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Transnationalism and Settlement of Latvian Emigrants in the Nordic Countries

Author:

Inese Šūpule

University of Latvia, Riga, LV
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Abstract

The intra-European migration flows have fostered debates about the intentions of migrants to settle in their destination country or return to their countries of origin. Based on a quantitative analysis of survey data (N = 1391), this article presents a typology of migration patterns among migrants from Latvia in the Nordic countries. Using two dimensions—attachment to the destination country and attachment to the country of origin—the article identifies and characterises the following four migration patterns: (1) bi-nationals, (2) settlers, (3) footloose migrants and (4) isolated migrants who focus on their country of origin and are willing to return (separated).

How to Cite: Šūpule, I., 2021. Transnationalism and Settlement of Latvian Emigrants in the Nordic Countries. Nordic Journal of Migration Research, 11(2), pp.124–141. DOI: http://doi.org/10.33134/njmr.424
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  Published on 04 Jun 2021
 Accepted on 05 Jan 2021            Submitted on 19 Nov 2019

Introduction

Some years ago, the debate on intra-European migration introduced the concepts ‘liquid migration’ (Engbersen, Snel & DeBoom 2010; Engbersen & Snel 2013) and ‘incomplete migration’ (Okólski 2001). According to Engbersen and Snel (2013), liquid migration is a typical phenomenon of post-accession migration. It is strongly labour-motivated and facilitated by the free movement of workers within the EU. Its main characteristics are the temporality of a stay abroad and invisibility because of the temporal nature of such residence. The concept ‘incomplete migration’ refers to migrants who work abroad but ‘live’ in the country of origin, where their families remain and to which they frequently return (Okólski 2001). Recent studies point out that these patterns have changed and that one should talk about the diversity of labour migration patterns and about the trend of transition to longer-term settlement (Friberg 2012; Hazans 2011, 2019; Bygnes & Erdal 2017).

What characterises migration patterns among migrants from Latvia in the Nordic countries? Is it a lasting temporariness (Grzymala-Kazlowska 2005) or do they have intentions to settle permanently? How do these migration patterns relate to transnationalism, understood as ‘a growing number of persons who live dual lives: speaking two languages, having homes in two countries, and making a living through continuous regular contact across national borders’ (Portes, Guarnizo, & Landolt 1999: 217)? These are issues that have not yet been explored in detail, especially in the context of the Latvian migrants in the Nordic countries. To fill this gap, this study focuses on the attachment of the Latvian migrants to the destination country and to the country of origin, and the return intentions of the Latvian migrants.

A sense of belonging and attachment forms within and in relation to a specific setting and different destination countries, as well as different countries of origin and changing migration policies, provide the context for migration experiences. The Nordic countries offer better working and living conditions compared to Latvia, and abroad salaries are an important reason for the most labour emigration from Latvia (Hazans 2019). Latvia as one of the poorest EU countries can hardly compete with the Nordic countries in economic terms and standard of living. Despite the economic growth and improvement of the labour market situation Latvia is experiencing in recent years, the main challenges Latvia faces are population decline, high inequality and uneven development, as growth in peripheral regions has lagged behind the Riga region (European Commission 2019). At the same time, the development of closer ties with the Latvian emigrants and support for return migration have received a great deal of attention in the mass media and policymaking in Latvia. This seems largely to be related to the hopes of politicians that return migration might be an instrument for meeting labour market demands while avoiding an inflow of immigrants (Kļave & Šūpule 2019). Various diaspora forums, conferences and other events are being organised for the purpose of cooperation, aiming to promote a sense of belonging among emigrants and their offspring.

Although Latvia as a sending country aims to maintain a sense of national belonging among the emigrant community, destination countries are fostering the social integration of migrants. This may result in a situation of being integrated in two localities and feeling attachment to two national settings, in other words, in a form of transnationalism. However, the migrant may also fail to integrate. In this situation, he or she may maintain a sense of belonging to Latvia. Alternatively, he or she may end up not being integrated in either locality. As these phenomena might concern a growing number of emigrants from Latvia, it is worth looking at the processes of transnationalisation and a sense of belonging among the Latvian emigrants.

Therefore, this article explores various aspects of attachment to the country of origin and to the host country and identifies migration patterns of the Latvian migrants in the Nordic countries. As will be revealed in the following, there is no one unified migration pattern but a diversity and a complex set of factors underlying these types. The online survey of 1391 Latvian migrants in the Nordic countries was used for the empirical analysis. The conceptual framework and methodology of the analysis are based on the typology of labour migration patterns among Central and Eastern European migrants in the Netherlands (Engbersen et al. 2013). The typology of the Latvian migration patterns is constructed by two dimensions: the degree of attachment to the country of origin and that to the host country.

The article is structured in the following way: After describing the analytical framework, context and data, the empirical findings are presented. Throughout the analysis, the four ideal–typical patterns of migration based on two dimensions (the degree of attachment to the country of origin and that to the host country) are tested. The analysis includes the development of characteristics of various Latvian migration patterns (in terms of time of emigration, plans to return to Latvia, gender, education, labour market position and others). The discussion on empirical findings contributes to pointing out similarities and differences with the findings on patterns of migration among the migrants of Central and Eastern European Countries and their integration in the Dutch society (Engbersen et al. 2013).

Theoretical Background

Previous studies show that there are a lot of concerns about migrants’ attachment, both to their country of origin and to the host country. In many articles, analysis of this attachment has been conceptualised as an integration–transnationalism matrix (Snel, Engbersen & Leerkes 2006; Erdal & Oeppen 2013; Engbersen et al. 2013; Carling & Pettersen 2014), arguing that integration in the host society does not exclude dual orientations or bifocality reproduced by migrants (Vertovec 2004).

Immigrants’ adaptation and attachment to the receiving country in the sociological tradition and in social psychology have been referred to by many concepts, for example, assimilation, acculturation, incorporation and integration (Alba & Nee 1997; Portes & Rumbaut 2001; Guibernau & Rex 2010). The first acculturation theory was elaborated by Thomas and Znanecki in their study of Polish migrants in America (1918–20). Probably, one of the most widely used theories of acculturation is that of John W. Berry. According to Berry (1997, 2001), there are two independent dimensions of acculturation strategies, namely, the degree to which immigrants preserve their ethnic culture and identity and the degree to which they adopt the host country’s culture, which can be measured by the frequency of ethnic relations with the other culture.

At the same time, scholars of transnationalism point out that more and more migrants maintain multiple links to their countries of origin, supporting relatives, investing in their home communities or engaging in political work related to their home countries (Pries 1999: 3). The improvement of global transportation and information systems (Skype, social networks, etc.) helps to retain closer ties with the country of origin. However, migrants’ attachment to their country of origin is not evenly spread among migrants, nor is migrants’ attachment to the host country, and this opens room for various typologies of migrants’ attachment. For example, several qualitative studies present various typologies among Polish migrants, and the main dimensions they use for their analysis concern the migrants’ intentions to stay in the host country and their family ties (Düvell & Vogel 2006; Eade, Drinkwater & Garapich 2006; Grabowska-Lusinska & Okólski 2009). The various types of labour migrants are described quite similarly with some particular differences: (1) migrants oriented on returning, circular migrants, (2) settlers or stayers, (3) transnational migrants with a strong bi-national orientation, (4) highly mobile global nomads with cosmopolitan orientation, ‘searchers’ and others.

The study of Andrzejewska and Rye on Polish migrants in rural Norway (2012) shows that particular groups of intra-European migrants can be marginalised in transnational social space. When operating in-between the cultures of the sending and receiving countries, some migrants fail to keep integrated in both.

In their study, Engbersen et al. (2013) suggest calling this marginalised group with weak attachments to both the home and the destination country as footloose migrants. They develop a typology of labour migration patterns among migrants in the Netherlands from Poland, Bulgaria and Romania based on two dimensions: attachment to the destination country and attachment to the country of origin. Their findings based on quantitative surveys suggest that there are four basic migration patterns: (1) circular migrants (mostly seasonal workers) with weak attachments to the country of destination, (2) bi-nationals with strong attachments to both the country of origin and that of the destination, (3) footloose migrants with weak attachments to both the country of origin and the destination country, and (4) settlers with weak attachments to the country of origin. Nevertheless, these four patterns are not exclusive, and they suggest that it is possible for there to be a range of intermediate forms as well.

Another approach is outlined by Dahinden (2010), who is taking a deeper look at transnational formations as the effect of the combination of mobility and locality. To the analysis of local ties in a receiving country and sending country, she has added the dimension of transnational physical mobility (Dahinden 2010: 58). She scrutinises several types of transnational formations. For example, one type is characterised by low physical mobility and a high degree of local ties (localised diasporic transnational formations). Another type is combining high physical mobility and high locality (localised mobile transnational formations). Transnational mobiles refer to people who are highly mobile but have a low degree of local anchorage. Finally, transnational outsiders display both low mobility and a low degree of local anchorage. This typology provides interesting insights into the transnational formations of mobility and locality. However, she has paid less attention to the migrants’ anchorage in the sending country.

Mentioned studies on the different typologies of migration patterns after EU enlargement allows one to conclude that both theoretically and empirically it is grounded to base analysis of migration patterns on two dimensions of attachment. The attachment of migrants to the destination country can be either weak or strong, as well as the attachment to the country of origin. By combining the two dimensions of attachment, Engbersen et al. (2013) developed the analysis model of four combinations of ideal-types, and conceptually this seems the most comprehensive and appropriate model for further studies. Therefore, this approach is used as a theoretical and methodological guide for analysis of migration patterns among emigrants from Latvia.

Contemporary Migration Trends from Latvia to the Nordic Countries and Analysis Thereof

During the last 20 years, immigration from the Baltic countries to the Nordic countries has increased significantly. According to the Nordic Statistics database (2019), there are more than 68,000 Lithuanians, 62,000 Estonians and 26,000 Latvians in the Nordic countries. The largest Lithuanian communities can be found in Norway and the largest Estonian ones in Finland (Figure 1). Latvians are not concentrated in any particular Nordic country, but the highest proportions live in Norway and Sweden.

Figure 1 

Population 1 January by reporting country, birthplace and time. 1999 and 2019. Birthplace: LT—Lithuania, LV—Latvia, EE—Estonia.

Source: Nordic Statistics database 2019.

Since 1999, the number of Latvians living in Norway has increased from around 280 to more than 10,000. The number of Latvians living in Sweden has increased from around 2100 to more than 8000. The increase of Latvians is comparably smaller in Denmark and Finland, where 5230 and 2382 Latvians, respectively, live. With regard to the gender distribution of Latvians in the Nordic countries in 2019, there were slightly more men than women (52% compared with 48%). Most Latvian emigrants to Nordic countries are aged 20–39 (Nordic Statistics database 2020).

Previous research on migration from Latvia suggests that, over the past decade, the nature of emigration has changed from short-term emigration to the permanent emigration of the whole family (Hazans 2011, 2019). Several studies have focused on the sense of belonging, identity and attitudes of the Latvian migrants. Focusing on practices and discourses of belonging, Kaprāns (2019) shows that the transnational aspect of identity and long-distance nationalism become normal among the Latvian emigrants in the UK, the favoured destination of the Latvian migrants. In their analysis of attitudes among the Latvian emigrants who are active users of social networking sites, Bucholtz and Sūna (2019) argue that migrants tend to selectively incorporate identity elements from Latvia and their host countries, and this promotes the formation of hybrid identities. A quantitative study of the Latvian emigrants (Koroļeva 2019) provides a description of the determinants of the sense of belonging to the host country’s society and Latvia. Koroļeva has found that the level of subjective life satisfaction and having a family back at home are important for strengthening the sense of belonging to Latvia. Most of those who have a weak sense of belonging to Latvia emigrated during or after the years of economic crisis of 2008–2009 and have left Latvia with a sense of resentment (Koroļeva 2019: 84).

Thus, a sense of belonging, the Latvian migrants’ attachment to the destination country and attachment to the country of origin have not been ignored in the previous migration studies. Still, there have been no quantitative studies on the various migration patterns of Latvians in the Nordic countries. Therefore, the construction of migration patterns by two dimensions—the degree of attachment to the destination country and to the country of origin—based on a quantitative analysis of survey data complements the previous studies on the Latvian migrants in the Nordic countries.

Data and Methods

The data source used for the analysis is the largest emigrant survey of the Latvian emigrants organised by the University of Latvia from August to October 2014 (More about the survey Mieriņa 2019). To engage with the Latvian emigrants, an online-based survey method was used. As suggested by other researchers, this is an appropriate data collection method to obtain a geographically dispersed, large sample under time constraints (Sue & Ritter 2012; McGhee, Moreh & Vlachantoni 2017; McCollum et al. 2017). To acquire more respondents, a diverse set of respondent recruitment channels were used: diaspora organisations, diaspora media, the largest social networking sites (draugiem.lv; Facebook, odnoklassniki, vkotankte), the largest online news portals in Latvia and the Latvian embassies abroad. The questionnaire was prepared in three languages: Latvian, Russian and English. However, the data collection method and self-selection of respondents to participate in the online survey limit the representativeness of the survey.

For the purposes of analysis of the Latvian migration patterns in the Nordic countries, a subsample has been developed. This subsample includes emigrants from Latvia who live in Norway, Sweden, Denmark and Finland. In total, the subsample has reached 1391 respondents, which represent 7.5% out of 18,569 Latvian emigrants older than 14 living in the Nordic countries in 2014 (Nordic Statistics database 2020). Table 1 presents the comparison between the subsample and the official Nordic statistics of the Latvian born inhabitants in every of four countries. Although the proportion of the host countries and age groups in the subsample corresponds to the official statistics, women are slightly overrepresented in this survey (Table 2). The greater volume of female respondents may be explained by two interrelated factors: women are more active users of online social media websites and they have a greater propensity to participate in scientific research (McCollum et al. 2017).

Table 1

Comparison of the statistics and the survey sample of the Latvian emigrants in four Nordic countries: gender and age (2014).

Norway Statistics N* Sample N** Statistics % Sample %

Gender Male 4685 221 60 41
Female 3166 324 40 59
Age 15–24 1033 64 13 12
25–34 3421 220 44 40
35–54 3132 239 40 44
55+ 265 22 3 4
Total (15+) 7851 545 100 100
Sweden

Gender Male 2202 145 41 38
Female 3187 238 59 62
Age 15–24 826 44 15 11
25–34 1904 145 35 38
35–54 1742 151 32 39
55+ 917 43 17 11
Total (15+) 5389 383 100 100
Denmark

Gender Male 1776 85 44 28
Female 2231 221 56 72
Age 15–24 1295 93 32 30
25–34 1620 127 40 42
35–54 952 79 24 26
55+ 140 7 3 2
Total (15+) 4007 306 100 100
Finland

Gender Male 566 52 43 33
Female 756 105 57 67
Age 15–24 242 20 18 13
25–34 486 48 37 31
35–54 501 76 38 48
55+ 93 13 7 8
Total (15+) 1322 157 100 100

* Statistics: Population as of 1 January 2014. Source: National statistical institutes.

** Survey sample: The Latvian emigrant survey organised from August to October 2014.

Table 2

Comparison of the statistics and the survey sample of Latvian emigrants: host countries, gender and age (2014).

Host country Statistics N* Sample N** Statistics % Sample %

Norway 7851 545 42 39
Sweden 5389 383 29 28
Denmark 4007 306 22 22
Finland 1322 157 7 11
Total 18,569 1391 100 100
Gender
Male 9229 503 50 36
Female 9340 888 50 64
Age
15–24 3396 221 18 16
25–34 7431 541 40 39
35–54 6327 545 34 39
55+ 1415 84 8 6

Note: * Statistics: Population as of 1 January 2014. Source: National statistical institutes.

** Survey sample: The Latvian emigrant survey organised from August to October 2014.

The survey focuses on a wide range of issues, with several questions related to integration in the host country and ties to the country of origin. Decisions with regard to the variables to be included in the analysis were made on the basis of both theoretical and data-driven considerations.

In the statistical analysis, the author partly repeats the methodology of Engbersen et al. (2013), and it consists of the following steps. First, the two dimensions of attachment are constructed. One dimension measures attachment to the host country, and the other measures attachment to the country of origin. These two dimensions underlie different typologies of labour migrants, including the one of Engbersen et al. (2013). Six indicators of attachment to the host country were included in the factor analysis (feels closer ties to the host country, feels affiliated with the people of the host country, follows the news of the host country, follows the culture of the host country, has close friends among the natives in the host country and knows most people in the neighbourhood of the host country). A similar number of indicators were used for the factor analysis of attachment to the country of origin (feels closer ties to Latvia, feels affiliated with the Latvian people, follows Latvian culture, follows Latvian news, visits Latvia at least every half year and has close friends in Latvia).

Afterwards, the respondents were divided into clusters using the scores of the respondents on two factors: attachment to the host country and attachment to the country of origin. This was done through a K-means cluster analysis, in which the number of clusters was set at four because of the theoretical expectation that four ideal–typical migration patterns exist.

Finally, four separate binary logistic regression analyses were carried out to examine whether cluster membership was related to individual migrant characteristics. The dependent variable in each model was a membership in a certain cluster. Independent variables were grouped in various sets of variables, which were used to predict which individuals are more likely to belong to a certain cluster. The first set of variables consisted of background characteristics: age, gender, host country and time of emigration (Table 5). Respondents’ ages ranged from 16 to 90 (mean 35.27; the lowest mean in Denmark 30.54). Gender was coded as 0 = male and 1 = female. Host country variables were included in the analysis to reveal if living and working in a particular Nordic country predicts the odds of membership in a certain cluster. Four Nordic countries were defined separately, and variables were coded as 0 = no and 1 = yes. As the last emigration wave from Latvia was connected with the economic crisis of 2008–2009 (Hazans 2019), 2008 has been defined as a reference point of migration. The variable on emigration time was coded as 0 = has emigrated before 2009 and 1 = has emigrated after 2008. Many of those who emigrated before 2009 thus have been living abroad more than 5 years.

The second set of predictors refers to occupational status and education. For occupational status, two variables were used: students (12% within the sample, the highest proportion in Denmark 25%) and unskilled workers (10% within the sample). Variables were coded as 0 = no and 1 = yes. For education, three variables were used: people with secondary education or lower (22% within the sample), people with a professional education (23% within the sample) and people with a tertiary education (51% within the sample). Of particular interest in this study are those educated in STEM areas (21% within the sample). Therefore, the set of background characteristics was supplemented by the variable on education in STEM areas (variables were coded as 0 = no and 1 = yes).

The third set of variables aims to find out relation between memberships in a certain cluster and return plans. Three variables were included in the analysis: those who plan to return in 5 years (20%); those who plan to return after retirement (21%) and those who do not plan to return (19%). Variables were coded as 0 = no and 1 = yes.

The fourth set of predictors captures the main three migration motives of the Latvian emigrants. Twenty-one per cent have migrated because of financial problems. The possibility to develop (to get a good education and/or build a career) was mentioned by 13% respondents. The same proportion of the Latvian emigrants has migrated to the Nordic countries to get married or to live together with a foreigner living in the host country. All variables on migration motives included in the analysis were coded as 0 = no and 1 = yes.

To capture the relation of disappointment and negative attitude to Latvia with a cluster membership, the variable ‘Thinks, that Latvian government is not interested in people like me’ has been included in analysis as well (variable was coded as 0 = no and 1 = yes).

Initially, other different variables were tested, for example, living in a city or in a village in a host country and in Latvia before emigration, having children and ethnicity of Latvian migrants (ethnic Latvian, ethnic Russian and other ethnicity). Contrary to expectations, the odds of cluster membership were not affected by these variables. Therefore, they are not included in the final equitation of the regression analyses. One of the possible explanations, why ethnicity of the respondents did not have any significant effects on cluster membership, is self-selection bias inherent for this survey. As mentioned earlier, the data collection method was an online-based survey method, which is characterised by self-selection bias, and probably those emigrants who have a relatively high attachment to Latvia were more motivated to participate in this survey.

Empirical Findings

Factor Analysis: Construction of Two Dimensions of Attachment

As mentioned earlier, the previous studies suggest that there are two dimensions underlying the different types of migrants: attachment to the host country and attachment to the country of origin (Engbersen et al. 2013). In this particular analysis, the factor ‘attachment to the host country’ was derived from indicators: (1) feels closer ties to the host country, (2) feels affiliated with the people of the host country, (3) follows the news of the host country, (4) follows the culture of the host country, (5) has close friends among the natives in the host country and (6) knows most people in the neighbourhood in the host country. The factor has an eigenvalue of 2,229 and explains 37 per cent of the variance in the six indicators mentioned (Table 3).

Table 3

Empirical measures of attachment to the host country and the country of origin (factor loadings).

Attachment to host country

Feel closer ties to host country (1_yes) 0,716
Feel affiliated with the people of the host country (1_yes) 0,706
Follow the news of the host country (1_yes, regularly) 0,652
Follow the culture of the host country (1_yes, regularly) 0,573
Have close friends among the natives in the host country (1_yes) 0,502
Know most people in the neighbourhood in the host country (1_yes) 0,461
Eigenvalue 2,229
Variance explained (%) 37%
Attachment to country of origin
Feel closer ties to Latvia (1_yes) 0,678
Feel affiliated with the Latvian people (1_yes) 0,617
Follow the Latvian culture (1_yes, regularly) 0,604
Follow the Latvian news (1_yes, regularly) 0,602
Visit Latvia at least every half year (1_yes) 0,522
Have close friends in Latvia (1_yes) 0,241
Eigenvalue 1,899
Variance explained (%) 32%

The factor ‘attachment to the country of origin’ was derived from the indicators: (1) feels closer ties to Latvia, (2) feels affiliated with the Latvian people, (3) follows the Latvian news, (4) follows the Latvian culture, (5) has close friends in Latvia and (6) visits Latvia at least every half year. The factor has an eigenvalue of 1,899 and explains 32 per cent of the variance in the six indicators mentioned.

Cluster Analysis: Construction of Four Main Types of Attachment and Their Description

Cluster analysis was used to situate the surveyed Latvian emigrants over two dimensions: attachment to the host country and attachment to the country of origin. Four clusters derived through a K-means cluster analysis correspond to four ideal types of attachment. The ‘bi-national’ pattern, where respondents are strongly attached to both the country of origin and the host country, is closest to 397 respondents. Three hundred and nineteen respondents have been classified as settlers who are strongly attached to the host country and less attached to the country of origin. Two hundred and sixty-five respondents are situated at the lower end of both axes and are regarded as ‘footloose’. Finally, 410 respondents are strongly attached to the country of origin, less attached to the host country and are referred to as ‘separated’. However, it should be stressed that the distinction between the clusters in some cases is blurred, because some respondents are relatively close to one or more of the other types. Cluster membership is derived if a respondent resembles the respondents with the strongest tendencies towards that type more than she or he resembles the respondents with the strongest tendencies towards the other types.

The analysis of the indicators of attachment to the host country and the country of origin by cluster membership supports the theoretical assumptions that there are substantial and significant differences between the clusters in terms of attachment to both the home and the host country (Table 4). The indicators of socio-cultural aspects of integration in the host country are much higher among bi-nationals and settlers, and, by contrast, lower among separated and the footloose. Bi-nationals and settlers regularly follow host-country news, follow host-country culture, have close friends among natives in the host country, know most people in the neighbourhood in the host country, feel closer ties to the host country and feel affiliated with the people of the host country.

Table 4

Average degree of attachment to the host country and the country of origin by cluster.

1
Bi-nationals
(N = 397)
2
Separated
(N = 410)
3
Footloose
(N = 265)
4
Settlers
(N = 319)

Attachment to the country of destination

Feel closer ties to the host country (%) 87 20 30 92
Feel affiliated with the people of the host country (%) 77 16 13 78
Follow the news of the host country (%) 83 26 23 76
Follow the culture of the host country (%) 50 3 2 28
Have close friends among the natives in the host country (%) 74 36 29 80
Know most people in the neighbourhood in the host country (%) 43 13 12 55
Attachment to the country of origin

Feel closer ties to Latvia (%) 92 94 39 34
Feel affiliated with the Latvian people (%) 83 85 28 23
Follow the Latvian culture (%) 51 31 3 6
Follow the Latvian news (%) 91 91 45 44
Visit Latvia at least every half year (%) 68 70 30 25
Have close friends in Latvia (%) 90 88 71 80

The indicators of attachment to the country of origin (Latvia) are much higher among bi-nationals and separated, and, by contrast, lower among settlers and the footloose. Bi-nationals and separated regularly follow the Latvian news, follow the Latvian culture, feel affiliated with the Latvian people, feel closer ties to Latvia and visit Latvia at least every half year. Altogether, the data allow one to conclude that the theoretical assumptions about the four migrations patterns are relevant in the case of the Latvian migrants. The next step of analysis aims to answer the question about the characteristics of these different migrant types.

Predicting Cluster Membership: Characteristics of Different Migrant Types

The next conceptual question is to find out whether cluster membership can be related to individual migrant characteristics. To examine this, the method of binary logistic regression analysis has been used. For each of the clusters (bi-nationals, separated, footloose and settlers), a separate binary logistic regression analysis has been carried out (descriptive statistics of the dependent and independent variables are reported in Table 5). The results of the regression analysis suggest several characteristics of migrants belonging to each cluster (Figure 2)

Figure 2 

Summary of regression results: main determinants of cluster membership.

Table 5

Descriptive statistics of the dependent and independent variables (N = 1391).

Total % n Norway % Sweden % Denmark % Finland %

Bi-nationals 28 397 30 30 24 29
Separated 30 410 33 27 26 29
Footloose 19 265 18 18 24 16
Settlers 23 319 19 25 25 27
Age (16–90; mean 35.27) 35.27 35.70 37.73 30.54 37.02
Gender (1_female) 64 888 59 62 72 67
Norway 39 545
Sweden 28 383
Denmark 22 306
Finland 11 157
People with secondary education or lower 22 305 23 21 23 18
People with a professional education 23 321 27 20 20 22
People with a tertiary education 51 714 47 55 53 55
Highly skilled STEM 21 297 21 27 17 15
Have emigrated after 2008 66 914 72 59 66 60
Students 12 174 5 14 25 11
ISCO group unskilled workers 10 145 11 8 15 6
Plan to return in 5 years 20 282 24 17 17 19
Plan to return after retirement 21 296 27 18 18 18
Do not plan to return 19 265 14 22 21 25
Partner other (neither Latvian, nor Russian) 21 288 13 23 28 27
Migration motive: financial problems 13 188 18 12 10 10
Migration motive: the possibility to develop (to get a good education and/or build a career) (1_yes) 13 184 6 9 26 15
Migration motive: get married or started to live together with foreigner (1_yes) 11 158 7 20 12 13
Think, that the Latvian government is not interested in people like me 34 474 37 34 32 31

The Latvian emigrants belonging to the group named ‘separated’ are characterised by a short stay in the Nordic countries. With other variables held constant, separated are more likely to be among those who have emigrated after 2008. With other variables held constant, males are more likely to be separated migrants. These are migrants who plan to return to Latvia in 5 years or to return after retirement.

By contrast, bi-nationals do not plan to return to Latvia within 5 years. The chances of being a bi-national increase if the respondent is a women and has a partner of ethnic origin other than Latvian or Russian. Bi-national migrants are more likely to have a tertiary education or a secondary education but are not among highly skilled in STEM areas or unskilled workers. The odds of being a bi-national increase slightly with age. With other variables held constant, bi-nationals are more likely to be among those who migrated to get a good education or build a career. They do not think that the Latvian government is not interested in people like them.

Like bi-nationals, settlers are more likely to be among women. The chances of being a bi-national increase if the respondent has emigrated before 2009. Settlers do not plan to return to Latvia within 5 years, and they do not plan to return after retirement. With other variables held constant, settlers are more likely to think that the Latvian government is not interested in people like them.

Footloose migrants also do not plan to return to Latvia within 5 years or after retirement. With other variables held constant, young persons and those who live in Denmark are more likely to be footloose migrants. The odds of being a footloose decrease with the age of emigrants. With other variables held constant, footloose migrants are more likely to think that the Latvian government is not interested in people like them (Table 6).

Table 6

Determinants of cluster membership: four logistic regression models.

Bi-nationals Separated Footloose Settlers

B Sig. B Sig. B Sig. B Sig.

Age 0.024 0.000 –0.006 0.391 –0.014 0.083 –0.010 0.165
Gender (1_female) 0.304 0.052 –0.556 0.000 –0.144 0.384 0.502 0.005
Norway 0.282 0.188 –0.157 0.491 0.029 0.910 –0.233 0.327
Sweden 0.019 0.933 –0.148 0.540 0.183 0.488 –0.104 0.667
Denmark –0.176 0.460 –0.264 0.299 0.540 0.045 –0.110 0.666
People with secondary education 0.884 0.057 –0.163 0.661 –0.297 0.402 –0.315 0.396
People with a professional education 0.582 0.215 –0.107 0.777 –0.006 0.986 –0.428 0.255
People with a tertiary education 1.067 0.020 –0.114 0.757 –0.541 0.125 –0.444 0.221
Highly skilled STEM –0.307 0.084 0.150 0.403 –0.123 0.539 0.309 0.114
Have emigrated after 2008 –0.227 0.117 0.497 0.002 0.508 0.003 –0.627 0.000
Students 0.322 0.111 0.091 0.679 –0.219 0.352 –0.297 0.213
ISCO group Unskilled workers –0.467 0.054 0.408 0.057 –0.093 0.687 0.138 0.575
Plan to return in 5 years –0.548 0.004 1.553 0.000 –0.405 0.039 –1.821 0.000
Plan to return after retirement 0.133 0.413 1.002 0.000 –0.536 0.008 –1.109 0.000
Do not plan to return –0.517 0.004 –1.546 0.000 –0.046 0.813 1.114 0.000
Partner other (neither Latvian nor Russian) 0.348 0.046 –0.242 0.283 –0.331 0.138 –0.074 0.696
Migration motive: financial problems 0.004 0.985 –0.035 0.856 0.221 0.266 –0.275 0.233
Migration motive: the possibility to develop (to get a good education and/or build a career) (1_yes) 0.361 0.070 –0.080 0.719 –0.336 0.177 –0.052 0.818
Migration motive: get married or started to live together with foreigner (1_yes) 0.345 0.102 0.072 0.795 0.089 0.750 –0.611 0.014
Think, that Latvian government is not interested in people like me –0.421 0.003 –0.102 0.480 0.251 0.090 0.375 0.012
Constant –2.646 0.000 –0.858 0.094 –0.889 0.084 –0.193 0.699
Nagelkerke r-2 0.140 0.274 0.073 0.248

Discussion and Conclusions

This study addresses the trends of transnationalism and settlement of the Latvian emigrants in the Nordic countries through the analysis of the attachment of the Latvian migrants to the destination country and to the country of origin, and return intentions of the Latvian migrants. The literature studies helped to construct a conceptual framework and research methodology based on the research done by Engbersen et al. (2013). Using two dimensions—attachment to the destination country and attachment to the country of origin—the article highlights four migration patterns: (1) bi-nationals, (2) settlers, (3) footloose migrants and (4) separated—isolated migrants who focus on their country of origin and are willing to return. The quantitative analysis offers several general conclusions.

Data analysis confirms that the theoretical assumptions about the four migrations patterns are relevant for the surveyed Latvian migrants, and they relate to transnationalism trends found in other studies. Bi-nationals are people who manage to feel strong attachment both to the country of origin and to the host country. They are interested in news and culture in both countries, feel closer ties to both countries and the people living there, regularly visit the country of origin and know people in the neighbourhood in the host country. Their active interest in news and cultural events can be partly explained by their comparably higher level of education, but the highly skilled in STEM areas are not overrepresented among them. The members of this cluster are not planning to return to Latvia within 5 years. In many cases their partners are not Latvians or Latvian Russians but are of some other ethnicity, often that of the host country. It is worth noting that many characteristics found in this analysis resemble the study of the Polish, Romanian and Bulgarian migrants in the Netherlands (Engbersen et al. 2013). For example, the Polish, Romanian and Bulgarian bi-national migrants also have the intention to stay in the Netherlands longer.

Another migration pattern is demonstrated by settlers who have less of an attachment to Latvia but, by contrast, have a strong attachment to the host country, have emigrated before 2009 and do not plan to return. They feel affiliated with the people of the host country and have close friends among natives in the host country. Interestingly, among both bi-nationals and settlers, there are more women than men. This allows one to conclude that the surveyed Latvian women migrants are more willing to integrate in host communities. However, unlike settlers, bi-nationals are not disappointed with Latvia, and they do not think that the Latvian government is uninterested in people like them.

The most challenging pattern for characterisation and explanation is the footloose migrants. This migration pattern relates to those respondents who have no strong attachment to Latvia, and who have not integrated into the host country, either. Their characteristics suggest that they are more among young persons and among those who live in Denmark. The representatives of this group do not plan to return to Latvia. Probably, their position in life may be characterised by cosmopolitanism and a sense of being a citizen of the world.

Finally, the fourth migration pattern is characterised by a strong attachment to the country of origin and low integration in the host country. The members of this cluster are planning to return to Latvia within 5 years or later but do not plan to stay in the host country. These characteristics were observed more among men, unskilled workers and those who have emigrated after 2008.

Altogether, an orientation towards the host country and permanent settlement characterise more than half of the surveyed Latvian emigrants in the Nordic countries (both bi-nationals and settlers), whereas one-third of the surveyed Latvian emigrants can be characterised by the concept of ‘incomplete migration’, which refers to those who work abroad but ‘live’ in the country of origin (Okólski 2001). The smallest surveyed emigrant group, referred as the footloose, are those who have no attachment to any particular country and feel like they are citizens of the world.

Transnationalism expressed through speaking two languages, having homes in two countries and making a living through continuous regular contact across national borders is characteristic of more than one-fourth of the surveyed Latvian emigrants in the Nordic countries.

The study does not reveal significant differences among the migration patterns of the Latvian migrants in the four Nordic countries, with one exception. Latvian migration to Denmark differs with a higher proportion of young people, students, those who emigrated not because of financial reasons but to develop (to get a good education and/or build a career) and those who have no strong attachment to Latvia or Denmark.

Considering the limitations of this analysis, three aspects should be mentioned. First, the particular sampling procedure of emigrants has certain drawbacks, and in this study, women are overrepresented in the sample. Second, this particular analysis neglects the trend of multiple migrations, when people move from one country to another and do not necessarily return to their country of origin. However, the available data suggest that moving from Latvia to one country and then moving to another country is not a very typical trend (85% lived in Latvia before their migration; only 8% moved to the current host country from another host country). Third, the ad-hoc survey cannot grasp the changes that can be observed in longitudinal studies. Probably, those who now are among the ‘separated’ plan to return to Latvia in the next 5 years and those who have emigrated after 2008 will develop an attachment to their host countries in 5 or 10 years. Therefore, generalisations should be made with caution, and further, preferably, longitudinal studies are required to test these findings.

Acknowledgements

This work was supported by the European Regional Development Fund, Activity 1.1.1.2 “Post-doctoral Research Aid” under Grant Nr. 1.1.1.2/VIAA/1/16/012, Project “Migration of highly qualified specialists: emigration and return migration in Latvia”.

Competing Interests

The author has no competing interests to declare.

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