Human Capital Loss Among Belarusian and Ukrainian Migrants to the EU

This policy brief examines the underutilization of human capital among involuntary migrants from Ukraine and Belarus in Poland and Lithuania. Focusing on those who migrated after 2020 (Belarus) and 2022 (Ukraine), the brief investigates the factors influencing the conversion of their pre-migration skills into gainful employment in their host countries. Our findings show that despite many migrants possessing high levels of education and professional qualifications, structural barriers and low convertibility of their skills, hinder their full labor market integration. This skill underutilization not only limits migrants’ professional growth and earning potential but also deprives the host countries of valuable skills and potential economic gains.

Effective labor market integration substantially benefits both host and sending countries and migrants themselves. For host nations, successful integration can alleviate critical skill shortages, boost productivity, and drive economic growth (Boubtane, Dumont, & Rault, 2016; Boubtane, 2019; Engler, Giesing, & Kraehnert, 2023; Bernstein et al., 2022). Conversely, inadequate integration leads to underemployment, diminished potential, and economic inefficiency. Countries of origin can benefit from remittances, the return of migrants with enhanced skills, and strengthened international economic ties. However, poor integration risks an uncompensated “brain drain” (Reinhold & Thom, 2009; Barrett & O’Connell, 2001; Iara, 2006; Barrett & Goggin, 2010; Co, Gang, & Yun, 2000). For migrants, the ability to continue their careers means higher earnings and less stress from the acquisition of a new profession, while the non-utilization of existing skills results in their depreciation, potentially causing permanent wage reductions even upon return to the home country (Bowman & Myers, 1967).

Migrants can be broadly categorized into voluntary migrants or forced migrants. Voluntary migrants assess labor market prospects beforehand and often possess convertible human capital – one that can be used in a new labor market. This group often includes professionals like IT specialists and scientists and those in low-skilled but highly transferable professions. Forced migrants, on the contrary, may be utterly unprepared for changes in jurisdiction and possess skills of limited transferability. For example, even highly specialized professions requiring extensive training and substantial human capital, such as lawyers, officials, and teachers, often prove “non-convertible“ (Duleep & Regets, 1999). These individuals’ skills are frequently country specific.

Low convertibility of skills generates significant negative consequences. Highly educated professionals, for instance, may find themselves relegated to low-paying, unskilled jobs, unable to leverage their expertise. This hinders their professional development and deprives host countries of valuable skills and potential contributions to economic growth. Addressing these mismatches is crucial for maximizing the benefits of migration for stakeholders in both home and host countries.

Forced Migration from Belarus and Ukraine

The political crisis in Belarus, starting with the contested 2020 presidential elections, led to widespread repression and significant forced migration. Belarus’s role in supporting Russia’s 2022 invasion of Ukraine exacerbated this situation, resulting in approximately 300,000 Belarusians seeking refuge in the European Union (Eurostat). This number accounts for a substantial proportion of the country’s 9 million population and its approximately 5 million-strong labor force (Belstat).

Russia’s full-scale invasion of Ukraine triggered the most significant wave of migration in Ukrainian history, with over 6 million of the pre-war 44 million population fleeing to the EU (UNHCR). About 90 percent of the initial refugees were women and children due to a mobilization law preventing most men aged 18 to 60 from leaving (UNHCR).

Online Survey and Migrant Differences

To better understand the situation of migrants, their integration into the EU labor market, and to develop data-driven recommendations for improving their conditions, the CIVITTA agency, in partnership with BEROC, conducted an online survey in the summer of 2024. This brief is based on the survey results. The survey includes responses from 616 Ukrainian nationals who migrated to Poland or Lithuania after Russia’s full-scale invasion of Ukraine in 2022, as well as 173 Belarusian migrants who left their home country after 2020. The research focuses on individuals aged 28 to 42, providing insights into their experiences and challenges in the labor market in their host countries. While we acknowledge the sample’s limitations in terms of representativeness, we believe the findings provide valuable insights into the specific challenges faced by involuntary migrants and their adaptation strategies in the new labor market.

Key differences characterize these migration waves. Ukrainian migration comprises of more women, while Belarusian migrants show a more balanced gender distribution, with 47 percent women in our sample versus 62 percent for Ukrainians. Family separation is also notable, as 91 percent of married Belarusians live with their spouses, compared to only 75 percent of Ukrainians (due to the mobilization law).

Survey respondents from both groups possess high levels of human capital with 60 percent of Ukrainians and 90 percent of Belarusians holding higher education degrees. Among Belarusians, 94 percent had over five years of work experience before migration, with and 79 percent of Ukrainians stating the same.

Ukrainian return intentions are split: 38 percent plan to return, 19 percent will not, and the rest are undecided. An end to the war and changes in Russian foreign policy would increase return rates to 70 percent. For Belarusians, 35 percent plan to return, 38 percent will not, and the rest are undecided. Education level is key, as less-educated Belarusians are more likely to stay abroad. An end to repression would increase the share of those Belarusians who want to return to 70 percent, and a regime change would increase this percentage to 82 percent.

Factors Conditioning Human Capital Loss

As expected, due to the involuntary nature of migration of the two groups in focus, a large fraction of survey participants reported losing their profession after migration. As Figure one shows, 48 percent of Belarusians and 63 percent of Ukrainians in our sample reported full loss of their prior careers. The lower percentage of Ukrainians fully retaining their careers (23 percent) compared to Belarusians (44 percent) could be attributed to several factors, including the more recent and disruptive nature of the Russo-Ukrainian war leading to more significant displacement and challenges in finding comparable work. The higher percentage of Ukrainians starting their careers from scratch (49 percent compared to 29 percent among Belarusians) also supports this idea.

Figure 1. Preservation of careers in the EU

Source: Authors’ computations based on survey data.

To foster an evidence-based discussions on the smooth integration of migrants into the EU labor market and the prevention of human capital loss, it is crucial to examine the individual factors that influence career continuity for Belarusian and Ukrainian migrants. We therefore utilize a logistic regression model to identify key predictors that increase the likelihood of migrants remaining in their profession after relocating to Poland and Lithuania.

In our quantitative analysis, an outcome binary variable for staying in the profession is equal to 1 if an individual either “continued career started in a home country (in the same position)” or “remained in the same profession but started working in a position lower than the one held before emigration.” As predictors, we consider a set of sociodemographic variables reasonably related to the probability of staying in the profession and dummy variables for the most common spheres of employment (see Table 1).

Table 1. Overview of model variables

Who Maintains Their Career After Emigration?

Based on the regression coefficients in Table 2, we can identify characteristics related to losing career-specific human capital. In our regression, we control for both home and host country factors. One noteworthy finding is that, while Ukrainian migrants in our sample report significantly higher rates of career loss than Belarusian migrants, nationality itself does not emerge as a significant predictor of career loss once other characteristics are accounted for.

Our results also show that the probability of staying in a profession is higher among men, those with more extended work experience and higher income before emigration, and those who were invited to a host country by an employer. The same holds for entrepreneurs, those who do not plan to return, and those employed in the fields of Architecture & Engineering and Information and Communication Technologies.

Table 2. Results of regression analysis

Note: *** Significant at the .001 level. ** Significant at the .01 level. * Significant at the .05 level.

Conclusion

Several conclusions and policy advice can be derived from the survey results.

The higher likelihood of entrepreneurs staying in their profession suggests that supporting migrant entrepreneurship can be a valuable strategy to retain human capital. This can be done, for example, by:

• Providing access to resources, mentorship, and funding for migrant entrepreneurs.
• Streamlining the procedures for migrants to start and operate businesses.
• Facilitating access to capital for migrant-owned businesses.

The research highlights the disproportionate impact of human capital loss on women.  Therefore, policies should include gender-specific programs that address women’s unique challenges in integrating into new labor markets. This could include:

• Skills retraining and certification programs: Designed to align women’s existing skills with the demands of the host country’s labor market, with consideration for childcare needs and other barriers women may face.
• Connecting women migrants with established professionals in their fields to facilitate knowledge transfer and career guidance.
• Language training programs: Tailored to the specific needs of women, potentially incorporating childcare support to enable participation.

The study highlights the positive role of international companies in supporting employee relocation. Respondents who were invited by an employer demonstrated the most successful integration into the new labor market. To enhance and strengthen these networks, policies may focus on:

• Encouraging corporations to hire and train migrant workers, potentially through tax breaks or other incentives. This could include partnerships with migrant-serving organizations to connect companies with qualified candidates.
• Developing digital platforms that connect migrants with diaspora networks, potential employers, and relevant resources.

In addition, policies should address the non-recognition of foreign qualifications, simplifying and expediting the procedures for recognizing foreign degrees and professional certifications. Initiatives to create targeted training programs could complement such policies and allow migrants to quickly acquire any missing skills or certifications required by the host country’s professional bodies. These policy measures would enhance the utilization of migrants’ human capital, benefiting both migrants and host countries while also supporting sending countries. This could be achieved by fostering a successful diaspora or facilitating productive reintegration in the case of return migration.

References

• Barrett, A., & Goggin, J. (2010). Returning to the question of a wage premium for returning migrants. National Institute Economic Review, 213, R43–R51. https://doi.org/10.1177/0027950110389752
• Barrett, A., & O’Connell, P. J. (2001). Does training generally work? The returns to in-company training. ILR Review, 54(3), 647–662. https://doi.org/10.1177/001979390105400403
• Bernstein, S., Diamond, R., McQuade, T. J., & Pousada, B. (2022). The contribution of high-skilled immigrants to innovation in the United States (No. w30797). National Bureau of Economic Research. https://doi.org/10.3386/w30797
• Boubtane, E. (2019). The economic effects of immigration for host countries. L’Economie politique, 84(4), 72–83. https://doi.org/10.3917/leco.084.0072
• Boubtane, E., Dumont, J.-C., & Rault, C. (2016). Immigration and economic growth in the OECD countries 1986–2006. Oxford Economic Papers, 68(2), 340–360. https://doi.org/10.1093/oep/gpv024
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• Co, C. Y., Gang, I. N., & Yun, M.-S. (2000). Returns to returning. Journal of Population Economics, 13, 57–79. https://doi.org/10.1007/s001480050121
• Duleep, H. O., & Regets, M. C. (1999). Immigrants and human-capital investment. American Economic Review, 89(2), 186–191. https://doi.org/10.1257/aer.89.2.186
• Engler, P., Giesing, Y., & Kraehnert, K. (2023). The macroeconomic effects of large immigration waves. IAB-Discussion Paper. https://doi.org/10.5167/uzh-239271
• Iara, A. (2006). Skill diffusion in temporary migration? Returns to Western European working experience in the EU accession countries (Development Studies Working Paper No. 210). Centro Studi Luca d’Agliano. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=921492
• Reinhold, S., & Thom, K. (2009). Temporary migration and skill upgrading: Evidence from Mexican migrants. University of Mannheim, unpublished manuscript.
• UNHCR. (n.d.). Operational Data Portal. https://data.unhcr.org/

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