economic migration case study

• Current issue
• Submissions

Intereconomics on X Intereconomics on LinkedIn

• Data protection

A service of the ZBW

Intereconomics Review of European Economic Policy

Intereconomics  / Volumes  / 2021  / Number 1  / The Long-Term Growth Impact of Refugee Migration in Europe: A Case Study

Volume 56, 2021  · Number 1  · pp. 50–58

The Long-Term Growth Impact of Refugee Migration in Europe: A Case Study

By Gerrit Manthei

• Share on LinkedIn
• Share per e-mail

Gerrit Manthei , University of Freiburg, Germany.

Many questions have been raised about the political and economic consequences of the recent surge in refugee immigration in Europe. Can refugee immigration promote long-term per capita growth? How are the drivers of per capita growth influenced by immigration? What are the policy implications of refugee immigration? Using an adjusted Cobb–Douglas production function, with labour divided into two complementary groups, this article attempts to provide some answers. By applying the model to current immigration data from Germany, this study finds that refugee immigration can lead to long-term per capita growth in the host country and that the growth is higher if refugee immigrants are relatively young and have sufficiently high qualifications. Further, capital inflows are a prerequisite for boosting per capita growth. These findings can inform policymakers of countries that continue to grapple with refugee immigration.

The issue of refugee immigration has dominated European politics for the past five years. The significant increase in immigration rates since 2015 and the mass migration into Southeast Europe, however, have not elicited uniform reactions across the continent. While most East European countries have been very restrictive, Germany and Sweden were initially more open to immigrants. This is because Germany, for example, can be characterised as a relatively tolerant society, and, initially, the majority of its population and the media were in favour of government policies (Haller, 2017). However, the subsequent change in public opinion (GfK Verein, 2018) led to policy revisions. Both Germany and Sweden have since adopted much stricter immigration regulations ( Migrationspaket in Germany and temporary law of temporary residence status in Sweden). It seems unlikely that these countries will witness any large-scale immigration in the coming years. 1 However, given the alarming consequences of climate change (Perch-Nielsen et al., 2008) and the large wealth gap between Europe and North and Central Africa (Stark, 2017), one can reasonably assume that immigration rates in the future will be higher than previously estimated. 2

Recognising the need for an in-depth analysis of immigration, many scholars have published studies on the social, political, demographic, economic and fiscal effects of refugee immigration in recent years. In Sweden, for example, most studies highlight the negative aspects of general and refugee immigration (Lundborg, 2013; Ruist, 2015), including the ones published before the 2015 surge. Similar findings have also been reported by studies that are not based on any individual country (Dustmann et al., 2017).

In Germany, some studies have focused on the positive economic effects of refugee immigration, especially those published in the first few months of the influx (Fratzscher and Junker, 2015). Later, however, papers on the negative economic effects of refugee immigration (van Suntum and Schultewolter, 2016), especially its effects on fiscal sustainability (Manthei and Raffelhüschen, 2018), became more pronounced. The present study attempts to offer a diverging viewpoint based on the theoretical assumption that population growth in absolute terms generally induces economic growth. 3 Accordingly, it examines the economic effects of refugee immigration by focusing specifically on per capita growth. It is important to add here that countries like Germany have a well-developed and comprehensive social system, in which the productive inhabitants support the less productive ones through tax-financed redistribution. Thus, negative per capita growth induced by refugees may place an additional burden on local taxpayers regardless of absolute economic growth.

The two main factors affecting the per capita growth effects of migration are age and qualification structure of the immigrants (Boubtane et al., 2016). Ceteris paribus , per capita growth can improve if the qualification structure of the refugees is better than that of the local population. Even a poor qualification structure among refugees can promote per capita growth provided a larger percentage of them are of working age compared to the native population, which then increases the labour force share of the total population (age structure effect). Another significant factor affecting per capita growth is capital mobility, particularly the increase of capital inflows from abroad, for example, via foreign direct investments (FDIs). If the increase in labour supply leads to a relative reduction in wages, economic theory suggests that the price of capital will rise and subsequently result in greater foreign investments (Samuelson, 1948) if factor price elasticity is sufficiently high. Ceteris paribus , this could lead to per capita growth. Apart from the above, other factors (e.g. state consumption and integration) can also affect per capita growth.

Interestingly, the growth effects of refugee immigration, whether per capita or absolute, have not been sufficiently researched. While the effects of general migration on growth have been extensively studied, those of refugee migration have not received much scientific attention. In light of future projections about refugee immigration, this topic is highly relevant not only from a scientific point of view but also from a political and social perspective.

Using an adjusted Cobb–Douglas production function with labour divided into two complementary groups, this article presents a two-step quantitative analysis of the long-term per capita growth effects of refugee migration. The research aims to determine whether the effects are mainly positive or negative, to assess the impact of individual drivers of growth and to derive policy implications. This article focuses on Germany because the country has accepted the highest number of refugees in Western Europe since 2015, and it represents a midpoint within Europe in terms of geography, per capita growth and the welfare state system.

Theoretical model

According to the Cobb–Douglas production function, the output (GDP in this study) is dependent on the production factors: labour and capital. Labour usually refers to the number of workers in an economy or their working hours. Capital is typically defined as all the assets in a national economy (i.e. cash and financial assets as well as buildings, land and machinery). Further, government consumption is considered in this study to better account for integration costs.

Taking the above factors into account, GDP ( Y t ) in every year t is given by:

Here β is the total factor productivity, which serves as a scaling factor to scale the model’s output to the actual GDP. c S,t denotes the impact of state consumption on GDP and includes, for example, integration costs. Capital is divided into two categories. The first category, state capital stock ( K S,t ), is mostly subject to the constraints of investment and depreciation (Equation 4) and is only indirectly influenced by immigration. The second category, private capital stock ( K P,t ), inter alia, depends on the size of the labour force in the national economy (Equation 7) and is therefore directly exposed to the effects of migration.

To capture the growth effects of refugee migration in a meaningful way, the labour factor needs to be differentiated according to productivity. Since productivity is more difficult to quantify in data lacking a migration context, the analysis uses qualification levels as they are strongly linked to productivity (Becker, 1962). Accordingly, the labour force is divided into two groups: an above-average productive group (white-collar workers), with excellent qualifications, and a less productive group (blue-collar workers), with lower qualifications. To consider the possible migration-related wage effects, wages are used instead of the number of workers. Thus, L WC,t is the sum of all the wages of white-collar workers, and L BC,t is that of blue-collar workers. Depending on the qualification structure of the immigrants, the ratio of blue- to white-collar workers can change and, following the theory of supply and demand, affect relative labour prices (wages).

The coefficients α 1 , α 2 , α 3 and α 4 are fixed over time and define the impact of each type of capital and wage factor on the output. The sum of all four coefficients is 1. α 1 and α 2 represent the share of GDP that is derived from gross profit. They show the influence of the two capital stocks (state and private) on nominal GDP. α 3 and α 4 denote the share of GDP derived from the labour force. These coefficients together capture the impact of the sum of all wages on GDP.

The following equation accounts for state consumption:

where c S,t is the scalar of state consumption, and ( C S,0 / Y 0 ) scales the impact of this scalar to GDP. The absolute consumption of the state is defined as

with C̅ S as a fixed level of state consumption. It does not vary with the size of the population P t , because some expenditures, such as defence, are relatively inelastic to changes in population size. Most other expenditures are calculated with a constant per capita sum c S flex . The rest of the state consumption is driven by integration costs E BI,t . This includes direct integration costs for services such as food, shelter, medical aid and language courses provided to immigrants. It also accounts for spending on unemployment, under-age immigrants, social assistance for the elderly and the costs incurred on deportation/voluntary departures. This paper treats integration costs as state consumption and assumes that the state finances these integration costs by cutting down its consumption or its investments. 4 However, the inclusion of integration costs under state consumption does not negatively affect the latter, as the category of expenditures is irrelevant to GDP. On the other hand, cuts in investments to pay for integration costs [ ( 1 - σ ) ∙ E BI,t ] do increase consumption. The factor σ , which takes a value between 0 and 1, denotes how much of the integration costs are covered by cuts in state consumption.

The state capital stock is estimated as follows:

Each year, the capital stock depends on that of the previous year ( K S,t -1 ) and on the development of the relative price of labour to capital ( lk t ; Equation 6). Further, it decreases by the fixed depreciation rate q A and increases with the state’s investment ( I S,t -1 ), which is calculated by

It is assumed that each year, a fixed quota ( q I ) is invested by the state. q I and q A are ideally fixed with the same value, so that the state capital stock decreases over time if investment cuts are used to finance integration costs ( 1 - σ ). In the short term, Y t increases for all σ < 1 as short-term consumption offsets long-term investment in the state capital stock because of α 1 < 1 . Subsequently, a negative relationship develops between immigration and the state capital stock because immigrants benefit from public capital spending without having contributed to it through, for example, tax or social contribution payments (Piras, 2011). With refugees unable to bring in their capital, 5 their immigration, or more precisely their integration and the associated costs, will lead to a long-term decrease in state capital and present a hindrance to growth.

The development of the relative price of labour to capital is given by:

lk t accounts for relative price changes of capital to labour to meet the principle of supply and demand. For example, an increase in the size of the labour force ( LF t ), ceteris paribus , leads to a decrease in wages and an increase in the price of capital.

Analogously, the development of the relative price of capital to labour ( kl t ) is given by:

Private capital is strongly affected by the size of the labour force and by the development of the relative price of labour to capital:

While K̄ FP is a fixed share of the private capital stock that is independent of labour force changes, k̄ LF is a fixed amount of per capita capital that each member of the labour force holds or attracts. Private capital is computed in this way because domestic firms may borrow money to satisfy higher demand for goods. But with a higher supply of labour, and the consequent increase in the factor price for capital, borrowing money in the host country will become more expensive than borrowing from abroad. This could stimulate capital inflows. In addition, the host country is favourably placed to attract long-term FDIs from the rest of the world. As the economic theory of factor price equalisation (Samuelson, 1948) states, an open economy with a relatively high factor price tends to encourage an inflow of the respective factor.

The sum of all white-collar workers’ wages is calculated by

w WC,t is the average yearly wage of a white-collar worker, and LF WC,t is the total number of white-collar workers. This yearly wage depends on the yearly wage in the base year ( w WC,0 ), the development of the ratio of blue- to white-collar workers and the relative price of labour in the host country:

The first quotient captures the development of the ratio of blue- to white-collar workers. In each year, the ratio of blue- to white-collar workers is calculated in relation to their ratio in the base year. 6 Such modelling implies that any change in the ratio has a direct impact on the wages of the workers. For example, if the proportion of blue-collar workers among immigrants is higher than that in the host country, immigration can lead to a relative increase in the wages of white-collar workers. If the ratio of total capital stock to total workforce increases, relative to the base year, the price of labour increases and thus the wages.

The number of blue- and white-collar workers in each period, as well as of P t , depends on three factors: demographics, migration and integration. The present analysis employs a population projection model to account for demographic changes and a future decrease in Germany’s total labour force, owing to the double ageing process. 7 However, the latter does not interfere with the analysis of migration-induced effects, because it is factored into all the calculations.

The second factor – migration – is modelled by dividing the number of immigrants in every year based on age and wage (two wage groups). Emigration is modelled by estimating the number of emigrants across population groups and by taking into account the significantly higher emigration of the non-integrators, because statistics clearly show that foreigners constitute a larger share of emigrants (Federal Statistical Office of Germany, 2019a).

Integration is the third factor that affects the number of blue- and white-collar workers. New refugees of working age (or who will attain working age within the projection period) who will not emigrate during the projection period will typically integrate first. This trend is modelled by assuming a logarithmic assimilation process (integration) with an individual duration for each wage group, while accounting for unemployment.

Data and scenarios

Descriptive statistics and data.

This case study considers 2014 as the base year, as Germany witnessed a significant increase in refugee immigration in the following year. The main sources of data are the national accounts of Germany (Federal Statistical Office of Germany, 2016a) and the survey of income and expenditure, EVS (Research Data Centre of the Statistical Offices of the Federal States, 2015).

In 2015 and 2016, the average age of immigrants entering Germany was 31 years (Federal Statistical Office of Germany, 2019b), while that of the German population in 2014 was approximately 44 years (Federal Statistical Office of Germany, 2016b). Further, the proportion of immigrants aged 65 or below was 98.5% (Federal Statistical Office of Germany, 2019b), while the proportion of the German population under 65 was only 78% (Federal Statistical Office of Germany, 2016b). Thus, ceteris paribus , immigration could have initiated per capita growth by increasing the working age population.

This paper considers workers with an income equal to or higher than 150% of the national average as white-collar workers. The analysis uses income for the 2014 labour force instead of qualification levels as it is directly linked to the necessary wage sums of Equation 1. According to EVS, the initial distribution of workers in Germany in 2014 was as follows: 24.3% white-collar and 75.7% blue-collar. Of the foreigners living in Germany before the 2015 immigration, 21.6% were white-collar, and 78.4% were blue-collar workers. Equations 8 to 11 suggest that a high share of blue-collar workers among foreigners (and refugees) can, if future refugee immigrants have the same income or qualification distributions as the foreigners already living in Germany, lead to a decrease in the wages of blue-collar workers and an increase in that of white-collar workers.

To measure the net growth effects of refugee immigration, two migration trends are developed (Figure 1). First, a hypothetical migration movement without high immigration numbers, plotted with the help of data obtained from the 13th coordinated population projection (Federal Statistical Office of Germany, 2015). The second migration trend is derived from the actual migration figures between 2015 and 2018 (Federal Statistical Office of Germany, 2019b) and is then linearly adjusted to long-run net immigration of 206,000 as in the second immigration scenario of the 14th coordinated population projection (Federal Statistical Office of Germany, 2019c). A ceteris paribus comparison of the two migration trends allows for an estimation of the net effects of refugee immigration, because of the 1.1 million net immigrants in 2015 (Federal Statistical Office of Germany, 2016c), about 890,000 were refugees (Federal Ministry of the Interior, 2016).

Figure 1 Net immigration trend in Germany and future projections

Note: The grey area on the left side marks the pre-projection period and serves to illustrate the changing immigration in recent years.

Source: Author’s own illustration based on Federal Statistical Office of Germany (2015, 2019b, 2019c).

Main scenarios

Three scenarios are hypothesised as part of the first step of the quantitative analysis. 8 Subsequently, per capita net-growth effects are estimated with the help of a base scenario, which includes the basic assumption about immigrants’ workgroup distribution (21.6% vs 78.4%) derived from the dataset and probable integration times (Table 1).

Table 1 Overview of the main scenarios

Source: Author’s own elaboration.

An average integration time of six years is considered for blue-collar workers, following the work by Manthei and Raffelhüschen (2018). The integration process for white-collar workers is set at nine years, which is 1.5 times longer than for that of blue-collar workers. This is due to the fact that it is extremely important to speak the host country's language in jobs requiring high qualification levels. Further, high-skilled immigrants may first work in jobs below their qualification level to gain financial security. Moreover, the process of acknowledging the qualifications achieved in the home country by German standards, which is required by many jobs, may be time-consuming.

Because the assumptions of integration time and qualification distribution are riddled with uncertainty, two other scenarios are presented – one highly pessimistic and one highly optimistic (Table 1). These scenarios serve as the lower (pessimistic scenario) and upper limit (optimistic scenario) of a result corridor.

In the optimistic scenario, the qualification distribution of immigrants is assumed to be identical to that of the natives in the host country. The share of white-collar workers in the pessimistic scenario is based on the UNESCO International Standard Classification of Education (ISCED11-A) of refugee immigrants in Germany. 9 According to data from the German Institute of Economic Research (2017), about 17% of the refugees entering Germany in 2016 were highly qualified (ISCED11-A level 6 or higher).

Main scenario results

Figure 2 shows the yearly per capita growth effects of both migration trends in the base scenario. As expected, in the first few years, when an assumed integration process delays the newly migrated refugees from entering the labour market directly, per capita growth effects are negative. They are also negative under both migration trends for most years of the projection period and only become slightly positive between 2021 and 2026. While this is mainly due to (e)migration in the early years, the negative growth effects after 2026 are primarily the result of demographic changes following the retirement of the baby boomer generation. As the 14th coordinated population projection includes higher emigration rates, the negative per capita growth effects in the second migration trend (dark green bars) are stronger at first. This is why the net effect of refugee immigration (green line) is also negative in the initial projection years. The break-even point is reached in the year 2021, after which the per capita net growth effects of refugee immigration remain positive until the year 2026. Subsequently, the net effect declines until the per capita growth effects of both migration trends converge. These results suggest that refugee immigration in Germany could indeed have a positive effect on its per capita growth in some years.

Figure 2 Yearly growth effects (per capita) in the base scenario

Note: The zigzag course in 2017/2018 is data-driven as the number of emigrants dropped sharply in 2017 (in the 14th coordinated population projection).

Source: Author's estimations.

Figure 3 displays the aggregated per capita growth effect across the years of the projection period. The net effect (dashed line) reaches a break-even point in 2026 and stabilises with a long-term positive growth effect of approximately 1.70%. This confirms the results presented in Figure 2, suggesting that refugee immigration could lead to long-term per capita growth even with a below-average qualification structure. However, it is important to note that the assumptions described in the ‘main scenarios’ above are subject to uncertainty. Therefore, the net per capita growth effects of the pessimistic and optimistic scenarios, in relation to the base scenario, are of interest, too. As expected, the curve of the pessimistic scenario (grey line) is below that of the base scenario. While a longer integration period shifts the break-even point to the right, it is only delayed by around two years and not by three years, as could be inferred by this scenario’s assumptions. The long-term net growth of 1.33% is lower than that of the base scenario, which highlights the importance of the qualification structure of the refugee immigrants.

Figure 3 Main scenarios: Aggregated net growth effects (per capita)

The curve of the optimistic scenario (green line) lies above that of the base scenario. Here, the break-even point is reached about three years earlier than in the base case (in 2023). Additionally, long-term growth is the highest at 1.96% at the end of the projection period. Thus, the results of the optimistic scenario confirm the implications above.

Sensitivity analysis

The second step of the quantitative analysis assesses the impact of individual variables. To examine the effect of each variable, the above three scenarios are remodelled fixing the concerned variable, for example, when analysing the influence of state capital and foreign capital inflows on per capita growth. Alternatively, the same data is used for refugees and residents, for example, for the respective age or qualification structure. Figures 4.A-H show the results in comparison with those from the first step of the quantitative analysis.

The immigrants’ age structure has a strong influence on the per capita growth trend (Figure 4.A). Without such a favourable age structure of refugees, per capita growth will be significantly lower in all three scenarios, by about one percentage point each (thus, half as strong). Weaker but significant effects exist for the qualification structure (Figure 4.B), the wage effects (Figure 4.G), and the relative price development (Figure 4.H). The integration time has no effect on the absolute growth number, but on its growth path (Figure 4.C). State consumption and the state capital stock have negligible effects (Figures 4.D-E).

Figure 4 Sensitivity analysis: Aggregated net growth effects (per capita)

Without migration-induced capital inflows from abroad (Figure 4.F), long-term per capita growth turns negative. 10 This finding underscores the importance of capital inflows, without which a negative correlation can be expected between per capita growth and refugee immigration, even if the qualification structure of refugees is the same as that of the natives (optimistic scenario: -0.62%).

Refugee immigration is currently one of the most crucial topics in European political discourse, and it is likely to remain so in the foreseeable future. The economic consequences associated with refugee immigration can significantly affect the lives of the European population. This study examines the long-term per capita growth effects of refugee immigration with the help of an augmented Cobb–Douglas production model and a two-step quantitative analysis that explored a range of economic scenarios.

The results indicate that refugee immigration can lead to long-term per capita growth. Key to this development is the age structure of refugees and, to a slightly lesser degree, their qualification structure. The length of time needed by refugees to integrate mainly determines the time required to reach the break-even point. Interestingly, the results show that private capital stock has the greatest impact on per capita growth. Without a migration-related increase in the available private capital stock in the host country, positive per capita growth is unlikely, even under optimistic assumptions. In fact, the per capita economic output could drop significantly.

As the proposed model does not contain assumptions that are specific to Germany, the results of the case study may be generalised to other countries affected by refugee immigration. But the effects of refugee immigration on the capital stock in the host country have not yet been conclusively researched. Thus, it is difficult to definitively assert that refugee immigration leads to long-term per capita economic growth in the host country.

Nonetheless, three political implications arise from these results. First, promoting the quick and successful integration of refugees will increase per capita growth. Second, granting permanent residence permits to young and highly qualified individuals will ensure their positive contributions in the long run. And third, reducing barriers to capital inflows is in everyone’s best interest as it is a prerequisite for per capita growth.

• 1 Partly because of the social situation, partly because of the COVID-19 pandemic.
• 2 From a purely legal point of view, those who migrate for economic reasons are not refugees, but they share similarities with refugees in terms of age and qualification structures. Thus, the assumption that both groups have similar implications seems plausible.
• 3 The expected rise in demand alone would lead to growth. Further, each additional employee increases the country’s economic output.
• 4 Borrowing, another possible alternative to finance these costs, is excluded from the model. For host countries that usually follow a strict policy of balanced budgets like Germany, this modelling seems realistic.
• 5 On average, refugees pay €7,100 per person to flee to Germany (Federal Office for Migration and Refugees, 2016), which may possibly constitute their entire mobile capital.
• 6 The equations of the wage bill of all blue-collar workers and of their yearly wage is designed analogously to Equations 9 and 10.
• 7 Growing life expectancy rates and lower birth rates.
• 8 The second step is a sensitivity analysis to assess the impact of single variables.
• 9 Education is segmented into 10 levels in the 2011 version (ISCED11). This paper uses the categorisation attainment (A) for individuals who graduated in their respective segment (ISCED11-A).
• 10 Because of the large population, the overall economic growth, without capital inflow, remains positive in the base scenario (0.83%).

Becker, G. S. (1962), Investment in Human Capital: A Theoretical Analysis, Journal of Political Economy , 70(5), 9-49.

Boubtane, E., J.-C. Dumont and C. Rault (2016), Immigration and Economic Growth in the OECD Countries 1986-2006, Oxford Economic Papers , 68(2), 340-360.

Dustmann, C., F. Fasani, T. Frattini, L. Minale and U. Schönberg (2017), On the economics and politics of refugee migration, Economic Policy , 32(91), 497-550.

Federal Ministry of the Interior (2016), 890.000 Asylsuchende im Jahr 2015, press release, https://www.bmi.bund.de/SharedDocs/pressemitteilungen/DE/2016/09/asylsuchende-2015.html (24 January 2019).

Federal Office for Migration and Refugees (2016), IAB-BAMF-SOEP-Befragung von Geflüchteten: Überblick und erste Ergebnisse, Forschungsbericht , 29, 1-80.

Federal Statistical Office of Germany (2015), Bevölkerung Deutschlands bis 2060 – Ergebnisse der 13. Koordinierten Bevölkerungsvorausberechnung.

Federal Statistical Office of Germany (2016a), Volkswirtschaftliche Gesamtrechnungen 2015: Detaillierte Jahresergebnisse , Fachserie 18 Reihe 1.4.

Federal Statistical Office of Germany (2016b), Bevölkerung und Erwerbstätigkeit 2015: Bevölkerungsfortschreibung auf Grundlage des Zensus 2011 .

Federal Statistical Office of Germany (2016c), Höchststände bei Zuwanderung und Wanderungsüberschuss in Deutschland, press release, https://www.destatis.de/DE/Presse/Pressemitteilungen/2016/07/PD16_246_12421.html (24 January 2019).

Federal Statistical Office of Germany (2019a), Bevölkerung und Erwerbstätigkeit: Wanderungen 2017 , Fachserie 1 Reihe 1.2.

Federal Statistical Office of Germany (2019b), Wanderungen zwischen Deutschland und dem Ausland: Deutschland, Jahre, Nationalität, Altersjahre , Table 12711-0007.

Federal Statistical Office of Germany (2019c), Bevölkerung Deutschlands bis 2060: Ergebnisse der 14. koordinierten Bevölkerungsvorausberechnung .

Fratzscher, M. and S. Junker (2015), Integration von Flüchtlingen: Eine langfristig lohnende Investition, DIW-Wochenbericht , 82(45), 1083-1088.

German Institute for Economic Research (2017), IAB-BAMF-SOEP-Befragung von Geflüchteten 2016: Studiendesign, Feldergebnisse sowie Analysen zu schulischer wie beruflicher Qualifikation, Sprachkenntnissen sowie kognitiven Potenzialen, Politikberatung kompakt , 123, 1-86.

GfK Verein (2018), Challenges of Nations 2018 , Nuremberg Institute for Market Decisions.

Haller, M. (2017), Die „Flüchtlingskrise“ in den Medien, OBS-Arbeitsheft , 93, 1-182.

Lundborg, P. (2013), Refugees’ Employment Integration in Sweden: Cultural Distance and Labor Market Performance, Review of International Economics , 21(2), 219-232.

Manthei, G. and B. Raffelhüschen (2018), Migration and Long-Term Fiscal Sustainability in Welfare Europe: A Case Study, FinanzArchiv , 74(4), 446-461.

Perch-Nielsen, S. L., M. B. Bättig and D. Imboden (2008), Exploring the link between climate change and migration, Climatic Change , 91(3-4), 375-393.

Piras, R. (2011), The Solow Growth Model With Endogenous Migration Flows and Congested Public Capital, Economia Politica , 28(2), 195-217.

Research Data Centre of the Statistical Offices of the Federal States (2015), Einkommens- und Verbrauchsstichprobe (HB) 2013 .

Ruist, J. (2015), The Fiscal Cost of Refugee Immigration: The Example of Sweden, Population and Development Review , 41(4), 567-581.

Samuelson, P. A. (1948), International Trade and the Equalisation of Factor Prices, The Economic Journal , 58(230), 163-184.

Stark, O. (2017), Global Integration and World Migration, ZEF-Discussion Papers on Development Policy , 233, 1-19.

van Suntum, U. and D. Schultewolter (2016), Das Costa Fast Gar Nix? Das Costa Ganz Viel! Kritik einer DIW-Rechnung zu den Ökonomischen Auswirkungen der Flüchtlinge, ifo-Schnelldienst , 69(4), 30-38.

Download as PDF

© The Author(s) 2021

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/ licenses/ by/4.0/ ).

Open Access funding provided by ZBW – Leibniz Information Centre for Economics.

Search results on EconBiz

• Employment Assimilation of Immigrants in the Netherlands: Catching Up and the Irrelevance of Education Zorlu, Aslan; Hartog, Joop
• Employment assimilation of immigrants in the Netherlands : catching up and the irrelevance of education Zorlu, Aslan; Hartog, Joop
• Employment Assimilation of Immigrants in the Netherlands : Catching Up and the Irrelevance of Education Zorlu, Aslan; Hartog, Joop
• The Effect of Integration Policies on the Time until Regular Employment of Newly Arrived Immigrants: Evidence from Denmark Clausen, Jens; Heinesen, Eskil; Hummelgaard, Hans; Husted, Leif; Rosholm, Michael
• The effect of integration policies on the time until regular employment of newly arrived immigrants : evidence from Denmark Clausen, Jens; Heinesen, Eskil; Hummelgaard, Hans; Husted, Leif; Rosholm, Michael

Show all results

More from this issue

• Why the COVID-19 Pandemic Could Increase the Corporate Saving Trend in the Long Run Markus Demary; Stefan Hasenclever; Michael Hüther
• COVID-19 and the Growth Potential Michael Grömling
• COVID-19: Lockdowns, Fatality Rates and GDP Growth Michael König; Adalbert Winkler
• Restoring Public Trust After Trump and COVID-19 Jiffer Bourguignon; Ekaterina Sprenger
• The New Transatlantic Partnership Steven Blockmans; Simon J. Evenett; Claudia Kemfert; Simona R. Soare; Stephan Wittig

• Main navigation
• Main content

What is “economic migration,” and why is it important enough for economists to study?

• Stephan D. Whitaker

As appeared in the Cleveland Fed Digest's Ask the Expert

Economic migration is the term used when people move from one region to another for a job. They could be moving any distance from their current residence, within a state, from Erie to Pittsburgh, for example, or cross-country, from Boston to Los Angeles. The people most likely to relocate for a job are people 25 to 54 years old, or “working-age adults.” Younger adults are more likely to move to attend school, and seniors most often move for family reasons.

Economic theory suggests, and a lot of historical experience has confirmed, that migration can be good for economic growth and productivity. We’re more likely to get highly productive, good matches between workers and firms when people can relocate freely and when a firm can expand its hiring search across the country to hire the best worker for the job.

The opposite also holds true. If a worker is not able to move out of his city or state, he has to accept the best job locally that he can find, whether or not it’s a good match. This puts a burden on the hiring firm, too; it also has to settle for what it can get. This issue is important because having mismatched skills and jobs keeps productivity lower than it could be otherwise. Higher productivity means economic growth that benefits everyone.

Personally, I’ve been intrigued by this. I grew up in this area of the country, a region that has been grappling with deindustrialization, which is closely tied to the migration issue. National policymakers want to see people migrate out of areas that have lost thousands of jobs because this helps alleviate unemployment and poverty. Regional policymakers always want to retain and attract educated workers for the local firms in growing industries. In recent years, all types of migration, including economic migration, have slowed down. Right now, economists are trying to determine how much of the slowdown is due to a lack of regions offering great economic opportunities or a growing similarity between job markets across the country.

Want to learn more?

You’re here today..

Don’t miss what we produce next. Subscribe to Cleveland Fed Digest.

Cleveland Fed Digest delivers right to your inbox once a month research you can use, expert answers to timely questions, and news of upcoming events. If you’re not yet a subscriber to Cleveland Fed Digest , share your email address (and just that!) to receive the newsletter each month. We welcome your feedback, too! Contact [email protected] with questions or comments.

Rest assured, we do not sell or share your email address, and you may unsubscribe at any time.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 17 November 2021

The economic dimension of migration: Kosovo from 2015 to 2020

• Labinot Hajdari   ORCID: orcid.org/0000-0002-3568-0320 1 &
• Judita Krasniqi 1  

Humanities and Social Sciences Communications volume  8 , Article number:  273 ( 2021 ) Cite this article

8189 Accesses

4 Citations

19 Altmetric

Metrics details

• Politics and international relations

A Correction to this article was published on 28 March 2022

A Correction to this article was published on 30 November 2021

This article has been updated

This article investigates the link between economic development and emigration from Kosovo between 2015 and 2020. The wider contexts to this study include the empirical and theoretical debates on migration as both an individual choice and a social decision. The recent history of emigration from Kosovo is analysed to understand how the past has influenced present migration patterns. This work aims to unpick the threads connecting economic development, the labour market, educational disparities, unemployment, and EU integration. Demographics, economics, and the political relationship between Kosovo and the EU have all affected emigration trends in Kosovo. In particular, this article examines the brain drain phenomenon and economic stability as two variables that permanently influence one another.

Similar content being viewed by others

Demographic and labor force impacts of future immigration flows into Europe: does an immigrant’s region of origin matter?

Irregular migration is skilled migration: reimagining skill in EU’s migration policies

Experts’ assessments of migration scenarios between the Middle East & North Africa and Europe

Introduction.

Migration is one of the most significant aspects of globalization. Migrants can be defined as people who change their country of residence for a particular time, as one main definition by the World Bank (World Bank Group, 2018 ). People choose or are forced to cross international borders for reasons that include: work opportunities, high poverty rates in their country of residence, war or conflict, and climate change (Brander et al., 2020 ). According to the European Committee on Migration, “the term ‘migrants’ is used … to refer, depending on the context, to emigrants, returning migrants, immigrants, refugees, displaced persons and persons of immigrant background and/or members of ethnic minority populations that have been created through immigration” (European Committee on Migration, 2002 ). According to Passerini et al. ( 2007 ) migration represents mobility and a set of relations between cultures, peoples, and identities. In addition to the benefits that migrants bring to both destination country and sending country, in recent decades migration has also involved various UN and international agencies wishing to protect migrants from human rights abuses and human trafficking. Concerns include inferior pay compared to destination country citizens, slave working conditions, human trafficking, and risks to women and children (UNODC, 2018 ).

The 2020 World Migration Report estimated ~281 million migrants constituting 3.6% of the global population. The impact of globalization is noticeable, with an increase of 128 million migrants since 1990 (McAuliffe and Khadria, 2020 ). The European Union (EU) holds 86 million migrants according to the same report, with 37.1 million more migrants than in 1990 (UN DESA, 2019 ).

According to the United Nations Department of Economic and Social Affairs (UN DESA) migration is closely related to economic, social, demographic, political, and technological changes in both sending and destination countries. Although migrants usually target higher-income countries, the reasons for migration are diverse. For some sending countries, their people migrate for economic, political, trade, or cultural reasons, while for countries such as Syria, Iraq, or Afghanistan, the high rate of migration is caused by long-term conflict (UN DESA, 2019 ). The most common reason for migration is a lack of employment in the sending country, coupled with greater labour demand and higher wages in the destination country. Nearly two-thirds of the estimated 281 million migrants in 2020 were labour migrants, motivated by a desire to find work (UN DESA, 2019 ).

This article takes Kosovo as a case study to identify the patterns linking economic development, stability, and migration trends. The impact of social history, the mismatched relationship between the educational system and labour market demands, high unemployment and demographic composition, and current migration trends (caused by the inertia characterizing the Kosovo–EU relationship) are investigated. This article also analyses the relationship between migration and the brain drain phenomenon to explain the ‘vicious circle’ of economic development and migration. A mixed-method analysis of the combined statistical data on migration between 2015 and 2020 is performed and examined alongside existing research on the historic impact of socio-political circumstances on migration trends. Although the social change in Kosovo is accelerated due to globalization, and migration motives have changed from being a collective decision or highly influenced by the family and society, towards an individual rational choice to maximize the utility of opportunity gaps between sending and destination countries. This migration pattern is one of the main arguments of Neoclassical theory at the macro level defined by Haris and Todaro’s theory and a part of the functionalist approach on migration (Haris, Todaro, 1970 ) as the data in Kosovo show that migration is still highly motivated by high unemployment, poverty and immigrant restrictions, which are highly ignored by functionalist theory, the migration motives and pattern in Kosovo is still best defined by Oded Stark and David Bloom’s New Economy theory on labour migration (Stark, 1991 ).

Nevertheless, it is important to note that although, in the case of Kosovo, migration trends are still strongly affected by the household or the family, the changes undergone by Kosovo in the last two decades—especially the societal transition from the collective family to more cellular families—have diluted the impact of larger families on migration. By examining the brain drain effect, this article claims that, although migration for socio-economic issues continues to be a leading cause of migration, the departure of highly skilled and well-educated people shows that reasons for migration have become more personal, as individuals pursue better living conditions to match their value in the labour market. However, according to de Haas ( 2021 ) if we define the functionalist “push and pull” theory as “most people migrate in expectation of finding better opportunities at the destination” it is only a general assumption and it fails to provide reasons for migration and, patterns of social differences and nature of migration processes, patterns or motives of migration, such as structural inequality and the impact of society and family in migration deployment. Thus, according to Stark, although individuals are engaged in migration, their decision to migrate can be undertaken influenced by other person or group of people such as family; there is more to migration than wage differentials because the labour market would have been equal and fair on the first place it would not have produced wage inequalities, thus there would be no motives for migration on the basis of wage differentials (Stark, 1991 ).

The historical context of migration and human rights in Kosovo

The history of Kosovo has significantly influenced migration, affecting the socio-political development and transition of Kosovo before and after the declaration of independence. Between 1969 and 2011, approximately 703,978 Kosovars emigrated, while in 2017, net migration was estimated at 833,739 (KAS, 2018 ). Factors behind migration constantly shift due to as global development evolves. Research has confirmed that both regular and irregular forms of emigration from Kosovo have increased, especially for reasons of employment, education, or family reunion (BPRG, 2020 ).

Source: Processed data, obtained from the Labour Force Surveys of the Kosovo Agency of Statistics (KAS) of 2015, 2016, 2017, 2018, 2019 and Q1 2020.

Source: Data obtained from the Labour Force Surveys of the Kosovo Agency of Statistics of 2016, 2017, 2018, 2019 and Q1 2020.

Source: KAS: Labour Force Survey: 2016—Q3-2020.

Source: KAS—Labour Force Survey q3-2020.

Source: Data from the Employment Agency of the Republic of Kosovo (EARK).

Source: KAS and Ministry of Internal Affairs of Kosovo.

Kosovo is a good Western Balkan location for studying different forms of migration. The historical background for emigration from Kosovo is directly related to the human rights context before and during the 1990s, and the socio-political development of the state-building and transitional process since 1999. The status of Kosovo in Former Yugoslavia has had a large impact on migration. Kosovo had been the least developed Yugoslav province, which in the 1970s saw Kosovo Albanians migrate to North Macedonia, Serbia, Slovenia, Croatia, and Bosnia Herzegovina seeking jobs and better living conditions. During the 1980s and 1990s, Kosovar Albanian emigrants headed increasingly for destination countries in Europe. This change of direction was influenced by the eruption of ethnic tensions accompanying the breakup of Yugoslavia (Dimova, 2007 ). Another aspect of emigration from Kosovo during the Yugoslav Federation—especially in the late 1980s and 1990s—was the persecution and expulsion of Albanian civilians, including the expropriation of their property. In The Road to Independence for Kosovo. A Chronicle of the Ahtisaari Plan , Henry H. Perritt, Jr. writes “Serbian policy toward the ‘Albanian problem’ was to cleanse Kosovo of as many Albanians as possible, to make their lives in Kosovo so miserable that they would be eager to emigrate” (Perritt, 2009 ). Proof of this was the gentlemen’s agreement reached between the former President of the Socialist Federal Republic of Yugoslavia, Josip Broz Tito and the Turkish Foreign Minister, Mehmet Fuat Köprülü, in the early 1950s. The deal was for the expulsion of the Albanian population from Kosovo to Turkey, which led to over 400,000 Kosovar Albanians being expelled to Turkey from 1950 to 1966 (Daskalovski, 2003 ). Meanwhile, the Serbian government continued with its campaign of settling Serbian families in Kosovo, encouraging them to move to Kosovo from other parts of Yugoslavia to maintain an ethnic balance (Perritt, 2009 ). This form of institutionally organized pressure—through the use of force, persecution, harassment, and expropriation—had its main objective to sustain the proportion of the Serbian population in Kosovo. It was considered necessary given that the Albanian population enjoyed the highest birth rate in Europe, and was perceived as a threat to the Serbian population, who had migrated to other Yugoslav centres due to the underdevelopment of Kosovo and low living standards (Dahinden, 2005 ). Discrimination against the Albanian population in Kosovo and Yugoslavia made it more difficult for Albanians to find jobs and secure their subsistence. This ethnic persecution led to the Kosovar Albanian student demonstrations of 1981—described by Misha Glenny as “the shock in the system”—when students at the University of Prishtina demanded better conditions and UN intervention to record human rights violations against Kosovar Albanians. The response was a political crackdown (Glenny, 2000 ).

Albanian students and the academic elite became the target of persecution, or “eliticide”, defined by Denis Gratz as the “systemic elimination of leading figures of a society or a group” (Gratz, 2011 ). Many were consequently forced to leave Kosovo. The highest level of emigration from Kosovo was recorded between 1998 and 1999, due to the ethnic cleansing and human atrocities committed against the Kosovar Albanians by Serbian and Yugoslav military, police, and paramilitary forces. According to the United Nations High Commissioner for Refugees (UNHCR), 600,000 people left Kosovo between 24 March and 19 April 1999 heading mainly to Albania and other bordering countries (Wilkson, 1999 ). The EU, the US, Canada, Australia, and others accepted some refugees to relieve the burden on Albania, North Macedonia, and Montenegro, who were not economically prepared to accommodate the number of refugees from Kosovo (Medecins Sans Frontiers, 1999 ).

UN Security Council resolution 1244 was adopted on 10 June 1999, leading to 600,000 Kosovar Albanians returning home to Kosovo in the first 3 weeks after the end of the war. Despite appeals from NATO and the UNHCR, this marked one of the fastest refugee returns in history (Wilkson, 1999 ). However, according to a World Bank report on migration causes in Kosovo in 2011 writes that the resolution of the conflict after 1999 did not incentivize many migrants to return. The main push factor for Kosovars remained labour migration, with resulting remittances. By World Bank estimates, an economic situation characterized by the highest unemployment rates in Europe saw Kosovo maintain the highest emigration rates in Eastern Europe from 1989 to 2003 (World Bank, 2011 ).

The theoretical debate on migration: the shift from social to individual-based migration

Among the first theories that explain migration is the neoclassical theory, which considers socioeconomic factors as the main reasons for migration. In particular, differences in employment, wages, demand, and the labour market are among the reasons that push individuals to search for places that offer better conditions. According to John Harris and Michael Todaro, the decision for migration is made at the level of the individual, from countries with low labour demand and low pay towards regions with high labour demand and high wages (Harris and Todaro, 1970 ). Moreover, this theory considers migrant individuals to be rational actors who migrate mainly for labour purposes due to social changes, and market and economic equilibrium. Migration according to the Neo-classical theory of the functionalist approach occurs when there are no obstacles to the movement of people, where migration is a change of location due to the social and global changes that affect the lives of people seeking new living locations to maximize their earnings. Contrastingly, Stark maintains that migration behaviour is conditioned by larger social entities and the interactions within them (Stark and Bloom, 1985 ). The New Economic labour migration theory opposes the neoclassical approach that migration is triggered by an economic comparison between costs and benefits. The New Economic model understands international migration to be the result of wage differences between countries; accordingly, the decision to migrate is not the sole choice of individuals but rather a collective decision to maximize income and employment opportunities while spreading the risk (Taylor, 1999 ). The neoclassical approach—which aligns with Sjaastad’s theory of migration between urban and rural areas—is criticized by Kurekova, who states that it has “mechanically reduced migration determinants, ignoring market imperfections, homogenizing migrants and migrant societies and being ahistorical and static” (Kurekova, 2011 ). Moreover, Oded Stark considers that the Neo-Classical theory fails to take into account the psychological and emotional aspects of migration, as well as the impact of migration on those left behind.

This article takes Kosovo as a case study to analyse migration trends via elements of neoclassical theory such as wages and income differentials. However, migration behaviour has historically been understood via New Economic theory, which takes into consideration the traditional elements that characterize Kosovar society, especially the primacy of society over the individual. Regardless of the financial benefit from remittances in Kosovo which according to the World Bank Report on “Migration and Economic Development in Kosovo” are the largest source of economic finance, supporting the livelihoods of Kosovars facing the highest unemployment rates in Europe (World Bank, 2011 ) due to the changes experienced in Kosovar society in the last two decades, the prevalence of individualism over collectivism is now visible. The reasons for migration have changed. For example, previously, socio-economic factors prevailed, where impoverished collective families saw individuals “responsible for cost returns” migrate to higher-income countries. In contrast, over the last two decades, young people have begun to migrate for educational reasons. Although the 2009 World Bank migration survey stated that the number of educational migrants was <10%, visa applications for study increased from 367 to 994 between 2013 and 2018 (EUROSTAT, 2021a , 2021b ).

Migration causes and motives: unemployment, the labour market, and education

This article is focused on economic and socio-political factors and, in particular, how both factors often combine to encourage emigration. The reasons for migration are rooted in the country of origin and the destination country. Favourable and unfavourable circumstances in the country of origin and destination country encourage individuals to migrate to a new location with better economic, socio-political, or environmental factors (Dubey and Mallah, 2015 ). Economic migration is related to poor economic conditions and scarce employment opportunities in the sending country. Pull factors in the destination country include higher wages and labour market demand. Push factors in the country of origin include the social, economic, and political environment, as well as unemployment, and the overall level of poverty. Migration can be understood as a search for new ways to survive. Apart from employment, pull factors are usually related to better general opportunities, including industrial and technological development in the destination country, as well as the opportunity to obtain a higher quality education (Hagen-Zanker, 2008 ).

Socio-economic factors are considered to be the main drivers behind emigration from Kosovo, especially the high unemployment rate (including youth unemployment), low minimum and average salaries, more people on the high poverty line, low access to education and health, corruption, and nepotism (NDI, 2019 ). Migration has influenced social identity, as the Diaspora comes to play an important role in the socio-economic development of Kosovo (BPRG, 2020 ).

Socio-political factors such as political instability, security, infrastructure, and inferior services contribute to dissatisfaction among Kosovars—particularly the youth—encouraging migration. An additional migration driver has been the increased desire among Kosovars to emulate EU standards around human rights, gender equality, and economic, social and cultural rights. Kosovo has the youngest population in Europe, but also the poorest. While 53 per cent of the population are under 25 years old (UNDP, 2019 ), youth unemployment in Kosovo remained at 46.9% in Q3 2020, which is 31.8% higher than youth unemployment in the EU (EUROSTAT, EUROSTAT, 2021a ). Numerous factors have contributed to the high unemployment rate, compounding the impact of the 1998–99 war that left Kosovo with a shattered economy and severely damaged infrastructure.

Before and during the 1990s, migration trends were understood through the prism of the rising conflict in former Yugoslavia, the violation of the basic human rights of Kosovar Albanians, ethnic discrimination (e.g. the dismissal of all Albanian civil servants from public administration at the beginning of the 1990s), and the rise of extreme poverty. Between 2015 and 2020, despite migration reasons remaining broadly the same, some of the underlying factors affecting migration changed.

In 2020, Kosovo’s population was ~1.8 million, with a GDP per capita of 4.145 USD.

Although economic growth over the last decade was the highest among World Bank Group member countries, it was insufficient to reduce unemployment and provide stable quality jobs (World Bank, 2021 ). The average unemployment among youths (15–24) between 2015 and 2019 was 53.5%.

According to labour market indicators for 2015 to Q1 2020, ~66.76% of working-age Kosovars were unemployed or inactive. Between 2015 and 2020, ~37% of the working-age population were out of the labour market (Krasniqi, 2021 ) (Fig. 1 ).

The most concerning labour market indicator was the high number of inactive women, which only fell by 1.5% between 2016 and 2020. In real numbers, the number of inactive women actually rose (KAS 2016, 2017, 2018, 2019 and Q1 2020) (Fig. 2 ).

Apart from high rates of unemployment (Fig. 3 ) and inactivity, the labour market in Kosovo is characterized by high gender inequality. In Q1 2020, 44% of men were employed compared to 14.1% of women (KAS, 2020 ). Women are nearly 66% less likely to be employed than men in Kosovo, an indicator of traditional gender stereotyping in the labour market (Fig. 4 ). Moreover, due to the effect of the COVID-19 pandemic, unemployment increased in 2020. Consequently, the number of registered unemployed also rose drastically. According to the Employment Agency of Kosovo, between March and October 2020, 81,911 job seekers registered for the first time, illustrating the impact of the pandemic on the labour market (EARK, 2020) (Fig. 5 ).

The high unemployment and inactivity rates in Kosovo over the last decade drove emigration between 2015 and 2020.

Migration trends 2015–2020

Migration trends from Kosovo between 2015–2020 were driven by several factors, particularly the high unemployment rate, low employment opportunities, high levels of institutional corruption and nepotism, poor living conditions, increasing levels of poverty, and inadequate standards of health and education, all of which remained unaddressed by the state. Young people, disillusioned by ongoing labour market irregularities including the violation of workers’ human rights, saw better life opportunities in EU countries and beyond (BPRG, 2020 ).

The population census of 2011 showed that ~30% of Kosovars live abroad. According to official data, between 2011 and 2017, more than 180,000 Kosovars emigrated, and between 2013–2017 around 170,000 departed via both regular and irregular migration (Government Authority for Migration, 2018 ) (Fig. 6 ). According to the Kosovo Agency of Statistics, 220,000 Kosovars emigrated over the last decade. Emigration was highest in 2015 when 75,000 left in one year (Fig. 6 ). Migration decreased in succeeding years, although 2018 was an outlier with 28,000 emigrants departing, mainly seeking employment in Germany, Slovenia, and Croatia according to the Ministry of Internal Affairs of Kosovo. By 2019, it was estimated that 1.96% of Kosovars lived abroad, including legal and illegal migrants (KAS, 2019 ).

Between 2014 and 2015, according to institutional data in Kosovo, 100,000 Kosovars emigrated for EU countries, discouraged by the political and economic situation in Kosovo post the 2014 elections. Over 2014–15, there was a large increase in Kosovar asylum seekers to the EU, from ~38,000 to 73,000, although in 2019 this number dropped steeply (EUROSTAT, 2021a , 2021b ). One main reason for this was the change in asylum policy by EU member states, which categorized Western Balkan countries as “safe” for returnees. Accordingly, in 2014 and 2015, almost 17,000 people returned to Kosovo (EU Commission, 2015 ), while according to official statistics of KAS, the number of repatriated was approximately 24,000 (Fig. 6 ).

According to the Kosovo Agency of Statistics (KAS), migration trends in Kosovo continued into 2019, when 1.96% of the resident population emigrated regardless of motive. Based on “Population Assessment for 2018” estimates, the number of legal and illegal emigrants in 2019 was 34,911. The majority of migrants were legal, leaving for a family reunion, long-term study, marriage, or employment reasons (KAS, 2019 ).

Official statistics listed the main destination countries as Germany (39% of total migrants), Switzerland (23%), Italy (7%), Austria (7%), Sweden (7%), and other countries (17%) (KAS, 2018 ).

The official data on migration and repatriation trends for Kosovo between 2012 and 2017 showed that the gap between emigrants and returnees increased significantly in 2015 and 2017 when a wave of migration was triggered in Kosovo (Fig. 6 ). The research found that these trends have a direct correlation with Kosovo’s signing of the Stabilization and Association Agreement (SAA) with the EU in 2015, which—in principle—allows citizens of the signatory country to move freely in the Schengen Area without a visa. For Kosovo, this was a long-awaited moment. However, after the SAA agreement, EU countries were reluctant to grant the visa waiver to Kosovar citizens, fearing an influx of labour migrants due to high unemployment rates in Kosovo. In response, a wave of illegal migration erupted among a mostly young population of 1.8 million population, disappointed by EU intransigence and frightened of being isolated. In past and present, the overriding factor encouraging emigration from Kosovo has been the effect of migration remittances. In 2017, remittances reached 759.2 million EUR, representing the second-largest category of income, with an annual increase of 9.9% (CBRK, 2018 ). In 2018, income from remittances increased to 800.5 million (a 5.4% annual increase) (CBRK, 2019 ), while in 2019 the value of remittances was 6.4% higher than in 2018. In 2020 remittances increased by 980.1 million EUR. This 15.1% increase was the largest to date (CBRK, 2020 ) despite the impact of COVID–19 on countries where the Kosovar Diaspora was concentrated (especially Germany and Switzerland, which account for 42.3% of remittances to Kosovo) (CBRK, 2021 ).

The brain drain and EU double standards

The impact of globalization and the integration of Western Balkan states into the EU—in particular the integration process for Kosovo—have deeply influenced domestic economies and social attitudes towards migration in societies affected by the “brain drain” effect. The contractual relationship between the EU and the Western Balkans—both collectively but also with individual countries post-SAA and Visa Liberalization Dialogue (VLD) evaluation by the EU—is a major determinant of migration policy and practice in Kosovo. The contradiction between the EU’s strategy to integrate the Western Balkans and the reluctant stance of EU countries to allow visa waiver for Kosovo has generated massive flows of migrants into EU countries. The SAA stipulates that, upon fulfilment of EU criteria, a country will be “granted” visa-free status. Despite this, as of 2021, Kosovo remains the only WBG country with positive feedback from the EC where the SAA has not been implemented.

Economic and political instability, together with low job opportunities at home, are some of the main push factors encouraging the educated and highly skilled to emigrate. In the meantime, the increase of legal forms of migration (linked to family reunions and education) show that pull factors within EU countries seeking qualified Western Balkan workers have made enforcement efforts by Kosovar migration monitors more difficult.

Figure 7 shows that according to the Employment Agency of Kosovo (EAK), the majority of registered unemployed were from elementary occupational backgrounds, while about 20% of unemployed in 2020 had either managerial or professional backgrounds (Table 1 ). In 2020, the number of jobseekers exceeded the 1978 job vacancies requiring degree-level qualifications by 178.9% (Fig. 7 ). According to this data, over 94% of degree holders (including Masters’ and PhDs) were unemployed (EARK, 2015 – 2020 ) (Fig. 7 ).

Source: Employment Agency of the Republic of Kosovo, 2015–2020.

The phenomenon of migration by qualified workers from developing countries has been called the “brain drain”. It can also be understood as a loss of university-educated human capital due to a lack of innovation within the home labour market. Sociological theory understands the brain drain as a phenomenon affected by capital fluctuations, as well as pull factors such as better quality of life, security, and employment opportunities in destination countries. Recent studies have also shown that, apart from EU integration, the Western Balkan brain drain is caused by a surplus of skilled workers, in professions that the labour market could not accommodate. This is caused by a lack of coordination between the labour market and the education system, which contributes to graduate unemployment. The lack of cooperation between academic institutions and the private sector has led to educated and qualified workers being seen for their quantity rather than their quality. This deficiency in coordination steepens the imbalance between the supply of qualified workers and labour market demand. In particular, there are too many graduates in economics and law, and too few in IT.

The brain drain in Kosovo is particularly seen among health workers, which has harmed the Kosovar health system. KAS figures state that 100,000 Kosovars emigrated in 2014 and 2015 (KAS, 2018 ) By 2018, it was estimated that about 854,198 Kosovo citizens lived abroad, mainly in Germany and Switzerland (MIA, 2018) According to the KAS report of 2019 there are 3555 doctors in Kosovo, an estimated ratio of 2.5 doctors per 1000 citizens. According to both the Chamber of Doctors and the Chamber of Nurses, in a country where the density of doctors and nurses per capita is almost the lowest among Council of Europe states (of which Kosovo is not yet a member), one doctor emigrates every two days, and two nurses emigrate every day. This level of migration has emptied medical centres of their qualified staff and deprived patients of medical care. It has also harmed the economy, reflected in wasted education spending and the cost to the taxpayer—to train one doctor costs nearly 100,000 EUR. Kosovo, with a population of 1.8 million, has seen medical centres close in cities such as Peja and Gjakova due to the medical brain drain. Compared to other Western Balkan countries, Albania has 1.2 doctors per 1000 people, Turkey 1.8 per 1000, and Bosnia Herzegovina 2 per 1000. Meanwhile, Germany has 4.2 doctors per 1000 and Sweden 5.4 per 1000 (World Bank Data, 2019 ).

Among the most popular destination countries for doctors and health workers emigrating from the Balkans is Germany, due to the overwhelmingly improved working conditions and wages. The Dean of the Medical Faculty at the University of Prishtina described how medical students take private German language courses in preparation for post-graduation emigration (Ahmetxhekaj, 2019 ). This migratory trend of doctors and nurses influenced Germany’s 2015 decision to open the labour market to six WBG countries in parallel with a tough new policy against asylum seekers. This provided a route for skilled migrants to avoid illegal or irregular migration by accessing programs to allow them to benefit from labour shortages in Germany. This has reduced human capital in Kosovo causing significant depletions in key professions. It is feared that Kosovo’s population will continue to shrink.

Compared to other Western Balkan states, Albania is the fourth highest in terms of high skilled workers emigrating. Starting with the massive migration after the fall of communism, the trend has not slowed subsequently. The Economist places Albania first on the list of Western Balkan countries, with migration at 29%, compared to Bosnia Herzegovina at 20%, and North Macedonia at 18%. In comparison, destination countries have benefited from migration, receiving skilled workers who fill gaps in the labour market, with spending on training unnecessary. Demand is high and spread across the labour market, in particular for doctors, engineers, and IT specialists, as well as low-skilled workers required for menial or dangerous roles The Economist ( 2020 ).

Conclusions

Migration is many things. It can be an individual decision to change the country of residence. It can be the social impact of a mass movement of people to other countries for economic purposes. A complex process, migration speaks to the regional and global changes impacting the lives of individuals and wider society. Migration trends in Kosovo are characterized by individual or collective decisions to pursue improved living conditions and escape high poverty rates. Such pull and push factors encourage emigration to high-income countries experiencing labour shortages. Emigration has different impacts on sending country and destination country.

Observing the economics of emigration from Kosovo over recent decades suggests that the main reasons for emigration were high poverty rates and human rights violations. Both of these causes aggravated the living conditions for ethnic Albanians in Kosovo, already suffering because of ethnic discrimination by the state. However, migration trends in Kosovo between 2015 and 2020 show that push factors not only influenced society but also individual decisions. This is explained by the large youth population in Kosovo, low opportunities, and high unemployment. Moreover, the high percentage of unemployed educated people in Kosovo explains the migration peaks of 2015 and 2017. The SAA and VLD oblige Kosovo to better “manage” migration by monitoring numbers, enforcing migration law, and policing borders. Despite these obligations, as long as half of young people in Europe’s youngest population cannot find work, Kosovars will continue leaving. Contemporaneously, while Kosovars are denied the visa waiver for political reasons, individual EU countries have opened legal migration pathways for highly skilled Western Balkan migrants, intensifying the brain drain in vital sectors such as health and IT.

Migration trends reflect the disconnect between education and labour market demands, characterized by the imbalance between the numbers of new graduates and employers’ capacity to absorb them into the workforce. As long as Kosovo remains the only Western Balkan country excluded from EU visa waiver, unemployed Kosovar youth will continue illegal migration, which highlights the absurdity of the EU’s counterproductive strategy of isolating Kosovo.

In conclusion, the doors of the EU remain (predominantly) closed to unqualified Kosovars. EU countries experiencing shortages in key professional sectors, including doctors and nurses, have welcomed suitably qualified Kosovars. The economic impact of selective Kosovar emigration to the EU has led to a health care crisis at home. Although unemployment remains the principle migratory push factor, the emigration of educated Kosovars has caused the most severe economic consequences, exacerbated by the dysfunction of the EU’s selective approach towards the citizens of Kosovo.

Data availability

All data analysed are included in the paper.

Change history

28 march 2022.

A Correction to this paper has been published: https://doi.org/10.1057/s41599-022-01119-2

30 November 2021

A Correction to this paper has been published: https://doi.org/10.1057/s41599-021-00998-1

World Bank Group (2018) Western Balkans labor market trends 2018. The Vienna Institute for International Economic Studies:9, Washington

Book   Google Scholar  

Ahmetxhekaj, K (2019) Ikja e trurit: A do t’i fike dritat mjeku i fundit qe largohet nga Kosova. Balkaninsight. https://balkaninsight.com/2019/12/04/ikja-e-trurit-a-do-ti-fike-dritat-mjeku-i-fundit-qe-largohet-nga-kosova/?lang=sq

Balkans Policy Research Group (2020) Kosovo: trends of migration require a new strategic approach. Political analysis. BPRG. https://balkansgroup.org/wp-content/uploads/2020/10/Kosova_Trendet-e-Migrimit-kerkojne-nje-qasje-te-re-strategjike-.pdf Accessed 19 Jun 2021

Brander P, Keen E, Juhasz V, Schneider A (2020) Compass: manual for human rights education with young people, 2nd edn. Council of Europe Publishing. https://rm.coe.int/compass-eng-rev-2020-web/1680a08e40 Accessed 19 Jul 2021

Central Bank of the Republic of Kosovo (2018) Annual report 2017. https://bqk-kos.org/repository/docs/2018/CBK_AR_2017.pdf Accessed 19 Jul 2021

Central Bank of the Republic of Kosovo (2019) Annual report 2018. https://bqk-kos.org/repository/docs/2018/CBK-AR-2018.pdf Accessed 19 Jul 2021

Central Bank of the Republic of Kosovo (2020) Annual report 2019. https://bqk-kos.org/wp-content/uploads/2020/10/CBK_AR_2019.pdf Accessed 19 Jul 2021

Central Bank of the Republic of Kosovo (2021) Annual report 2020. https://bqk-kos.org/wp-content/uploads/2021/07/CBK_AR_2020.pdf Accessed 19 Jul 2021

Dahinden J (2005) Contesting transnationalism? Lessons from the study of Albanian migration networks from former Yugoslavia. Global Netw 2(5):191–208. https://doi.org/10.1111/j.1471-0374.2005.00114.x

Article   Google Scholar  

Daskalovski Z (2003) Claims to Kosovo: nationalism and self-determination. In: Bieber Florian, Daskalovski Zidas (eds) Understanding the WAR in KOSOVO. Frank Class Publishers, London, pp. 17–20

de Haas H (2021) A theory of migration: the aspirations- capabilities framework. Comp Migr Stud 9(8):1–35. https://doi.org/10.1186/s40878-020-00210-4

Dimova R (2007) From past necessity to contemporary friction: migration, class and ethnicity in Macedonia. Max Planck Institute for Social Anthropology Working Papers (94). https://www.eth.mpg.de/pubs/wps/pdf/mpi-eth-working-paper-0094 Accessed 19 Jul 2021

Dubey S, Mallah V (2015) Migration: causes and effects. Geography. Semantischolar. https://www.semanticscholar.org/paper/Migration%3A-causes-and-effects-Dubey-Mallah/c4068d658b873a5e5073913527736c4b0864a5cb Accessed 19 Jul 2020

Employment Agency of the Republic of Kosovo, (2015–2020) https://aprk.rks-gov.net/

European Commission (2015) Commission Staff Working Document: Kosovo 2015 report. European Commission. SDW (2015) 215 final. Brussels:58. https://ec.europa.eu/neighbourhood-enlargement/sites/near/files/pdf/key_documents/2015/20151110_report_kosovo.pdf Accessed 19 Jul 2021

European Committee on Migration (2002) Towards migration management strategy. Council of Europe, Strasbourg

EUROSTAT (2021a) Permits by reason, length of validity and citizenship 2010–2015. https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=migr_resfirst&lang=en

EUROSTAT (2021b) Youth unemployment. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Youth_unemployment Accessed 19 Jul 2021

Glenny M (2000) Balkans: 1804–1999: nationalism, war and great powers. Granta Books, London, p. 624

Google Scholar  

Government Authority for Migration (2018) Extended profile on migration 2013–2017. Prishtina. https://mpb.rks-gov.net/Uploads/Documents/Pdf/EN/41/EXTENDED%20MIGRATION%20PROFILE%202013-2017_final%20II%20(1).pdf Accessed 19 Jul 2021

Gratz D (2011) Elitocide in Bosnia and Herzegovina and its impact on the contemporary understanding of the crime of genocide. Natl Pap 39(3):409–424. https://doi.org/10.1080/00905992.2011.565318

Hagen-Zanker J (2008) Why do people migrate? A review of the theoretical literature. Mastricht Graduate School of Governance Working Paper: WP002. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1105657

Harris J, Todaro M (1970) Migration, unemployment and development: a two sector analysis. Am Econ Rev 1(60):126–142. https://www.jstor.org/stable/1807860

Harris JR, Todaro MP (1970) Migration, unemployment and development: a two-sector analysis. Am Econ Rev 60(1):126–142

Henry Jr HP (2009) The road to independence for Kosovo: a chronicle of the Ahtisaari Plan. Cambridge University Press, Cambridge, pp. 19–21

Kosovo Agency of Statistics (2015–2020) Labour Force Survey. https://ask.rks-gov.net/en/kosovo-agency-of-statistics/general-statistics

Kosovo Agency of Statistics (2018) Statistical Yearbook. Office of the Prime Minister of the Republic of Kosovo. https://ask.rks-gov.net/media/4356/vjetari-statistikor-shtator-2018-final.pdf Accessed 19 Jul 2021

Kosovo Agency of Statistics (2019) Statistical Yearbook. Office of the Prime Minister of the Republic of Kosovo. https://ask.rks-gov.net/media/5494/vjetari-2019_ang-final.pdf Accessed 19 Jul 2021.

Krasniqi J (2021) Who pays the highest price? The impact of COVID-19 on women’s employment in Kosovo. Democracy for Development Institute https://d4d-ks.org/en/papers/who-pays-the-highest-price-the-impact-of-covid-19-on-womens-employment-in-kosovo/

Kurekova L (2011) The effects of structural factors in origin countries on migration: the case of Central and Eastern Europe. DEMIG (8):45 International Migration Institute. University of Oxford. https://ora.ox.ac.uk/objects/uuid:c60b318d-f3da-49b5-97a0-e3050d5f810e/download_file?safe_filename=WP45%2BThe%2Beffects%2Bof%2Bstructural%2Bfactors%2Bin%2Borigin%2Bcountries.pdf&file_format=application%2Fpdf&type_of_work=Working+paper Accessed 19 Jul 2021

McAuliffe M, Khadria B (eds) (2020) World Migration Report 2020. International Organization for Migration. https://worldmigrationreport.iom.int/wmr-2020-interactive/

Medecins Sans Frontiers (1999) Kosovo refugees statistics. https://www.msf.org/kosovo-refugees-statistics

National Democratic Institute (2019) Kosovo public opinion survey. NDI Kosovo. https://www.ndi.org/sites/default/files/NDI%20Kosovo%20Public%20Opinion%20Poll%202019.pdf Accessed 10 Jul 2021.

Passerini L, Lyon D, Capussotti E, Laliotou I (2007) Women migrants from east to west: gender mobility and belonging in contemporary Europe. Berghahn Books, New York

Stark O (1991) The migration of labor. Blackwell, Cambridge and Oxford

Stark O, Bloom DE (1985) The new economics of labor migration. Am Econ Rev 75(2):173–78. http://www.jstor.org/stable/1805591

Taylor JE (1999) The new economics of labour migration and the role of remittances in the migration process. Int Migr 37(1):63–88. https://doi.org/10.1111/1468-2435.00066

The Economist (2020) The Balkans are getting short of people: the demography of south-eastern Europe threatens its hopes of prosperity. The Economist. https://www.economist.com/europe/2020/08/20/the-balkans-are-getting-short-of-people

The World Bank (2011) Migration and economic development in Kosovo. WBG poverty reduction and economic management unit Europe and Central Asia region: 60590-XK. https://openknowledge.worldbank.org/bitstream/handle/10986/12868/605900ESW0P123000Migration0Econ0Dev.pdf?sequence=1&isAllowed=y

The World Bank (2019) Physicians (per 1,000 people). World health organization global helaht workforce statistics, OECD. The World Bank DATA. https://data.worldbank.org/indicator/SH.MED.PHYS.ZS?end=2018&locations=XK&start=2018&view=bar Accessed 19 July 2021

The World Bank (2021) The World Bank in Kosovo. https://www.worldbank.org/en/country/kosovo/overview Accessed 19 Jul 2021

UN DESA (2019) International migrant stock 2019. Population Division, New York

UNDP (2019) Social Cohesion in Kosovo: Context review and entry-points. https://www.undp.org/content/dam/kosovo/docs/ResearchAndPublications/UNDP%20FBA%20Social%20Cohesion%20Report%20Final_English.pdf Accessed August 2021

United Nations Department of Economic and Social Affairs, Population Division (2020). International migration 2020 highlights (ST/ESA/SER.A/452). https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/undesa_pd_2020_international_migration_highlights.pdf

United Nations Office on Drugs and Crime (2018) An introduction to human trafficking: vulnerability, impact and action. Vienna. https://www.unodc.org/documents/human-trafficking/An_Introduction_to_Human_Trafficking_-_Background_Paper.pdf

Wilkson R (1999) Kosovo: one last chance. United Nations High Commissioner for Refugees. Geneva. https://www.unhcr.org/3c6914bc5.pdf Accessed 19 Jul 2021

World migration report 2020. International Organization for Migration, https://worldmigrationreport.iom.int/wmr-2020-interactive/

Download references

Acknowledgements

This publication is financed by the Polish National Agency for Academic Exchange as part of the "International Academic Partnerships" under decision no. PPI/APM/2018/1/00019/DEC/1.

Author information

Authors and affiliations.

Universum College, Prishtina, Kosovo

Labinot Hajdari & Judita Krasniqi

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Judita Krasniqi .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Informed consent

Additional information.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Hajdari, L., Krasniqi, J. The economic dimension of migration: Kosovo from 2015 to 2020. Humanit Soc Sci Commun 8 , 273 (2021). https://doi.org/10.1057/s41599-021-00923-6

Download citation

Received : 30 July 2021

Accepted : 27 September 2021

Published : 17 November 2021

DOI : https://doi.org/10.1057/s41599-021-00923-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Causal Relationships Between Economic Dynamics and Migration: Romania as Case Study

• First Online: 17 March 2016

Cite this chapter

• Ioan Ianos 3  

Part of the book series: Advances in Geographical and Environmental Sciences ((AGES))

961 Accesses

7 Citations

Starting from an analysis made on Romania as a case study, the paper develops causal connections between economic dynamics and migration. The analysis is focused on internal and external migration flows during the post-socialist period. The data sources are collected from official statistics, empirical observations and different academic papers. The methodological steps are defined by each significant economic period and the impact on migration phenomenon. The results show an important correlation between the increasing domestic migration flow and the deindustrialization process. The effects of mining restructuring have totally changed the orientation of interregional flows. The traditional rural-urban flows changed direction in the reverse way. Especially, the metropolitan and peri-urban areas are the main winners in comparison with the cities. Excepting the first 2 years (when the ethnic emigration was dominant), during the entire next period, the emigration increased due to economic factors. If in the first three periods (until 2000) a permanent migration can be remarked, especially of highly educated people to USA and Canada, and working emigration especially in Israel, Germany and Austria, through temporary contracts. After 2001, the emigration flows increased dramatically, especially to Spain and Italy. During the financial and economic crisis, the preferences of migration flows changed the main destination, by replacing Spain with Italy (less touched by crisis). The economic consequences on the origin country are less visible at the national or regional level but relevant for some rural localities or small towns.

This study was developed with funding of the projects ESPON GROSSE “Emergence of Growth Poles Network in South-East Europe” and UB 1322 “Integrated and sectorial analyses in trans-scalar territorial dynamics”.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Adumitroaie E, Dafinoiu I (2013) Perception of parental rejection in children left behind by migrant parents. Rev Sociol Interv Soc 42:191–203

Google Scholar  

Agnew J (2001) How many Europes? The European Union, eastward enlargement and uneven development. Eur Urban Reg Stud 8(1):29–38

Article   Google Scholar  

Bailey AJ, Yeaoh BSA (2014) Migration, society and globalization: introduction to virtual issue. Trans Inst Br Geogr 39:470–475

Bartram D (2013) Migration, return, and happiness in Romania. Eur Soc 15(3):408–422

Baubock R (2003) Towards a political theory of migrant transnationalism. Int Migr Rev 37(3):700–723

Bernat JS, Viruela R (2011) The economic crisis and immigration: Romanian citizens in the ceramic tile district of Castelló (Spain). J Urban Reg Anal III(1):45–65

Bonjour S (2011) The power and morals of policy makers: reassessing the control gap debate. Int Migr Rev 45(1):89–122

Bradatan CE, Sandu D (2012) Before crisis: gender and economic outcomes of the two largest immigrant communities in Spain. Int Migr Rev 46(1):221–243

Buch CM, Kuckulenz A (2009) Worker remittances and capital flows to developing countries. Int Migr 48(5):89–116

Careja R (2013) Emigration for development? An exploration of states’ role in the development-migration nexus: the case of Romania. Int Migr 51(5):76–90

Ceobanu AM, Koropeckyj-Cox T (2013) Should international migration be encouraged to offset population aging? A cross-country analysis of public attitudes in Europe. Popul Res Policy Rev 32:261–284

De Haas H (2010) Migration and development; a theoretical perspective. Int Migr Rev 44(1):227–264

De Haas H (2012) The migration and development pendulum: a critical view on research and policy. Int Migr 50(3):8–25

Docquier F, Peri G, Ruyssen I (2014) The cross-country determinants of potential and actual migration. Int Migr Rev 48(S1):37–99

Dominguez-Mujica J, Guerra-Talavera R, Parreno-Castellano JM (2014) Migration at a time of global crisis: the situation in Spain. Int Migr 52(6):113–127

Gamlen A (2014) Diaspora institutions and diaspora governance. Int Migr Rev 48(1):180–217

Garip F (2012) An integrated analysis of migration and remittances: modelling migration as a mechanism for selection. Popul Res Policy Rev 31:637–663

Goeler D, Krisjane Z (2013) On the variability of migration systems (with experiences from Latvia and Albania). Transnationalism or transregionalism? Mitt Osterr Geogr G 155:125–147

Heller W (2013) Who moves within the country? Who emigrates? Who immigrates? Current migrational trends in Romania. Southeast Eur J Polit Soc 2:244–267

Heller W, Ianoş I (2004) Spatial pattern of economy and migration in post-socialist Romania. Eur Reg 1:4–12

Ianoș I (1994) Trente ans de dynamique urbaine en Roumanie: entre homogeneisation et individualisation regionale. Espace Geogr 4:350–360

Ianoş I (1998) The influence of economic and regional policies on migration in Romania. In: Heller W (ed) Romania: migration, socio-economic transformation and perspectives of regional development. Sudosteuropa-Studie 62:55–76

Ianos I (2001) Domestic migration and economic policies in post-totalitarian Romania. In: Petrakos G (ed) Restructuring, stability and development in southeastern Europe (conference proceedings). University of Thessaly, Volos, pp 164–171

Ianos I, Virdol D (2002) Recent characteristics of emigration from Romania. In: Aschauer A (ed) Reden uber Raume: Region-Transformation-Migration. Potsdamer Geographische Forschungen 23:71–90

Jennissen R (2011) Ethnic migration in central and eastern Europe: its historical background and contemporary flows. Stud Ethn Natl 11(2):252–270

Krasteva A (2010). Labor migration in Southeastern Europe. European, regional and national perspectives. http://annakrasteva.wordpress.com/2010/12/05/labor-migration-see/ . Accessed 5 Dec 2012

Leon-Ledesma M, Piracha M (2004) International migration and the role of remittances in Eastern Europe. Int Migr 42(4):65–83

Lianos TP, Cavounidis J (2008) Immigrant remittances, stability of employment and relative deprivation. Int Migr 48(5):118–141

Lindstrom DP (2003) Rural-urban migration and reproductive behavior in Guatemala. Popul Res Policy Rev 22:351–372

Marcu S (2010) The irregular immigration towards the European Union through the Romanian eastern border. Bol Asoc Geógr Esp 53:367–371

Martin R, Radu D (2012) Return migration: the experience of Eastern Europe. Int Migr 50(6):109–128

Neumayer E (2006) Unequal access to foreign spaces: how states use visa restrictions to regulate mobility in a globalized world. Trans Inst Br Geogr NS 31:72–84

Okólski M (2000) Recent trends and major issues in international migration: central and east European perspectives. Int Soc Sci J 52(165):329–341

Piperno F (2011) The impact of female emigration on families and the welfare state in countries of origin: the case of Romania. Int Migr 50(5):189–204

Rangelova R, Vladimirova K (2004) Migration from central and eastern Europe: the case of Bulgaria, South-East Europe. Rev Labour Soc Aff 3(7):7–30

Rotariu T, Mezei E (1998) Internal migration in Romania (1948–1995). In: Heller W (ed) Romania: migration, socio-economic transformation and perspectives of regional development. Sudosteuropa-Studie 62:121–149

Salt J, Almeida JC (2006) International migration in Europe. Rev Eur Migr Int 22(2):155–175

Sandu D (2001) Migraţie şi mobilitate internaţională. https://sites.google.com/site/dumitrusandu/dumitrusandustudiiinrevistesauinvolumec . Accessed 5 May 2015

Sandu D (2005) Dynamics of Romanian emigration after 1989: from macro- to micro-level approach. Int J Sociol 35(3):36–56

Sandu D (2010) Home orientation in transnational spaces of Romanian migration. Stud Univ Babes-Bolyai Sociol LV(2):15–36

Voss PR, Hammer RB, Meier AM (2002) Migration analysis: a case study for local public policy. Popul Res Policy Rev 20:587–603

Download references

Author information

Authors and affiliations.

Interdisciplinary Centre for Advanced Research on Territorial Dynamics, University of Bucharest, 4-12 Regina Elisabeta Blv. Sector 1, Bucharest, Romania

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Ioan Ianos .

Editor information

Editors and affiliations.

University of Las Palmas de Gran Canaria, Las Palmas, Spain

Josefina Domínguez-Mujica

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Singapore

About this chapter

Ianos, I. (2016). Causal Relationships Between Economic Dynamics and Migration: Romania as Case Study. In: Domínguez-Mujica, J. (eds) Global Change and Human Mobility. Advances in Geographical and Environmental Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-0050-8_16

Download citation

DOI : https://doi.org/10.1007/978-981-10-0050-8_16

Published : 17 March 2016

Publisher Name : Springer, Singapore

Print ISBN : 978-981-10-0049-2

Online ISBN : 978-981-10-0050-8

eBook Packages : Earth and Environmental Science Earth and Environmental Science (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

• Browse All Articles
• Newsletter Sign-Up

Immigration →

• 11 Apr 2024
• In Practice

Why Progress on Immigration Might Soften Labor Pains

Long-term labor shortages continue to stoke debates about immigration policy in the United States. We asked Harvard Business School faculty members to discuss what's at stake for companies facing talent needs, and the potential scenarios on the horizon.

• 08 May 2023
• Research & Ideas

How Trump’s Anti-Immigrant Rhetoric Crushed Crowdfunding for Minority Entrepreneurs

When public anxiety about immigration surges, Black, Asian, and Hispanic inventors have a harder time raising funds for new ideas on Kickstarter, says research by William Kerr. What can platforms do to confront bias in entrepreneurial finance?

• 14 Feb 2023

Is Sweden Still 'Sweden'? A Liberal Utopia Grapples with an Identity Crisis

Changing political views and economic forces have threatened Sweden's image of liberal stability. Is it the end of the Scandinavian business-welfare model as we know it? In a case study, Debora Spar examines recent shifts in Sweden and what they mean for the country's future.

• 01 Nov 2022
• What Do You Think?

Why Aren’t Business Leaders More Vocal About Immigration Policy?

Immigration fuels the American economy, feeds the talent pool, and can directly affect company performance. And yet few executives and entrepreneurs have waded into the policy dialogue, says James Heskett. Open for comment; 0 Comments.

• 30 Mar 2021
• Working Paper Summaries

Whose Job Is It Anyway? Co-Ethnic Hiring in New US Ventures

The impact of immigration has been particularly sharp in entrepreneurship, yet there is remarkably little evidence about how immigration in the workplace connects to the creation and scaling of new firms. The economic consequences of greater workplace and entrepreneurial diversity deserve closer attention.

• 11 Jan 2021

The Political Effects of Immigration: Culture or Economics?

This paper reviews and explains the growing literature focused on the political effects of immigration, and highlights fruitful avenues for future research. When compared to potential labor market competition and other economic forces, broadly defined cultural factors have a stronger political and social impact.

• 03 Nov 2020

An Executive Order Worth $100 Billion: The Impact of an Immigration Ban’s Announcement on Fortune 500 Firms’ Valuation

President Trump’s executive order restricting entry of temporary foreign workers to the United States negatively affected the valuation of 471 publicly traded Fortune 500 firms by an estimated $100 billion. Closed for comment; 0 Comments.

• 15 Jun 2020

The Seeds of Ideology: Historical Immigration and Political Preferences in the United States

Researchers test the relationship between historical immigration to the United States and political ideology today.

• 11 May 2020

Immigration Policies Threaten American Competitiveness

At this time of crisis, America risks signaling to global innovators and entrepreneurs that they have no future here, says William R. Kerr. Open for comment; 0 Comments.

• 21 Apr 2020

Changing In-group Boundaries: The Role of New Immigrant Waves in the US

How do new immigrants affect natives’ views of other minority groups? This work studies the evolution of group boundaries in the United States and indicates that whites living in states receiving more Mexican immigrants recategorize blacks as in-group members, because of the inflow of a new, “affectively” more distant group.

• 06 Apr 2020

Where Do Workers Go When the Robots Arrive?

Marco Tabellini and colleagues investigate where workers go after losing their jobs to automation and Chinese imports. Open for comment; 0 Comments.

• 17 Feb 2020

The Impact of Technology and Trade on Migration: Evidence from the US

Labor mobility can re-equilibrate local labor markets after an economic shock. Both robot adoption and Chinese import competition between 1990 and 2015 caused large declines in manufacturing employment across US local labor markets (commuting zones, CZs). However, only robots were associated with a decline in CZ population, which resulted from reduced in-migration rather than by increased out-migration.

• 01 Jan 2020

Why Not Open America's Doors to All the World’s Talent?

SUMMING UP: The H-1B visa program is exploited by some employers to replace high-paid talent, but that doesn't mean foreign workers should be shut out of working in the United States, according to many of James Heskett's readers. Open for comment; 0 Comments.

• 19 Jun 2019

Migrant Inventors and the Technological Advantage of Nations

This study provides robust econometric evidence for how immigrant inventors shape the innovation dynamics of their receiving countries. Countries receiving inventors from other nations that specialize in patenting particular technologies are more likely to have a significant increase in patent applications of the same technology.

• 08 Jun 2019

The Gift of Global Talent: Innovation Policy and the Economy

High-skilled workers in today’s knowledge-based economy are arguably the most important resource to the success of businesses, regions, and industries. This chapter pulls from Kerr’s book The Gift of Global Talent to examine the migration dynamics of high-skilled individuals. He argues that improving our knowledge of high-skilled migration can lead to better policy decisions.

• 07 Feb 2019

Immigrant Networking and Collaboration: Survey Evidence from CIC

This study compares United States-born and immigrant entrepreneurs’ use of networking opportunities provided by CIC, the former Cambridge Innovation Center. Immigrants clearly take more advantage of networking opportunities at CIC, especially around the exchange of advice. It remains to be seen whether this generates long-term performance advantages for immigrants.

• 01 Nov 2018

Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning

Passengers arriving at international hubs often endure delays, especially at immigration and security. This study of London’s Heathrow Airport develops a system to provide real-time information about transfer passengers’ journeys through the airport to better serve passengers, airlines, and their employees. It shows how advanced machine learning could be accessible to managers.

• 01 Oct 2018

Is the US Losing its Ability to Attract Highly Skilled Migrant Workers?

As debates sharpen on the benefits and drawbacks of migrant labor, William R. Kerr's new book explores why global talent flows matter to national economic development and security. Book excerpt and author interview. Open for comment; 0 Comments.

• 19 Sep 2018

From Immigrants to Americans: Race and Assimilation During the Great Migration

The Great Migration of African Americans and the mass migration of Europeans both contributed to forming the modern American racial and ethnic landscape. This analysis finds that native whites more readily accepted European immigrants as African Americans arrived in the US North during the first Great Migration, facilitating the assimilation of European immigrants in northern urban centers.

• 07 Aug 2018

Gifts of the Immigrants, Woes of the Natives: Lessons from the Age of Mass Migration

Investigating the economic and political effects of immigration across US cities between 1910 and 1930, this paper finds that political opposition to immigration can arise even when immigrants bring widespread economic benefits. The paper provides evidence that cultural differences between immigrants and natives were responsible, at least in part, for natives’ anti-immigration reactions.

Causes and impacts relating to forced and voluntary migration Case study: Mexico and the USA

There are two types of migration, forced and voluntary. People migrate for many different reasons. Migration has positive and negative impacts on society.

Part of Geography Population

Case study: Mexico and the USA

According to the International Boundary and Water Commission for the United States and Mexico, the border between the USA and Mexico is 1,954 miles long. Illegal migration is a huge problem. U.S. Border Patrol guards the border and trys to prevent illegal immigrants from entering the country. Illegal migration costs the USA millions of dollars for border patrols and prisons.

There are more than 11 million unauthorised immigrants living in the USA.

Many Americans believe that Mexican immigrants are a drain on the economy. They believe that migrant workers keep wages low which affects Americans. However other people believe that Mexican migrants benefit the economy by working for low wages.

Mexican culture has also enriched the USA border states with food, language and music.

Impact on Mexico

The Mexican countryside has a shortage of economically active people. Many men emigrate leaving a majority of women who have trouble finding life partners. Young people tend to migrate, leaving the old and the very young.

Legal and illegal immigrants together send some $6 billion a year back to Mexico. Certain villages such as Santa Ines have lost two thirds of their inhabitants.

There is a large wage gap between the USA and Mexico. Wages remain significantly higher in the USA for a large portion of the population. This attracts many Mexicans to the USA.

Many people find living in rural Mexico a struggle because they have to survive with very little money. Farmland is often overworked and farms are small.

It is estimated that 10,000 people try to smuggle themselves over the border every week. One in three get caught and those that do are likely to continue trying to cross the border at least twice a year.

More guides on this topic

• Methods and problems of data collection
• Consequences of population structure

Related links

• BBC Weather
• BBC News: Science, Environment
• BBC Two: Landward
• SQA: Higher Geography
• Planet Diary
• Scotland's Environment
• Greenhouse Gas Online
• Geograph British Isles

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Wiley-Blackwell Online Open

Migration aspirations and migration cultures: A case study of Ukrainian migration towards the European Union

Christof van mol.

1 Department of Sociology, Tilburg University, Tilburg, The Netherlands

2 Netherlands Interdisciplinary Demographic Institute (NIDI)/KNAW/UG, The Hague, The Netherlands

5 Centre for Migration and Intercultural Studies (CeMIS), Universiteit Antwerpen, Antwerpen, Belgium

3 Department of Sociology, Erasmus Universiteit Rotterdam (EUR), Rotterdam, The Netherlands

Kenneth Hemmerechts

4 Vrije Universiteit Brussel (VUB), Brussels, Belgium

Christiane Timmerman

An abundant body of research focused on macrolevel, mesolevel, and microlevel factors explaining why individuals move across international borders. In this paper, we aim to complement the existing literature by exploring how, within a single country, mesolevel factors differently impact migration aspirations, focusing on a case study of Ukraine. We particularly focus on how migration aspirations of individuals in two different regions can be explained by their international social networks with family members, on the one hand, and with friends, on the other. Furthermore, we explore whether regional migration characteristics play a role, as well as the interaction of such characteristics with individuals' frequency of contact with transnational networks. Our analyses are based on the EUMAGINE project and suggest that the interplay between regional migration characteristics and transnational social contact are key for explaining the decline of migration systems over time.

1. INTRODUCTION

The determinants of international migration are a classical question of interest to migration scholars (e.g., Borjas, 1987 ; Massey, 1999 ; Ravenstein, 1885 ; Sjaastad, 1962 ). When investigating the causes of international migration, scholars focused on macrofactors (e.g., Borjas, 1989 ; Todaro, 1969 ), mesolevel factors (e.g., Boyd & Nowak, 2012 ; Curran & Rivero‐Fuentes, 2003 ; Faist, 2000 ; Massey, 1990 ; Massey et al., 2005 ; Stark & Taylor, 1991 ), and individual characteristics such as age, gender, or socio‐economic status (e.g., Feliciano, 2005 ; Sjaastad, 1962 ). With this article, we contribute to scientific knowledge on the determinants of international migration in two ways. First, we aim to advance current understanding on the interplay between mesolevel factors—social networks—and migration aspirations, by explaining why some people aspire to migrate whereas others do not, despite coming from the same country and having similar background characteristics. We particularly explore how social networks differently influence migration aspirations within a single country, through a comparison of a region that is heavily impacted by emigration with one characterised by little migration. Second, most research focused on retrospective evaluations of migration determinants, that is, on individuals who already moved abroad. In this paper, our point of departure instead is that international migration necessarily starts with an individual, or individual household, aspiring to move abroad to, for example, improve his or her living conditions. As such, the premigration phase encompasses migratory aspirations, which can be defined as “the conviction that migration is desirable” (Carling, 2014 , p. 2). These aspirations can be considered as a crucial step towards actual migratory behaviour.

Examining migration aspirations necessarily implies focusing on migrants' country of origin. We hence focus on a case study of Ukrainians' aspirations to move to the European Union (EU), on the basis of unique survey data from the EUMAGINE project ( http://www.eumagine.org ). The choice to focus on Ukraine is informed by recent migration statistics showing that Ukraine figures among the top countries of origin of migrants arriving in the EU (Eurostat, 2014 ; Van Mol & de Valk, 2016 ), and Ukrainian migration is the largest of all former Soviet Union countries' migration flows towards the EU (Fedyuk & Kindler, 2016 ). The country has a long tradition of emigration, although until recently, most Ukrainian migrants left for the countries of the former Soviet Union. The move to the West can be considered relatively new. Consequently, research into Ukrainian migration to Europe only recently emerged (e.g., Danzer & Dietz, 2014 ), and much remains unknown about these migration dynamics.

The central research question we address in this paper is the following: What mesolevel factors explain migration aspirations of Ukrainians and how do they interact with the regional emigration context in which they occur? On the one hand, we investigate the “international social networks” of our respondents, distinguishing between contacts with family and friends abroad. On the other hand, we focus on two different migration regions, namely, a high‐ and low‐migration area.

2. MIGRATION ASPIRATIONS: THEORETICAL BACKGROUND AND HYPOTHESES

2.1. determinants of migration aspirations.

In sociology, social psychology, and economics, “aspirations express goals or goal‐orientations (or desired future end‐states) that are relevant to well‐being broadly defined” (Bernard, Dercon, Orkin, & Taffese, 2014 , p. 5). As goals, they “serve to mobilise and direct energy into action with respect to their objects, thus providing motive power for action” (Haller & Miller, 1963 , p. 11, cited in Bernard et al., 2014 , p. 5). Consequently, premigration aspirations are a central part of the migration decision‐making process (Timmerman, Heyse, & Van Mol, 2011 ). In this paper, our point of departure is the assumption that migration aspirations are not simply a function of external factors such as natural disasters, political oppression, poverty, wage differentials, or historical formed political, economic, and cultural relations between countries. Although these factors undoubtedly play a role, there is abundant evidence that migration aspirations are also largely dependent on information, perceptions, and value systems (Carling, 2013 , 2014 ; De Haas, 2011 , 2014 ). Whether or not someone develops an aspiration to move abroad partly depends on the information or “images” that he or she receives about potential destination countries, and on his or her perception of the economic and political situation in the sending country. Importantly, migration aspirations are not the same as migration intentions. The latter refer to more concrete plans of people to move abroad and partly depend on one's assessment of the “ability” or “capability” to do so in terms of available resources and legal possibilities (Carling, 2013 , 2014 ; De Haas, 2011 ). Of course, migration aspirations do not automatically result in migratory intentions and/or behaviour (Cairns & Smyth, 2011 ). Therefore, migration aspirations should “be treated as a measure of migration potential rather than a proxy measure of actual future migration” (Bjarnason & Thorlindsson, 2006 , p. 291). Thinking of migration as a function of migration aspirations and capabilities within a given social, economic, and political context thus enables us to link microtheories and macrotheories of migration in a meaningful way. After all, macrolevel factors and developments shape opportunities for migration and simultaneously enable (or constrain) individual migration capabilities (De Haas, 2011 ). Similarly, Engbersen, Snel, and Esteves ( 2016 ) argue that macrolevel situations affect the motivations of potential migrants, who may (or may not) decide to move, which in turn influences macrolevel outcomes such as growing or declining migration flows between countries.

This paper links individual and mesolevel factors to migration aspirations of Ukrainians, with a main focus on the interaction between mesolevel factors and the regional contexts in which they emerge. As Timmerman, Hemmerechts, and De Clerck ( 2014 , p. 497) argue, migration aspirations are not equal within or across societies and over time. They strongly depend on information, perceptions, and values of individuals. These perceptions become increasingly important today, as more and more people are exposed to migration‐related images through the mass media, social media, and cheap travel opportunities. Timmerman, Hemmerechts, and De Clerck distinguish between three types of perceptions (linked to the macrocontext, mesocontext, and microcontext) that may affect their migration aspirations. At the macrolevel, perceptions and migration aspirations are influenced by factors that are common to all potential migrants in a country such as national migration policies, the overall economic and political situation in a country such as the human rights situation, and images spread by the mass media. Perceptions and migration aspirations are also shaped by microlevel characteristics of individuals such as gender, age, educational attainment, and labour market situation. Migration aspirations are finally also indirectly formed through perceptions affected by mesolevel factors such as international social networks linking potential migrants with family and friends in other countries, as well as the specific location where people live. More specifically, in some locations, migration seems to be a “normal thing to do.” In the following paragraphs, we discuss existing scholarship on different levels, in more detail.

2.2. Mesolevel factors

Mesolevel factors in migration research generally refer to the role of migration networks, defined as “sets of interpersonal ties that connect migrants, former migrants, and non‐migrants in origin and destination areas through ties of kinship, friendship, and shared community origin” (Massey et al., 2005 , p. 42). Existing scholarship extensively documented how family and friendship networks, community organisations, and other intermediaries stimulate and facilitate migratory movements (e.g., Boyd & Nowak, 2012 ; Curran & Rivero‐Fuentes, 2003 ; Faist, 2000 ; Massey, 1990 ; Massey et al., 2005 ; Stark & Taylor, 1991 ). Garip and Asad ( 2013 ) distinguish two types of social support that are relevant for migration (based on DiMaggio & Garip, 2011 ): social facilitation and normative influence . The first refers to actual support for migrants, making migration easier and decreasing the costs. The latter points to the influence that previous migrants have on migration aspirations of prospective migrants. This “normative influence” is particularly relevant for this paper. Through all kinds of communication (personal contacts, visits, letters, emails, social media, etc.), previous migrants influence the perceptions of potential migrants about migration and potential destination countries (Timmerman, De Clerck, Hemmerechts, & Willems, 2014 ).

In some sending communities, large numbers of out‐migration may generate a “culture of migration.” With an increasing number of emigrants, values and cultural perceptions of a local community may change, due to the previously described normative influence (Massey et al., 2005 , p, 47). In such communities, migration becomes a normal thing to do, whereas staying at home is perceived as a failure (Massey et al., 2005 , p. 47; Castles, de Haas, & Miller, 2014 , p. 44). Moreover, as nonmigrants are constantly confronted with stories about and the symbols of successful migration (luxurious presents, large houses, and “conspicuous consumption” of migrant families), they may develop feelings of “relative deprivation,” stimulating their aspirations to migrate (Stark & Taylor, 1989 , 1991 ). The rise of a culture of migration in sending communities—next to social support in migrant networks and other “feedback mechanisms”—is one of the factors that give migration a self‐perpetuating character, often coined by the term “cumulative causation” (Massey, 1990 ; Massey et al., 2005 ). Recent migration research, however, also identified “negative feedback mechanisms” that may have a “migration‐undermining” effect (De Haas, 2010 ; Engbersen et al., 2016 ). For example, returning migrants may talk about unemployment, harsh migration policies, and the sometimes hostile public opinion climate in destination countries, which can discourage potential newcomers to come to Europe. As such, settled migrants may turn from “bridgeheads” to “gateclosers” (Fonseca, Esteves, & McGarricle, 2016 ; Snel, Engbersen, & Faber, 2016 ). Recent work of Timmerman, Hemmerechts, and De Clerck ( 2014 ) in the Turkish context also hints at the existence of such negative feedback loops. These authors showed that individuals living in high‐migration areas have less positive ideas about moving to Europe and are less likely to have migration aspirations compared to individuals living in low‐migration areas. Their argument is that negative reports of migrants about moving to and living in Europe are widespread in high‐migration areas, whereas they are lacking in low‐migration areas. This shows that cultures of migration may also affect migration aspirations negatively.

In sum, migration aspirations may be highly influenced by the social networks of a given individual as well as the migration characteristics of the region where he or she lives in. On the basis of this previous scholarship, two hypotheses can be formulated with regard to the influence of mesolevel factors on migration aspirations. First, we expect that individuals who have more frequent contact with relatives ( Hypothesis 1a ) and friends ( Hypothesis 1b ) abroad are more likely to dispose of migration aspirations. Second, people living in regions with a high number of emigrants are less likely to have migration aspirations, due to “thicker” negative feedback loops ( Hypothesis 2 ).

2.3. Microlevel and macrolevel factors

There is ample evidence that individual background characteristics and macrolevel factors impact migration decisions, and henceforth also migration aspirations. As such, it is important to control for possible confounding factors in the analysis.

First, international migration used to be a gender‐specific phenomenon in which mainly males participated. Although recent research observes an increasing “feminisation of migration” (Castles et al., 2014 ), there is still ample evidence that women often have slightly different reasons than do men to migrate (e.g., Timmerman & Hemmerechts, 2015 ; Timmerman, Martiniello, Rea, & Wets, 2015 ) or may not be able to migrate because of limited sets of rights and responsibilities (Van Mol, 2017 ). Second, it is generally expected that the younger strata of the population are more likely to engage in migration movements (e.g., Charles & Denis, 2012 ; Pekkala, 2003 ), as they are freer from constraints that tie individuals to the home country (e.g., mortgages, properties, and families). Third, educational attainment and social status may affect someone's migration aspirations as well. It has been widely reported, for example, that migrants are a group that is positively selected in terms of education (Feliciano, 2005 ; Grogger & Hanson, 2011 ). Furthermore, in contrast to the popular belief that the poorest people are most likely to migrate, various studies showed that international migrants are usually not drawn from poorer parts of population, as it generally is a costly enterprise (Amit, 2007 ; Angelucci, 2014 ; De Haas, 2007 ). Fourth, household demands such as marital status and parenthood may also influence the timing of migration aspirations and decisions. It has been reported, for example, that single or previously married women have higher risks of migration compared to married women (Kanaiaupuni, 2000 ). Furthermore, a Swedish study revealed that care responsibilities for children may form a constraint to migration for individuals, particularly when they are at early school age (Fischer & Malmberg, 2001 ). Consequently, we take marital status and the eventual presence of children into account in our analyses. Finally, migration aspirations are also influenced by macrolevel factors such as natural disasters, poverty, unemployment, and violence or political oppression in the sending countries of migrants (for an overview, see, for example, Castles et al., 2014 ). Although these factors affect the perceptions and aspirations of all potential migrants in a certain country in more or less the same way, they are unfortunately hard to examine in a single‐country case study as ours.

3. THE UKRAINIAN CONTEXT

With almost 6 million Ukrainians living abroad, Ukraine is one of the leading migrant‐sending countries worldwide (Duvell, 2007 ; IOM, 2008 ; Kubal, 2012 ; Vollmer, Bilan, Lapshyna, & Vdovtsova, 2010 ). Today, more than 10% of Ukrainians works abroad, or about one fifth of the total working age population, generally on a temporary basis (Strielkowski & Sanderson, 2013 ). The large majority of these Ukrainians live in the Russian Federation or one of the other successor states of the former Soviet Union (World Bank, 2010 ). Since the early 21st century, there is also a continuous inflow of Ukrainian migrants in other countries of the EU. In 2009, for example, Ukraine was ranked fourth among the top countries of origin of newly arrived migrants in the EU, after India, Morocco, and China (Eurostat, 2014 ). Recent forecasts of Ukrainian migration towards the EU estimate that by 2050, between 1 and 2 million Ukrainians will be living in the EU (Cajka, Jaroszewicz, & Strielkowski, 2014 ). It is worth noting that the recent political tensions and military conflicts since 2013 may have a profound effect on Ukrainian migration dynamics, but these have yet to be studied (Fedyuk & Kindler, 2016 ). It is plausible, for example, that neighbouring EU countries become a destination for Ukrainian asylum seekers (Szulecka, 2016 ). Recent empirical evidence from Poland indeed suggests an increase in applications for residence permits and refugee status since the escalation of the armed conflict (Brunarska, Kindler, Szulecka, & Toruńczyk‐Ruiz, 2016 ). However, an analysis of the effect of these recent tensions falls beyond the scope of our paper, as our data were collected before these events occurred.

Initially, Ukrainians primarily moved to Southern European countries such as Italy and Portugal. Baganha et al. ( 2004 , p. 27) describe, for example, how Ukrainians all of a sudden became the largest immigrant population in Portugal in the early 2000s. These authors offer three explanations for this sudden mass inflow: the lack of control by other EU member states in granting short‐term visa, the ease of movements within the Schengen area, and human trafficking practices by Eastern European “travel agencies” that offered attractive “package deals” to Ukrainians, including travel documents, transportation, and job opportunities (particularly in construction work for the UEFA European Championship in Portugal in 2004). But also Portuguese regularisation programs for irregular migrants in the early 2000s made the country more attractive than other EU countries.

The EU enlargements of 2004 and 2007 also brought large Ukrainian communities within the EU territory. Already before the accession, large numbers of Ukrainians lived in countries such as Poland and Hungary. Since 2004, there was a continuous inflow of Ukrainian nationals in the EU—both in the “old” (EU15) and “new” EU countries of 2004 and 2007 (EU12). According to numbers of the Organisation for Economic Co‐operation and Development, Italy, Germany, and to a lesser extent Spain are the main receiving countries for Ukrainians in the EU15 (OECD, 2015 ). With about 10,000 Ukrainians arriving annually, Poland is the main receiving country among the new member states (Fedyuk & Kindler, 2016 ; Malynovska, 2006 ).

Several characteristics of Ukrainian emigration suggest an influence of individual characteristics on migration aspirations. It can be observed, for example, that Ukrainian migration is highly gendered (Dietz, 2010 ; Fedyuk & Kindler, 2016 ). In the Czech Republic and Portugal, for example, flows of male migrants predominate, as they mainly work in the agricultural and construction sectors in these countries (Dietz, 2010 ). Ukrainian migration towards Italy and Slovakia, in contrast, is characterised by a high number of female migrants, who generally work in the care and domestic services sector (Dietz, 2010 ; Tyldum, 2015 ). Considering the socio‐economic profile of Ukrainian migrants, it has been reported that those with higher education mainly move to Russia instead of the EU (Danzer & Dietz, 2014 ; Dietz, 2010 ; Marques & Góis, 2010 ). Moreover, many Eastern European migrants seem to experience occupational downgrading once they arrived in the EU (Danzer & Dietz, 2014 ; Heyse, Mahieu, & Timmerman, 2015 ; Pereira, Snel, & 't Hart, M., 2015 ). Also for the Ukrainian diaspora, it has been observed they mainly work in low‐skilled jobs (IOM, 2008 ). In Europe, these low‐skilled jobs are mainly situated in agricultural, construction, care, and services sectors (Dietz, 2008 , 2010 ; Markov, Ivankova‐Stetsyuk, & Seleshchuk, 2009 , cited in Strielkowski & Weyskrabova, 2014 , p. 34).

Structural factors at the macrolevel, including the labour market situation, however, also influence the size of migration flows from Ukraine. The most prominent emigration motives of Ukrainian migrants seem to be low salaries and a lack of job opportunities in the homeland (Dietz, 2008 , 2010 ). Nevertheless, in certain regions of Ukraine, emigration is more widespread than others. On the country level, about one fifth of the population in working age resides abroad (Duvell, 2007 ). However, a population survey conducted in the frontier areas of Volyn and Lviv revealed higher numbers; almost half of the respondents had relatives who live abroad (Malynovska, 2006 ). In Zakarpattya, this number rose to around 70%. Furthermore, Ukrainian migrants appear to “maintain close ties with their family and friends; visit Ukraine very often and invest their earnings in Ukraine” (Markov et al., 2009 , cited in Strielkowski & Weyskrabova, 2014 , p. 34). This suggests that feedback mechanisms operating through social networks can also be detected in Ukraine, underlining the relevance of the Ukrainian context for studying mesolevel factors influencing migration aspirations. In this paper, we further unravel how these social networks and regional migration characteristics impact on migration aspirations of potential migrants.

4. METHODOLOGY

Our empirical analysis is based on a unique dataset on migration aspirations, collected in the framework of the EUMAGINE project, funded by the Seventh Framework Programme. The project investigated the influence of perceptions of human rights and democracy on migration aspirations and decisions of Ukrainians in four research areas: (a) Zbaraz, a region with high emigration rates in Western Ukraine; (2) Novovodolazka, an area in Eastern Ukraine with a specific human rights situation; (3) Znamyanska, area with low emigration rates in Central Ukraine; and (4) Solomyansky rayon/Kyiv, a region including the capital, with an immigration history. In each area, a representative sample of 500 respondents aged 18–39 was drawn, as this population has the highest probability of perceiving emigration as a valuable option. A stratified cluster sample with random walks was used to collect the sample. Within the selected households, respondents were randomly chosen. The selected respondents were questioned face to face with structured paper‐and‐pencil questionnaires. The data had to be weighted to account for differences in the selection probability of respondents. A selection probability weight was calculated for the within‐household selection for each stratum. 1

In line with the purposes of this paper, we use data from two regions characterised by contrasting migration numbers: Zbaraz (in the Ternopilska region), a high‐emigration area, and Znamyanska area (in the Kirovogradska region), a low‐emigration region (Vollmer et al., 2010 ). This implies that we leave out the two other Ukrainians regions that are part of the EUMAGINE project. Both regions are not relevant in view of our focus on the impact of a “contrasting” regional emigration context, more specifically a high‐ versus low‐emigration context, on migration aspirations. The other two regions in the EUMAGINE project, characterised by a specific human rights situation and an immigration context, are not relevant for the purposes of this paper and therefore not included.

In the Zbaraz area, many seasonal workers leave in order to work abroad. A survey on labour migration in 2008 pointed to 50,400 labour migrants who were working abroad, but still “officially” living in Ternopil villages (Vollmer et al., 2010 ). Symbolically, the population and local authorities of this region even considered to construct a monument to honour the labour migrants who contributed significantly to the economic welfare of their families and the development of the region. Znamyanska, the low‐emigration area, is situated in the north of Kirovogradska region. This region is known for its low‐scale emigration. According to Vollmer et al. ( 2010 ), migration processes had virtually no influence at all on the development of the population in this region. The transnational networks of respondents in both regions are different given their migration history. Respondents in the Zbaraz region, for example, more often reported to have family abroad (34.3%) compared to those from the Znamyanska region (13.3%; weighted data, based on the sample of 801 respondents). Therefore, a comparative analysis between both regions is relevant for uncovering how transnational social networks and regional characteristics are related to migration aspirations.

4.2. Variables

4.2.1. dependent variable.

Our dependent variable is migration aspirations to Europe, which were measured by two questions. First, the question “Ideally, if you had the opportunity, would you like to go abroad to live or work some time during the next five years, or would you prefer to stay in Ukraine?” On a total of 999 respondents, 460 respondents indicated having migration aspirations (weighted data). Respondents who indicated to have migration aspirations were also asked a second question, namely, to which country they would prefer to go. Subsequently, we restricted our sample of aspiring migrants to respondents who indicated to prefer a European destination country. The combination of these two questions thus resulted in a dichotomous variable that measures the migration aspirations to Europe (0 =  no migration aspirations [ n  = 534], 1 =  migration aspirations [ n  = 324]). The 141 respondents not included in our analyses are hence either potential migrants who prefer a non‐European destination country ( n  = 125) or respondents with no information on their preferred destination ( n  = 16; weighted data).

4.2.2. Independent variables

As stated previously, we expect transnational contacts of individuals to provide feedback about migration experiences and possible destinations, feeding into migration aspirations. Therefore, the frequencies of transnational contact with family members and friends abroad are considered as crucial variables. Respondents had to indicate how often they had contact (spoken, written, and SMS) with their family and friends abroad over the last 12 months. Importantly, they were explicitly asked to indicate relatives or friends on whose help they could count on if needed, in order to avoid reference to “weak ties” (Granovetter, 1973 ). Furthermore, these family members and friends abroad had to be above 16 years old. In our empirical analyses, we use the mean frequency of contacts with significant family members and friends abroad, which ranged between never and 365 times.

Second, we are interested in how the broader migration characteristics of the region in which individuals live influence migration aspirations. Therefore, a second dichotomous independent variable indicates the region where respondents live. The region with low emigration numbers is thereby used as the reference category (0 =  Znamyanska , 1 =  Zbaraz ).

4.2.3. Control variables

As migration aspirations likely vary according to individual background characteristics and general perceptions of the macrosituation in Ukraine and Europe, we have two categories of control variables.

In our analyses, we control for six individual background characteristics on the basis of our literature review. The first is a dichotomous variable indicating gender (0  = female , 1  = male ). The second is a continuous grand‐mean‐centred variable, indicating age in years (using the mean age in the sample without full listwise deletion = 28.50). Third, respondents' education was measured by a continuous variable, indicating years of education, theoretically ranging from 0 ( no education ) to 23 years. Fourth, we constructed an index measuring the material wealth of respondents using principal component analysis (Cronbach α = .76, weighted data). Different questions in the survey measured whether respondents had access to a modern flush toilet connected to sewerage in residence, running hot water, shower in residence, radio, satellite dish and receiver, video/VCR/DVD player, computer at home, internet connection at home, washing machine, bicycle, moped/motorcycle, and car/truck/van. Components with an eigenvalue higher than 1 were combined into an index. The explained variance of each component was used to multiply with the regression factor score of the component in question. The multiplied scores were then summed into one index. The data used to construct the material wealth index is the sample without full listwise deletion. The range‐standardised scale goes from 0 ( low material wealth ) to 4 ( high material wealth ). Fifth, marital status is included in our analyses as a dichotomous variable (0  = unmarried/divorced/widowed/separated , 1  = married/cohabitation ). Finally, we include a dichotomous variable indicating whether the respondent has children (0 =  no children , 1 =  at least one child ).

Next to these individual background characteristics, we included two variables measuring the perception of respondents of the quality of life in both Ukraine and Europe. In five questions, respondents were asked about their opinion about the quality of schools, the quality of life for men and for women, governmental poverty reduction, and health care in Ukraine and Europe. The answer options ranged from very bad to very good on a 5‐point Likert scale. The perception of the quality of life in Europe is coded from 0 ( very bad ) to 4 ( very good ), and the perception of the quality of life in the Ukraine from 0 ( very bad ) to 4 ( very good ). These items were used to construct to composite scales (Cronbach α = .78 for Europe and .72 for Ukraine, weighted data).

4.3. Analytic strategy

Given the dichotomous nature of our dependent variable, we conducted a stepwise logistic regression analysis for analysing the impact of social networks and region of origin on migration aspirations in Ukraine. At the first stage, we introduce frequency of contact with family. At the second stage, we investigate the relationship between frequency of contact with friends. At the third stage, we add the region of origin and the control variables to the model. In the fourth and fifth stages, we investigate the interaction effect between the region of origin and frequency of contact with the transnational family, on the one hand, and with the transnational friendship network, on the other hand. A listwise deletion of missing values results in a sample of 801 respondents. This entails the further exclusion of 57 respondents (weighted data). Before running the analysis, collinearity among variables was tested. The variance inflation factors in the model with all the variables included did not go beyond 2.160, indicating no problems of collinearity.

5.1. Descriptive results

In a first analytic step, we investigate the descriptive statistics of our variables, for the total sample and for both regions separately (Table  1 ).

Descriptive statistics of the total sample, Znamyanska, and Zbaraz

Source . EUMAGINE project, weighted data.

Regarding our dependent and independent variables, it can be observed that 38.31% of respondents ( n  = 307) had aspirations to migrate to Europe. Furthermore, when looking more closely to the numbers of the two regions, it can be noticed that the share of respondents with migration aspirations was higher in the high‐emigration region (Zbaraz, 42.68%) compared to the low‐emigration region (Znamyanska, 35.10%; χ 2  = 4.91, p  < .05). Next, Table  1 clearly shows that our respondents had more frequent contact with their family networks abroad compared to contact with friends. Significant differences between the two regions can also be detected here. Respondents in Zbaraz have more frequent contact with family ( t  = 6.46, p  < .001) and friends ( t  = 2.33, p  < .05) compared to respondents in Znamyanska.

With regard to the control variables, Table  1 reveals that 40% of the respondents in the total sample are male. There are no significant differences regarding the gender composition between the two regions. The age profile of respondents from both regions, however, significantly differs ( t  = −4.66, p  < .001). The average age of respondents in the sample is 28.76 years, and those from Znamyanska are significantly older compared to the respondents from Zbaraz. Also, regarding the socio‐economic background variables, significant differences can be observed. Respondents from Zbaraz studied significantly longer ( t  = 6.24, p  < .001) and have lower scores in terms of material wealth ( t  = −7.21, p  < .001). Finally, when considering the family characteristics, respondents from the high‐emigration region (Zbaraz) are more likely to be unmarried (χ 2  = 5.39, p  < .05) and without children (χ 2  = 19.42, p  < .001).

We also consider possible differences between the two regions regarding the perceptions of respondents on the quality of life in Ukraine and the EU. Compared to individuals in the high‐migration region, respondents in the low‐migration region do not have a significantly more positive image on the quality of life in Ukraine ( t  = 1.09, p  = .27). However, respondents from the high‐migration region dispose of a significantly more positive perception of the quality of life in Europe ( t  = 7.05, p  < .001).

5.2. Multivariate results

As a final analytic step, we aim to explain the migration aspirations of respondents in both regions through stepwise logistic regression models. Results are presented in Table  2 . Model 1 only includes the mean frequency of contact with family abroad. As expected, there is a significant correlation with migration aspirations. In Model 2, the mean frequency of the respondents' contacts with friends abroad is included. Interestingly, no statistically significant correlation with migration aspirations is observed. Thus, as far as transnational contacts affect migratory aspirations of those left behind, this goes only for contacts with family abroad.

Logistic regression on European migration aspirations (odds ratios, reference category = no migration aspirations)

Source . EUMAGINE project.

Model 3 presents the full model, including control variables and the region that respondents live in. Controlling for confounding factors, this model confirms the significant relationship between frequency of contact with family members abroad and migration aspirations for our sample. Once again, the relationship between frequency of contact with transnational friendship networks is proven to be nonsignificant. Remarkably, no significant differences between both regions are detected when controlling for other factors. Although our descriptive analysis revealed higher percentages of migration aspirations in the high‐emigration region (Zbaraz) compared to the low‐emigration region (Znamyanska), it seems that this difference can be explained by the intensity of transnational family contacts and a negative perception of the quality of life in Ukraine.

In the last step, we investigated two interaction terms, more specifically, between the region of origin and frequency of contact with the transnational family network (Model 4) and with the transnational friendship network (Model 5). Both interaction effects were not statistically significant. Nevertheless, the coefficients also indicate that in regions characterised by a high number of emigrants (in our case Zbaraz), having more frequent contact with family members in Europe slightly decreases the likelihood of having migration aspirations to Europe.

As an additional robustness check, we also estimated models for the regions separately (see Tables  3a and ​ and3b). 3b ). These results are largely in line with the findings of the pooled model discussed above; namely, that in our sample the frequency of contact with family members abroad is significantly correlated with migration aspirations, and this relationship seems to be somewhat more pronounced in the Znamyanska region, characterised by a low number of emigrants.

Logistic regression of European migration aspirations in Zbaraz (odds ratios, reference category = no migration aspirations)

Logistic regression of European migration aspirations in Znamyanska (odds ratios, reference category = no migration aspirations)

6. DISCUSSION AND CONCLUSION

In this paper, we aimed to investigate what mesolevel factors that influence migration aspirations, focusing on a case study of Ukraine. Two hypotheses were formulated on the role of social networks and the characteristics of sending communities. First, we expected that respondents with more frequent contact with relatives and friends abroad are more likely to have migration aspirations. Second, we postulated that in sending regions characterised by high numbers of emigrants, respondents are less likely to have migration aspirations due to the existence of negative feedback loops. Our results only partially confirm both hypotheses.

First, the analysis revealed that in our sample, those individuals who have more frequent contact with family members abroad are more likely to have migration aspirations. The same correlation was not detected, however, for frequency of contact with friends. This might be related to the changing composition of networks of migrants over time. It has been widely demonstrated, for example, that over time, contacts with the home‐country decrease (e.g., Hedberg & Kepsu, 2008 ; Levrau, Piqueray, Goddeeris, & Timmerman, 2014 ); and this holds particularly true for contacts with extended family and dispersed friendships (Eve, 2008 ; Mollenhorst, Volker, & Flap, 2014 ; Viry, 2012 ). After all, maintaining relations requires a considerable effort and time (Ryan & Mulholland, 2014 ), and “migrants' physical absence hampers such maintenance, leading to a progressive decrease in contact frequency” (Koelet, Van Mol, & De Valk, 2017 , p. 454). Furthermore, “the combination of the obligation to help kin, and the high level of structural embeddedness means that kin are both cognitively and time‐wise less demanding relationships to maintain than non‐kin relationships” (Roberts, Dunbar, Pollet, & Kuppens, 2009 , p. 139). From this perspective, international family networks are logically most strongly related to migration aspirations.

Second, our analysis shows that for our sample, in principle, no statistically significant differences can be detected in terms of migration aspirations between people living in low‐ and high‐migration regions. Interestingly, however, our analysis suggests that in high‐emigration regions, compared to low‐emigration regions, a higher frequency of contact with family members abroad is less strongly correlated with migration aspirations. Once again, this does not hold true for frequency of contact with friends abroad, which might be related to the fact that transnational friendship connections generally decrease over time, as well as by the lower level of structural embeddedness of nonkin relationships. Negative migration stories of close relatives abroad, in contrast, thus seem to have a higher potential for curbing migration aspirations in regions characterised by a culture of migration. The mechanism behind this relationship, however, remains to be uncovered by future research. It might be possible, for example, that in high‐migration regions, migration is omnipresent in stories of friends and relatives living nearby as well, leading to a cumulative effect of negative feedback. Potential migrants might thus be more regularly confronted with negative stories in their wider social circles and, hence, dispose of a more complete set of information on the disadvantages of migration. These findings are in line with a comparison made of migration aspirations between high‐ and low‐emigration areas in Turkey, demonstrating that perceptions on Europe were significantly more negative in the high‐ compared to low‐emigration region (Timmerman, Hemmerechts, & De Clerck, 2014 ). The family feedback mechanism may then constitute a “turning point,” adding negative information from a well‐trusted source and, hence, lowering their migration aspirations. In low‐migration regions, such cumulative effect might be absent, as there might be only a single feedback loop within the proper family instead of multiple feedback loops within the wider community. This might explain why migration aspirations are not as heavily affected. In particular, qualitative research in home communities might have the potential to uncover the mechanisms behind this relationship.

Finally, some limitations of our study should be mentioned. First, our data do not allow for any causal interpretations, as it is based on cross‐sectional data. Future studies could benefit from a longitudinal perspective, allowing to track changes over time. Such approach would allow to disentangle more precisely the relationship between increasing emigration numbers, transnational social contacts, and migration aspirations. Second, the explained variance of our models remained rather low, suggesting there are other factors at play that are not captured by our study. It is plausible, for example, that the variation in migration aspirations is explained by personality characteristics. It has been shown, for example, that compared to the local population, migrants have different attachment styles (Polek, Van Oudenhoven, & Berge, 2011 ), higher achievement and power motivation, and lower affiliation motivation and family centrality (Boneva & Frieze, 2001 ). Future research could try to build more inclusive models, incorporating psychological characteristics as well. Third, the data on which our analyses are based were collected before the start of the Ukrainian conflict. Given the changed geo‐political situation and the enduring conflict, it is not unlikely migration aspirations and the number of people who are willing to migrate significantly changed. Furthermore, it is also plausible that the main motivations for migration changed due to the conflict, particularly for individuals and families living in the conflict zone.

In conclusion, in this paper, we highlighted the importance of transnational family ties in the migration decision‐making process among Ukrainian individuals. The family remains at the core of the migration process and has the potential to stimulate and curb existing migration dynamics. In particular, this last point is interesting, as it suggests that the cumulative effect of migration can reach a certain threshold. From the moment onwards when migration in a community reaches its saturation, feedback mechanisms from family members abroad play an important role in the stagnation and decay of out‐migration over time.

ACKNOWLEDGEMENTS

This work was supported by the European Commission, Directorate‐General for Research and Innovation, 7th Framework Programme for Research—Socio‐economic Sciences and Humanities (Grant 244703). The contribution of the first author is funded by the European Research Council Starting Grant project (263829) “Families of migrant origin: A life course perspective.”

The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of the European Communities. Neither the European Communities institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. The EUMAGINE project is cofunded by the European Community FP7 2007–2013, under the Socio‐economic Sciences and Humanities Programme.

Van Mol C, Snel E, Hemmerechts K, Timmerman C. Migration aspirations and migration cultures: A case study of Ukrainian migration towards the European Union . Popul Space Place . 2018; 24 :e2131 10.1002/psp.2131 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

1 See also Ersanilli ( 2012 ).

• Amit, V. (2007). Structures and dispositions of travel and movement In Amit V. (Ed.), Going first class? New approaches to privileged travel and movement (pp. 1–14). New York & Oxford: Berghahn Books. [ Google Scholar ]
• Angelucci, M. (2014). Migration and financial constraints: Evidence from Mexico . Review of Economics and Statistics , 97 ( 1 ), 224–228. 10.1162/REST_a_00487 [ CrossRef ] [ Google Scholar ]
• Baganha, M. I. , Marques, J. C. , & Góis, P. (2004). The unforeseen wave: Migration from Eastern Europe to Portugal In Baganha M. I., & Fonseca M. L. (Eds.), New waves: Migration from Eastern to Southern Europe (pp. 23–40). Lisbon: Luso‐American Foundation. [ Google Scholar ]
• Bernard, T. , Dercon, S. , Orkin, K. , & Taffese, A.S. (2014). The future in mind: Aspirations and forward‐looking behaviour in rural Ethiopia . CSAE working paper . WPS/2014‐16. University of Oxford: Centre for the Study of African Economies.
• Bjarnason, T. , & Thorlindsson, T. (2006). Should I stay or should I go? Migration expectations among youth in Icelandic fishing and farmking communities . Journal of Rural Studies , 22 ( 3 ), 290–300. 10.1016/j.jrurstud.2005.09.004 [ CrossRef ] [ Google Scholar ]
• Boneva, B. , & Frieze, I. H. (2001). Toward a concept of a migrant personality . Journal of Social Issues , 57 ( 3 ), 477–491. 10.1111/0022-4537.00224 [ CrossRef ] [ Google Scholar ]
• Borjas, G. J. (1987). Self‐selection and the earnings of immigrants . The American Economic Review , 77 ( 4 ), 531–553. [ Google Scholar ]
• Borjas, G. J. (1989). Economic theory and international migration . International Migration Review , 23 ( 3 ), 457–485. 10.2307/2546424 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Boyd, M. , & Nowak, J. (2012). Social networks and international migration In Martiniello M. & Rath J. (Eds.), An introduction to international migration studies. European perspectives (pp. 79–104). Amsterdam: Amsterdam University Press. [ Google Scholar ]
• Brunarska, Z. , Kindler, M. , Szulecka, M. , & Toruńczyk‐Ruiz, S. (2016). Ukrainian migration to Poland: A “local” mobility? In Fedyuk O., & Kindler M. (Eds.), Ukrainian migration to the European Union. Lessons from migration studies (pp. 115–132). Dordrecht: Springer. [ Google Scholar ]
• Cairns, D. , & Smyth, J. (2011). I wouldn't mind moving actually: Exploring student mobility in Northern Ireland . International Migration , 49 ( 2 ), 135–161. 10.1111/j.1468-2435.2009.00533.x [ CrossRef ] [ Google Scholar ]
• Cajka, P. , Jaroszewicz, M. , & Strielkowski, W. (2014). Migration incentives and flows between Belarus, Moldova, Ukraine and the European Union: A forecasting model . Economics & Sociology , 7 ( 4 ), 11–25. 10.14254/2071-789X.2014/7-4/1 [ CrossRef ] [ Google Scholar ]
• Carling, J. (2013). Steps toward a theory of migration aspirations . Paper presented at Aspirations and Capabilities in Migration Processes, International Migration Institute, Oxford.
• Carling, J. (2014). The role of aspirations in migration . Paper presented at the Determinants of International Migration, International Migration Institute, Oxford.
• Castles, S. , de Haas, H. , & Miller, M. J. (2014). The age of migration. International population movements in the Modern World . Basingstoke: Palgrave Macmillan. [ Google Scholar ]
• Charles, A. , & Denis, M. (2012). Internal migration in Ghana: Determinants and welfare impacts . International Journal of Social Economics , 39 ( 10 ), 764–784. 10.1108/03068291211253386 [ CrossRef ] [ Google Scholar ]
• Curran, S. R. , & Rivero‐Fuentes, E. (2003). Engendering migrant networks: The case of Mexican migration . Demography , 40 ( 2 ), 289–307. [ PubMed ] [ Google Scholar ]
• Danzer, A. M. , & Dietz, B. (2014). Labour migration from Eastern Europe and the EU's quest for talents . Journal of Common Market Studies , 52 ( 2 ), 183–199. 10.1111/jcms.12087. [ CrossRef ] [ Google Scholar ]
• De Haas, H. (2007). Turning the tide? Why development will not stop migration . Development and Change , 38 ( 5 ), 819–841. 10.1111/j.1467-7660.2007.00435.x [ CrossRef ] [ Google Scholar ]
• De Haas, H. (2010). The internal dynamics of migration processes: A theoretical inquiry . Journal of Ethnic and Migration Studies , 36 ( 10 ), 1587–1617. 10.1080/1369183X.2010.489361 [ CrossRef ] [ Google Scholar ]
• De Haas, H. (2011). The determinants of international migration . Conceptualising policy, origin and destination effects. IMI working paper 320. Oxford: IMI.
• De Haas, H. (2014). Migration theory . Qua vadis. IMI working paper 100. Oxford: IMI.
• Dietz, B. (2008). Die Ukraine im europäischen Migrationssystem . Aus Politik und Zeitgeschichte , 35 ( 36 ), 33–38. [ Google Scholar ]
• Dietz, B. (2010). Migration from Ukraine: A challenge for the European Union? In Baganha M. I., Marques J. C., & Góis P. (Eds.), Imigração Ucraniana em Portugal e no sul da Europa: a emergência de uma ou várias comunidades? (pp. 187–210). Lisbon: Alto‐Comissariado para a imigração e Diálogo Intercultural. [ Google Scholar ]
• DiMaggio, P. , & Garip, F. (2011). How network externalities can exacerbate intergroup inequality . American Journal of Sociology , 116 ( 6 ), 1887–1933. 10.1086/659653. [ CrossRef ] [ Google Scholar ]
• Duvell, F. (2007). Ukraine—Europe's Mexico? Central and East European migration, country profile . Oxford: Centre of Migration, Policy and Society. [ Google Scholar ]
• Engbersen, G. , Snel, E. , & Esteves, A. (2016). Migration mechanisms of the middle range: On the concept of reverse cumulative causation In Bakewell O., Engbersen G., Fonseca M. L., & Horst C. (Eds.), Beyond networks. Feedback in international migration (pp. 205–230). Basingstoke: Palgrave Macmillan. [ Google Scholar ]
• Ersanilli, E . (2012) Survey Report, EUMAGINE Project Paper 7, http://www.eumagine.org/outputs/PP7%20-%20survey%20report%20-%2020121001.pdf , accessed 6 June 2013.
• Eurostat . (2014). Immigration in the EU: European Commission .
• Eve, M. (2008). Some sociological bases of transnational practices in Italy . Revue Européenne des Migrations Internationales , 24 ( 2 ), 67–90. [ Google Scholar ]
• Faist, T. (2000). The volume and dynamics of international migration and transnational social spaces . Oxford & New York: Oxford University Press. [ Google Scholar ]
• Fedyuk, O. , & Kindler, M. (2016). Migration of Ukrainians to the European Union: Background and key issues In Fedyuk O., & Kindler M. (Eds.), Ukrainian migration to the European Union. Lessons from migration studies (pp. 1–14). Dordrecht: Springer. [ Google Scholar ]
• Feliciano, C. (2005). Educational selectivity in U.S. Immigration: How do immigrants compare to those left behind? Demography , 42 ( 1 ), 131–152. 10.1353/dem.2005.0001 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fischer, P. A. , & Malmberg, G. (2001). Settled people don't move: On life course and (im‐)mobility in Sweden . International Journal of Population Geography , 7 ( 5 ), 357–371. 10.1002/ijpg.230 [ CrossRef ] [ Google Scholar ]
• Fonseca, M. L. , Esteves, A. , & McGarricle, J. (2016). The economic crisis as feedback‐generating mechanism? Brazilian and Ukrainian migration to Portugal In Bakewell O., Engbersen G., Fonseca M. L., & Horst C. (Eds.), Beyond networks. Feedback in international migration (pp. 113–132). Basingstoke: Palgrave Macmillan. [ Google Scholar ]
• Garip, F , & Asad, A.L . (2013). Mexico–US migration in time. From economic to social mechanisms . IMI working paper 67. Oxford: IMI.
• Granovetter, M. (1973). The strength of weak ties . American Journal of Sociology , 78 ( 6 ), 1360–1380. [ Google Scholar ]
• Grogger, J. , & Hanson, G. H. (2011). Income maximization and the selection and sorting of international migrants . Journal of Development Economics , 95 ( 1 ), 42–57. 10.1016/j.jdeveco.2010.06.003 [ CrossRef ] [ Google Scholar ]
• Haller, A.O. , & Miller, I.W. (1963). The occupational aspiration scale: Theory, structure and correlates . Michigan State University Agricultural Experiment Station Technical Bulletin 288 .
• Hedberg, C. , & Kepsu, K. (2008). Identity in motion: The process of Finland–Swedish migration to Sweden . National Identities , 10 ( 1 ), 95–118. 10.1080/14608940701819850 [ CrossRef ] [ Google Scholar ]
• Heyse, P. , Mahieu, R. , & Timmerman, C. (2015). The migration trajectories of Russian and Ukrainian women in Belgium In Timmerman C., Martiniello M., & Rea A. (Eds.), New dynamics in female migration and integration (pp. 68–101). New York & London: Routledge. [ Google Scholar ]
• IOM (2008). Migration in Ukraine: A country profile 2008 . Geneva: International Organization for Migration. [ Google Scholar ]
• Kanaiaupuni, S. M. (2000). Reframing the migration question: An analysis of men, women, and gender in Mexico . Social Forces , 78 ( 4 ), 1311–1347. 10.1093/sf/78.4.1311 [ CrossRef ] [ Google Scholar ]
• Koelet, S. , Van Mol, C. , & De Valk, H. A. G. (2017). Social embeddedness in a harmonized Europe: The social networks of European migrants with a native partner in Belgium and the Netherlands . Global Networks , 17 ( 3 ), 441–459. 10.1111/glob.12123 [ CrossRef ] [ Google Scholar ]
• Kubal, A . (2012). Facts and fabrications: Experiences of law and legality among return migrants in Ukraine . IMI working paper 59. Oxford: IMI.
• Levrau, F. , Piqueray, E. , Goddeeris, I. , & Timmerman, C. (2014). Polish immigration in Belgium since 2004: New dynamics of migration and integration? Ethnicities , 14 ( 2 ), 303–323. 10.1177/1468796813504100 [ CrossRef ] [ Google Scholar ]
• Malynovska, O.A. (2006). Trans‐border migration of the population of the Ukrainian western frontier areas in the context EU enlargement . Reports & Analyses 6 . Center for International Relations: Warsaw.
• Markov, I. , Ivankova‐Stetsyuk, O. , & Seleshchuk, H. (2009). Ukrainian labour migration in Europe: Findings of the complex research of the processes of Ukrainian labour migration . International Charitable Foundation: Lviv.
• Marques, J. C. , & Góis, P. (2010). Quando os extremos se tocam: imigrantes ucranianos em Portugal In Baganha M. I., Marques J. C., & Góis P. (Eds.), Imigração Ucraniana em Portugal e no sul da Europa: a emergência de uma ou várias comunidades? (pp. 25–118). Lisbon: Alto‐Comissariado para a imigração e Diálogo Intercultural. [ Google Scholar ]
• Massey, D. S. (1990). Social structure, household strategies, and the cumulative causation of migration . Population Index , 56 ( 1 ), 3–26. [ PubMed ] [ Google Scholar ]
• Massey, D. S. (1999). Why does immigration occur? A theoretical synthesis In Hirschmann C., Kasinitz P., & de Wid J. (Eds.), The handbook of international migration: The American experience (pp. 34–52). New York: Russell Sage Foundation Publications. [ Google Scholar ]
• Massey, D. S. , Arango, J. , Hugo, G. , Kouaouci, A. , Pellegrino, A. , & Taylor, E. J. (2005). Worlds in motion: Understanding international migration at the end of the millennium . Oxford: Clarendon Press. [ Google Scholar ]
• Mollenhorst, G. , Volker, B. , & Flap, H. (2014). Changes in personal relationships: How social contexts affect the emergence and discontinuation of relationships . Social Networks , 37 ( 0 ), 65–80. 10.1016/j.socnet.2013.12.003 [ CrossRef ] [ Google Scholar ]
• OECD . (2015). OECD international migration database . Accessed from https://stats.oecd.org/Index.aspx?DataSetCode=MIG on February 18, 2016.
• Pekkala, S. (2003). Migration flows in Finland: Regional differences in migration determinants and migrant types . International Regional Science Review , 26 ( 4 ), 466–482. 10.1177/0160017603259861 [ CrossRef ] [ Google Scholar ]
• Pereira, S. , Snel, E. , & 't Hart, M. (2015). Economic progress, stagnation or decline? Occupational mobility of non‐EU immigrants in Europe In Vallejo J. (Ed.), Immigration and work (pp. 129–165). Emerald Group Publishing Limited. [ Google Scholar ]
• Polek, E. , Van Oudenhoven, J. P. , & Berge, J. M. F. T. (2011). Evidence for a “migrant personality”: Attachment styles of Poles in Poland and Polish immigrants in the Netherlands . Journal of Immigrant & Refugee Studies , 9 ( 4 ), 311–326. 10.1080/15562948.2011.616163 [ CrossRef ] [ Google Scholar ]
• Ravenstein, E. G. (1885). The laws of migration . Journal of the Statistical Society of London , 48 ( 2 ), 167–235. 10.2307/2979181 [ CrossRef ] [ Google Scholar ]
• Roberts, S. G. B. , Dunbar, R. I. M. , Pollet, T. V. , & Kuppens, T. (2009). Exploring variation in active network size: Constraints and ego characteristics . Social Networks , 31 ( 2 ), 138–146. 10.1016/j.socnet.2008.12.002 [ CrossRef ] [ Google Scholar ]
• Ryan, L. , & Mulholland, J. O. N. (2014). French connections: The networking strategies of French highly skilled migrants in London . Global Networks , 14 ( 2 ), 148–166. 10.1111/glob.12038 [ CrossRef ] [ Google Scholar ]
• Sjaastad, L. A. (1962). The costs and returns of human migration . Journal of Political Economy , 70 ( 5 ), 80–93. [ Google Scholar ]
• Snel, E. , Engbersen, G. , & Faber, M. (2016). From bridgeheads to gate closers. How migrant networks contribute to declining migration from Morocco to the Netherlands In Bakewell O., Engbersen G., Fonseca M. L., & Horst C. (Eds.), Beyond networks. Feedback in international migration (pp. 134–155). Basingstoke: Palgrave Macmillan. [ Google Scholar ]
• Stark, O. , & Taylor, J. E. (1989). Relative deprivation and international migration . Demography , 26 ( 1 ), 1–14. 10.2307/2061490 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stark, O. , & Taylor, J. E. (1991). Migration incentives, migration types: The role of relative deprivation . The Economic Journal , 101 ( 408 ), 1163–1178. 10.2307/2234433 [ CrossRef ] [ Google Scholar ]
• Strielkowski, W. , & Sanderson, M. (2013). Structural channels for Ukrainian labour migration in the Czech Republic . Trames , 17 ( 2 ), 313–323. [ Google Scholar ]
• Strielkowski, W. , & Weyskrabova, B. (2014). Ukrainian labour migration and remittances in the Czech Republic . Tijdschrift voor Economische en Sociale Geografie , 105 ( 1 ), 30–45. 10.1111/tesg.12052 [ CrossRef ] [ Google Scholar ]
• Szulecka, M. (2016). Regulating movement of the very mobile: Selected legal and policy aspects of Ukrainian migration to EU countries In Fedyuk O., & Kindler M. (Eds.), Ukrainian migration to the European Union. Lessons from migration studies (pp. 51–72). Dordrecht: Springer. [ Google Scholar ]
• Timmerman, C. , De Clerck, H. , Hemmerechts, K. , & Willems, R. (2014). Imagining Europe from the outside: The role of perceptions of human rights in Europe in migration aspirations in Turkey, Morocco, Senegal and Ukraine In Chaban N. (Ed.), Communicating Europe in times of crisis external perceptions of the European Union (pp. 220–247). Basingstoke: Palgrave Macmillan. [ Google Scholar ]
• Timmerman, C. , & Hemmerechts, K. (2015). The relevance of a ‘culture of migration’ and gender dynamics in understanding migration aspirations in contemporary Turkey In Abadan‐Unat N., & Mirdal G. (Eds.), Emancipation in exile. Perspectives on the empowerment of migrant women (pp. 219–236). Istanbul: Bilgi University Press. [ Google Scholar ]
• Timmerman, C. , Hemmerechts, K. , & De Clerck, H. M. L. (2014). The relevance of a “culture of migration” in understanding migration aspirations in contemporary Turkey . Turkish Studies , 15 ( 3 ), 496–518. 10.1080/14683849.2014.954748 [ CrossRef ] [ Google Scholar ]
• Timmerman, C. , Heyse, P. , & Van Mol, C. (2011). Europe seen from the outside In Harbers H. (Ed.), Strangeness and familiarity: global unity and diversity in human rights and democracy (pp. 146–167). Groningen Forum. [ Google Scholar ]
• Timmerman C., Martiniello M., Rea A., & Wets J. (Eds.) (2015). New dynamics in female migration and integration . New York & London: Routledge. [ Google Scholar ]
• Todaro, M. P. (1969). A model of labor migration and urban unemployment in less developed countries . The American Economic Review , 59 ( 1 ), 138–148. [ Google Scholar ]
• Tyldum, G. (2015). Motherhood, agency and sacrifice in narratives on female migration for care work . Sociology , 49 ( 1 ), 56–71. 10.1177/0038038514555427 [ CrossRef ] [ Google Scholar ]
• Van Mol, C. (2017). Moroccan women in Madrid. Between change and continuity . Identities. Studies in Global Power and Culture , 24 ( 1 ), 100–118. 10.1080/1070289X.2015.1091319 [ CrossRef ] [ Google Scholar ]
• Van Mol, C. , & de Valk, H. A. G. (2016). Migration and immigrants in Europe: A historical and demographic perspective In Garces‐Mascarenas B., & Penninx R. (Eds.), Integration processes and policies in Europe. Contexts, levels and actors (pp. 31–55). Dordrecht: Springer. [ Google Scholar ]
• Viry, G. (2012). Residential mobility and the spatial dispersion of personal networks: Effects on social support . Social Networks , 34 ( 1 ), 59–72. 10.1016/j.socnet.2011.07.003 [ CrossRef ] [ Google Scholar ]
• Vollmer, B. , Bilan, Y. , Lapshyna, I. , & Vdovtsova, S. (2010). Ukraine. Country and research areas report . EUMAGINE Project Paper 3 .
• World Bank . (2010). World Bank bilateral migration matrix 2010 . Accessed from http://databank.worldbank.org/data/views/reports/tableview.aspx on August 1, 2014.