Recent migration from the new European borderlands

Introduction

The recent Enlargements of the European Union (EU) in 2004 and 2007 lead to the incorporation of 12 new member states, 8 of them bordering countries that have been part of the Soviet Union and are now referred to as NIS (Newly Independent States). This has created a new borderland between East and West with new flows of goods, people and capital across the borders. Despite the newly imposed migration regulations (stricter and more rigid than before), there are significant and increasing flows of migrants from the NIS into the EU and elsewhere in the world (Israel, USA, Canada and Russia). Whilst the New Member States were originally the target of this migration (before their incorporation into the EU) migrants now head increasingly for other destinations in Europe and elsewhere. In this respect both new and old EU member states are targets of migration (Okolski, 1997, Drbohlav, 1996, Bedzir, 2000, Stola, 32766, Stola, 2000, Dietz and Segbers, 1997, Iglicka and Sword, 1998, IOM/ICMPD, 1999).

This paper relates to the new migration situation between NIS countries and the Enlarged European Union.  The paper focuses upon the following factors: the characteristics of different kinds of migrants; their destination countries; the activities and financial situation of migrants and finally the role of social capital and gender in determining these patterns.

The new European borderland represents a geographical fault line in several respects.

Although economies have improved in most of the NIS countries since the turn of the century, living standards are still low in comparison to the EU and many households in the NIS depend upon the remittances from migrants. As a result of the incorporation into the EU, the rising living standards in the new EU member states have created even greater contrasts along the borderlands. Particular countries and regions belonging to the NIS have established a tradition of migration, some of it to old European Union countries (Germany and Southern European countries such as Portugal, Spain and Italy) some to new European Union countries such as Poland, the Czech Republic, Hungary and Slovakia (King, 2001, Wallace and Stola, 2001).

The character of migrations has changed in relation to earlier periods of migration, such as the recruitment of labour migrants in some Western European countries in the mid twentieth century, which was focused upon industrial workers. Alternatively, emigration to the New World or out of communist Eastern Europe was normally one way and permanent (Castles and Miller, 1993). More recently people from the post-communist countries have more opportunities to travel and did so in great numbers after the collapse of communism going to buy and sell goods as “suitcase traders” or going as labour migrants to the EU or to the Central European accession states.  They no longer carry out industrial work, but rather reflecting changes in the post-industrial labour markets of Europe, there is a demand for short term and flexible services workers or an expendable workforce in industries such as construction, catering, tourism and agriculture.

In addition, the changing domestic arrangements in Western European households mean that there are more elderly people and children to be cared for as women go out to work and “outsource” their former domestic roles to cleaners, babysitters, care workers etc. and this is also a consequence of the lack of welfare coverage in places such as Southern Europe, forcing families to find “private” solutions, often ones involving Eastern European care workers (Ehrenreich and Hoschild, 2003, Bakan and Stasiulis, 1997). There are thus both male and female migrations taking place independently. In this context the domestic organization of the household in the sending country is important for understanding how migration operates as a “household work strategy” both socially and economically (Wallace, 2002, Stark, 1991). Arlie Hochschild has argued that this represents a “care chain” in which the children of the affluent west are cared for by female migrant workers and then their children are in turn cared for by someone else (Ehrenreich and Hochschild 2003). The darker side of these movements is the trade in human trafficking, the sex industry and the migration of criminal individuals or organized groups, where migrants from the East have been prominent (Lazaridis, 2001). This new migration situation in the Eastern borderlands of the European Union has hardly been researched at all and thus it is important for yielding new empirical findings for social science and policy makers.

Studies of migration have tended to emphasise the role of networks in the migration process and the way in which social capital can be used to assist with finding information about potential regions. Once the person has migrated, social capital can be used to develop business opportunities, find accommodation, find jobs and overcome bureaucratic problems (Portes, 1995, Portes, 1997).   Hence migration usually takes place as a result of “chains” of people.  However, the initial impetus might come from existing relationships between sending and receiving countries on account of preceding historical connections or economic links such as those of colonial past (Sassen, 1988).  We will consider the extent to which this is the case with new migration from Eastern Europe

Research Questions

The research questions reflect the preliminary exploratory investigation of these data which start with simply trying to understand descriptively what patterns are emerging and comparing them with what is known about previous migration.

1. What are the motivations of migrants

One clear reason for migration is economic. The collapse of the economic system in the former Soviet Union in the early 1990s meant that large proportions of the populations of Eastern and Central Europe lost their economic security and were plunged into poverty.    Unable to make a living at home, many of them turned to migration.  However, other possible reasons for migration suggested in the literature include ethnic and civil strife, ecological catastrophe and political persecution.  In the region we are considering, there were several civil and ethnic wars in the post-Soviet period. For example in Moldova, the secession of  Trans-Dinistra and the tension between Romanian and Russian populations lead to a armed conflict in the early 1990s which is still not entirely resolved now. Trans-Dinistra  operates as a more or less separate state outside the control of the Moldovan authorities. In Armenia the civil war over Ngorno-Karabackh lead to waves of refugees from Azerbaijan in the early 1990s and this is also unresolved. In Georgia the secession of South Ossetia and Abkhazia lead to large numbers of displaced persons (they still occupy the main hotels in Tbilisi) and continued conflict in regions not controlled by the Georgian state. The proximity of Georgia to Chechnya means that they are inevitably drawn into that conflict too.  Ukraine and Belarus have avoided any violent conflict despite the significant number of ethnic minorities living in those countries.  However, there has been environmental devastation through the Chernobyl nuclear explosion in 1986, leaving many regions still full of nuclear fallout, which we might expect to provoke migration of people.  Therefore, in all these countries we have plenty of reasons for migration due to ethnic and political conflict or environmental damage.  

2. What are the characteristics of migrants?

Migrants are usually male and younger, although increasingly women migrate as well. Therefore we would expect to find migrants with these kinds of characteristics. Education might also play a part in migration with migrants being slightly better educated than other population groups. We might also find some ethnicities more likely to migrate than others.

3. What is the role of migrant networks and social capital?

Studies of migration have tended to emphasise the “chain” effect of settlement patterns. Migrants from one country follow their countrymen to a new destination. The kinds of networks that people have can be characterised in terms of their “social capital”. Yet many of the new countries that people from NIS countries migrate to are entirely new ones, where they may not have contacts. Therefore it is not clear how initial migration patterns are established or how they continue.

4. What role does the financial situation of households play?

We were also interested in the extent that the financial situation of the individual migrant might influence their migration. In particular: was it poverty that encourages people to migrate?  Given the substantial economic insecurity in the region, we might expect this to be a strong reason for migrating. Perhaps the lack of secure future for young people may play a role in this too.

5. What are the destination countries of migrants from the New European borderlands?

Traditionally Europe, especially Germany was seen as a destination country for work migration and the New World countries were seen as countries for emigration. However, Russia also attracted many migrants from NIS countries.  On the other hand the opening of labour markets in Sweden, the UK and Ireland may have also attracted migrants from outside the EU.

6. What activities do migrants undertake in their destination countries?

Migrants traditionally work in sectors of the economy where temporary work is required and where an illegal status can go undetected. However, this may differ between countries, especially East and West.  We might assume that the activities would differ between destination countries and that women might be carrying out different activities to men.

Finally we carry out a logistic regression to see which factors were most important in determining migration among the migration sample.

Methods of Research

The new migrations from countries belonging to the NIS into the EU are under-explored until now because migration data have not been collected systematically and comprehensive survey research has been lacking. Although migration potential surveys have been long used as instruments for estimating migrations, they have deficiencies. The advantage of such surveys is that they provide systematic, statistically testable data. The disadvantage is that they survey only the people who are still at home, not the ones who have left and the percentage of real migrants picked up in such surveys is rather low. Thus, they can ask people only to think hypothetically about migration, something which has grave methodological problems. On the other hand ethnographic studies of migrants themselves carried out by researchers who conduct lengthy unstructured interviews after winning the trust of the (often illegal) migrant and talking to them in their own language provides more rich and accurate data. But it is unsystematic and there is the problem of finding the migrants who may be in any one of several countries across Europe. For this reason we sought a form of data collection that could combine the systematic and statistical reliability of the standard survey with the accuracy and depth of the ethnographic study. We term this the “ethno-survey” and it is adapted from the surveys developed by Princeton professor Douglas Massey for studying border regions between the US and Mexico (Massey et al., 1987, Massey and Espinosa, 1997, Massey and Zenteno, 2000).  This survey enables us to systematically compare migrants with non-migrants in the same regions.

The ethno-survey involved the questioning a sample of 400 respondents drawn from 2 regions with high rates of migration in each country (although in Moldova they were drawn from everywhere). The survey was carried out by partners in the respective countries using a random routing method along with a multi-stage random sample. Twenty households were chosen from the ones that had migrants in them and these were interviewed using in-depth methods. This paper concentrates only upon the quantitative study, although it is informed by our reading of the qualitative interviews.  It was not difficult to find households with migrants in them because the numbers of migrant households was quite high.  However, the numbers are much reduced compared to the full sample with only 8% having actually migrated, which number 161individuals. Of the different nationalities, 3.3% of Armenians were migrants, 10.8% of Belarusians, 1.8 % of Georgians, 13.5% of Moldavians and 11.3%  of Ukrainians.

The sample survey was followed up with 20 in-depth interviews with migrants in each country. These were transcribed and translated into English. Here we have analysed only the interviews from Belarus, Moldova and Ukraine since the interviews from Georgia were lost and those from Armenia have not yet been coded. The analysis was carried out using the framework analysis method designed by Ritchie and Spencer, which involves coding and charting interviews according to dominant themes and then comparing them (Ritchie and Spencer, 1994).

In this analysis we are focusing upon the people who actually migrated in the sample since 2004. These are necessarily temporary migrants because they were interviewed after their return to the country of origin. However, they can give us a picture of actual patterns of migration in the recent past.

Results

Motivations for migration

The questionnaire asked a range of questions about motivations for migration, which can be broadly broken down into political motivations and economic motivations[1]. In order to better understand the motivation behind the actions of migrants and non-migrants, respondents were asked a series of questions about the more popular perceived reasons for migration.  As Figure 1 shows, the predominate belief is that people migrate from their countries in order to improve their economic situation.  This reason is followed by three additional economic factors, including fear of unemployment, better welfare facilities, and professional development, each of which more than 60% of the population agree are significant factors.  Meanwhile, socio-political reasons such as ethnic problems, military conflict, political difficulties, religious tensions and crime are considered important causal factors by less than 20% of the population.  Hence, although there are abundant reasons for ecological and conflictual migration from this region, this motivation is not predominant.

Figure 1

From this examination of beliefs, we can see therefore that economic motivations override all other ones.

Characteristics of migrants

Traditionally migrants were men in the younger age group with lower education. We might also expect them to be financially worse off if they are interested in migration. We therefore analysed the data by age, gender and education. Age was coded into two groups.  Those participants between the ages of 18 and 35 were classified as young, participants 36-55 were middle aged and 56 plus were regarded as retired, but with such a small number (19) they were excluded from the analysis.   Education was coded into the following categories:  those who finished less than tenth year are classified as having low education, those finishing secondary school (12 years) or vocational training are medium educated and those with any University education are highly educated. Missing data were excluded.  In addition we included religion as a factor since this is a way of indicating which ethnic group a person belongs to.  Finally we included an account of their financial situation, coded as below subsistence for those whose household could not afford basic food and clothing, subsistence for those who could, and financially stable for those who could afford the above basics plus consumer goods like televisions and even larger items such as cars or a home.

From the sample population of 2003 participants, 161 had travelled to another country for more than a month for temporary work or study since 2004.  Belarus, Moldova and the Ukraine constitute the largest groups of immigrants with 26.7, 33.5 and 27.3 percent of the migrant population respectively.  Armenia and Georgia contributed only 20 migrants in total (Table 1).   However, this seriously underestimates the number of migrants from Georgia and Armenia. It would seem that this kind of ethno survey is not a good way of capturing the patterns of migration in those countries, although it works better for Moldova, Belarus and Ukraine.

In terms of demographic characteristics, women are underrepresented in the returned migrant population as they constitute only 44.1% compared to 55.9% of men.  We can see from Table 1 that younger people are significantly more likely to migrate as are the lower educated, which was also unexpected. There appeared to be more migrants from rural areas than urban ones, which is an unusual finding.  However, these are very small numbers and the samples were not representative at a national level, so we should be cautious about drawing conclusions too readily.

Table1 Basic Demographic Factors of Returned Migrants

*p<.05, * *p<.001 ˇ

Migration networks and social capital

Migrant social networks were coded by assigning the designation ‘yes’ to all participants who answered that they had a friend or family member abroad who was willing to help them migrate.  It did not distinguish how many contacts each migrant has abroad.  Migrants were significantly more likely to have friends and family abroad than non-migrants.  However, we note that at least half of the non-migrants also had social networks abroad.

However, when we turn to the qualitative analysis we find a different story. 16 of the 60 respondents reported using friends as a way of migrating and a further 16 mentioned that family contacts were used (often a spouse who was already in the destination country). Hence, more than half used social capital of some kind. However, what is perhaps more surprising is that nearly half did not use social capital or migration networks.  Of these, the most common resort was to some kind of agency, either one recruiting workers, one recruiting students or for “cultural exchange”. Altogether one third (19) of the sample of 60 interviewees had used agencies.  In some cases these agencies organised housing and income for the migrants – and this was the most common way of going to North America.

4. Financial situation of migrants

The sample shows that overwhelmingly, those who are financially stable are migrants, while those who need financial help are neither very likely to migrate, and they also make up an almost negligible minority amongst returned migrants.  This may be explained, however, by the fact that returned migrants have most likely brought money and goods home with them, thus increasing their family’s wealth and these numbers are only the result of migration rather than a prediction.

Which is the most important factor?

Finally we put all this together in a logistic regression model to see which factors were most important in determining migration. In this case the dependent variable was whether respondents had migrated or not and hence a logistic regression was necessary.

~ Reference category

* p<.05

** p<.001

In order to better understand the effect that each of the previously mentioned independent factors have on the probability that a respondent has migrated, a binary logistical regression was conducted.  In the first block, the demographic variables of age, education, religion, gender, country of origin, and regional type are set as independent with the enter method.  For the second, backward stepwise likelihood ratio method was used with social capital, social capital in NIS countries, social capital in EU countries and social capital in other countries as the additional independent variables.  In the third block financial situation was added as the independent variable.

According to the Negelkerke R Square, the factors in block 1 explain 12.1% of the variation, a significant portion. By examining the p-values for each individual factor compared to the reference category, one finds that Catholics were more than twice as likely to migrate as Orthodox and men were twice as likely to migrate as women.  Armenians and Georgians were significantly less likely to migrate than Ukrainians.

In block 2, the social capital values were added. However, as they were of very low significance, all but the factor social capital other were rejected from the analysis, leaving an R square of .124.  At the end of this block, 12.4% of the variation was explained.  The important variable stayed the same as before, though Armenia lost some significance.           

In block 3, financial situation was added. According to the Chi squared values, those who are financially stable are significantly more likely to have migrated. Armenia was no longer significantly different than the Ukraine.  Georgians were still less likely to migrate, but now Moldavians were more likely to migrate than Ukrainians.  As well, those of a lower educational background became significantly more likely to migrate than those of higher education.  Men and Catholics were still more likely to migrate, though the gaps between them and the reference categories shrank.  In the end, 14.8% of the variation was explained by these variables.      

Destination countries

If we look at the destination countries of the whole sample, we see that Russia stands out as by far the most important country (see Figure 1)

Figure 1

The favourite destination of the surveyed region was overwhelmingly Russia for both men and women, though in a greater proportion for men.  Poland and the USA were both also popular destinations for female migrants.  Men were spread thinly over a larger number of destinations.

However, given that each of the countries under consideration has a different historical relationship to both East and West Europe, it seemed worthwhile to break the information down by country of origin, despite the small numbers.

Below we consider destination countries for each group of migrants

Figure 2

As shown in Figure 2 both men and women of Armenia have preferred Russia as a destination for migration. Women equally preferred Turkey and Great Britain as destinations while men spaced themselves out widely in Italy, Germany, Great Britain and other countries.

Figure 3

Belarusian men also find Russia a preferable destination, though the women do not.  The men also show a preference for Germany and Great Britain, as well as some interest in the US, Czech Republic, Italy, Poland and other places.  Women, however, are concentrated in the US, followed by Poland, and Great Britain.  However, the small numbers of migrants makes generalizations difficult for this portion of the analysis.

Figure 4

Figure 4 demonstrates that the men from Georgia stray from the pattern of moving to Russia, like citizens of the previous two countries as they moved to only Turkey and France.  Georgian women are more spread out between Turkey, the US, Russia and Greece.  As only 7 people migrated from Georgia, it is difficult to generalise from these findings.

Moldavians, both male and female, overwhelmingly choose to move to Russia, though a larger proportion of women chose to go.  Both genders had representatives in Italy, France and the Ukraine.  Only men migrated to Greece, Germany and Great Britain, while only women migrated to Portugal and Turkey.  As there were a larger number of Moldavians to migrate than Georgians or Armenians, these results are more accurate.

Figure 5

Figure 6

The most preferred destination for Ukrainian women was Poland, followed by Russia and Italy.  Men from the Ukraine, though, were more spread out.  Though they did migrate to Russia and Poland in significant numbers, they were also in Portugal as well as a number of other European countries and the US.

5. Migrant activities

An important category of migrants were students. Students went to Russia in some cases, but also to the USA, to Sweden, to the Netherlands, to Germany, China, the Czech Republic, the UK and in the case of Moldavians, some went to Romania to study.  In most cases the students also worked in a variety of service occupations such as bartender, book keeper, and waitress. In some cases the terms of the grant covered all their expenses, but in most cases this was not so. Therefore, students shade into workers, even if the purpose of their migration was not mainly to work.

As we saw above, many migrants went to Russia. They worked either selling on the market (Moldavians sell fruit) or for the men it was construction work that drew them there. Women were more likely to work in a shop or a kitchen.  It seems that the economic improvements in Russian lead that nation to draw workers from their own “near abroad”. Indeed, one of the respondents had bargained to improve his wages.  Given that all of the countries we are concerned with had Russian as a main or a second language, the problems of communication were minimal. However, respondents from the Caucasus faced problems of prejudice.

Those who went to the USA mostly went on academic grants or cultural exchange programmes. Although they might have worked whilst they were there, they were mainly invited for other reasons.  However, one Ukrainian went to Canada as a construction worker on his own initiative, helped by the large Ukrainian community in that country.  It is perhaps surprising that not more Ukrainians had gone to Canada for this reason.

In terms of European migration, there was a different pattern. The main destination region in Europe however, was Southern Europe, especially Italy but also Portugal, Spain and Greece. In these countries 6 of the 9 respondents were women and they were employed as care workers, looking after elderly people. The men worked as builders or gardeners and often these were a husband-wife team. They were recruited entirely through informal networks and began their stays as illegal workers, although they often managed to legalise their status later.

The Central European New Member States attracted some people. Of the 11 who went to these countries, four were Moldavians going to Romania, where they had common language links, and the rest were Ukrainians and Belarusians going to Poland where they worked either trading on markets or as agricultural workers, continuing a pattern established early in the 1990s (Iglicka, 1999, Sword, 1999). Agricultural work such as fruit picking as well as work in construction, bars, restaurants and shops were the kind of activities that they  carried out.

Those going to Northern Europe mostly went through agencies or on temporary workers or student schemes of various kind (such as by becoming an au pair or temporary agricultural worker). They mainly carried out agricultural or construction work and in most cases this work was arranged by an agency who dealt with the travel and immigration problems.   Although many went to Northern Europe as students, the student schemes were often a disguised way of recruiting workers, since they did not attend language schools but rather worked on farms, speaking mainly to other migrant workers.  Students were not necessarily unhappy about this since it expanded their personal experience and brought them money.

Hence, we see a distinct pattern whereby migrants going to North America mainly went on temporary grants and cultural exchange schemes. Those going to Northern Europe went with agencies of various kinds, either to study or to work. Those going to Southern Europe did so by informal networks and the women worked as care workers whilst the men did agricultural or construction work.  In Russia it was likewise construction work or catering that drew migrants there.

Conclusions

First we need to sound a note of caution in the interpretation of these data. First of all the number of actual migrants in our sample was small in comparison with the population in general so that in analysing a total number of 161 respondents for all countries, most findings were non-significant.

Secondly, we should be aware that even these were not representative at a country level. In order to find locate suitable respondents we focused the sample on regions that were likely to have higher numbers of migrants within each country.

Thirdly, the sample that we have greatly underestimates the migration from these countries in general. It reflects only those who had returned and who happened to be there at the time of interview. Many more may be absent or away for longer periods.

However, the advantage of this kind of survey is that it is the nearest thing to a representative sample survey of migrants, which makes quantitative analysis possible in a way that can not normally be done. It also enables us to make systematic comparisons with non migrant populations in the same regions.

There are a number of conclusions that we can draw from this analysis.

First of all, we can confirm that the motivations to migrate were mainly economic ones rather than political ones. Political factors played a very small role in this kind of migration despite the ample reasons for political as well as environmental migration from this region and the large numbers of refugees and displaced persons living there.

We found that the financial situation of migrants was very important since migrants were significantly better off then non-migrants (indeed they were more than four times as likely to be better off). However, this also reflects the fact that households with migrants in them were better off as a result of migration rather than this being a cause.  Therefore migrating was an important source of household financial well-being.

Social networks were barely significant  in determining migration according to the quantitative analysis (the significant in fact disappears in the logistic regression once we control for other factors)  but the qualitative analysis showed that informal networks were the main channel of recruitment to Southern Europe whilst for Northern Europe and North America it was agencies of various kinds, where social networks were unnecessary.

In terms of destination countries, Russia was overwhelmingly the main destination, although Poland was also important, especially for women; Italy and Great Britain also featured.  Russia was the most important destination among all national groups, although among the Georgians France, Turkey and Greece were important and among the Ukrainians, Poland, Italy and to some extent Portugal were important. For Moldavians, Romania was an important destination country due to the fact that Moldavians and Romanians share a common language and history.

We could therefore see that there was a significant flow of migrants to the East. In terms of new destination countries, those in Southern Europe were becoming more important for some countries and Britain was also visible as a destination but mainly in this sample through various kinds of recruitment or student agencies.

There are some general implications to be drawn. First of all, we need to expand our idea of migration. It is not only one way and permanent but includes the circulation of people around Europe and the world. Many of these migrants are students, which seem to represent an important kind of migration. Although the main reason for these people to move was to study and improve their human capital, in  fact students mostly either worked to support themselves or the student migration scheme was actually a disguised way of recruiting workers.

Secondly, not all migration is not only or even mainly into the European Union. The most common migration is to Russia, reflecting the booming economy in that country, the relaxation of migration restrictions and the fact that it was easier for migrants to travel and adapt to life in that country. Even of the migrants going to the West, a popular destination is the United States, using various kinds of temporary schemes.

Thirdly, the main countries attracting migrants are not the traditional ones (Germany, France, the Netherlands) but rather non-traditional ones such as Southern Europe and the New Member States.  In Southern Europe the care of the elderly was a major reason for recruiting female migrants from Eastern Europe, something we might term “care migration” which is a response to the limited provision of welfare in Southern European countries alongside an ageing population.

As predicted, there is an ambiguous overlap between what is legal and what is illegal and this tends to reflect the migration regime of the receiving country. In the Southern countries migrants start as illegal and then regularise their status over time. In North America and the Northern European countries, migrants have to find some other “gateway” to migrate and this is usually through legitimate means, even if they later work illegitimately.

What we did not find was some of the patterns we might have expected. Since women were not usually caring for children (except in the case of the two au pairs one of which was a man) we did not find the feminised “care chains” described by US scholars.

Secondly, we found that migration networks were important only in some circumstances because many of the destinations of the migrants were new ones, to countries where there was no previous cultural link. In this respect various kinds of agencies step in to facilitate migration. In circumstances where migration is more and more circumscribed by various regulations, the agencies are often in a better position to deal with immigration.

Pulling all this together, it would seem that those Western countries with a long tradition of migration (such as the USA, the UK, Germany) have effectively closed their gates to new migration from the East. The only way to enter those countries is through designated schemes and agencies.  However, those countries where migration is a relatively new phenomenon (Southern Europe,  New Member States) have not yet been able to close all the migration gates effectively and so in these countries migration is relatively common and more irregular, using social networks as a main mechanism.

The implications of this analysis is that the European Union will need to compete with other more open and easier destinations such as Russia or even the USA to attract future migrants from the border regions of Europe. Once the supply of workers in the New Member States dries up due to demographic and economic changes, it is possible that the new wave of potential migrants from further East will have already departed for other destinations. Given the xenophobic backlash against Eastern European migration in recent years within the EU, it is possible that the member states of the EU will not even notice this problem until it is too late.

The paper was originally published in Hungarian Sociological Review.

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