New Immigrant Destinations in a New Country of Immigration:

Settlement Patterns of Non-natives in the Czech Republic

Eva Janská1, Zdeněk Čermák1 and Richard Wright2

1Department of Social Geography and Regional Development, Faculty of Science, Charles

University, Prague 2, Czech Republic

2Department of Geography, Dartmouth College, Hanover, NH, USA

Pre-print version

Published in: Population, Space and Place 20, 680–693 (2014)

Introduction

In a short timespan. the Czech Republic (CR) has evolved from a country of emigration to an

intermediate transit country to a country of immigration: that is, it now ranks among the

countries gaining population via international migration. While non-natives1 constitute a little

over 4 per cent of the total population (Cizinci 2010), their geographies are uneven. Non-

natives concentrate in Prague and the capital is now home for over one third of that population.

So just as in other countries of immigration, flows of the foreign born often involve major

metropolitan centres and the largest cities function as what many call immigrant gateways.

Such settlement patterns are never static. Over time, some immigrants and their offspring find

opportunities elsewhere and a geographical diffusion of non-natives away from traditional

gateway cities occurs (e.g., Wright and Ellis 2000). New patterns of direct settlement from

abroad sometimes reinforce these internal movements. In the US, for example, a growing body

of scholarship on “new immigrant gateways” has emerged. Such places have little or no prior

history of immigration and receive immigrants directly from abroad or via secondary migration

from other places within the country. In this context, Singer et al. (2008) document the

extraordinary recent growth in immigrant populations in places such as Dallas, Atlanta,

Phoenix, and Washington DC.

Although the Czech Republic has been a country of immigration for a much shorter period than

the US and many others, this research evaluates the role urban immigrant gateways play in

the settlement process. This analysis assesses the degree to which Prague has maintained

1 For our purposes, “non-natives” are first- or second- or third-generation immigrants, and not Czech citizens.

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its position as the primary gateway during this period and how the roles of secondary cities

and other places have changed. We also ask: How do patterns of settlement vary by

nationality? To what extent is the internal migration of non-natives in the Czech Republic

changing and becoming an important component in total population mobility? How are rates

of mobility tied to changing non-native geographies, over time and by nativity? And, because

of theories that link internal migration and economic opportunity and belonging, what does all

this imply for immigrant incorporation?

We focus on the 2001-2010 period because this is when the CR started registering significant

net gains of newcomers from abroad. While related studies have focused on the immigration

process and the geography of the immigrant stock, the patterns of the internal migration of

foreign nationals in the Czech context remains unexplored. These types of mobilities are

gaining significance, both in terms of rate and volume (Novotný, Janská, Čermáková 2007;

Drbohlav and Čermák 2005). They therefore increasingly influence non-native settlement

geographies. Thus, new “immigrant gateways” are emerging in Czechia, produced by both

direct settlement from abroad and by the internal movement of non-natives.

This article adds to scholarship on the internal migration and integration of non-natives in

immigrant receiving countries. A recent spurt of research has augmented findings in North

America and Europe (e.g., Hall 2009; Nogle 1994; King and Newbold 2007; Wright and Ellis

2000; Stillwell and Hussain 2008; Champion 2005). For example, in Spain, Silvestre and Reher

(2012; see also Maza et al. 2013; Reher and Silvestre 2009; 2011) distinguished between the

characteristics of one-time movers and multiple movers. More pertinent for our research, they

also compared patterns of movement, concluding that internal migration produced de-

concentration, generally in line with spatial assimilation perspectives on regional mobility. Zorlu

and Mulder (2008) obtained a similar result for the Netherlands. Recent research on internal

migration in Estonia centered on the rhythms of movement of mainly Russian-speaking ethnic

minorities associated with gateway cities; during communism, gateways acted as a magnet for

non-natives but in the post Soviet period, movement tends to be centrifugal (Tammaru and

Kontuly 2011). Outside of the European context, Ishikawa and Liaw (2009) found differences

foreign residents and native Japanese migration processes and that non-native migration

could be differentiated by nativity and education.

In the Czech Republic, as in other places, the geography of non-natives shaped mostly by

direct immigration from abroad. At this point, however, the similarities between Czechia and

other places begin to dissipate. The interregional migration rates of the non-natives are high

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relative to those of Czechs, the trend in those rates is upwards, and direct immigration has

recently stagnated. Furthermore, patterns of settlement do not follow a simple hierarchy.

Prague indeed dominates but this overall settlement structure is differentiated by nativity with

certain secondary centres and smaller places gaining non-native populations from internal

migration and direct immigration. We use these geographies and spatial processes to

comment on immigrant incorporation and the links to labour markets and economic

opportunity. We caution that although the analysis reveals differential patterns of diffusion and

concentration by key immigrant group, scholars should take care not to infer any simple social

process of adaptation that can be easily read off from such maps (Wright and Ellis 2000).

The Czech Context

Between 1945 and 1989, the Czech lands lost population to emigration. The expulsion of

approximately 2.8 million Germans after World War 2 started this pattern of movement

dramatically. While the borders closed and formal international migration subsided following

the communist coup in 1948, politically motivated unauthorized emigration was steady. Most

Czechs became disaffected with totalitarian rule and some departed; between 1948 and 1989

approximately 500,000 people exited the country (Srb 2004). As a consequence, and despite

a trickle of workers from Vietnam and the USSR (see Alamgir 2013), rates of natural increase

meant that the ethnic homogeneity of the population actually increased over these 40 years.

With the democratic transformation and the Velvet Divorce from Slovakia after 1989, the Czech

Republic shifted from being a country of emigration, to a transit country, and then to a country

of immigration. It is now one of the few states in Central and Eastern Europe with net gains

from immigration (Drbohlav et al. 2010). Much of that growth is recent (Figure 1). More

precisely, there has been a substantial increase in the number of migrants from abroad since

2001 – from about 25,000 per year at the start of the period to approximately 100,000 in 2007.

The global economic crisis, however, dented that trend and produced a decrease in the

number of immigrants arriving after 2008. For example, only 28,000 immigrated and 12,500

emigrated in 2010 (Cizinci 2010).

Ukrainians, Vietnamese, Slovaks, Russians and Poles represent the largest groups of

newcomers. Together they accounted for 68% of all non-natives in the country as of December

2010. We can divide non-natives another way, differentiating a) those who take up qualified

employment positions as experts, managers, technicians and skilled professionals (mainly

from the EU), from b) labour migrants, many of whom fill low-ranking positions in the job market

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(e.g., unskilled occupations are more typical for Ukrainians while Vietnamese are more likely

to work as shop keepers). Slovaks, who lived together with Czechs in common state between

1918-1993, occupy a specific position. After the 1993 split and when compared to other

immigrants, they received preferential treatment in labour markets and other areas of social

life. Their migration behaviour is very similar to the movement of Czechs and will not concern

us for the rest of this analysis.

Figure 1 about here

As in most other countries gaining population from abroad, large urban areas attract

newcomers. Being by far the biggest city in the Czech Republic, Prague stands out and is the

home to one-third of all non-natives, followed by Brno. Spa towns also prove attractive

destinations for some (e.g., Karlovy Vary, Poděbrady, Teplice) as are towns with substantial

economic, especially foreign, investment (e.g., Pilsen, Mladá Boleslav and Pardubice). Non-

natives also settle in the border regions (e.g., the districts of Karlovy Vary, Teplice). In general

terms, the non-native population in the Czech Republic forms a west-east gradient across the

country, with their share progressively decreasing from west to east. While populous places,

especially Prague, are key centres, the former occupies a dominant position not only in terms

of immigration but also as a destination for non-natives moving internally to the country. It

accounts for 38 per cent of the volume of internal migration of non-natives and is the

destination of 34 per cent of the total number of international immigrants (2006–08).

What explains these geographies? Immigrants concentrate in large cities for well-known

reasons. A gateway city is a large urban area with a legacy of hosting new arrivals. It is a place

that, for historical reasons and thanks to the opportunities it offers, traditionally takes in a large

number of immigrants (e.g. Singer 2004; Painter and Yu 2010; King and Newbold 2007; Hou

2006; Crowley et al. 2006). Such cities offer a wider range of employment options as well as

the chance for social interaction and convivial contact with co-ethnics. Initial settlers lay the

foundations for others to join them via networks associated with work or family or along the

lines of gender.

Over time, the hold that the gateway exerts on immigrant settlement can weaken. Why do non-

natives begin to disperse from initial points of concentration? Explanations of such diffusion

from gateways fall into three areas. The first is associated with tight labour and housing

markets in that often occur in gateway cities (Ley 2007; Card and Lewis 2005). Second, much

like the process of initial settlement in primary gateways, some “pioneers” move out from the

original place of settlement seeking better work or cheaper housing or lured by a job offer. A

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process of cumulative causation kicks in, and produces growing non-native populations in

these new destinations as well as increased enclave economy vitality, which in turn attract

more co-ethnics, either from within the country or directly from abroad. Third, and related, is

the idea of spatial assimilation and immigrant incorporation. Over time, a maturing non-native

population obtains sufficient socioeconomic and cultural experience/capital for some to leave

gateway enclaves to seek opportunities elsewhere – a process that operates from the intra-

metropolitan scale to the interregional scale (Wright and Ellis 2000; Lichter and Johnson 2009;

Singer et al. 2008).

The progression down the settlement hierarchy can also be understood as related to the

process of counter-urbanisation (e.g., Champion 2005; Stillwell, Hussain 2008; Collantes et al.

2013). In the Czech case, such diffusion is also partly the product of political processes during

the post-socialist transformation, EU expansion, and the global economic restructuring of

agriculture. This means that migrants no longer migrate just to large towns because some take

up available low-status job opportunities, for example, in rural farm work. In Greece, for

instance, a large influx of agricultural workers from Albania reversed the process of rural

depopulation that had been going on for decades (Kasimis and Papadopoulos 2005). Similarly,

in the UK, since 2001, labour migration to provincial towns and rural areas has accelerated

(Green, Jones, and Owen 2007). Accordingly, the following sections consider the geography

of non-natives and their migration between 2001 and 2010, contrasting the non-natives with

the native born, and also comparing the patterns of the two largest immigrant groups

(Vietnamese and Ukrainians). We frame the analysis in terms of the Czech urban hierarchy,

allowing to see the migration relationships among gateway cities, their hinterlands, and other

locations for each of these groups.

Data and Methods

Our data derive from official statistics from the Czech Statistical Office or from the registries of

other institutions such as the Czech Interior Ministry and the Czech Ministry of Labour and

Social Affairs. Census data, which would traditionally assist in such a case as this, are

inappropriate. The relevant data from the last census in 2001 are incomplete – approximately

48 per cent of documented resident non-natives were not included in the census (Čermáková

2002). This article thus relies on data that indicate the number of non-native persons by region

by date (documented using valid residence permits) and their recorded movements (the

number who register and de-register as residents over a specific time period). “Non-native”

people are documented in a population register and are not Czech citizens.

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We base our definitions of migration on those used by the Czech Statistical Office, which

considers migration as a formally documented change in address between municipalities in

the Czech Republic (internal migration) or the receipt of a residence permit (international

migration). The Czech statistical office changed the registration system for foreign nationals in

2001. It follows that internal migration data from earlier years are incompatible with those after

2001. Accordingly, our analysis focuses mainly on the period between 2001 and 2010 to

ensure data compatibility. The analysis does not take into account undocumented non-natives,

whose numbers can only be estimated,2 or individuals granted asylum status, who are few in

number compared to the total number of documented non-natives in the country.3 To create a

detailed portrait of some of the most recent trends (e.g., migration rates, hierarchical structure),

we refer specifically to the 2006-8 period, thereby avoiding the recessionary period of 2008-

2010.4

A milestone in statistical observation occurred when the Czech Republic joined the European

Union in 2004. From that point, two categories of immigrant were measured, each of which is

subject to a different residence system. EU citizens with a right to free movement across

borders, who are subject to a registration obligation, were distinguished from citizens of “third”

countries, who are required to apply for a residence permit (Cizinci 2010).5 The character of

registration of EU citizens on the one hand results in the underestimation of their numbers and

on the other, is skewed by cases of formal registration for utilitarian reasons.6 In the case of

citizens from third countries, they are required to register any change of address or any change

in their residence status if they are away from their registered place of residence for more than

30 days. Compliance, however, is not universal and, importantly, probably improved since the

first two years after its introduction in 2001. Given these data quality issues, we focus not just

on non-natives as a whole but also on the two largest, non-native groups – Ukrainians and

Vietnamese.

To assess the links between migration and settlement structure we divided Czech

municipalities into six classes, five of which are categorised on the basis of population size or

2 Estimates vary considerably – between 15,000 and 30,000 undocumented immigrants may be residing in the Czech Republic (Drbohlav, 2008). 3 For example, between 1993 and 2008, there were 83,000 applications for asylum, of which only 2,377 people or 2.9% were granted asylum. 4 Recessions perturb patterns and depress rates of migration and we leave analysis of the global economic

downturn on Czech migration to another paper. 5 Complicating things further, of course, is the fact that, as in most other countries, the number of emigrants from the Czech Republic (notably Czech citizens) is incomplete and therefore significantly underestimated. 6 Based on information from staff at the Czech Statistical Office (CSO) hundreds of German citizens registered formally to obtain cheaper Czech driver’s licenses.

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its position in the settlement size hierarchy (Prague, regional centres – regional towns, large

towns – 10,000 or more inhabitants, small towns – 2,000 to 10,000 inhabitants, villages – up

to 2,000 inhabitants). Municipalities located in the hinterland of Prague and regional centres

that represent a type of suburban settlement formed a sixth group. The criterion with which

these municipalities were selected was that 30% or more of the inhabitants had to be

commuting daily to the relevant centre (see Ouředníček, Temelová, Pospíšilová 2011).

The analysis uses net migration and migration efficiency to gauge changes in the distribution

of Czechs compared to non-natives. While several measures of population concentration are

available, we applied the Gini coefficient to analyse the distribution of different groups in the

Czech Republic. To assess the relationship between individual processes connected with

spatial changes in the population we used a simple two-dimensional measure of dependence

using the Pearson correlation coefficient. Dependency measurements and a quantitative

analysis of spatial concentration were carried out on 77 territorial units (76 districts plus

Prague).

The geography of non-natives in the Czech Republic

As already noted, the major cities, Prague, Brno, and Pilsen contain the largest non-native

concentrations, along with some border regions (mainly in the west and northwest), while rural

districts in the south-east (Moravia) had relatively few (Figure 2).

Figure 2 about here

Notable differences, however, occur by nativity. Vietnamese are heavily concentrated in the

border regions in Bohemia. Russians have a very different geography; most are concentrated

in two territorial units, 65 per cent of whom reside in Prague or the Karlovy Vary region. Citizens

from the Czech Republic’s neighbouring states (Poles, Germans, and Slovaks) were typically

more concentrated in the border regions. Citizens from countries of the global north tended to

concentrate in Prague (usually over 50% of the given community).

Prague dominates the geography of non-natives in both absolute and relative terms. This

pattern is evident both cartographically (Figure 2) and hierarchically (Table 1). Table 1 shows

the share of the resident non-natives by municipality size. Large towns also play an important

role as migration destinations for non-natives. This is most evident when examining the

location quotients by size category of municipality. Calculated by dividing the proportion in

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column 5 by that in column 6, these quotients make plain that Prague dominates as an

immigrant gateway. Non-natives are 2.8 times more concentrated in Prague than the

population as a whole. In addition, regional cities also boast slight non-native concentrations,

with this population about 1.13 times more likely to be located in such places than are Czechs.

After these two types of place, there is a steady decline in overall immigrant concentration

further down the urban hierarchy. Fusing the information in both Figure 2 and Table 1 we see

that it is not always the case that the larger the town, the larger the concentration of non-

natives; it also depends on the location of the settlement, especially in relation to the country’s

western border (Uherek 2003).

Table 1 about here

Despite the recent sharp increase in their number, the spatial distribution of non-natives was

highly uneven over the last decade. Their distribution is more concentrated than that of Czechs

and this concentration has increased since 2001 (see Table 2).

Table 2 about here

Those with long-term residence visas are more unevenly distributed than those with permanent

resident status. This is not too surprising as the labour market activity of members of the former

group is more flexible, both in the sense of that they are able to perform various types of jobs

and in the sense that they can more easily move to where the jobs are.7 While several factors

influence the line of work and where a non-native lives (e.g., Grygar, Čaněk, Černík 2006),

many non-natives hold long-term residence visas living in districts where there is a large

demand for unskilled labour in response to foreign investment (e.g., the districts of Mladá

Boleslav, Pardubice, and Pilsen). The patterns of change in the geographies of Ukrainian and

Vietnamese nationals follow different paths. While the Vietnamese became less concentrated

over the 2000s, the opposite holds for the Ukrainian population. The increasing concentration

of Ukrainians in particular neighbourhoods in Prague and other large towns stems from the

location of low-cost accommodation in particular neighbourhoods, the type of work most of

them perform, and the need to live close to work (Leontieva 2010). In contrast, the Vietnamese,

whose initial concentrations were in the border regions of Bohemia, have an increasing

presence in other regions. This diffusion is connected with the spread of their business

activities, mostly retail trade. Ninety-one per cent of all Vietnamese hold visas for work mainly

in retail (which for small businesses is somewhat independent of the settlement hierarchy). In

7 Non-natives must report the change of their place of residence at relevant regional office of the Ministry of Interior if is longer than 30 days.

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contrast, Ukrainians work mainly in construction industry and manufacturing, activities that are

far more connected with the structure of urban spaces and hierarchies. (Jíchová 2010,

Čermáková, Schovánková, Fiedlerová 2011).

The Internal Migration of Non-natives

What determines the geography of non-natives in the Czech Republic? Differential fertility and

mortality rates have thus far had a negligible influence. Accordingly, migration, both directly

from abroad and internal to the country, is key. Table 3 shows that, in contrast to the relatively

low and stable rates of internal migration of Czech nationals, the migration rate of non-natives

has increased in the 2000s. As the decade progressed, non-natives constituted an increasing

share of those people moving internally in the Czech Republic, such that by 2009, they

represented over one sixth of all such movers. The fact that the gender ratio has remained

relatively stable indicates that the increases in the migration propensity of non-natives are not

driven changes in the proportion of internal migrants who are male. To put this in some sort of

perspective, in the US, differences in the interstate migration rates of the native- and foreign-

born populations are negligible for every year since 1994 with native-born rates topping those

of the foreign born over half the time (Ellis et al. 2013).

Table 3 about here

Some of the characteristics of non-natives who migrate within the country differ from those of

internal migrants who are Czech. Not only is there a larger share of males among non-native

internal migrants, owing to the larger share of male in the foreign population overall, but

migration intensity in the early years of economic activity (age 20–29) is also higher. The

distribution of migration intensity by age conforms to very common patterns of migration

behaviour: i.e., a high rate of mobility at a young age (20–35 years), with a secondary increase

at ages 0–5 and after age 60 (Figure 3). The highest migration intensity among Czechs occurs

among those aged 25-29. In contrast, for non-natives, it occurs at a younger age (20-24 years).

Figure 3 about here

Prague dominates the regional patterns of internal migration, but this is changing. Between

2007–08, for instance, Prague’s migration turnover accounted for 38 per cent of the total

volume of internal migration. Earlier in the decade, this figure was 55 per cent. In terms of net

migration, in 2002–2003 Prague’s net gains of non-natives accounted for 88 per cent of the

total such net gains by district. In 2007–2008 that figure had more than halved to 40 per cent.

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More generally, Prague and the majority of districts recorded net gains of non-natives in the

early 2000s, but by the end of the period this had changed in favour of Prague’s hinterland, so

that, for instance, the districts Prague-East and Prague-West currently have moderate non-

native migration gains from Prague. Alongside Prague, other attractive secondary migration

centres have emerged, most notably Pilsen and Pardubice, and in the past two years also

Brno.

Assessments of migration effectiveness8 using 77 districts of the Czech Republic capture

these shifts from another aspect. Migration effectiveness measures the population relocated

within the country per 100 internal movers. In other words, migration effectiveness gauges the

ability of places to attract and retain people. For non-natives, the migration effectiveness at the

start of the observed period (2001-2) was 50.5% and by the end (2009-10) it had fallen to

16.3%. Among the Czech population migration effectiveness at the district level remained

much more steady, ranging between 12-18% during the observed period. Thus, internal

migration is producing a larger net shift in the redistribution of non-natives relative to that of

the native born. The trends converge but it is unclear if this is the result of the recession at the

end of the decade or something else. To summarise, migration rates and proportional

redistribution remained relatively stable among native-born Czechs during this decade.

Meanwhile, the propensity of non-natives to migrate internally tripled while migration

effectiveness dropped by two thirds to match that of Czech migrants.

Figure 4 about here

Switching the viewpoint to simple net migration, we find large differences between patterns of

internal migration for Czechs and non-natives. Table 4 shows that in many instances, the type

of places that gained working-age Czechs were losing non-natives.9 For non-natives, small

settlements experience migration losses to larger settlements. In contrast, suburbs and small

towns are gaining Czechs at the expense of other settlements. So Czechs are suburbanising

or moving to smaller settlements while Prague and regional cities gain non-natives as a whole

at the expense of other types of settlement.

Table 4 about here

8 Effectiveness is the ratio of net migration to gross migration expressed as a percent. 9 As we strongly suspect that most non-natives migrate internally for economic reasons (reflected, for example, in the age structure of these migrants), we restricted the population of internal Czech migrants to people of working age (15–59).

10

The clear associations between the internal migration of non-natives and the Czech urban

hierarchy vary by nativity (Table 5). The share of both Vietnamese international and internal

migrants moving to Prague is smaller and the share moving to large towns (10,000 or more

inhabitants) is much larger than Ukrainians and other non-natives. Thus, the Vietnamese are

de-concentrating because of direct immigration from abroad, and internal migration. In

contrast, Ukrainians are a driving force behind the net gains of non-natives experienced by

larger Czech cities.

Table 5 about here

We next examine non-native internal migration using paired correlation coefficients by

comparing patterns of net migration at the district level for seven different types of migrant for

the non-recession years of 2006-8. In addition, we assess the effect of economic factors on

this regional differentiation. Given the dominant position occupied by Prague, the absolute

figures of the correlations for characteristics were overly influenced by the extreme values for

Prague, so the correlation analysis uses net migration rates (i.e., standardized by population).

We again restrict the population of internal Czech migrants to people of working age (15–59).

Using the 77 districts as the basis for analysis, Table 6 shows a positive and significant

correlation between the net migration rates of non-natives (both international and internal

migration) compared to the net migration rates of Czechs (top row of Table 6, first two entries).

In the aggregate, the same places gained both working age Czechs and non-Czechs through

migration. While earlier analysis shows that differences do exist by position on the urban

hierarchy, Table 6 provides additional perspective by comparing net migration gains and

losses in other ways. Moving across the top row, we find no significant association between

the district-scale net migration of Czechs and that of Ukrainian internal migrants. The same

holds for both Vietnamese internal movers and those who moved directly to the Czech

Republic from abroad.

Reading the table in another way, we find that areas that were attractive internal-migration

destinations for Vietnamese and Ukrainians were not generally those attracting international

immigrants from these countries. The correlation between district level net migration for

international Ukrainian movers and internal Ukrainian migrants is -.35 and highly significant.

For Vietnamese, the correlation is stronger (-.56) and also highly significant. With the

Vietnamese community, this has to do with the existence of a gradual wave of migration out of

the west and northwest border regions to other parts of Bohemia, while these border regions

continue to be attractive for international immigrants from Vietnam.

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The relationships between economic factors (expressed as the districts’ unemployment rates

and average wage levels) and net migration behave as we might expect. Economic effects

shape the net migration of both Czech citizens of productive age and non-natives (both

international and internal). For example, the correlation between district-level net migration and

wages is negative for all groups, with three of the correlations reaching the level of statistical

significance. The strongest correlation in this regard is between the net migration of Czechs

and district-level unemployment. The effect of economic factors on district-level net migration

is less pronounced for selected groups of non-natives. In the case of Vietnamese migration

the insignificant correlation coefficients stem from the fact that many Vietnamese migrate to

the west and northwest Bohemia (areas marked by a higher rate of unemployment and lower

average wages). Here the economic appeal of the region as a destination of immigration is not

connected so much to internal conditions; rather the dominant factor is its close proximity to

regions inhabited by populations in Germany with strong purchasing power just across the

international border.10

Discussion and Conclusions

Like many other countries with increasingly significant immigrant populations, newcomers to

the Czech Republic tend to settle in large cities. Between 2001 and 2010, the regional

concentration of non-natives increased. In terms of both the volume and the intensity of

immigration, Prague dominates, followed by some regional centres. Ukrainians, the largest

immigrant group, is a main force behind this trend. These large flows, however, mask more

subtle undercurrents. When we distinguish between the two main groups, we find that while

Ukrainians were increasingly concentrated, Vietnamese were becoming less so. Furthermore,

Prague’s “gateway” role is not so simple. For Ukrainians, it is not a gateway city in the sense

of receiving international migrants who then migrate on to other regions of the country. As

Prague is a less attractive migration destination for the Vietnamese community than it is for

Ukrainians, the majority of Vietnamese migrate to large towns (towns with more than 10,000

inhabitants, not including Prague) and regional towns.

These patterns derive in large part from the types of work the Vietnamese and Ukrainians

perform. The former are far more likely to be involved in small-scale retail employment while

10 We are aware of the shortcomings of using simple correlations in this manner and are cautious in

our interpretation of the results.

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the latter tend to work construction or similar jobs involving unskilled manual labour. These

labour market attachments shape the patterns of settlement. The decrease in the

concentration of Vietnamese over the decade reflects the evolution of their penetration into the

retail sector and its more distributed geography. The increase in concentration of Ukrainians

concerns opportunities for work. Labour market attachment rather than other forces matter

most for these geographies.

The internal migration of non-natives has become an important component of overall migration

within the Czech Republic. In 2008 the rate of internal mobility of non-natives was five times

higher than that of Czechs. But while this share increased over the decade of the 2000s, we

also found that migration effectiveness rates for the two groups converged. Moreover, the

decline in migration effectiveness occurred while inter-regional migration rates increased for

non-natives. Non-natives are moving much more within the Czech Republic while their patterns

of migration become more restricted. The late 2000s recession surely played into this. The

broader lesson here is again that economic forces shape population geographies and, more

specifically, scholars need to be much more attentive to recessionary cycles in shifts in forms

of migration.

One important finding relates to the character of migration flows among municipalities. Non-

natives were increasingly concentrated in large cities. For Czech migrants the opposite holds;

migration streams flow from Prague and other regional centres into smaller municipalities and

municipalities located in agglomerations. Some of the results of our analysis point to some

possible new trends. It is apparent from the relationship between Prague and its hinterland that

non-natives are starting to become part of these suburbanisation processes putting the breaks

on the drift toward concentration.

There is also a link between international and internal migration and regional economic

development. Economic conditions, expressed as unemployment rates and average wages,

significantly influence regional net migration. The effect of economic factors, however, is

stronger for non-natives migrating to districts that are more attractive destinations. In the case

of districts with lower net migration, economic conditions are not always the decisive factor

determining net migration. In the case of non-natives, social and ethnic ties may be key, but

that specific question again remains for future research to unpack.

Our research also relates in part to the debate about the relationship between immigration and

internal migration. One theory is that immigrants migrate to particular places and their

concentration results in locals leaving for various reasons (including labour market competition:

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Hatton and Tani 2005). The literature finds little support for this (see Wright et al. 1997; Card

1990). A different view suggests that under certain circumstances the native born migrate out

of a region (e.g., as part of suburbanisation and counter-urbanisation processes) and the

vacancies in housing and labour markets come to be filled by immigrants. Although our data

imperfectly address this issue, our results suggest that in many cases the situation in the Czech

Republic resembles the second scenario, where immigrants are not directly competing with

the native population. This question of integration processes connected with internal migration

is important. One of our next research steps is to ascertain, using surveys, the most significant

reasons (ethnic ties, economic prosperity, housing, labour market, etc.) that shape the

concentration/deconcentration processes of the two largest groups of non-natives.

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Figure 1: The size of the five main non-native groups in the Czech Republic, 2001-10

Source: Cizinci 2010

18

Figure 2: Percent share of non-natives in the Czech Republic by district in 2010

Source: Cizinci 2011

19

Figure 3. Migration rate by age – Czechs and non-natives (annual average 2006-08)

Source: Authors’ calculations from CSO Note: NN-Non-natives

0

5

10

15

20

25

300

-4

5-9

10

-14

15

-19

20

-24

25

-29

30

-34

35

-39

40

-44

45

-49

50

-54

55

-59

60

-64

65

-69

70

-74

75

-79

80

-84

85

-89

90

-94

mig

rati

on

rat

e (

%)

age groups

male NN

female NN

male

female

20

Figure 4 Migration effectiveness of non-natives and Czechs for 77 districts

Source: Authors’ calculations from CSO

0

10

20

30

40

50

60

70

2002 2003 2004 2005 2006 2007 2008 2009 2010

mig

rati

on

eff

ect

ive

ne

ss (

%)

years

Czechs

Non-natives (Total)

Vietnamese

Ukrainians

21

Table 1: The Share of non-natives by total population by commune category: 2010

Communes Total population

Non-natives

Non-native share by Commune (%)

Share of Non-natives in the CR (%)

Total population by size category (%)

Location Quotient

Prague 1 289 556 171 324 11,5 37,3 12,0 3,10

Regional Cities

1 656 833 80 227 4,8 17,5 15,5 1,13

Communes in suburbs

779 743 26 650 3,3 5,8 7,3 0,80

Other towns (>10,000 population)

2 699 918 89 416 3,5 19,5 25,2 0,77

Communes with 2-10,000 population

1 825 104 44 355 2,6 9,7 17,0 0,57

Communes with <2000 population

2 459 086 46 994 2,0 10,2 23,0 0,45

Total 10 710 240 458 966 4,3 100 100

Source: Počty obyvatel 2011, Ministry of Interior CR, authors’ calculations

22

Table 2: Gini Indexes recording the spatial concentration of the native and non-native

populations in the Czech Republic

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Total Population 0,39 0,39 0,39 0,39 0,39 0,39 0,39 0,39 0,40 0,40

Total Non-native

Population

0,62 0,62 0,61 0,62 0,64 0,64 0,65 0,65 0,67 0,67

Vietnamese 0,70 0,70 0,70 0,70 0,69 0,69 0,67 0,66 0,66 0,65

Ukrainians 0,64 0,66 0,64 0,66 0,68 0,70 0,72 0,73 0,74 0,74

23

Table 3: Internal migration of non-natives in the Czech Republic, 2001-10

Year Total non-native (NN) population

Male NNs Male Czechs

(%)

Share of NN of total internal migration (%)

Migration rate of NNs (%)

Migration rate of Czechs (%)

2001 5 978 66,6 47,2 3,4 3,7 1,7

2002 9 868 66,7 47,4 5,0 5,5 1,9

2003 10 285 65,7 47,0 5,5 5,3 1,8

2004 11 722 62,3 46,8 6,1 6,1 1,8

2005 17 933 62,2 46,8 8,4 6,9 2,0

2006 22 973 61,5 46,8 10,2 7,8 2,0

2007 42 756 61,4 46,8 16,7 12,3 2,1

2008 42 743 62,6 46,7 17,1 10,5 2,1

2009 41 600 62,7 46,2 17,8 9,8 1,9

2010 37 107 63,2 46,4 15,4 8,7 1,9

Source: Cizinci 2010, Demografická 2010

Note: The migration rate is the share of the migrants from particular group to the total

population of that group.

24

Table 4: Net migration flows between commune size category (annual average 2006-08)

Czech citizens 15-59

Destination

Origin PH RC Z VM MM VES Total

Prague 0 -1 212 3 798 -1 779 -378 1 265 1 695

Regional Cities 1 212 0 4 483 -1 132 -74 1 279 5 768

Communes in suburbs -3 798 -4 483 0 -1 030 -488 67 -9 732

Other towns (>10,000 population) 1 779 1 132 1 030 0 1 308 6 387 11 635

Communes with 2-10,000 population 378 74 488 -1 308 0 1 687 1 320

Communes with <2000 population -1 265 -1 279 -67 -6 387 -1 687 0 -10 685

Total -1 695 -5 768 9 732 -11 635 -1 320 10 685 0

Non-natives 11 Destination

Origin PH RC Z VM MM VES Total

Prague 0 -429 218 -1 420 -755 -817 -3 204

Regional Cities 429 0 -386 -552 -516 -406 -1 431

Communes in suburbs -218 386 0 -25 11 26 179

Other towns (>10,000 population) 1 420 552 25 0 -208 -225 1 564

Communes with 2-10,000 population 755 516 -11 208 0 -76 1 393

Communes with <2000 population 817 406 -26 225 76 0 1 498

Total 3 204 1 431 -179 -1 564 -1 393 -1 498 0

Source: own calculation from CSO

Net migration is the migration balance of the category of communes of destination and origin.

Positive/negative values are related to the destination category of communes (table columns).

Czech nationals are represented by the age group of economic active of 15-59.

11 95% of non-natives are of working age.

25

Table 5: The share of the selected immigrant groups immigrated into the particular commune

categories (2006-08)

Direct International migration (%) Internal migration of immigrants (%)

Size category of communes

All Non-natives

Ukrainians Vietnamese Czechs (15 – 59)

All Non-natives

Ukrainians Vietnamese

Prague 34 33.8 16 8.3 26.8 30.6 19.3

Regional Cities

16.7 16 15.6 10.5 17.9 19 18.6

Communes in suburbs

5.6 7.5 4 14.1 9.4 9 5.1

Other towns

(>10,000 population)

20.7 17.5 32.1 17.6 18.4 16.3 26.2

Communes with 2-10,000

population

11.5 11.4 17.5 19.1 12.9 10.5 18.9

Communes with <2000 population

11.5 13.7 14.8 30.5 14.5 14.6 11.9

Total 100 100 100 100 100 100 100

Source: Authors’ calculations from CSO

Data for direct international migration means the share of group of immigrants into size

category of communes to total immigrants into this size category.

Data for Internal migration is the share of immigrants group into the size category of communes

to total internal migrants of the relevant group. Czech nationals are those of working age (15-

59).

26

Table 6: Paired correlation relations between net international and internal migration and

selected district variables (77 units, Pearson correlation coefficient)

Czechs

Non-native

(Internal) Non-native

(International) Ukrainian (Internal)

Ukrainian (International)

Vietamese (Internal)

Vietnamese (International) Unemp Wage

Czechs .225* .260* .062 .285* .173 -.006 -.468** .342**

Non-native (Internal)

-.120 .914** -.244* .442** -.098 -.197 .305**

Non-native (International)

-.113 .798** -.272* .645** -.297** .546**

Ukrainian (Internal)

-.349** .171 .061 -.120 .196

Ukrainian (International)

-.077 .225* -.237* .396**

Vietamese (Internal)

-.560** -.165 .233*

Vietnamese (International)

-.034 .153

Source: our own calculation from CSU

Notes: ** Correlation is significant at p< 0.01 * Correlation is significant at p< 0.05.

Unemp –unemployment rate at 31. 12. 2007; Wage – average wages of employees in 2005.

Nets migration are as annual average of 2007-08 and were relativized to population size of

district (as 31. 12. 2007)