The Relationship between Education and Migration. The Direct Impact of a Person’s Education on Migration

This brief is based on a section from a large policy report, which investigates to what extent education directly influences major migration decisions. The results indicate that education does not have a clear and persistent effect on most of the migration decisions of Ukrainians — while in 2005-2008 education did not have any effect on the probability of migration at all, in 2010-2012 an inverse relation between qualification and probability of migration appeared. It has been observed that education is positively related to the probability of finding high profile positions, such as professionals, technicians or clerks. Still, the analysis of 2005–2008 data tends to support the “brain-waste”, or better to say, “skills-waste” hypothesis for white-collar Ukrainian migrants but not for blue-collar workers. In 2010-2012 the hypothesis doesn’t hold. *

Education and Decision to Migrate

With the rise in overall education levels across the globe, the rate of skill transfer via migration has also increased. Barrientos (2007) showed that in 1990-2000 the share of migrants with higher education in the world rose from 29.8 to 34.6 percent while the share of low-educated migrants declined from 44.9 to 36.4 percent. A substantial share of the education-migration literature is devoted to the impact of education on a person’s decision to migrate and choice of destination country.

Does better education help a migrant from Ukraine to gain additional benefits from migration and thus to improve a person’s productivity and wage? This question has been part of a large-scale research project “The relationship between education and migration in Ukraine” (Vakhitova and Coupé, 2013), which offers a comprehensive analysis of the relationship between education and migration in Ukraine while controlling for the impact of other factors, and provides recommendations on migration and education policy.

Migration processes in the two periods 2005-2008 and 2010-2012 are considered separately. To study the propensity to migrate, two modules of the Labor Migration Survey, i.e. the External Labor Migration Survey for 2005-2008 (ELMS) and the Labor Migration Survey for 2010-2012 (LMS), were supplemented by the corresponding waves of Labor Force Survey. Other migration decisions are considered conditional on the decision to migrate. For this purpose the migration surveys are used.

Propensity to Migrate

2005-2008

In 2005-2008, a typical migrant who leaves Ukraine to find a job abroad is a middle-aged, unmarried man without small children who lives in the rural settlement of Western Ukraine. The analysis of the 2008 LFS data reveals no statistically significant impact of education on the probability to migrate.

2010-2012

In 2010–2012, individuals who are most likely to migrate are very similar to the 2005-2008 migrants in most socio-demographic aspects. However, in the post-crisis period Ukrainians with a middle level of education (i.e. upper secondary and post-secondary non-tertiary education) are statistically more likely to migrate as compared to other respondents. Moreover, whilst the size of the effect of education is still small relative to the effect of the geographic region, it is now comparable to the effect of gender, rural location or marital status

Migration Destinations

2005-2008

In 2005-2008, out of 1381 respondents-migrants:

• 642 (49.2%) chose to migrate to the CIS, with the majority going to Russia (627).
• 365 (24.4%) respondents worked in CEE, Turkey or Egypt.
• 289 (19.5%) individuals had working experience in Southern European states.
• 85 (6.8%) respondents migrated to developed Western European countries and USA.

A regression analysis for the 2005-2008 period supports unconditional comparison. Keeping everything else constant, more educated migrants are more likely to select Western countries rather than CIS. Additionally, more educated individuals are more likely to migrate to the South European states: Spain, Italy, and Portugal.

2010-2012

In 2010-2012, the distribution of migrants by four major destination groups did not change much. But the following changes (as compared to 2005-2008) took place:

• The proportion of well-educated female migrants increased from 44.7% in 2005-2008 to 77.8% in 2010–2012, while for men it changed from 32.3% to 56.3%. The share of oversea workers with tertiary education migrating to Western Europe and USA grew to 65.3%.
• No male migrants with lower secondary and primary education went to Western and Southern Europe in 2012, but the share of female workers with the same level of education in Western Europe went from 0 to 5.5%.
• Female migrants to the CIS had a higher level of education, while the educational level of males working there declined.

However, an empirical analysis for the period of 2010-2012 reveals that after controlling for other factors, neither occupation nor education affect the choice of destination. Geographical variables and household structure play a much more important role.

• Even after controlling for age and occupation, females are more likely to work in CEE and Southern Europe relative to the CIS.
• Individuals from households with small children are less likely to look for a job in developed countries while the presence of elderly increases such a probability.

Migrants from urban settlements and from the Western and Central regions of Ukraine are more likely to go to Southern Europe.

Skills of Ukrainian Migrants

2005-2008

All occupations were grouped into three large categories, i.e. white-collar workers, blue-collar workers and unskilled workers.

Most Ukrainian migrants get predominantly blue-collar or unskilled jobs abroad. In fact, 80 percent of the well-educated migrants are in these occupational groups (Tab.1, upper table). Moreover, at least some post-secondary education is required to become a white-collar worker – 90% of migrants employed as white-collar workers have this level of education (Tab.1, lower table). It is also noticeable that 37% of the migrants had no job at home prior to migration (Tab.2).

A regression analysis reveals that in 2005-2008 skills seem to have a dual effect on the occupation abroad. Some highly skilled migrants are relatively more likely to work as white-collar workers than others – as unskilled ones. The result is particularly clear if skills are measured with a previous occupation at home. On the one hand, respondents reporting a white-collar occupation before migration are significantly more likely to work abroad as white-collar workers compared to those previously with blue-collar occupations. But, on the other hand, people who held white-collar jobs at home are more likely to end up as unskilled laborers rather than blue-collar workers, relative to previously blue-collar workers or even previously unemployed. More educated migrants are found to be more likely to accept a job abroad of similar or lower level.

2010-2012

Overall, in 2010–2012 the skill mismatch among migrants seemed to remain substantial. Still more than 70% of well-educated migrants worked aboard as blue-collar workers or unskilled employees. Nevertheless, similar to 2005-2008, those who found a white-collar occupation abroad during 2010-2012 were more likely to be better educated (Tab.3). 40% of the migrants reported no job at home before departure (Tab.4)

Several important differences between the two periods are worth mentioning:

• The proportion of migrants who got a white-collar job abroad almost doubled from 5.8% in 2005–2008 to 10.3% in 2010–2012 (Tab.1, Tab.3). Such change is particularly striking given that the share of individuals employed at these occupations before migration had not changed much (13.5% in 2005–2008, Tab.2; 14.4% in 2010–2012, Tab.4).
• The proportion of migrants who found a blue-collar occupation abroad decreased at all educational levels (Tab.4). However, this decline, at least partially, may be due to a 10 percentage point reduction in the share of migrants with blue-collar occupations before migration.

A regression analysis suggests that, similar to the previous period, an occupation prior to migration seems to be a better reflection of a migrant’s skills than education. However, the impact of education becomes more pronounced in 2010–2012, at least for more educated individuals. Migrants with tertiary education are significantly more likely to get white-collar rather than blue-collar jobs abroad.

In contrast to the previous results, no skills waste is observed anymore after controlling for the impact of other factors. Individuals reporting both white-collar and blue-collar occupations at home are significantly more likely to find a corresponding job abroad.

Conclusion

What can be concluded from this difference in effects between education and occupation abroad?

The empirical analysis indicates that education does not have a clear and persistent effect on most of the migration decisions of Ukrainians. Moreover, its impact on various aspects of migration decisions differs in two studied periods.

In 2005–2008, in particular, education did not affect the probability to migrate. However, more educated individuals were more likely to migrate to wealthier countries even though they tended to work at lower-level jobs there. In 2010–20012, semi-skilled individuals are relatively more likely to migrate, but neither education nor occupation prior to migration is related to the choice of the destination.

It has been observed that education is positively related to the probability of finding high profile positions, such as professionals, technicians or clerks. This effect is weak, though became more pronounced in 2010-2012. However, very few migrants managed to obtain such positions.

The analysis of 2005–2008 data tends to support the “brain-waste”, or better say, “skill-waste” hypothesis for Ukrainian white-collar migrants but not for blue-collar migrants. In 2010–2012, after controlling for other factors, no skill waste is observed, neither for white-collar nor for blue-collar workers.

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References

• Vakhitova, Ganna; Coupe, Tom. “The relations between education and migration in Ukraine / Ganna Vakhitova, Tom Coupe; International Labour Organization, ILO Decent Work Technical Support Team and Country Office for Central and Eastern Europe (DWT/CO-Budapest). – Budapest: ILO, 2013

* This study was prepared within the EU-funded large-scale project “Effective Governance of Labour Migration and its Skill Dimensions” implemented by the International Labour Organization in collaboration with International Organization for Migration and the World Bank in Ukraine and Moldova in 2011–2013.