanent residents of the country to pay compulsory health insurance. Therefore, many people who did not register their departure earlier did this in 2010. We can see the number of emigrants increased by several times in comparison with previous period. Young people started to migrate because of better education strategies. The UK kept its leading position as the number one destination country. However, Ireland took number two, Germany number three and a “new” destination country, Norway, went to position number four. The USA stayed number five and Spain went in to sixth position. It looked as though economic stability had already returned and migration flows would stop or at least decrease. As Pridemore et al. (2007) mention after the adoption of new systems economic and social equilibrium had to return and emigration should decrease.

However, reality showed it differently. Lithuania joined the Eurozone from 2015. Citizens felt quite a rapid increase of prices and almost no change in wages. It appeared as though Lithuania still had not provided sufficient well-being for its citizens. Emigration continued in 2015 and 2016. Forty-four thousand five hundred and thirty-three citizens left Lithuania in 2015 in comparison with 36,621 citizens in 2014. In addition, the emigration number increased in 2016 up to 50,978. Statistics show that the fourth emigration wave of Modern Lithuania started again. Therefore, it is evident that emigration as a “survival strategy” continues in Lithuania. In addition, more cases of a “new start” strategy appeared.

2.2 Lithuania in the Migration Picture of the Current EU

Migration flows of all today’s EU members during 1990–2014 are presented in Fig. 2. According to this information we can depict countries with positive migration flows (14 countries), with negative migration flows (4 countries) and with changing flows (10 years) in the analysed years. The biggest immigration number per 1000 inhabitants was fixed in Cyprus and Luxemburg. Those two countries had in average more than 10 immigrants per 1000 citizens in analysed years. Malta, Austria, Sweden and Germany also had high immigration rates. In addition, Belgium, Denmark, Netherlands, United Kingdom, Finland, Italy, Hungary and France are countries with positive inflow of emigrants too. Czech Republic and Slovakia are the countries where migration flows changed from negative into positive in 2000 and 2014. Ireland, Portugal and Spain were changing from emigration to immigration and finally again to emigration countries. However, Poland, Estonia and Slovenia, which usually are known as emigration countries, had a positive inflow in one of analysed years. Romania, Latvia and leading Lithuania with Bulgaria had negative outflows of migrants in all cases.

Fig. 2

Migration flows in Europe in 1990–2014 (number of migrants per 100 citizens). Source: Designed and calculated by authors in accordance with the Statistical office of the European Union Eurostat (2015a)

Comparing Lithuania with other Baltic States (Latvia and Estonia), we can see that migration from Estonia is low, from Latvia it increased in the last years and from Lithuania is high for the last 25 years. Moreover, these are for mostly non-economic reasons as political and economic changes were very similar in all three Baltic States. However, it could be explained by a feeling of injustice. For example, a study of Zickute (2013), based on Burkhauser et al. (1996) proposed criteria, which tells that the middle-class should include those inhabitants, whose income exceeds the poverty risk line by 2–5 times showed that Lithuania’s distribution in inequality increased rapidly from 2007 to 2011. “There was 40% of the population belonging to the middle class in 2007, while only 9% of middle class and even 90% of poor citizens in 2011” (Zickute 2013). Twenty seven percent of Latvians were in the middle class and 70% in the working class in Latvia in 2007 and 2011. Estonia, according to its data had a “fair” society class distribution. The majority of the population were respectively 50 and 60% in the middle class in 2007 and in 2011. In addition, it could also be an image formed by media that justice is missing. This is reinforced by the media, forming a negative opinion. However, it needs a deeper analysis.

3 Lithuanian Diasporas in the Main Destination Countries

3.1 The Main Destination Countries of Lithuanian Emigrants

Looking at the main destination countries (see Fig. 3), the top six countries are highlighted. These results already we presented shortly in the subsection “The main emigration waves in Modern Lithuania” of this chapter. The United Kingdom, Ireland, Germany, Norway, the United States and Spain according to the statistical office of Lithuania were highlighted as the main destination countries. However, even looking at statistics of 2001–2015, there are changes of destination countries. The popularity of Norway started to increase during and after the economic crises. The United States was more attractive before Lithuania became an EU member in 2004 and got free movement in it later. The popularity of the UK increased dramatically when Lithuania joined the EU. According to the Lithuanian statistics department, around 147,000 citizens moved to the UK in 2004–2015. The newest data was taken for selection Lithuanian diasporas for analysis. Therefore, the UK, Ireland, Germany, Spain and Norway were selected and presented in more details in this chapter.

Fig. 3

Emigration from Lithuania by its destination countries. Note: Designed by the author in accordance with Source: Statistical office of Lithuania 2016, www.stat.gov.lt

3.2 Economic Factors in the Main Destination Countries and Their Connection with the Migration Flows

Figure 4 demonstrates minimum wages and people at risk of poverty in 2015 in Lithuania and its main emigration destination countries in Europe. Data shows that the minimum monthly wage is higher in all destination countries and percent of people living at risk of poverty is lower comparing Lithuania with other presented countries. The Lithuanian minimum wage is more than twice as low as in Spain, which has double the difference with Ireland, Germany and the UK.

Fig. 4

Monthly minimum wages in bi-annual data and PPS index in 2015. Source: the statistical office of the European Union Eurostat 2017. Note: Norway is not included, as it does not have fixed minimum monthly wage

The average of the risk of poverty or social exclusion was 24.5% in Europe in 2014. In comparison (see Fig. 4) just 15% of citizens in Norway lived at the risk of poverty and social exclusion when this percent was 27.3% in Lithuania and 28.6% in Spain in 2015.

GDP per capita in PPS could be the explanation of not stopping emigration in Lithuania (see Fig. 5). Purchasing power standard increased from 49 (in 2004) up to 75 (in 2015) in Lithuania. However, it is still lower in comparison with Lithuanian emigration destination countries. Norway, which became very attractive for Lithuanian emigrants in last decade, has its PPS at 160—more than two times higher than in Lithuania. In addition, it is an interesting fact that Spain, even though its minimum wage and PPS are at a very middle level, is still attractive for Lithuanians because the mentioned indicators are higher than in Lithuania and moreover, Spain has more attractive weather for Lithuanians.

Fig. 5

People at risk of poverty or social exclusion and GDP per capita in PPS in Europe in 2004 and 2015. Source: the Statistical Office of the European Union Eurostat (2015b) and (2016)

According to a regression analysis depicting the main economic factors in Lithuania, it was found that the unemployment rate, the Gini coefficient and Tax Freedom Day explains 70.7% of emigration reasons (Kumpikaite and Zickute 2013). The biggest influence for the emigration rate from highlighted indicators has the Gini coefficient and the lowest—unemployment rate. The Gini coefficient demonstrates income inequality When the Gini coefficient is higher than 30, inequality of incomes becomes an important issue in the country. The comparison of those main factors such as the Gini coefficient, Tax freedom day and unemployment level are presented in Table 1.

Table 1 Some economic factors of Lithuania and destination countries in 2005–2015

According to that data, the Gini coefficient is lower in all destination countries with some exception in Spain in comparison with origin Lithuania. The lowest Gini index is fixed in Norway and does not exceed 30 in 10 years, and Germany, where the index reached a level of 30 in 2007–2008 and 2014–2015. The UK, even as the main destination country for Lithuanians has its Gini coefficient at 30 but it is lower than in Lithuania. In addition, looking at tax freedom day, it is the shortest in the UK and the longest in Germany and Norway. Tax freedom or liberalization day demonstrates how long European employee in average should work for taxes. It is seen that tax freedom day arrives to Germany and Norway only in July. It means that employees work for taxes for more than a half of the year there. The Lithuanian tax freedom period became shorter in the explored 3 years and should arrive in May in 2017. It is forecasted that tax freedom day will be the earliest in comparison with the other explored countries in Lithuania in 2017. However, Lithuanians had to work 1 month longer in comparison with employees in the UK, Ireland and Spain in 2011. The unemployment rate as well as the Gini index could explain the increased popularity of Norway as the destination country to Lithuanian migrants. Once again, the unemployment rate was higher in Lithuania after economic crises in comparison with all analysed destination countries during most of that period. The exception was 2006–2008—the “golden years” of Lithuania. However, the unemployment rate was similar in Ireland as in Lithuania but Lithuanians still kept going there. Notwithstanding, remembering the minimum wage and PPS in Ireland (see Fig. 4) it was much higher in Ireland than in Lithuania. However, statistical data demonstrated that the economic situation became worse in Spain. Therefore, it could be the reason of decreased Lithuanian emigration flows to that country.

4 Empirical Study of Emigration Waves in the Main Lithuanian Host Countries

4.1 Push and Pull Factors as Theoretical Background for a Study

As the basis of the study, the push-pull factors were taken (see Fig. 6). Kumpikaitė-Valiūnienė and Žičkutė (2017), which present these factors in more detail. According to Martin (2003) individuals are motivated and sustained by three major types of influences. Positive and negative factors in the origin area are called demand-pull factors, positive and negative factors in the destination area are called supply-push factors and the third network factors connecting origin and destination countries. Early decision-making theory (Lee 1966), cited by Maslauskaitė and Stankūnienė (2007) identifies also personal factors, such as family and personal sensitivity, intelligence, and knowledge about conditions in other countries. According to the push-pull theory (Cohen 1996) people depart because of social and economic forces in the place of origin, or because they were attracted to the place of destination by one or more social and economic factors there. The importance of different factors depends on every person and can change in life periods. According to the Network theory (Massey et al. 1993), the existing migrants’ network helps to find a job, place to live and to decide the mean of travelling (Kumpikaitė-Valiūnienė and Žičkutė 2017).

Fig. 6

Push and pull economic and non-economic factors

Regarding the case of Lithuania, such migration networks and created support mechanisms in the destination countries work as pull factors that facilitate the realisation of migration intentions (Sipavičienė and Stankūnienė 2013). Around 80% of Lithuanian residents have migrants in their close social environment (family, friends, relatives, etc.) and 80% of departing citizens find a job abroad through these networks (Sipavičienė 2011). Just an example of one family with six children in Lithuania: one sister and a brother went to the UK as tourists in 1999 and stayed illegally there. One other sister also moved there after several months. Later, when Lithuania joined the EU, two other sisters moved after their school graduation and the mother joined them too. Finally, the oldest sister with her two teenagers followed her family and departed to the UK in 2011. This situation demonstrates that almost every resident of Lithuania could tell similar stories about their relatives, friends or co-workers.

4.2 Data Collection and Sample

One thousand three hundred thirteen respondents from the UK, 692 from Norway, 322 from Germany, 276 from Ireland and 95 from Spain participated in the poll conducted on 24 October 2016 and 29 January 2017. The total selected sample was 4140 during that period. The survey was conducted via Internet contacting Lithuanian diaspora centres in different countries, sharing a link to the questionnaire in social media and asking everyone to spread that information. The questionnaire was prepared based on push-pull factors presented in the previous section. The comparison according to the emigration period and push and pull factors was made in accordance with these countries.

Statistical analysis was performed using IBM SPSS Statistics 23. Percentage and crosstabs analysis for push and pull factors chosen by host countries and emigration waves was used.

The limitation of this is that a small sample of respondents of some periods from some countries took part in this study (see Table 2). Therefore, results are not very reliable. Moreover, Spain was excluded for further analysis for a small sample to look at different emigration waves. Almost 75% of respondents were females. Looking at the respondents’ age, the majority of them is at 20–34. This corresponds with statistical data, telling that these groups make up the biggest group departing from Lithuania. However, it should be noted that 32.4% at the age of 40–60 participated in the study in Germany. Speaking about the respondents’ education, the most educated respondents live in Ireland and Germany.

Table 2 Number of respondents in accordance with countries and migration waves

4.3 Comparison Analysis of Lithuanian Diaspora in the UK, Norway, Germany and Ireland

Analysing respondents according to their previous and present occupation (see Table 3), we can see that the majority of them were students, specialists and service employees and sellers. It demonstrates that a part of Lithuanians leave the country directly after graduating a high school, college or university. Generally, just a number of students, the unemployed, housewives, army and service employees decreased, comparing respondents’ previous and current occupations. Housewives mostly left the country because of family reasons, following their husbands working abroad.

Table 3 Number of respondents in accordance with their previous and current occupation

The biggest employment fields, which explored migrants were employed as service employees and sellers, specialists, and unskilled workers. It should be mentioned that the biggest changes can be seen in unskilled workers. Their number increased from 153 up to 472. However, the number of managers and self-employed individuals increased quite dramatically also (managers from 147 up to 246 and self-employed from 182 up to 236). A high change of managers is seen in the UK (from 29 up to 94) and Ireland (from 7 up to 21). The number of unemployed individuals mostly increased in the UK (from 60 up to 173) and Norway (from 24 up to 98). In addition, Norway employed qualified specialists of agriculture more than other countries.

Looking at the attractiveness of destinations based on previous occupation, some insights could be given. Ireland was the most attractive country for service employees and sellers (26.7%) among all destination countries. Students selected the UK the most. Even 23.2% of all the UK respondents studied before they left Lithuania. Qualified workers and masters selected mostly Norway and the UK. In addition, Ireland was more attractive for unemployed persons.

Push factors are presented in Table 4. Low wages in Lithuania became more and more important in the UK, Norway and Germany in every wave of migration. This factor remains the most important among all other push economic and non-economic factors. Personal life conditions was the second most important factor to all countries and mostly pushed respondents to depart to Norway. 45.5% of respondents selected this factor in comparison with less than 40% in other destination countries. In addition, 54% of people highlighted the importance of personal life conditions in Norway in the period 2004–2008. Price politics of products is the third most important economic push factor among all destination countries except Norway. Wage difference and income inequality pushed people to migrate rather than price politics to Norway and Ireland. This factor’s importance grew considerably after 2015 in Ireland. This corresponds with the Gini indexes in those countries as well (see Table 2).

Table 4 Economic and non-economic push factors

Speaking about non-economic push factors, Family reasons were the most important in Norway and Germany. The desire to change dominates for more than 30% of migrants before Lithuania joined the EU in Germany. Study and education systems influenced people to leave to the UK at almost 20% and to Germany 13% of respondents. In addition, 28% of respondents left to Germany because of studies in the period 2004–2008.Study and education systems looked the least attractive in Norway. Social conditions were evaluated as the highest in Germany (25.2%). Political corruption in Lithuania moved almost 32% of respondents to move to Norway. However, this percentage is more than 20% for other countries as well. In addition, a fact of political corruption was more important during previous emigration waves. However, Norway is something of an exception, as political corruption pushed to move people in the second and third waves.

Pull factors are presented in Table 5. Higher incomes are the main economic pull factor in all explored countries. Norway is the most attractive in accordance to this factor. 66.7% of respondents selected Norway because of its income possibilities. This evaluation is the highest among all push and pull economic and non-economic factors among the explored countries. In addition, it should be mentioned that this factor is more important in every way in the UK. However, it stayed almost the same in Norway starting from the second emigration wave, when Norway’s popularity grew. The UK is much more attractive because of the possibility to get a job there. Its importance also grew during every migration wave in this country. However, the importance of this factor increased for departing to Norway and Germany in the last of analysed periods. In addition, the UK and Germany are preferred because of lower taxes and lower costs of living.

Table 5 Economic and non-economic pull factors

Going next to non-economic pull factors, it is evident that relatives living in Ireland and the UK are the most important factors. This was especially important for respondents who left to Ireland in 2004–2016. In addition, this factor is the most important among all economic and non-economic factors in Ireland. More than half of all respondents highlighted the importance of relatives living in Ireland when deciding to migrate. The main reason which pulled to move to Germany, was a higher possibility for self-development (34.2%). This measurement was the highest in accordance with other factors. However, Norway was even more attractive because of this factor (42.9%). The second most important factor was the possibility of self-realisation (31.3%) in Germany. In addition, Germany was leading because of its health care (26.5%), whereas the health system in Ireland attracted just 4.9% of migrants. Moreover, Germany (13.5 and 16.1%) and Norway (13.8 and 20.9%) pulled more Lithuanians because of their prestige and political stability. Norway and Germany were selected for their higher tolerance in comparison with other countries too. Language importance was highlighted by one third of respondents, who migrated to the UK. Weather did not look attractive and almost did not influence decisions to depart among surveyed respondents in analysed countries, as all evaluations were lower than 10%. Moreover, the distance from the home country was not the reason for any respondent from Ireland. However, this is not surprising, as it is more complicated to reach it in comparison with other three countries.

4.4 “Brexit” Influence on Lithuanian diaspora

According to Statistics Lithuania (2016), 147,100,000 residents migrated to the UK during 2004–2015. It is 40.2% of all declared net migration during that period. This is 5.1% in comparison with all population of Lithuania. This percent was lower (4.7%) in 2014. However, “Brexit” could have an influence on Lithuanian migration flows to the UK. “Economists” (2016) writes: “According to the experts consulted, if Britain were to leave the EU, Lithuania would see a decline in UK-bound exports and a decrease in remittances from Lithuanians living in Britain after the end of the withdrawal process, which would take approximately 2 years. Moreover, future emigrants to Britain would face problems in moving to the country and finding employment.”

In addition, according to “Standard & Poor’s” (2016) Brexit will have the biggest impact on Lithuania in comparison with all Eastern European countries. This will happen because of the biggest Lithuanian diaspora living in the UK. According to this agency, 5.4% of Lithuanians live there and their transfers to Lithuania are around 1.2% of the GDP. Therefore, according to “Standard & Poor’s” evaluation, Lithuania is the most vulnerable country (index—3.44), Latvia—the second (3.32), Hungary—the third (2.28), Poland—the fourth (2.03), Slovakia—the fifth (1.69), Estonia—the sixth (1.63).

However, it does not appear to be entirely true. According to the bank of Lithuania, transfers from the UK were 213.5 million Euro or 0.6% of GDP in 2014 and around 300 million Euro or 0.8% of GDP. In addition, a part of Lithuanians living in the UK probably will move to other countries, such as Ireland or Norway due to “Brexit”. Those people would continue transferring money to Lithuania. Moreover, on the other hand, re-emigrants would have an impact on the GDP working in Lithuania.

The study presented in this chapter included questions about “Brexit” as well. Those results highlighted the following features connected with “Brexit” of Lithuanian diaspora living in the UK. One hundred and thirty-three (133) respondents moved from the UK to other countries and 57 returned to Lithuania. In addition, 111 respondents have different concerns connected with “Brexit” and waiting for the UK decisions for emigrants. In addition, some respondents were motivated to move businesses to other countries or to get citizenship in the UK, 1 respondent returned to Lithuania and 2 moved to other countries from Ireland. Four other respondents from the UK mentioned the decrease of the value of the pound in comparison with the Euro, one got married with a UK citizen to get citizenship and 2 mentioned increased racism. This corresponds with Cambridge News (2016) information about Lithuanian emigrant: “Laura Gudaiskiene, 31 claims she’s become a victim of racial abuse following the Brexit vote by locals telling her to “go home”.” However, the majority of respondents do not feel any changes and any influence of “Brexit” while the study was conducted and still were awaiting for future decisions concerning emigrants by the UK government.

5 Conclusion

This chapter has sought to give an overview of Lithuanian migration after its Independence in the main host countries. More than 670,000 people left from Lithuania after it gained its Independence in 1990. The situation had to stabilize when new economic, political and social systems were established and stabilized in the country. However, looking at the example of Lithuania, we see that expected economic wealth and prosperity did not arrive (Kuzmickaitė 2003).

The conducted study revealed that economic factors are the main motives Lithuanians leave to explored host countries. Moreover, the importance of pull factor “low wages” in Lithuania grew during every analysed period. In addition, the results of the study showed growing importance of income inequality as well. However, results depicted growing importance of such factors as possibility of self-development, higher tolerance and higher possibilities for self-realisation. In addition, self-realisation was important for 60% of respondents who departed to the UK before Lithuania joined the EU in 2004. Moreover, comparison analysis of statistical data in analysed countries highlighted that the Gini coefficient and unemployment levels were the second highest in Lithuania after Spain. It explains why Lithuanians leave to those countries and why the popularity to move to Spain decreased in the last decade.

However, growth and inequality is a huge issue in the EU, and migration of this dimension is not a sustainable solution for the leaking side. Growing emigration rates brought different problems to Europe, such as increased terrorism, social alliance and end of the EU equality. “Brexit” was just the first exit, which could be followed by France after terrorist attacks in Paris and Nice. Such political changes could have a huge influence on migration diasporas among all Europe. “Brexit” will have an impact not just on the EU relations with the UK but also on migrants living in the UK. As it is the main destination country for Lithuanians, “Brexit” is important for them as well as for Lithuania. Lithuanian emigrants are trying to get citizenship of the UK in order to feel safe in the UK. However, according to Lithuanian rules, when a Lithuanian gets citizenship of other country, he or she loses a citizenship of Lithuania. Therefore, this will influence a decrease of official Lithuanian citizens and they probably, being foreign citizens, will not have a big interest in returning to Lithuania even in the distant future. However, even though “Brexit” is announced, Lithuanians continue leaving to the UK. It means that Lithuanian diaspora there as well as social media and relatives have an important impact for people making a decision to migrate to the UK. However, this presumption needs deeper analysis and a new study evaluation of diaspora and social media influence on a decision to migrate is in the nearest plans.

The current situation is a very important issue for Lithuania. Not stopping emigration for 25 years and “Brexit” influenced dramatic demographic changes, which continue. We see the drop in Lithuania’s population, citizens aging, lack of qualified specialists and other problems. It arises as a necessity of important solutions of stabilisation of the demographic situation in Lithuania. Therefore, the conducted study of the main emigration host countries highlighted the main push and pull factors, which could be used for looking into the means for solutions.

Therefore, it became a prior field for a new government to look for the means of decreasing emigration and situation stabilisation. The results of this study have a practical impact in providing important material analysing and discussing emigration issues and looking for the means of stopping emigration and increasing the number of returnees. Concluding, results of the study will be useful for preparing a plan of a means on the state migration policy level but also on the corporate and labor policy levels for the purpose to “prevent” and “heel” emigration.